diff --git a/your-project/README.md b/your-project/README.md
index 0c5c97c..6be7833 100644
--- a/your-project/README.md
+++ b/your-project/README.md
@@ -1,9 +1,9 @@
 <img src="https://bit.ly/2VnXWr2" alt="Ironhack Logo" width="100"/>
 
 # Title of My Project
-*[Your Name]*
+Jan Potthoff
 
-*[Your Cohort, Campus & Date]*
+Data Squad, Lisbon, Aug.-Oct. 2019
 
 ## Content
 - [Project Description](#project-description)
@@ -16,35 +16,48 @@
 <a name="project-description"></a>
 
 ## Project Description
-Write a short description of your project: 3-5 sentences about what your project is about, why you chose this topic (if relevant), and what you are trying to show. 
+Comparison of decriminalization on drug abuse related deaths and drug related crime in European countries and a broad estimate for tax revenues of a chosen European state in case of legalization and taxation of recreational marijuana with basis on the evolution of tax revenues in Colorado from 2014.
 
 <a name="hypotheses-/-questions"></a>
 
 ## Hypotheses / Questions
-What are the questions you would like to answer with your project? Write your hypotheses here.
+Decriminalization affects drug related deaths and drug related crimes.
 
 <a name="dataset"></a>
 
 ## Dataset
-Where did you get your data? What dataset did you use or did you build your own datset? If so, did you use an API? Did you scrape a web? Provide links to the data if available.
+Eurostats - death statistics - csv
+Eurostats - crime statistics - csv
+Eurostats -  statistical report of drug related deaths - xls
 
 [Dataset]() 
 
 <a name="workflow"></a>
 
 ## Workflow
-Outline the workflow you used in your project. What were the steps you went through?
+- Searching for interesting datasets
+- check datasets
+- come up with questions based on the data
+- online research 
+- clean data
+- work on data
+- visualize findings of the independant data
+- merge data from the different datasets
+- analyze and visualize then visualize joined data
+- research on tax revenues in Colorado, research population counts and drug use through official surveys
+- create a presentation
 
 <a name="organization"></a>
 
 ## Organization
-How did you organize yourself? Did you use any tools?
+I used my computer
 
 <a name="links"></a>
 
 ## Links
 Include the links to your repository, slides and trello. Feel free to include any other links associated to your project. 
 
-[Repository](https://github.com/)  
-[Slides](https://slides.com/)  
-[Trello](https://trello.com/en)  
\ No newline at end of file
+The external sources are listed in the end of the report.
+
+[Repository] https://github.com/janpotthoff/Project-Week-4 
+[Slides] https://www.canva.com/design/DADlRmjxhqs/I1WzHLjZ3TbrfXJZXsn6pg/edit?category=tACFasDnyEQ#1 
diff --git a/your-project/Week 4 - Project/.ipynb_checkpoints/week4-project-checkpoint.ipynb b/your-project/Week 4 - Project/.ipynb_checkpoints/week4-project-checkpoint.ipynb
new file mode 100644
index 0000000..17bf420
--- /dev/null
+++ b/your-project/Week 4 - Project/.ipynb_checkpoints/week4-project-checkpoint.ipynb	
@@ -0,0 +1,4706 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import scipy.stats as st\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deaths = pd.read_csv(\"hlth_cd_asdr_1_Data.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>UNIT</th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Flag and Footnotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                            GEO  UNIT    SEX    AGE  \\\n",
+       "0  2001  European Union - 28 countries  Rate  Total  Total   \n",
+       "1  2001  European Union - 28 countries  Rate  Total  Total   \n",
+       "2  2001                        Belgium  Rate  Total  Total   \n",
+       "\n",
+       "                                               ICD10 Value Flag and Footnotes  \n",
+       "0  Mental and behavioural disorders due to use of...     :                NaN  \n",
+       "1    Drug dependence, toxicomania (F11-F16, F18-F19)     :                NaN  \n",
+       "2  Mental and behavioural disorders due to use of...     :                NaN  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>UNIT</th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Flag and Footnotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>717</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>North Macedonia</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>718</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>719</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     TIME              GEO  UNIT    SEX    AGE  \\\n",
+       "717  2010  North Macedonia  Rate  Total  Total   \n",
+       "718  2010          Albania  Rate  Total  Total   \n",
+       "719  2010          Albania  Rate  Total  Total   \n",
+       "\n",
+       "                                                 ICD10 Value  \\\n",
+       "717    Drug dependence, toxicomania (F11-F16, F18-F19)   0.1   \n",
+       "718  Mental and behavioural disorders due to use of...     :   \n",
+       "719    Drug dependence, toxicomania (F11-F16, F18-F19)     :   \n",
+       "\n",
+       "    Flag and Footnotes  \n",
+       "717                NaN  \n",
+       "718                NaN  \n",
+       "719                NaN  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.tail(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(720, 8)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                            GEO  \\\n",
+       "0  2001  European Union - 28 countries   \n",
+       "1  2001  European Union - 28 countries   \n",
+       "2  2001                        Belgium   \n",
+       "\n",
+       "                                               ICD10 Value  \n",
+       "0  Mental and behavioural disorders due to use of...     :  \n",
+       "1    Drug dependence, toxicomania (F11-F16, F18-F19)     :  \n",
+       "2  Mental and behavioural disorders due to use of...     :  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths1= deaths[[\"TIME\", \"GEO\", \"ICD10\",\"Value\"]]\n",
+    "deaths1.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/pandas/core/indexing.py:494: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  self.obj[item] = s\n"
+     ]
+    }
+   ],
+   "source": [
+    "deaths1.loc[deaths1['Value'].str.startswith(':'), 'Value'] = ''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                            GEO  \\\n",
+       "0  2001  European Union - 28 countries   \n",
+       "1  2001  European Union - 28 countries   \n",
+       "2  2001                        Belgium   \n",
+       "\n",
+       "                                               ICD10 Value  \n",
+       "0  Mental and behavioural disorders due to use of...        \n",
+       "1    Drug dependence, toxicomania (F11-F16, F18-F19)        \n",
+       "2  Mental and behavioural disorders due to use of...        "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths1.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deaths2=deaths1[\"\"!=deaths1[\"Value\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO                                              ICD10 Value\n",
+       "4  2001  Bulgaria  Mental and behavioural disorders due to use of...   1.1\n",
+       "5  2001  Bulgaria    Drug dependence, toxicomania (F11-F16, F18-F19)   0.1\n",
+       "6  2001   Czechia  Mental and behavioural disorders due to use of...   1.1"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths2.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO                                              ICD10 Value  \\\n",
+       "4  2001  Bulgaria  Mental and behavioural disorders due to use of...   1.1   \n",
+       "5  2001  Bulgaria    Drug dependence, toxicomania (F11-F16, F18-F19)   0.1   \n",
+       "6  2001   Czechia  Mental and behavioural disorders due to use of...   1.1   \n",
+       "\n",
+       "   deaths/100k  \n",
+       "4          1.1  \n",
+       "5          0.1  \n",
+       "6          1.1  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths2[\"deaths/100k\"] = [float(i) for i in deaths2[\"Value\"]]\n",
+    "deaths2.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Mental and behavioural disorders due to use of alcohol'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "just = [i for i in deaths2[\"ICD10\"]]\n",
+    "just[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    }
+   ],
+   "source": [
+    "plodeath=deaths2[\"Drug dependence, toxicomania (F11-F16, F18-F19)\"==deaths1[\"ICD10\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    }
+   ],
+   "source": [
+    "ploalc=deaths2[\"Mental and behavioural disorders due to use of alcohol\"==deaths1[\"ICD10\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fed4c29a2b0>"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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okLm5uRlVKpW0fft2h0uXLilrW1cQBHz77bdpqampNvPnz2/5oPsmIlZMiIiIqBGqqKgQtVqt3mQyCTKZTBo+fHju66+/ng0As2fPzklLS1MFBwfrJEkSXFxcjD/88MPZB93nxIkT8/r16+ev0Wj0ISEhpX5+fuW3W18ul+P7778/16dPH//33nvP/I9//OPqg8ZA9GcmcMo7IiIiqi4uLi7NYDDkWDsOImp64uLi3AwGg29NbbyVi4iIiIiIrI6JCRERERERWR0TEyIiIiIisjomJkREREREZHVMTIiIiIiIyOqYmBARERERkdUxMSEiIqJGJz09XT5gwAA/T0/P4MDAQF379u21q1evbmbtuO6FxWLBX/7yF01eXt59nW8dPnzYduPGjU5Vr9etW+f08ssvtwSAF198sfVrr73mfus2O3futNfr9Tq5XB62atUq5+pt06ZN82jXrl1gu3btAleuXHmzbdu2bQ56vV7Xrl27wCFDhvgajcab8Y8bN87L29s7SKPR6A8ePKiuKc633nqrRZs2bQIHDhzodz/HWddufd8eRGhoqBYAUlJSlMuXL3epiz7vxZQpUzz9/f0Dp0yZ4ll9eXR0tMOePXvsql4PHTrU99bf973w8PAI1mg0eq1Wq9dqtfo9e/bYpaSkKG1sbDpotVp927ZtAwcPHuxb9VBTANi7d6+6U6dOAT4+PkF6vV7Xo0cP/6NHj9oCwDvvvNN86dKlrvcaBxMTIiIialQsFgsGDBjg361bt+KMjIyTiYmJSd9+++259PT0Wp/Efquqk2tr+vbbb50CAwPLXFxcLPezfUxMjHrHjh03T7BHjRpV8M4771y+3TZt2rSpXLVqVdqAAQNyqy/fsGGDU1xcnPrUqVOJx48fT/roo49a5uXliWazGZMnT/bbsGHDudOnTyd6e3tXfvzxx24A8N133zmdO3fOJi0tLWHZsmUXpk+f7l3TPr/44ovme/bsSd22bdv5uzmuuv7d3Nrfre/b/fRR9To2NjYZAE6fPq3auHHjPSUmdXGc69evd0tOTk5csWJFRvXlP/30k8PPP/9s/8A7qGb//v2pycnJp5KTk0/16dOnBAC8vLwqkpOTT6WkpCRmZWUpv/zyS2fg+oWD0aNHt3377bczLly4kHDq1Kmkf/7zn5dTUlJUAPDCCy/krlix4g+J850wMSEiIqJGZfv27Q4KhUKaO3fuzSepazSayvnz518BAJPJhClTpngGBQXpNBqN/oMPPnADrl9FDgsLC4iMjPRv165dUEpKitLPzy9w6NChvr6+vkEDBw7027p1q0OHDh20Pj4+QXv37lUD16/8tm/fXqvT6fShoaHauLg4FQBERUW5PvbYY227devWzsfHJ2jq1KmeALB06VLX559/3qsqtsWLF7tNmDDBC7dYt26dy+DBg/OB61fc27VrF1jV9tprr7m/+OKLrQGgU6dOAdOmTfMIDg7W+fr6Bu3atcu+vLxcePfdd1tv377dWavV6leuXOkcFRXlOnbs2BqTgyoBAQGVnTt3LhPF35/iJSYm2nTt2rVYoVDA0dHRotfrS7ds2eKUnZ0tVygUlpCQkAoA6Nu3b+HWrVubAcD333/fbNSoUbmiKKJXr14lhYWF8gsXLiiq9zty5EjvjIwMVb9+/dq98cYbLbKzs2W9e/duq9Fo9AaDQXvkyBFb4HqFZ9CgQX4dOnTQDhkyxC8qKsq1d+/ebSMiItp5eHgEv/POO80XLFjgrtPp9AaDQZudnS27EbeqW7du7QIDA3VhYWEBsbGxNsD1CsHIkSO9Q0JCtNOmTbtZTajpfSssLBSHDRvmGxwcrNPpdPq1a9c2q/r9RkZG+v/lL3/RREREBNz6+QEAtVodCgDz58/3iImJsddqtfo33nijRWlpqfD000/7ajQavU6n02/fvt2hpj4HDx7su2bNmpuVvoEDB/pV7b+KxWLBlClTPNu1axeo0Wj0VdWsyMhI/9LSUllQUJC+eoUrJSVFuXr16ubLly9312q1+l27dtkDwP79++1DQ0O1np6ewdWrJ6+++qp71d/K7NmzW9/u81MbuVyODh06lGRmZioA4MMPP2zxzDPP5FYlMADw+OOPF48ZMyYfABwcHCyenp4VVX9jd72f+wmOiIiI/hyuRb/hZbpy9p5OLu5E3qJtqfOTr6fX1n7y5EnbkJCQ0traly5d6ubk5GROSEhIKisrEzp27KgdMGBAIQCcOnVKHRsbm6jVaitTUlKU6enpNhs3bjwXFhaWFhISolu3bp1rTExM8vr165u9/fbbrXr27HnWYDCUHzt2LFmhUGDr1q0Oc+fO9dy9e/fZqv7i4uJO2draWvz9/YP+/ve/Z48fP/5aUFBQq4qKigyVSiWtXbvWbcWKFRdujfP48eP2Xbt2/cPymphMJuHkyZNJGzdudFq4cGHrvn37pv7zn/+8FBMTY7d69eqLwPWT3rvpqyahoaFlb731VuuioqLs4uJi8fDhw446na68ZcuWJrPZLBw4cED96KOPlm7cuNE5KytLCQBZWVkKX1/fyqo+WrVqVXnhwgWFj4/PzVLA+vXrL+7fv99p//79qa1atTI999xzXgaDofTHH388u23bNofnnnvOLzk5+RQAnD592ubIkSPJ9vb2UlRUlGtqaqptXFzcqbKyMjEgICDo1VdfzUxKSjo1YcIErxUrVri+9tprVyZOnOjz2WefXQgODq746aef7KZNm+b966+/pt6IT/nbb78ly+X/O521sbGRbn3fZsyY4dGzZ8/C7777Li0nJ0cWHh6uGzhwYCEAJCYmquPj4xPd3d3N0dHRDtU/P9Xfv7fffjtz8eLF7nv37j0DAK+//rq7IAhITU09FRsba/PEE0+0O3v2bMKtfe7YscN+yZIl7mPGjMnPzc2VHT9+3H7z5s2/qyytXr262cmTJ22TkpISs7Ky5J06ddI99thjxT/99NMZtVodWvX+VQkICKgcO3bsVXt7e/PChQuzAWDlypVu2dnZipiYmOQTJ07YDB482H/8+PHXtmzZ4njmzBmb+Pj4JEmS0Lt3b/+dO3fa9+vXr/jWz0j37t01oihCqVRa4uPjk6u3lZaWCsePH7eLiopKB4CkpCTbsWPH5t7aR3UdOnQo2bdvn0PPnj1r/Vu+FRMTIiIiatTGjBnjffToUXuFQiElJCQk/fjjj47Jycnqbdu2OQNAUVGR7NSpUzZKpVIKCQkpqX5S6eHhUdGpU6cyANBoNGWRkZGFoiiiQ4cOpW+99VZrAMjLy5MNHz7cLy0tzUYQBMloNN68j/6RRx4pdHV1NQOAv79/+dmzZ1X+/v7FXbt2Ldq4caNTcHBwudFoFKr2UV1BQYHc2dn5rm7jGjZs2DUAiIiIKJkzZ85d37J2t4YMGVJ45MgRdceOHbUuLi7GDh06FMtkMkkURaxevfrc7NmzvSorK8WePXsW3FptuRdHjx512Lx58xkAGDhwYNHkyZPlVWNs+vbtm29vby9VrRsREVHk7OxscXZ2ttjb25uHDRuWDwDBwcGl8fHx6oKCAjE2NtZ+2LBhbau2qaysvPm7GTJkyLXqSUlt9u3b57h79+5mUVFRLQGgoqJCOHPmjBIAunXrVuju7m6uWvfWz09tDh8+bP/CCy9cAYDQ0NDy1q1bV548edLm1j779+9fPHPmTJ9Lly7J165d69y/f/9rCsXvik74+eefHZ555pk8uVwOLy8vU+fOnYsPHjyo9vHxKbjjwVUzcODAfJlMhrCwsPLc3FwFAOzatcvxwIEDjnq9Xg8ApaWlYnJysk1NiUlVcll9WXp6ukqr1eozMzOVPXr0KOjcufMfPucAEBISoi0uLpZ17969cNWqVekA0KJFC1NycrLNvRwDExMiIiKq1e0qG/UlODi47Pvvv795K8qaNWsuZmVlycPDw3UAIEmSsHjx4otDhw4trL5ddHS0g1qt/l0ioFQqb54Ii6IIGxsbCQBkMhnMZrMAAPPmzfPo3r170Z49e86mpKQoIyMjA2raXiaT3UxaJk+enPP222+31Gg05aNHj86p6ThkMplkNpshk8kgl8sli+V/oZWXl//u7L8qLrlcfjOuurZo0aLLixYtugwAAwYM8AsICKgAgN69e5ccP348BQCqrrADQKtWrYxpaWk3k6SsrCxl9WrJvbKzs7ur340oijCZTILZbIaDg4Pp1opBFXt7+7tK+iRJwqZNm84YDIaK6ssPHjxod+vn5dbX9+PWPoYPH567cuVKl82bN7usWrUq7UH7r03V+wdcP+aq77NmzcqaM2dOjZ/RO6kaY5KVlSXv0qWLdt26dU6jRo0q0Ol0ZcePH1ePHj06HwDi4+OTV61a5RwdHX1zbE95ebloa2t7T+8nx5gQERFRozJgwICiiooKYdGiRc2rlhUXF988Z+nTp0/BsmXLmlfNEBQfH68qLCy873OawsJCmaenZyUArFixwu1utomMjCzJyspS/uc//3GdMGFCXk3r+Pn5lSclJakAwNPT05SXlye/fPmyrKysTNi9e/cdB2c7Ojqaqx/3gzCZTLh8+bIMAI4cOWKbnJysHjJkSAEAZGZmygGgrKxM+OCDD1pOnTr1KnD9Cvy6detcLRYL/u///s/OwcHBfKfEpHPnzkWrVq1yBa4nis7Ozqb7Hfzv4uJi8fT0rKwacG2xWPDLL7/Y3mm7W9+3nj17Fi5evNi9KjE8dOjQHfu4lZOTk7m4uFhW9bpr167Fa9eudQGuf/6ysrKUISEh5TVtO3Xq1JyqgeBhYWF/WOfRRx8t2rRpk4vJZMKlS5fkR48ete/WrVvJH3v6HwcHB3NRUZHsdusAQL9+/QrXrFnjVlBQIALA+fPnFVW/73vRqlUr08KFCzM++OCDVgDw0ksvXdm4caNr9ZnBSkpKfvdZTU1NVQUFBdVYYakNExMiIiJqVERRxPbt28/+/PPPDh4eHsHBwcG60aNH+y5YsCADAGbPnp2j1WrLg4ODde3atQucNGmST/Xbr+7VvHnzLi9YsMBTp9PpTSbTnTe4YdCgQdfCw8OLmzdvbq6p/bHHHiv473//6wAAKpVKeumll7I6duyo69atm8bf37/Gk9jq+vXrV5SammpbNYj7bmLav3+/2t3dPeSHH35wnj17to+/v38gcP0WqK5du2rbtm0bOHnyZJ+vv/76XNUtRQsXLmzZpk2bQJ1OF9ivX7/8gQMHFgHAM888U+Dj41Ph4+MTNG3aNJ9PPvnkjuNlFi1adCk2Nlat0Wj08+fP9/jqq6/uaqau2nzzzTfnVq1a5RYQEKBv165d4ObNm+84ZfSt79t77713yWQyCVqtVu/v7x/4yiuveNxrHJ06dSqTyWRSQECA/o033mgxd+7cKxaLRdBoNPrhw4e3XbFiRZqtra1U07ZeXl6mtm3blo8ePbrGMRljxozJDwwMLNPpdIE9evTQvPHGGxne3t63/SAOHTo0f8eOHc2qD36vyZAhQwqHDRuW17FjR61Go9EPHjy4bX5+/h0TmpqMHj06v6ysTNy1a5e9t7e3ac2aNedefvllT29v76DQ0FDtli1bnGfOnHmlav1jx47ZV43luVtCVamHiIiICADi4uLSDAbDfd368WfSs2dP/1mzZmU/9dRTRTW1X7hwQfHss8/6Hj58+HRDx0aNR1FRkajX6/UnTpxIqhqv1NQdOnTI9oMPPmi5devWPySmcXFxbgaDwbem7VgxISIiIroHOTk5Ml9f3yAbGxtLbUkJAPj4+Biff/75nPt9wCI9/LZu3eoQEBAQOGnSpCt/lqQEAK5cuaJYtGhR5r1ux4oJERER/Q4rJkRUX1gxISIiIiKiRo2JCRERERERWR0TEyIiIiIisjomJkREREREZHVMTIiIiKjRkclkYVqtVl/19fLLL7esbd01a9Y0O378uM397uvAgQPqcePGed3v9kRUN+75yY9ERERE9U2lUlmSk5NP3c26W7dubWYymQpqeqr23Xj00UdLH3300dL72ZaI6k6Tmi7Yzc1N8vX1tXYYRERED7X3338fLVvWWqBoEOHh4Th06JApNDQ0rvry6dOne+zevbuZTCaTevToUThs2LBrTz/9dDt7e3uzg64Hn90AACAASURBVIODefPmzWcLCgrEadOm+ZSVlYk+Pj4V69evT2vevLm5U6dOAWFhYcUHDx50LCoqki1fvjytb9++xdHR0Q6LFy9237t375m9e/eqZ8+e7V1RUSHa2NhYvvrqq/MGg6HCWu8DUVNzu+mCm1TFxNfXFzExMdYOg4iI6KGWlJQEnU4HAMja+yHKr6bWaf82zTVo1fPvt12noqICI0aMEAVB0APASy+9lDVgwIDCH374wfncuXMJoigiJydH5ubmZu7du3f+k08+WTB+/PhrAKDRaPRLliy52L9//+JZs2a1njdvXusvv/wyHQBMJpNw8uTJpI0bNzotXLiwdd++fX93cAaDofzYsWPJCoUCW7dudZg7d67n7t27z9bpG0BENWpSiQkRERE1Dba2tti8eXN5UFBQUtUyo9EIlUplGT58uO+TTz6ZP3z48IJbt8vNzZUVFRXJ+vfvXwwAkyZNyh02bFibqvZhw4ZdA4CIiIiSOXPmKG/dPi8vTzZ8+HC/tLQ0G0EQJKPRKNTPERLRrZiYEBERUa3uVNloSAqFAidOnEjatm2b46ZNm5yXLVvW4tdff72nco6NjY0EAHK5HGaz+Q9Jx7x58zy6d+9etGfPnrMpKSnKyMjIgLqKn4huj7NyERER0UOhoKBAvFHRKFi+fHl6cnKyGgDs7e3NhYWFIgC4urqaHR0dzbt27bIHgC+++MK1S5cuxXe7j8LCQpmnp2clAKxYscKtPo6DiGrGxISIiIganbKyMgwdOtSmarrg6dOne+Tn58v69u3bTqPR6Lt06RLw5ptvpgPAqFGj8qKiolrqdDp9YmKiatWqVefnzZvnqdFo9PHx8bbvvffepbvd77x58y4vWLDAU6fT6U0mU/0dIBH9Qb3NyiUIwpcAngRwRZKkoBvLNgKoKok2A5AvSVL7GrZNA1AEwAzAJElS+N3sMzw8XOLgdyIiogdTffC7NSUkJJRWH2NCRA8/a83K9RWAjwGsrlogSdLwqp8FQVgM4A+D1qrpKUlSTr1FR0REREREjUa9JSaSJB0QBMG3pjZBEAQAzwCIrK/9ExERERHRw8NaY0y6AciWJOl0Le0SgP8KgnBcEITJt+tIEITJgiDECIIQc/Xq1ToPlIiIiIiI6p+1EpNnAXxzm/ZHJEnqAKAfgL8KgvBobStKkvSZJEnhkiSFN2/evK7jJCIiIiKiBtDgiYkgCHIAQwBsrG0dSZIyb3y/AuA/ADo1THRERERERGQN1qiY9AaQLElSRk2NgiDYCYLgUPUzgMcAJDRgfERERERE1MDqLTERBOEbAL8ACBAEIUMQhAk3mkbgltu4BEFoLQjCDzdeugM4KAhCHICjAHZIkrSrvuIkIiKixsfe3v6et/Hw8AjOysqqk4l91Gp1aF30Q0R3rz5n5Xq2luXjalh2CcATN34+B8BQX3ERERHRw8loNEKhUFg7DCKqJ3zyOxERETVa0dHRDmFhYQGRkZH+7dq1CwKATz/91CU4OFin1Wr1I0eO9KnpCe29e/duGxgYqPP39w/88MMP3aqWq9Xq0BdeeMEjICBAbzAYtOnp6XIASE5OVrZv316r0Wj0f/vb31o32AES0U31+YBFIiKysuKLR2Hj5g+52sXaodBD6vzPH6I0J7VO+1S7aeDX7e93vf6pU6fUsbGxiVqttvK3336z2bRpk0tMTEyySqWSRo8e7b18+XLXGTNm5FbfZt26dWnu7u7m4uJiITQ0VD969OhrLVu2NJeVlYldunQp/ve//505depUz3//+9/N33///azp06d7T5w48eqMGTNy3333XU7zSWQFrJgQETVRlfnpuLBpOi79901rh0L0QEJCQkq0Wm0lAOzatcshISFBbTAYdFqtVn/w4EHHc+fOqW7dZtGiRe4BAQH6sLAw3eXLlxWJiYk2AKBQKKQRI0YUAEBYWFjJhQsXlADw22+/2U+aNCkPAKZMmZJ7a39EVP9YMSEiaqJyT3wLQELRuQMovRQPdesQa4dED6F7qWzUF7Vaban6WZIkYdiwYbmffPJJZm3rR0dHO+zfv98hJiYm2cHBwdKpU6eAsrIyEQDkcrkkitevy8rlcphMJqFqO1EUpXo8DCK6A1ZMiIiaIHNlCfITvodD2+6QqV1w5dAn1g6JqE707du3MDo62jkzM1MOANnZ2bLU1FRl9XXy8/NlTk5OZgcHB0tsbKxNXFyc3Z367dChQ/HKlStdAGDlypWu9RM9Ed0OExMioiYoPzEalsoSuHV6Hs07PY+S9BgUXzxq7bCIHlhYWFj5K6+8ktmrVy+NRqPRR0ZGatLT0383VdfQoUMLTCaT0KZNm8A5c+Z4GAyGkjv1++mnn1787LPPWmg0Gn1mZian/iKyAkGSmk7VMjw8XIqJibF2GEREViVJFpxZNRQyG0e0Gfk1LKZKnFk1CHI7N/g9+zUEQbhzJ/SnlpSUBJ1OZ+0wkJCQUBoUFJRk7TiIqO7ExcW5GQwG35raWDEhImpiitN+QWX+Rbh2uP44KVGuRPO/TEbZ5UQUnd1v5eiIiIhqxsSEiKiJyfvtG8jtmsOxXa+by5oFPgllM29cOfQpJIvZitERERHVjIkJEVETUpF3HsUXfoGL4WkIsv/dJi+IcrToOg0VuWdRkPJfK0ZIRERUMyYmRERNSG7sRggyJZxDhv6hzVHTGzbNNbh6eDkks9EK0REREdWOiQkRURNhLi9CwaloOGn7Qq52/kO7IIho0XUaKgsycC1xuxUivDeSJEEqLYIlJwOWtARYzp+EZLHceUMiInoo8QGLRERNxLWErbAYy+ASOqLWdez9usG2VQiu/roSzfT9Icr/8MDseiMZK4GSAkilBUBx/vXvJQWQSvIhlVT9XABUvS4tAG5JRMSwvpA//XcIoqzB4iYioobBxISIqAmQLGbknfgWao8OsG0RUOt6giDAvet0pG2airy4TXALG3Wf+7MA5cWQSvKrJRS3JBY3XlclIqgsqy0owNYBgl0zwM4JgpsXBJ9ACHZOgF0zCHZOEOyawXI+Dua962EyVkA+4mUIMv4X1pRlZ2djzpw5qpMnTwY7OTmZFAqF9OKLL14eO3ZsvrVjI6L6wX/ViYiagKJzB2AsvISW3WffcV07746w8+6MnKNfwjl4EGRKO0jGipvVi5sJRUk+UFJYbdmN76WFNVYzblLYXE8w7JwAOyeIzb1u/vy/780A9Y3Xaoe7qoCIAZ0AWweYf1gBk6kC8pGvQ1Ao77gdPXwkScKgQYPQq1cv886dO08CQGpqqvK7775rVn09o9EIhYLPQiRqKpiYEBE1Abm/fQOFQ0s4tH30d8stl89Dysn4Q9LhUmBBelk+riwdBJciOVBZXnPHggioHf+XULTwhnCjigG1EwR7JwhqJ8C+2fXvdk4QlDb1dpzy7iMgKG1g2voRjF/Ph2Lsm/W6P7KOn376CUqlEiNGjDBVLdNoNJXz58+/EhUV5bp161bn0tJS0Ww2C8eOHUt59dVX3f/zn/+4VFZWCv37989fsmTJJQD49NNPXZYtW+ZuNBqFDh06lKxevfqCXC7Hpk2bHF977TUPs9ksuLi4mH755ZfUwsJCccKECd7Jycm2JpNJmD9//qXRo0ezOkPUgJiYEBE95MqvnkZpxnG4d5sJQZRfHzR+7gRMP62FdOa336+stAHsmsHGzgl2iubIF67BJXwEZI4tfp9gVCUctg4QxMY1T4qsyyBAYQPTpg9g/HIeFOPegWBjZ+2wmqzkwx+iKDe1Tvt0cNVAG/H3WtsTExPRoUOH27Wr4+PjE93d3c1btmxxPHPmjE18fHySJEno3bu3/86dO+3d3d1NmzZtcomJiUlWqVTS6NGjvZcvX+46ZMiQghkzZvju27cvWavVVmZnZ8sA4OWXX27Vs2fPwu+++y4tJydHFh4erhs4cGCho6MjZ1wgaiBMTIiIHnK5sd9AkNugWdBTMCf9AvNPayFdPAXYO0P2xBSI/mE3xm84QlD8b7B7y5wzOLt6BPJdZHDvdn9jTaxFFt4XUChh2vAOjJ//HYrnF0FQO1o7LKonY8aM8T569Ki9QqGQJk+efKVbt26F7u7uZgDYtWuX44EDBxz1er0eAEpLS8Xk5GSb2NhYISEhQW0wGHQAUF5eLrZo0cK0b98+u06dOhVptdpKAKjqZ9++fY67d+9uFhUV1RIAKioqhDNnzig7dOhQSzmRiOoaExMiooeYqewaCpJ2wallKCwrXoSUdQ5wdod80CyI4f1uOwbDxs0fTtq+yI3dAJfQZ6Gwb96AkT84mSESUKhgWvsGjJ+9CMXEDyDY/3GaZHowt6ts1JfAwEBs3rwZEyZMAACsWbPmYlZWljw8PFwHAGq1+mYVQ5IkzJo1K2vOnDk51ft4++23WwwbNiz3k08+yay+fP369U417VOSJGzatOmMwWCoqPMDIqK70rjq80REdNckkxF5O9+DZK6AY9xJwGSC/Jl/QDlnLWRdnrqrgeHNu0yBZDEh58iXDRBx3ZPpu0Ix7h1IORkwLp8FqeCqtUOiOhAZGYny8nJ88803Ny+gFhcX13jO0q9fv8I1a9a4FRQUiABw/vx5RWZmprxv376F0dHRzpmZmXIAyM7OlqWmpip79OhRcvToUYfk5GRl1XIA6NmzZ+HixYvdLTcmdTh06JBtPR8mEd2CFRMiooeMZKyA5egOGPdvQJ7iHNQyB6iffQNi4CP3/HwPlbMXnIMG4drJLXANHwOlU+t6irr+iJpwKCa8D+Oqf6Jy+SwoJy2G4NLS2mHRAxAEAVu3bsW4ceNkHh4ewS4uLia1Wm1esGBBRllZ2e8SlCFDhhQmJibadOzYUQtcr6asW7fufFhYWPkrr7yS2atXL43FYoFCoZCioqIu9urVqyQqKipt8ODB/haLBa6ursbDhw+ffu+99y5NnjzZW6vV6i0Wi+Dl5VWxd+/eM9Z5B4j+nARJkqwdQ50JDw+XYmJirB0GEVG9kMpLYP7le5gPbgKKr6HYsyUuG1Ph9dQSON4yG9e9MBZl4/SXg+CkfRwejy+ou4AbmCU9CcYv5gJKWygmLYbY3MvaIT20kpKSoNPprB0GEhISSoOCgpKsHQcR1Z24uDg3g8HgW1Mbb+UiImrkpJICmHZ/icp3h8O8ayWE1v5QTP0IBW42UDbzgkObRx6of4WDO1zaD0P+qR2oyD1fR1E3PNFLB8XkJYDJCOPymbBcfniPhYjoz4iJCRFRIyUVXIVp+yeofHcEzD+tgejfAYoXlkM54X1U2MpQlhUPl/bDIQgP/k+5W8fxEOU2uHJ4WR1Ebj3ijaQNogzGFbNgyUixdkhERHSXOMaEiKiRkXIvwbTvG1iO7wYkM8T2vSDrMRKiu+/NdXJjN0BU2qFZ4IA62adc7QzXsFG4+utKlGUnwdbd+rfx3C+xhTeUUz9C5cqXYPzsJSiefxeib7C1wyIiojtgxYSIqJGwXD4P44a3UfnBGFiO74bYsR+Uc9ZCMfzl3yUlxuKrKEz5L5oFDoBMZV9n+3cNGwWZyhFXDj3cVRMAEFxbQzn1IwgOLjB+PheWWx80SUREjQ4TEyIiK7OkJ8O4+lUYlzwPS+JByB55Gsp/rIdi8GwILq3+sP61+C2QLGa4tB9Rp3HIVA5w6zQOxWmHUJIRW6d9W4PQrAUUU5dCcG0F46p/wJz0i7VDIiKi22BiQkRkBZIkwXLuBCo/nwPjx9NgOXcCsl5jofzHBsifnAbB0a3G7SymSuTFb4K9X1eonOt+1imX9s9AbueKK4c+QVOYtVFwcIFi8hII7n4wrXkN5pP7rR0SERHVgokJEVEDkiQJ5uRfYVz2AowrZkPKOgtZv8nXE5LHxkOwq/Gh1DcVpv4X5tI8uHZ4tl7iExW2aN55IkozY1FyoWlUGAQ7JygmLYbgGQDTuoUw//Zfa4dEd+Htt9/GU089ZavRaPRarVb/008/2d1rH+vWrXN6+eWX+VAboocEB78TETUAyWKGJeFnmPeug3TpDNDMHfKn/gax4xMQFKq760OSkBu7ASoXP9h5d663WJsFD0ZOzBpkH/wEdj5dIAhCve2roQi29lBM+ADGr+fD9O17gLECss51M3EA1b1ffvkF0dHR+Pbbb8vCwsKSsrKy5BUVFff8QRw1alQBgIJ6CJGI6gErJkRE9Ugym2CO2QXjv8bDtO4NoLIC8mHzoJy7FrKIwXedlABA2aU4lGcnwSV0RL0mC6JMgRZdJqP8SjKKTv9Ub/tpaILKForx70IM6ATTln/B9PN31g6JapGVlQU3NzeoVNf/Plq1amXy9fU1enh4BE+dOtVTo9Hog4ODdQkJCSoAWL9+vVNISIhWp9PpIyIiNOnp6XIAiIqKch07dqw3AAwdOtR33LhxXqGhoVpPT8/gVatWOVvtAImoRqyYEBHVA8lYAcuxH2DavxHIz4bQ2h/yUa9DDOoGQZTdV5+5sd9AVDmgmb5/HUf7R066J5Bz7GtcObwMDv497jvmxkZQqCAf8yZM37wFc/SngLEC8sjR1g6rUYv/9QMU5KXWaZ9OLhqE/GVOre2PPfYYFi5ciP79+9t269bN+9lnn83r379/MQA4OTmZUlNTT3388ceuL7zwgtfevXvP9OnTp3jEiBHJoijiX//6l9vChQtbrly5MuPWfrOzsxUxMTHJJ06csBk8eLD/+PHjr9XpgRHRA2FiQkRUh6TyEph/3Qbzz98Bxdcg+ARCNngWxIDOD1TlMBZdRuHpvXANGwVRYVuHEddMEGVoETEN6dFzUZC8E830T9b7PhuKIFdAPvI1mDYtgnn3F0BlGWSPT2wSt6w1Ffb29jh+/Di++uqrioSEBNNzzz3X9rXXXssAgOeeey4PACZNmpT3yiuveAHA+fPnlYMGDfK8evWqorKyUvTy8qqoqd+BAwfmy2QyhIWFlefm5ioa7oiI6G4wMSEiqgNSSQHMh7bAfHgLUFYMoV045JGjIPgZ6uSEN+/EdwAkuLR/5sGDvUsO7SJh00KLK4dXwDHgcYiypnMeJ8hkkA/7B0wKG5j3rgcqyyEbMIPJSQ1uV9moTzKZDJ07d7ZMmDDhUkhISNmaNWtcAUAU/3cXuiAIEgDMmDHDe+bMmZdHjRpVEB0d7bBw4cLWNfVpY2Nzc6q5pjDrHFFTwzEmREQPQCrMgSl6GSrfGwHz/62G2KY9FDOWQTnxA4ht2tfJia7FWIZrJ/8Dh7Y9oHT843NN6osgCGjR9a8wFl5C/sn/NNh+G4ogipAPng3ZI0/DfGgLTJsXQ7KYrR0WAUhJScHp06dvvo6NjbX19PSsBIDVq1e7AMAXX3zhHBoaWgIARUVFMm9vbyMAfPXVV65WCJmI6gArJkRE90HKy4Jp/wZYju0ELGaI7SMh6zESYku/Ot9XQfIumMsL6m2K4Nux9+0CtUcorh75As0CBzTIbWQNSRAEyJ6cDihtYf5pDUzGcsif+ScEWdMYU/OwKi4uxgsvvIDLly/byuVyva+vb8XXX399ITw83OnatWsyjUajVyqV0oYNG84BwPz58y89++yzbZ2cnEyPPPJI0cWLF+9+VgkiajSEplTKDA8Pl2JiYqwdBhE1YZbsNJj3rYflxP8Bggxi2OOQ9xgBwdWjXvYnSRLOrh4OQZSjzeh1VrnVqCQjFmnfToR7t5lw6zi2wfffUEx718O8ayXEwG6Qj3wFglxp7ZCsJikpCTqdztphICEhoTQoKCip6rWHh0dwTExMUqtWrUzWjIuI7l9cXJybwWDwramNFRMiortgyUiBee86WBJ+BhQ2kEUMgezRZyA4Na/X/ZakH0NF7lm0fux1q41/sPMMhb1vBHKOfQXnkMGQqRysEkd9k/ccCShVMG/7GMavX4Vi7MJ7ms6ZiIgeDBMTIqLbsJyLg2nvOkipxwAbO8gix0D2yNA7PqG9ruTFboDM1hlO2scbZH+1adF1Os6tG43c4+vQImKqVWOpT/KuQyEobGDashjGL/8Bxbi3IajU1g6LbsjMzDxp7RiIqP4wMSEiuoUkSbCkHL3+lPa0k4BdM8j6ToKsy1MQbOwaLI7K/AwUnT0At87PQ5Rb98q9rbsOju16Iff4OriEDofctuk+m07WqT+gUMH07bswfj4HiucXQbC1t3ZYRERNHhMTIqIbpLzLMJ/4EZbYHyFduQA4tYB84AsQOz4BQWnT4PHknfgWEEW4GIY1+L5r0iJiGgrP7EXO0a/Qsvtsa4dTr2Shva8nJ+sXwvjZi1BM/KDBqmRERH9W9TZdsCAIXwqCcEUQhIRqyxYIgpApCMKJG19P1LJtX0EQUgRBOCMIwj/qK0YiIqm0COYj21G5fCYqFz17/YF7akfIn54L5dy1kHUdYpWkxFxZgmsJW+HUrjcU9vU7juVuqVz90Ez3BPJOfAtjUba1w6l3sqBuUDz3NqQrF2BcPhNSYa61QyIiatLq8zkmXwHoW8PyJZIktb/x9cOtjYIgyAB8AqAfAD2AZwVB0NdjnET0JyMZK2FOOADj6tdQ+dZQmLb8CyjOh+zxCVDOWw/ltCjIOvaDILfeAwXzT+2ApbIELlaYIvh2mneZDEgWXD3yhbVDaRBiQCconl8EKT/7enJyreknZERE1lJvt3JJknRAEATf+9i0E4AzkiSdAwBBEDYAeArAqbqLjoj+bCSLBVJaPMy//QjLyX1AeQlg7wxZl6cghvaG4KFpNE/9liQL8mI3wLZlINStgq0dzu8onTzgHDwEeSc3wy18DJTNvKwdUr0T27aHYuJiGL+ci8rlM6GctBiCW/1MD03/I5PJ4O/vb1N1cfL7778/ExAQUGntuIio/lhjjMkMQRDGAogB8JIkSdduafcAkF7tdQaAzg0VHBE1LZbL52GJ/RHm2B+BgiuA0gZiUDfIQvtAaNuhUT5IrzjtF1ReuwCPfm9ZO5QauXV+HtcSv8eVXz6DZ783rR1OgxB99FBMXgLjF3NQuXwmFJM+hOjua+2wmjRbW1ts3ry5vPpzTKozGo1QKKxX1SSiuleft3LVZBmAtgDaA8gCsPhBOxQEYbIgCDGCIMRcvXr1QbsjoiZAKsyB6cC3qPxoEoxLnof5wAaILf0gHzEfyle3QDH8ZYiajo0yKQGuTxEst3ODo6a3tUOpkcK+OVzaj0BB0k6U55yxdjgNRvRoB8WUpQAkGFfMgiXztLVD+tOJiopyjYyM9P/LX/6iiYiICCgoKBC7dOmi0ev1Oo1Go1+7dm0zAEhJSVG2adMmcMSIET7+/v6BXbt2bVdcXCwAQEJCgioiIkITEBCg1+v1usTERBUAvPrqq+5BQUE6jUajnz17dmtrHifRn1WDVkwkSbp5c64gCCsBRNewWiaA6vcGeN5YVlufnwH4DLj+5Pe6iZSIHjZSeQksCT/DHLsH0tlYQJIgeGmvz6pl6AnB/uGY3rYi7zyK0w6jecRUiLLGezXYreNYXIvfhCuHlsH7qQe+xvTQEN19oZwahcqVL8H42Wwonn8fok/THgZ57NgHyMtLrdM+XVw06Nhxzm3XKSsrw9ChQ20EQdB7eXlV7Nmz5ywAJCYmquPj4xPd3d3NRqMRO3bsOOPi4mLJysqSd+7cWTty5Mh8ALh48aLN2rVrz0VERFx44okn2qxevdp5+vTpeSNHjvT7+9//fnns2LH5paWlgtlsFrZs2eJ45swZm/j4+CRJktC7d2//nTt32vfr16+4Tg+ciG6rQRMTQRBaSZKUdePlYAAJNax2DEA7QRD8cD0hGQFgZAOFSEQPEclsgiX1GCy/7YHl1CHAVAm4tIYscgzE0N4Qmz984x9yYzdCkCngEjLU2qHclty2GVzDx+Dq4eUou5wI25aB1g6pwQhuHlBOXXo9Ofn871CMewdi2/bWDqvJqe1Wrm7duhW6u7ubAcBisQizZs3y/PXXX+1FUcSVK1eUGRkZcgDw8PCoiIiIKAOA0NDQ0rS0NNW1a9fE7Oxs5dixY/MBQK1WSwCkXbt2OR44cMBRr9frAaC0tFRMTk62YWJC1LDqLTERBOEbAD0AuAmCkAHgdQA9BEFoD0ACkAZgyo11WwP4XJKkJyRJMgmCMAPAbgAyAF9KkpRYX3ES0cNFkiRIF5Ngjt0DS/xeoKQAUDtC7Njv+rgRb32jGcR+r8zlRSg4FQ0nbV/I1S7WDueOXDuMRF7sBmQf+gS+Qz+1djgNSnBuCeXUKBhXvgTjl/OgGPsmxIBO1g6rXtypstHQ1Gq1pernFStWuOTm5spPnjyZpFKpJA8Pj+CysjIRAJRK5c27KGQymVS1vCaSJGHWrFlZc+bMyanf6InodupzVq6a5riscX5JSZIuAXii2usfAPxhKmEi+vOyXE2/Poj9xI9A7iVAroSo7wqxQx+I7cKtOrVvXbmW+D0sxjK4hI6wdih3Raa0g1un8cjevwQlF4/BzrujtUNqUIKjKxRTlsL4xRwYv54P+cjXIAvqZu2w/lQKCgpkbm5uRpVKJW3fvt3h0qVLytut7+zsbGnZsmXlmjVrmo0ZMya/rKxMMJlMQr9+/QoXLFjQevLkyXlOTk6W8+fPK5RKpeTh4WFqqGMhIj75nYjqSHHaL8j9bT08+r0JuW2zOulTKr4GS9ze6+NG0pMBQYDQNvT6rVpB3SDY2NXJfhoDyWJGXuxGqD1CYdtCa+1w7ppLyNPIPb4O2Yc+hZ/Xlw9ttep+CfbNrs/W9eU8mNYtAJ755/WnxlODmDhxYl6/fv38NRqNPiQkpNTPz6/8TtusXbv2/KRJk3zefPPN1gqFQvruu+/ODhkypDAxMdGmY8eOWuB6VWbdunXnmZgQNSxBkprOePHw8HApJibG2mEQ/elYjGU489VQGIuy4dC2O7wGLr7vE1SpshyWU4dgid0DS+oxwGKB0NofYvvekLWPhODUOJ6CXtcKz+xD+raX4PXk+3DUGaj7EwAAIABJREFU9LJ2OPckL34Lsn58G96DlsKhzZ+zYiBVlML41XxI5+MgH/ISZJ36WzukB5KUlASdTmftMJCQkFBa23TBRPRwiouLczMYDL41tbFiQkQPLOfYahiLsuGk64+CpB3Ii/0Grh3ufs4KyWKGdCb2+riRhJ+ByjLAqQVkj464Poi9pV89Rt845MV+A4VDSzj4d7d2KPfMOXAAco99jSuHPoW9X1cIQkPPRG99gkoNxfh3YVzzOkybPwSMFZB1HWLtsIiIHipMTIjogVQWZiHn2NdwDHgcHn3fgKWiCNkHPrp+S5J77VdcJUmCdOk0LL/tgTnuJ6AoD7Cxg2iIhKxDbwi+IRDEP8cJbvnV0yhJj4F7t79BEB++f5YFmQLNI6Ygc+erKEz9EU4Bj1k7JKsQlDZQPPcmTOvfgmnbvyFVlkPek5NKEhHdrYfvf0AialSy9y8BBKDlo3+DIAho/fjrOLtmJDJ2/BNtRq+DTPn7cSDS/7N353FR1P8fwF+fmT1Y2OW+b5X7DEFU1AyPvFNTyxOvUrOvHZaaWVqWpaZlZqWZad6WpiaeeGaiKYQcgoAoCorc93LszszvD4+feYLuMhyf5+PRI3Z35jOvRZR9z+cqugnu/GHwcYch5F0FWAkYr45g2vYA49kBRPrYuavNUmHcVhCJHKZ+g8SO8tRMPHuh4Ow65EWvhLF7tyZZYOkCkcggGTUX2t8WgjuwGqitBvvi+BY394aiKOpptMzfHBRF6UTltXMoSz8Cq7ApkKpsAdza38Kx7wJk/j4JOYe/gEOfz4GqcvAJx8GdPwLhSgIAgLQKgOTl6WD8u4IYGov5NkSlrSpGacp+mPr0g0RhInacp0YYFtadpiLrz/dQkrwXZn4DxY4kGsJKIHl1NrRSA3BHNwC1VWD7T6XFCUVR1BPQwoSiqKci8FrkHF8CqbE9LIPH/Oc1I8cgWLV/DflnfoJB9nWoMq8DnBbE2gVsr4lgn+sBYm4rUvLGpThxJwSupsksEfw4qjZdobD1Rf7pVTDx6gNG0vJ6v+4gDAvJy9PBSWXg/t4OQVMDyaB3WszwRIqiqKdBCxOKop5KUcIfqCm4BKcBX4GRGgAABJ6HkJkA7t/DME48hgoDFnlCEhTBg6Ho8AqIvRu9a3wPgdOg6Px2GDm3h4FlG7HjPDNCCKw7vYmrO6aiOGEHLNo+bDurloMwDNiXpgEyBbjjm6HVVEMydBYIy4odjaIoqlGihQlFiUgoyYN217cQ1KViR6kXTtAgryYOCsYY8kM7UBv1B4Bb7wel+YBMAdavCxy8Q3Hl1JfIqYhHa+v3aFFyn7JLx6CtyIV99w/EjqIzRs6hMHIKQf7ZX2DmPwiMVCF2JFERQiDp8zogV4A7uAZaTS0kw+c0iw1B9Y1lWbi5uRkQQnwAYPfu3Zc8PT1rxczE8zzCwsI89u3bd8nc3Jx/8hmPFh0drcjKypK9+uqrev8FYGhoGKRWq+MyMzOlU6ZMcTpw4MBlXVw/LCzMY/fu3RlWVlacLvNSLRctTChKJIK6HJo1MyGU5oM4ib9fQH0UVl8DDx5WBp4g7P9/8GScvMH0nQzGJwxEdut5B5UC13ZOw80TX8O+x4diRW6UCuO2QmbiCGXrzmJH0Zk7vSZXto5HYdwWWIVOEDtSoyDpNhqQysFF/gCtpgaS0Z+2yIUe6kOhUGDHjh3Vj9rHRKPRQCpt2ALvt99+M/H19a161qIEAGJiYgxjYmKMHlYY6Ou9ubq6ag4cOHD5SdevqxEjRhQuWbLEatGiRTd1l5JqyWhhQlEiEDS10Kz/CELhDUgnLgLTJkjsSHVWnZ+G0o2jYP7cK1B1m/nE41WtwmARMhaFMb/CyLkdTDx6NkDKxq/qZjKqbsTD9oX3mt2+H4b2AVC27oKCc+thHjAUrEHLXdzgXpIuw0Ckcmh3LYNm7QeQjl0AIm/ZPUr1tXz5cotdu3aZqdVqhuM4cvjw4fTevXu7lZaWslqtlsydO/fG6NGjS1JTU2V9+vRxDw0NrYiJiVHa2NjUHjx48JJSqRSSkpLkkyZNciksLJSwLCv8/vvvl319fWs+/vhjm507d5rX1taSfv36lXzzzTc37r/+pk2bzCdPnlwAAKmpqbLevXu7t23btjI2NlYZEBBQOWHChIL58+c7FBYWStatW3c5PDxcXVZWxkycONH54sWLCq1WS+bMmXNj6NChpV9++aV9dXU14+XlpXzvvfdyUlJSFJcvX5Zfu3ZN7uDgULNt27bMiIgIl4SEBEOWZbF48eKsAQMGlC9fvtxi9+7dpuXl5ZLc3Fzp0KFDC5cuXZoDAJ988onNpk2bLAFgzJgx+XPnzs27N39qaqqsf//+7omJicn3X9/Nza3m3Xffda6pqWEMDAz4devWXQkMDKxZvny5RWRkpGlVVRVz7do1eZ8+fUpWrlyZDQDDhw8vCQsL86KFCaUrtDChqAYm8By0Wz+HcCUBkpEfN6miRBAE5BxbAlaugnXYlDqfZ9PpDaizY3Hj0GdQWHtDZuqox5RNQ2HcVjBSQ5j6DhA7il7YdJqKjA0jUBCzATad3xQ7TqPBdngJkBmAiz0ENJGhjSdjv0J+cZpO27Qy80CX4BmPPaaqqgpDhgwxIIT4ODk51URFRWUAwIULFwwTEhIu2NjYcBqNBnv37r1kbm7O5+TkSNq3b+81cuTIEgC4du2awcaNGy+HhYVd7du3b+v169ebTZ06tWjkyJGt3n///ZsRERElarWacBxH/vjjD+NLly4ZJCQkpAiCgB49erjt379f2adPn4p7M8XGxio7dep09c7jrKwsg23btl0ODg7ODAgI8N60aZNFTEzMxc2bN5suWLDALjw8POPDDz+0Cw8PL/v9998zCwoK2JCQEO+XXnqpbPbs2TdiYmKM1q9ffw0Apk+frkhPTzf4559/LiqVSmHevHk2hBCkpaUlx8XFGfTt29c9IyMjCQASEhKMEhMTLyiVSj4oKMhn4MCBpYQQbN682SI2NjZFEAQEBwd7d+/evbxTp05V939vDQwMhPuvX1RUxJw7d+6iVCrFrl27VDNnznQ8ePBgBgAkJycbxsfHJysUCt7Nzc3v/fffz3Vzc9NYWVlxtbW15ObNm6ytrS0dzkU9M1qYUFQDEgQB2j9XgE86Cbb/m2ADu4kdqV7K0g9DnR0Lu+6z63UXnLBSOPb7EhkbRyB774dwHb4GDNtyx9hrKgtQlnoQZgFDwMpVYsfRCwMrDxh79kJR3BZYBA2HxMhC7EiNBtv2RTBBPemcqyd41FCuLl26lNnY2HAAwPM8eeeddxzPnDmjZBgGeXl5suzsbAkAODg41ISFhVUBQFBQkDozM1NeXFzM5ObmyiIiIkoAwNDQUAAgHDhwwPivv/4y9vHx8QEAtVrNXLx40eD+wqS0tFRiZmZ2dxiXg4NDTWhoaBUAeHh4VHXr1q2MYRi0bdtW/fnnn9sDwPHjx40PHjxounz5clsAqKmpIZcuXXroOL7evXuXKJVKAQCio6OV06ZNy7udv9re3r42MTHRAAA6d+5cdqcQ6NevX/Hx48eVhBD07du3xNjYmL/z/LFjx1QPK0wepqioiH311VdbZWZmGhBCBI1Gc/cHtHPnzmUWFhYcALi5uVVnZGTI3dzcNABgYWGhvXbtmszW1rZO16Gox6GFCUU1IO7YJvCnd4F9/lVIugwVO0698Joq5J5YBgMrD5j5D673+TITezj0nIusyJnI+/t72HZ9Rw8pm4bi+B0QeG2zWCL4cazDJqMs7TDyz66FXfj7YsdpVJpSUfKkno2GZmhoeLcwWLVqlXlhYaEkMTExRS6XCw4ODv5VVVUMAMhkMuHOcSzLCneefxhBEPDOO+/kzJgxo+Bx12ZZVuA4DuztldXuvQbDMDAwMBBuHweO48idtrdv334pMDCw5t62/v777//uPgvAyMioTnNX7v/50cXP06xZsxy6du1aHhUVlZGamirr1q2b553X7v9e3lu01NTUkHv/TCjqWTSvgc0U1YhxMQfAHVwDJqgH2D6TxI5TbwXn1kNTfhO24TNBmKdb7tTYozvMAoeiMHYDyq+c0nHCpoHX1qI4YQeUrTpBbuYsdhy9kpu5wNS3P4oTtqO2LEfsOFQzVFpaylpaWmrkcrmwZ88e1Y0bNx67ooCZmRlva2tbu2HDBlMAqKqqIuXl5UyfPn3KNmzYYFlaWsoAwJUrV6TXr19/4OZtq1atqlNSUuT1yRgeHl62dOlSG56/9dn91KlTCgAwNjbmKioqHvk5rFOnThUbN240B4CEhAR5Tk6OLCAgoBoA/v77b+Pc3Fy2oqKC7Nu3z7Rr164V4eHhFfv27TMtLy9nysrKmH379pmFh4eXP6r9+69fVlbGOjo61gLAqlWrLOvy3nieR35+vtTT07PmyUdT1JPRwoSiGgB38R9od3wF4h4CydCZTW6TtdqyHBSc+xXGni/CyPHZ5sTYdp0OuaU7rh+YC0153pNPaGbK0qKgVRfCIqhl7PFh1eF1AED+mdUiJ6Gao9dee60oPj7eyMPDw+fXX3+1aNWqVfWTztm4ceOV77//3trDw8MnJCTEKysrS/Lyyy+XDRs2rKhdu3ZeHh4ePoMHD25TUlLywB2YF198sfTQoUP1Gn+5cOHCG1qtlnh5efm4ubn5fvTRRw4A0KdPn/K0tDSFl5eXz+rVq83uP2/mzJl5PM8TDw8Pn1dffbXNqlWrMhUKhQAAAQEBlS+99FIbX19f3wEDBhQ///zz6s6dO6tHjhxZ2LZtW+/g4GDvMWPG5D9uGNf91581a9bNTz75xNHb29tHq9XW6b39/fffhkFBQZUNvToa1XwRQRCefFQTERISIsTExIgdg6L+g89KgWbVdBArJ0inLAORG4odqd6yImeh/PJJuI//A1LVs+/YXlN0BRkbR0Nh6wvXoT8+dQ9MUyMIAi5vHgNBU402Y39vUsN5nkXOsSUoOv8b3Mb9DrmZi9hxqDpISUmBt7f4y5gnJSWpH7VcsBiuXr0qHTFihGt0dHS6WBmWL19uce+kdTGNHz/eadCgQSUDBw58ZM8MRd0vPj7eMjAw0PVhrzWt27YU1cTwBdnQrJ0NqMwgnbCwSRYlldfOoSztMCxDx+ukKAEAuXkr2HWfBXV2LPL/WaOTNpuCqpwEVOemwDxoeIspSgDAKnQ8GIkMedGrxI5CUc/ExcVFM2HChIKioiL6+QmAn59fFS1KKF2ik98pSk+E8iJo1tza50M6cTGIylzkRPUn8FrkHF8CqbE9LIPH6LRtU58BqLx2DvlnVsPIMRhGTsE6bb8xKvx3Cxi5CqY+/cSO0qAkRhYwDxqBgrO/oDp0HAysPMSORFFP7bXXXisW8/pvvfVWIYBCMTPc8d577z12sQCKqi9a8VOUHgg1amjWfgCUF0M6/kswlk1z347ihD9QU3AJts+/A0ZqoNO2CSGw6/4BZCaOyN43B9oqUX/X652m/CbK0o/CzG8QGGnL21TPMmQMGLkKuad+EDsKRVEU1UjRwoSidEzQaqDZMA9CTgYko+eBcRJ/nPbT0FaVIC96JYyc2kHlrp/9VliZERz7LwRXXYLrBz5Bc5rzdr+i+O0ABJg/94rYUUTBGhjDsl0EKi6fhPpGgthxKIqiqEaIFiYUpUMCz0O7/SsI6TGQvPw+WK8OYkd6annRK8HVVMA2/H29zodQWHvC5vl3UXHlbxT+u0lv1xETr6lGccIfULXpCpmJvdhxRGMRNAKsoTly/17RrItQiqIo6unQwoSidIg7sBp8XBTYXhPBtusjdpynVp2fjuKEHTAPHAoDSze9X8/8uVegavMC8k5+h6qbF/R+vYZWenE/uOrSFrNE8KMwUgWsQidAnR2LymtnxY5DURRFNTK0MKEoHdGe2gHuxFYwHQeCDR8ldpynJggCco59BVauglXHyQ1yTUII7F+cC4mRJbL2zgZX03wWeREEAYVxW2Fg5QFDx7ZixxGdWcAQSFU2yPv7e9prQj2WUqkEAKSmpspWrlz5xNVDUlNTZe7u7r56D0ZRlN7QwoSidICLPwZuz/dgfLtA8tK0Jr0UbFn6YaizY2HdaSokCpMGu65EYQLHfl9AU3YTN6IWNJsPreqsGNQUXGpxSwQ/CiORwarjZFTlXkB5xgmx41BNQHp6unzbtm1Nb1lDiqLqjRYmFPWM+Iw4aLd9CeLiB8mIOU16s0BeU4XcE8tgYOUBM//BDX59Q/tAWHeagrK0KBQn7mzw6+tDYdwWsApTmHj1FjtKo2Hq0w8yMxfknfoBAs+JHYdq5ObMmeMQExOj9PLy8vn000+tU1NTZcHBwZ4+Pj7ePj4+3lFRUUb3nxMSEuIZHR19d/m74OBgz9OnT7e85fAoqomh+5hQ1DPgczKg+fVjEAt7SMcuAJHKxY70TApiNkBTfhMOfT4TrcCybDcOlddicPPYEhjaBzTIHBd9qS29jvKMv2DZfgIYSdP+2dAlwkhgHTYF2XtnozT1IEy9+4odiXqMg3FfIbckTadt2ph6oFfQjDodu2DBgutLly61OXbs2CUAKC8vZ06ePJlmaGgoJCYmykeMGNE6KSnpP7vDjx07tuDnn3+2DAsLy0pISJDX1NQwHTt2rNLpm6AoSudojwlFPSWhOBeaXz4A5IpbGygaqsSO9Exqy3JQcHYdjD1fhJGIcyEIYeDQZz4YuRGy984Gr2m6nyWKzm8DGAbmAUPFjtLoGHv0gIGVB/KjV0HgNGLHoZqQ2tpaMnLkSFcPDw+fYcOGtcnIyHhgk6Vx48YVHz582KSmpoasXLnScuTIkXQjQIpqAmiPCUU9BaGy9Nau7rVVkL7xHYiptdiRnlnuX8sAAtg+/7bYUSA1soRjn89wdcf/kHPsKzi8OFfsSPXG1apRnLQbxu49IFU1/Z8PXSOEgXWnqbi26x0UX9gD84CXxY5EPUJdezYayoIFC2ysra01O3bsuMLzPBQKRfD9x6hUKr5Lly5lmzdvNv3zzz/N4+LiksXISlFU/dAeE4qqJ0FTA82vcyAU50A6dgEY21ZiR3pmlVkxKEs7DMt24yBV2YodBwCgdOkAy9BxKEnajdKLB8SOU2+lyZHgaypa/BLBj6Ns1RkKuwDkn1kNXlMtdhyqkTIxMeEqKiruji0tLS1l7ezsNCzL4ocffrDguIfPU5oyZUrBrFmznAIDAyutrKzoZCaKagJoYUJR9SBwHLSbP4NwLRmS4XPAtA4UO9IzE3gtco4tgdTYDpYhEWLH+Q/rsClQ2AfixuEvUFOcJXacOhMEHoVxW6Gw8YXCzk/sOI0WIQQ2nd+EtiIPRQnbxY5DNVKhoaFVLMsKnp6ePp9++qn1O++8k7dlyxYLT09Pn4sXLxooFAr+Yed16dJFbWRkxI0fP54O46KoJoIO5aKoOhIEAdrd34JPPgXJwLfA+ncVO5JOFCf8gZqCdDj1XwxG+sBQbVERRgLHvguQsWEEsvfNRqtXfwEjkYkd64kqMs+gtvjqrUUE6BLBj2XkFAIjl/YoOLsWZv6DwcoeWGCJaqEqKiqQlJQEuVwunDlz5j+z79PS0u4Ozfrxxx+vA4Cnp2dtenr63R1aMzMzpYIgkMGDB5c1XGqKop4F7TGhqDrijmwA/88esOEjwYY1/FK6+qCtKkVe9EoYOYVA5d5N7DgPJTO2g0OveajOTUHu39+JHadOiuK2QGJkAWOPnmJHaRJsOr0JrqoEhf9uFjsK1UysWLHCokOHDt5z5869zrJNdwl3imppaGFCUXXAnd0LLmotmOBeYHu9JnYcncmPXgmuphy2L7zfqO/sG7uFw/y5V1H072aUZ/wldpzHqinKREVmNMwChoJhpWLHaRIUtr5QtXkBhTEboK0qETsO1Qz873//K7x582bChAkTisXOQlFU3dHChKKegEs5De3Or0E8QiEZ0rg/wNdHdX46ihK2wzxwGAys3MWO80Q2z78NAytPXD/4CTTluWLHeaSiuG0grBTmAUPEjtKkWHd6A3ytGgXn1osdhaIoihIJLUwo6jH4q8nQbvoUxN4d0tGfgLDNY1qWIAjIOfYVWLkKVh0nix2nThiJHI79v4TA1SJ73xwIvFbsSA/gqstRkrwHJp69IDGyEDtOk2Jg6QYT7z4oOr8Vmop8seNQFEVRIqCFCUU9Ap9/DZp1swFjC0jHfwkiV4gdSWfK0o9AnR0L605vQKIwETtOncnNXGDX/UOor8ch//RqseM8oPjCn+A1VTAPGi52lCbJuuMkCLwWBf/8InYUiqIoSgS0MKGohxDKCm9toMiwkE1cDKI0EzuSzvCaKuSe+AZyS3eY+Te9Te1MffrC1HcA8v9Zg4prZ8WOc5fAcyg6vw2GDs9BYeMtdpwmSWbqBDO/QShO/AO1pdfFjkNRFEU1MFqYUNR9hOpKaH6ZBVSW3uopsXAQO5JOFcRsgKb8JuzCZ4AwTXO1GtvwmZCZOeP6/o+gVReJHQcAUH75JDSl12FON1R8JlbtXwMIg/zTP4kdhRKZUqms87GRkZGqqKioJ641/c4779jv2rVL9UzBKIrSG1qYUNQ9BK0Gmg1zIeRmQjr6UzCOnmJH0qnashwUnFsHY4+eMHIKFjvOU2NlhnDqvwhcdTmuH5gHQXjo/moNqihuK6QqGxi7vSB2lCZNqrKG+XOvoCRlH2oKr4gdh2oijh49qjp58uQTK5lly5bdGDRoUHlDZKIoqv5oYUJRtwk8D+3vCyFc+heSYTPBeIaKHUnncv/6FsCtFa6aOgMrd9i+MB0VmdEojNkoapbq/HRUZp2DWeArIEzzWCBBTJah48BIDJAX/aPYUahGZvPmzSYBAQFe3t7ePmFhYR5ZWVmS1NRU2fr1661Wrlxp4+Xl5bN3716lvb29P8dxAICysjLG1tY2oKamhgwZMsR17dq1ZgDw/vvv2/n5+Xm7u7v7jhgxwoXnxb/BQVEtHf0NSlG3cftWgj9/FGyfSWDbvih2HJ2rzIpBWVoUrDpOhszYTuw4OmEWMBSV184h99QKGDoEwdDeX5QchXFbQSRymPk3j403xSZRmMEieBTyz6xGVW4KnbMjsu3xXyG7NO3JB9aDo4kHhgbOqPd5PXv2rBg+fPhFhmHw9ddfW86fP9929erV2REREflKpZKbP39+LgB4e3ur9+3bpxowYED5tm3bTLp27Voql8uFe9uaMWNG3pIlS3IAYNCgQa22bt1qMnLkyFKdvEGKop6K3npMCCG/EELyCCFJ9zz3FSHkIiEkgRCykxBi+ohzMwkhiYSQ84SQGH1lpKg7tH/9Bu7k72DDBoPt2vxWVBJ4LXKOLYHU2A6WIRFix9EZQgjse34MqdIa2fs+BFfd8CM0tFUlKE3ZD1Pvvk1qhbPGziJ4FFgDE+Sd+kHsKFQjcuXKFVmXLl3cPTw8fJYvX2578eLFhy6XOGzYsOItW7aYAcBvv/1mPnz48Ac2Wty/f78qICDAy8PDwyc6OlqVlJTUfJZepKgmSp89JusArABw725ZUQBmC4KgJYQsAjAbwKxHnB8uCEKBHvNRFACAO38E3N4fwfh3BTvgzWazgeK9ihN3oqYgHY79F4GRGogdR6dYAxUc+36JK79NxI2oz+DYf1GD/hkWJ+6EwNXQJYJ1jJWrYNluHHJPfovK7DgYOQaJHanFepqeDX353//+5/z222/fHDVqVGlkZKRq/vz59g87bsSIESWfffaZQ25uLpuUlGQ4YMCAsntfV6vV5L333nP5559/kt3c3DTTp0+3r66upsPbKUpkevtLKAjCXwCK7nvukCAId3ZFOwPAUV/Xp6i64C/FQvvbQpDWgZC8+mGTXaXqcbRVpcg79SMMHYNh7N5d7Dh6YWjvD5tOb6Is/QiKE3Y02HUFToOi87/DyDkUBpZuDXbdlsL8uWGQGFki79QKCILw5BOoZq+8vJx1dnbWAMC6devu7mKqUqm48vLyu/+Am5iY8AEBAZWTJ0927t69e6lE8t/7sGq1mgEAW1tbbWlpKbNnz57msyY8RTVhYt4dmABg/yNeEwAcIoTEEkImPa4RQsgkQkgMISQmP5/uFkzVHX/jEjTr54JYOUMa8TmIVCZ2JL3Ij14Jrqb81vLAzbA36A6LkDFQunTEzeNLUZ2f3iDXLMs4Dm1FLu0t0RNGqoBV+4lQXz+PiszTYsehGpharUb37t0VNjY2ATY2NgGffPKJzZw5c26MGDGija+vr7eFhcWdG50YMmRIyd69e029vLx8Dhw4oASAV155pXj37t3mI0aMeGBNcUtLS27UqFH53t7evuHh4R6BgYGVDfneKIp6OKLPu1CEEFcAkYIg+N33/BwAIQBeFh4SgBDiIAjCdUKINW4N/5p2uwfmsUJCQoSYGDol5VGE8iIIxTdBHL1AmJbdYy0U5aD2h/8BjASyN1eAmFiJHUkvqvPTkbFxJMwDhsKu+6NGTTYfWnURMjaMACNXos2ojWCk+h0yfmXrBGgqC+A+fmez7G1rDHhOg0trXwZrYIzWozY26+K6MUlJSYG3t/iLDiQlJan9/PxSxM5BUZTuxMfHWwYGBro+7LUG/3RKCBkHoD+AUQ8rSgBAEITrt/+fB2AngOa3bmsD45KjUbt0LDTfv4nahSOg3f8T+Jstc48AobIUmjWzAK0G0omLmm1RIggCbh5fAlauglXYFLHjNAiJoTkc+nyG2qKryDm6SK/XqspNgfpGPCyChtOiRI8YVgrrsMmozruI8vSjYsehKIqi9KhBCxNCSG8AMwG8JAiC+hHHGBFCVHe+BvAigKSHHUs9mcBpod23Etpf54CY2UEydAYYu9bg/toGzTcTULvsNWhPbINQ2jKGwQm1VdCsnQ2hJBfScQvA2LiKHUlvytKPoDIrBtad3mhRq0UpnUNh2X4CSi7sQUnyPr1dpzBuCxipIUxoElSpAAAgAElEQVR9B+jtGtQtJl59IDdvhdzoHyDwnNhxKIqiKD3R26pchJAtAF4AYEkIyQYwD7dW4ZIDiLrdHX9GEIQphBB7AD8LgtAXgA2AnbdflwDYLAjCAX3lbM6EknxotsyHkJkEpsNLkPR/E0QqA9uuL4SKEvAJx8D9GwVu30pw+1eBtAkC+1wPMP7PgxgYiR1f5wSOg3bzZxCyUyEZ8ykYV3H2vGgIvKYauX8tg9zSHWb+L4sdp8FZd5wEdfa/yDnyBRR2vpCbuei0fW1lIcpSD8HM/2WwcpVO26YeRBgW1p2mImvPDBTGboRlu7FiR6IoiqL0QG+FiSAIIx7y9JpHHHsDQN/bX18GEKivXC0Fn3YOmq0LAE0NJCM+Avvcf1djIkrTW3t2hA0GX5ANPu4I+LgoaLcvBnYtA+MTBiaoJxiPdiASqUjvQncEQYB259fgU05DMvhdsL6dxY6kVwUx66Epy4HrsJ9a5DAjwkjg2HcBMjaMQHbkbLQasQ6MRHeLGxQl7IDAaWAe9KrO2qQeT+UWDmP37sg99T2MnEPpposURVHNUMueAd0MCTwH7aFfoPllFojKHNJpqx4oSu7HWDpC0nMspDM2QPrm92BC+4HPiIP21zmoXTAUml3LwF+90KSX6+Si1oE/tw9s9zFgO7wkdhy9qi3LQcG5dTD26AEjp2Cx44hGqrKBQ69PUJ2fity/lumsXV5bi+L47VC26qTznhjq0QghsOsxBxJDS2Tv/RBc7UNHA1MURVFNmD43WKQamFBeBM2WzyFkxIEJ6Q3JwLdBZHXfTI8QAuLsA8bZB0L/qeDTzoGPOww+5gD407sBc3uwQd3BBPUAY+Wsx3eiW9yZP8EdWQ+mXV+wPceLHUfvcv/6FgBg8/w7IicRn6rN8zBvOxJF/26GkXM7GLuFP3ObZWmHoVUXwoIuEdzgJAoTOPaZj8zfp+Dm8SVweHGu2JEoiqIoHaI9Js0En3Eetd++DuFaMiRDZ0I6bFa9ipL7EVYC1rsjpCM/huzjPyB55QMQC3twRzdBs2Qsar97A9pTOyCUP7A8fKPCXfgb2l3fgvHqAMng6c1+qdHKrFiUpUXBst04yIztxI7TKNh0ngYDay/cODgftWU5z9SWIAgojNsCmbkrjFw66ighVR9GTiGwDB2HkqTdKE07LHYcSo+USuUDzy1evNhqxYoVFgCwfPlyi8zMzLtjjR0cHPxzcnL0esP13utTFKV7tMekiRN4HtzxzeAOrQWxdIBk4ldg7Frr9BpEbgg2uBfY4F4QygrAnT8KPu4wuD9XgIv8AYx7u1u9KL6dQGT63TeiPvjMRGg3fwbi6AnJqLkgbPOeayHwWuQc+wpSlS0sQ8aIHafRYCQyOPZbiMubRiF73xy0GrYKhH26eVNVOQmozk2GXfcPmn2R25hZd5yMyqtncSPqcxja+UGqshU7EtVAZs6ceXcJyY0bN1o+99xzVa6urhoxrk9RlO7RHpMmTKgshWbtbHAH14AJeAHSaSt1XpTcjxhbQvL8K5C9/ROk7/4Ctutw8LmZ0G5dgNrPXoZm6xfgU89C4MRd0pPPvQrNujkgpjaQjv+yURVM+lKcuBM1Bemw6fqu3jcWbGrkZk6w7/Ehqm7EI+/0T0/dTmHcVjByJUy8++kwHVVfhJXCoe8CgNcie/9cuoRwCzJ9+nT7uXPn2qxdu9YsKSnJMCIiorWXl5dPRUUFAYDFixdb+/j4eHt4ePjExcUZ3HvOnTbc3d19U1NTZQDQo0ePNr6+vt5ubm6+S5YssbxzjKGhYdC0adMcPD09fQIDA72ysrIk97e1dOlSSz8/P29PT0+fXr16tSkvL6efqSjqGdEekyaKz0yCZvN8oKIEksHvgmk/oMHv4DK2rcD0fh3sixMhZCaCizsMPvE4+LgoQGkG9rlb81GIg0eDZhNK86H5ZRYgkd7aQNGo+e/hoa0qRd6pH2HoGAxj98cvdtBSmXj1RsW1syg4uxZGTiFQurSv1/ma8lyUpR2BRdsRYGWGekpJ1ZXczAm23WbixsFPURDzK6xCJ4gdqdladuErXCpN02mbbiYeeMd3xlOfP378+OIff/zResmSJVnPP//83ZUQLC0ttcnJySkLFy60Wrhwoc22bduuPq6dTZs2ZdrY2HAVFRUkKCjIZ/To0cW2trZcVVUV07Fjx4rvvvvu+pQpUxy/++47q8WLF/9nLOioUaOK33vvvQIAeOutt+yXL19uOWfOnLynflMURdEek6ZGEARo//oNmlXvAKwU0jdXgO3wkqjDSgjDgGkdCOmQ9yD7aAckY+aDcfUDd3o3NN9NgWbpOGiPboRQ9Gzj++tCqKqA5pcPgKpySMcvBDFvGfMs8k+vAldTDrvwGXSI0WPYhc+A3NwV1/d/DG1lYb3OLYr/HYAA8+foEsGNhanPABh7voi86JVQ59B9eClg5MiRxQAQGhqqzsrKkj/p+EWLFtl4enr6BAcHe9+8eVN64cIFAwCQSqXC8OHDSwEgODi48urVqw+sNx4bG6sIDg729PDw8NmxY4fFnXMpinp6tMekCRHU5dD+vgh88ikwvl0gGTYTRPHg5EAxEYkMrF8XsH5dIKjLwSeeABcXBe7gGnAH14C4+oEN6gnGv6vOezIEbS006z+GkH8N0gkLwTi467T9xqo6Px1F8dthFjAEBlYt4z0/LUaqgGP/hbi8KQLZBz6Gy8srQMiT78/wmmoUJ/wBVevnITOxb4CkVF0QQmDf/UNU3UjA9X1z0HrMZrCy5rc5rNiepWejoRkYGAgAIJFIBK1WS+58zfP83WNqamoIAERGRqpOnDihiomJuahSqfjQ0FDPqqoq5s45DHPr3waJRII7bd1r0qRJrbZv336pY8eOVcuXL7c4ceIE3W2Vop4R7TFpIvjsVNR+Nxn8xTNg+78JyZhPG11Rcj9iqALbvj9kU76F7IMtYHu/BqjLod35za39UX79CFzCCQia2me+lsDz0G77EsLl85C88gEYt5axf4cgCLh5fAlYuRLWYVPEjtMkGFi6wTb8fVRe/QcF59bV6ZzSiwfAVZfCou3D9o2lxMQaqODQ53PUlt3AzaOLxY5DNSClUsmVlpY+cVUTV1fXmvPnzxsBwN9//214/fp1OQCUlJSwJiYmnEql4uPi4gzi4+PrVdWq1WrG2dlZU1NTQ7Zu3Wr+dO+Coqh70R6TRk4QBPBndkO75wdAaQbplOVgXHzEjlVvxMwWkvBREF4YCSEnA/y/UeDOHwGffAqQG4EJ6Ao2qCdIqwAQpn71siAI4CK/B59wHGy/N564oWRzUp5+FJVZMbDrNgsShanYcZoMM//BqLx2FnmnVsLIMRiG9oGPPPbOEsFyS3cYOraMgrepMXIMglXoBOT/8zOUrTrBxPNFsSNROqBWq9G9e3cFgAAAeOONN3LvfT0iIqJg2rRpLjNmzOBjYmJSHtVORERE8aZNmyzc3Nx8g4KCKl1cXKoBYMiQIaU//fSTVevWrX1bt25dHRgYWFmffB988MGN0NBQb3Nzc23btm0rKioqmvfSjxTVAEhT3s37fiEhIUJMTIzYMXRGqFFDu30J+IRjYLzaQ/LK7GY1kVvgOQgZ58HFRYFP/AuorQJMrG5Pmu9Z5xXGtMe3gNv/E9guwyDpP1XPqRsPXlONS78OBSMzQpvRm0AYep+hPriacmRsHAXwHFqP3gyJ4uF/tyqzYpD5+2TY9/wYZv6DGjglVVcCr8WVba+hpugK2ozZSvfxeUYpKSnw9vYWOwaSkpLUfn5+jyw6KIpqeuLj4y0DAwNdH/YaHcrVSPE5GdAsnwI+8QTY3q9DMvaLZlWUAABhWDDuwZC+8sGtTRxHfAzG3g3cyd+hWTYRtcsmQntiK4SSRy8bz/17CNz+n8A81w1s35Y1lKkgZj00ZTm3JrzToqTeWLkKTv2+hKYyHzcOzcejbtIU/rsFrIEJTLx6N3BCqj4II4Fjn88BQcD1/R9B4LViR6IoiqLqiRYmjYwgCODO7YNmxVQINWpIJy2FJHxkvYc3NTVEZgD2uW6QjvsCsjnbIRn4FiA1ALdvFWoXvoran6aDO7cfQlXF3XP4tHPQ/r4YpE0QJMNmNfvv0b1qy3JQcG4djD16wMgpROw4TZbC1hc2naehPOM4is7/9sDrtaXXUZ5xAmYBQ8BI6YI7jZ3M1BF23T6A+vp55J9dK3YciqIoqp7obdZGRKitgnbXt+BjD4K4tYV0+BwQVcubT0eUpmDDBoMNGwyh4Pqt/VHioqDdvhjY9Q0Y7zAwbm2h3bsSxMYV0ojPQCQPrOTYrOWeXA4IgM3z74gdpcmzCB6FyqxzyP3rGxg6BEJh7XX3taLzvwGEgXngUBETUvVh6tMXFZnRyD+9Gkrn9jC0DxA7EkVRFFVHLecWcyPH516FZsVU8P8eAttjLKQTF7fIouR+xNIBkp5jIZ2xAdI3vwcT2h/85fPQ7vwGMDKGdMIiEIOWtTxoZfa/KEs9BMt2Y+k4eh0ghIFD70/BGpgiO3I2uNpb81+5WjWKk3bB2KM7pCqbJ7RCNSZ23WdBqrJB9r454GrKxY5DURRF1REtTBoBLu4wNCumQKgogXTCYkh6jgNh6OIe9yKEgHH2gXTgW7eGek1YCOmkZSDGFmJHa1ACz+Hmsa8gVdnCsl2E2HGaDYnCDI59F6C2NBs5RxYBAEqTI8HXVMAiiC4R3NSwchUc+34OTXnu3T9PiqIoqvGjQ7lEJGhqod2zAvw/e0Bc/SEd+TGIiZXYsRo/QnD59GLwNZUw8xsIU/9BLabnoDhxJ6rz0+DYfyEYqULsOM2KkVMwrDq8jvzTq2DkHILC89tgYOMDhZ2/2NGop2BoHwirDq8h//QqKFuFwdS7r9iRKIqiqCegPSYiEQquQ/PDm+D/2QP2hRGQTvqGFiV1VJkVg9qiTEgMzZH/zxqk/zwAV/94C2WXjjfrlXi0VaXIO/UDDB2DYezeQ+w4zZJV+4kwdAzGjUOfo7YoExZBI0DIAxs+U02EVfsJMLQPRM6RhagtyRY7DlVPSqX4mwgPGTLEde3atWZi56ColoIWJiLgEk+gdvlkCMW5kIz7ApI+k0BYOnSrrkqSI8HIVWg1Yi3cX9sDq/YTUZ2fhqw/30Pa6n7IPfUDaktviB1T5/JPrwJXU35reWD6YVkvCMPCsc/nYA1UkBhZwNizp9iRqGdAGAkc+i4ACEH2/o+b9Y0LqmnRaunPIkU9DC1MGpCg1UD75wpoN34CYu0E2ds/gfXuKHasJoWrqUBZ+hGYePUCI5FDZmwH605vwOP1SDgN/BoG1l4oOLsW6WtewtU/pqEs/SgETiN27GdWXXAJRfHbYRYwBAZW7mLHadakKmu0Gr4OLkNXgmGlYsehnpHM2A723T9EVU4C8s/8LHYc6hnd34NhaGgYBADr16837dixowfP87h69arU1dXV79q1axKtVovJkyc7+vn5eXt4ePh89dVXlgAQGRmpateunWf37t3bODo6+k+dOtXhxx9/NPf39/f28PDwuXDhgvzONaKiolR+fn7erq6uflu2bDEBALVaTYYOHerq4eHh4+3t7bNnzx4VACxfvtwiIiLC+c654eHhbpGRkao7WV9//XVHT09PnyNHjii3bdtm0qpVK19fX1/vcePGOYWHh7s1zHeRohovOsekgQjFN6HZ9CmErItgOw8F22cSiIR+6KmvsrTDELQ1MPUZ8J/nCSOBcZuuMG7TFbVlOShJ+hPFSbuQtWcGJEYWMPUdCDP/QZCZOIiU/OkJgoCbx5aAlRnBOqxlbSIpFrmZk9gRKB0y8eqF8sxTyP9nDYyc28PIMUjsSE3KkqQtSCvL0mmbHsZOeN9PdwtLRERElOzYscNs4cKFVlFRUSazZ8++4ezsrF2yZImliYkJl5SUlFJVVUXatWvnNWDAgDIAuHjxoiIpKemCtbW11sXFxV8ulxckJiamfPbZZ9ZLly61/uWXX7IAICsrSx4fH5+SnJws79Gjh+fAgQMTFy1aZE0IQVpaWnJcXJxB37593TMyMpIel7Gqqopp37595erVq7PVajVp3bq1//Hjxy96eXnVDhgwoJXOvhkU1YTRHpMGwKWcRu23kyDkZUEy+hNIBrxJi5KnVJK8B3LzVlDY+j7yGJmxHazDJsPjtT1wHvQNFDa+KDi3DulrBiJzx5soSzvSpHpRyi8dQ2XWOVh1egMShanYcSiqSbLrNgtSYztc3/8RuGq6hHBz9PPPP19btmyZnUwmEyZPnlwEAIcPHzb+7bffLLy8vHyCgoK8i4uLJcnJyQYA4O/vX+ni4qJRKBSCs7NzTZ8+fUoBIDAwsOratWt3N8caMmRIEcuy8Pf3r3Fycqo5f/68QXR0tHLMmDGFABAUFFRtb29fm5iY+NhdWFmWxbhx44oB4Pz58wZOTk41Xl5etQAwfPjwIv18VyiqaaE9JnokcBy4Q2vAHd8CYu8O6eh5IBZN7459Y1FTnAX19fOw7jytTnMsCCOBqvXzULV+HpryXBQn7UZJ0i5kRc6ExNACpr4DYOY/GDJTxwZI/3R4TTVunvgacks3mAe8LHYcimqyWJkRHPsuwJWtE3HjyBdw7PsFnatVR7rs2XhWEolE4DgOAMBxHDQazd0/xCtXrsgYhkFBQYGE4ziwLAtBEMjSpUuvDRkypOzediIjI1VyuVy485hhGBgYGAh3vuY47m679/+cPO7nRiKRCDzP331cU1Nz9wawTCbjJRL6sYuiHof2mOiJUJoPzerp4I5vAdN+AKRTV9Ci5BmVJO8BCPNUy35KVTaw7jgJ7hP3wHnQMijs/FAQsx7pvwxE5o6pKE07DL4R9qIUxG6Apizn1oR3hv5Co6hnYWjnD+uwKShLPYTS5Eix41BPwcXFpTY2NtYQADZv3myq1WoJAGg0GkyYMMH1119/vezu7l796aef2gBAz549S3/88UermpoaAgAJCQnysrKyen32+eOPP8w4jsOFCxfkWVlZ8sDAwOpOnTpVbNy40fxOmzk5ObKAgIDqNm3a1F64cMGQ4zhcunRJmpCQ8NAdgAMCAqqzsrLkqampMgDYtm0b3VGZokB7TPSCT4uBZusCQFMNyfAPwQbRlX2elSDwKE3eC6VLB0hV1k/dDmFYqFp3gap1F2jK81B8YTdKEnchO3IWWENzmPkOgKnf4EYxx0BTfhMFZ9fC2L07jJxCxI5DUc2CZbuxqLh6BjlHF0Nh/1yj+LtOPZxarUb37t0VAAIA4I033sidNm1afv/+/d08PT19unXrVqpQKHgAmD17tl2HDh3Ke/XqVREaGqpu27at96BBg0rffffdgszMTLm/v7+3IAjE3Nxcs2/fvoz65HBwcKgNDAz0rqioYJctW3bV0NBQmDlzZl5ERISLh4eHD8uyWLVqVaZCoRB69uxZ8f3339e4ubn5urm5Vfv4+Kgf1qZSqRS+/vrrq71793Y3NDTkAwMDK5/5G0ZRzQARBOHJRzURISEhQkxMjGjXF3gO3OH14I5uALF2gWT0p2CsnZ98IvVEFdfO4ur2N+DY70uYeL6o07YFnkPF1TMoTvgD5ZdPAgIHI+dQmPkPhsotXLSVmbL2zkb5pRNwG7+jxWwgSVENQVN+E5fWD4fc1Bmthq8BoauvPSAlJQXe3t5ix0BSUpLaz88vRewc+lBaWsqYmJjwPM8jIiLC2d3dvXrevHl5YueiKH2Lj4+3DAwMdH3Ya7THREeE8iJoti6AcOlfMMG9IBn0NoiM7sytKyUXIsHIlVC16arztgnDQtWqE1StOkFTkY+SC3+iOHEnsvfOBqswuzsXRW7WcEVmZfa/KEs9BKsOk2hRQlE6JlXZwr7nR8iOnIW80z/BpvObYkeiWqBly5ZZbtmyxVKj0RBfX1/19OnTC8TORFFio4WJDvCXz0Oz+TOgqgKSoTPBtusjdqRm5dbeJYdh6tMfjET+5BOegVRpBav2E2HZbhwqr/2DooSdKIzdhMKY9TByCoFZwBCo2rwARiJ7cmNPSeA53Dz2FaQqG1i2i9DbdSiqJTPx6IEK34EoOLsWSpcOMHIKFjsS1cLMmzcvj/aQUNR/0cLkGQg8D+7EFnAHfwGxcIBk4mIwdm3EjtXslKUfeejeJfpEGBZK1zAoXcNu96LsuacXxRSmPgNgFjAYcjMXnV+7OHEnqvPT4NjvSzBS2utGUfpiG/4+1NfjkL3/Y7QZswUShYnYkSiKolo0uirXUxIqS6H99UNwB34G498V0rdW0qJET0ouREJm5gKFnZ8o17/VizIB7hN3w+XlFTByDEZh3GZcWvsyrvw2CaUXD4DX1urkWlx1GfJO/QBDx2AYe9BFEyhKn1iZIRz7LoBWXYCcwwvQnOZcUhRFNUW0x+Qp8FeTodn0KVBRDMmgt8F0GEjXw9eT2pIsqK//C+vO/xP9e0wIA6VrRyhdO0JTWfD/vSj75oA1MIGpb/9bc1HMn34D37zoleBqym8tD0x/pihK7xS2PrAOm4q8v79DSdJumPkPEjsSRVFUi0ULkzrQcDWQsnIIggDu7+3g9q0CTK0hnfodGEdPseM1ayXJe2/vXdJP7Cj/ITWyhFXoeFi2G4vKa+dQnPgHCuO2ojB2Ewwd2sIsYDCM3bvXa05MdcElFMVvh1nAyzCwctdjeoqi7mXZLgKVV88g59hXMHQM0ssQTYqiKOrJ6FCuJ4jNPoQP9vZASXEmtBvmgYv8AYx3R8je+okWJXomCDxKkiOhdG7/THuX6BMhDJQu7eHUfxE8X98Pmy5vQVuRh+v7P0baT32Qc3wpqgsvP7EdQRBw89gSsDIjWIe90QDJKYq6gxAGDr3ng5HIkb1vTqPcbLUlUiqV/3m8fPlyi4iICLoGP0U1Y7QweQJHE09UaysR/ftk8CnRYPtPhWTMfBCF8sknU89EnRULTVkOTH37ix2lTiRGFrBsNxZuE3bCZeiPMHIORfH535Dx6zBc2TYRJcl7wWuqH3pu+aVjqMw6B6tOb0CiMG3g5BRFSVXWsO/5EapzU5B36kex41CNjEZDi1WKagi0MHkCy6tX0bpcgrOqEkgmL4OkyzA69r+BFCfvASMzgqrNC2JHqRdCGCidQ+HUfyE8Ju2HTZe3oa0sxPUDc2/1ohxbguqC/994mNdU4+aJbyC3dIN5wMsiJqeols3YvRvM/F9GYcx6VFw7K3Yc6jGGDBniunbtWrM7jw0NDYMAIDIyUhUaGurZu3fv1q1atfJ96aWXWvE8DwDYtm2bSatWrXx9fX29x40b5xQeHu4GAMeOHTN87rnnvLy9vX2CgoK84uPj5cCtHppu3bq5dejQwSMsLMxz8ODBrhs2bLh75+ill15qtXHjRnoniaJ0iM4xeQLGwQPtLwRgi/RfXFFq4CZ2oBaCq1WjPP0oTLz6gJEaiB3nqUkMzWHZLgIWIaOhzopFUeJOFMf/jqK4LTC0D4RZwMuoKb4GTdkNuA5dCcLQv5IUJSbbF6ajMjsW1/fPRZuIrbQHE8DSxL1ILc3RaZueJnZ4z//xcwerqqowZMgQA0KIDwCUlpayPXv2LH1S2ykpKYrz589fdnV11QQHB3tFRUUpu3TpUvn222+7HD9+/KKXl1ftgAED7q5SEhgYWH3u3LmLUqkUu3btUs2cOdPx4MGDGQBw4cIFw4SEhAs2Njbc3r17ld98843NmDFjSgoLC9nY2Fjljh07rjzjt4KiqHvQHpMnIGa2aDfkOxhIjHA6c5fYcVqMsvTD4DVVMPVtuL1L9IkQBkbO7eDU7wt4TDoAm+ffhlZdjOsH5qHgnzUwdu8OI+d2YsekqBaPkSrg2O8LcFXFuHHoM7qEsIgUCgV27NhRffHixeSLFy8mz549+0ZdzvP3969s06aNhmVZ+Pr6qjMyMmTnz583cHJyqvHy8qoFgOHDhxfdOb6oqIjt27dvG3d3d9+ZM2c6paWl3b0b1qVLlzIbGxsOAPr161eRmZlpcOPGDcmaNWvM+/XrVyyVSnX9timqRaO3Z+tALlEg2PFFnMvaj6GBM6CQ0vkl+vb/e5f4ix1F5ySGZrAMiYBF8Bios2NRfvkkLIJHix2LoqjbFNZesO78P+T+tQzFiTtb/BDLJ/VsiEEikQgcxwEAOI6DRqO5O8ZaLpffrSZZloVWq33s+OtZs2Y5dO3atTwqKiojNTVV1q1bt7sr2xgaGvL3Hvvqq68Wrl692nzHjh3ma9euzdTV+6Eo6hbaY1JHHV0HoZarxr/Zh8SO0uzVlmRDnR0LU5/+zXo+DyEERk4hsO36LqRKK7HjUBR1D4vgUTByaY+bx5egppCO1mlsXFxcamNjYw0BYPPmzaZPKj4CAgKqs7Ky5KmpqTIA2LZtm/md18rKylhHR8daAFi1apXl49qZMmVKwapVq2wAIDg4+OGrmVAU9dRoYVJHrmZ+sFW1xumru8WO0uyVJO8FQGDq01fsKBRFtVCEMHDo9SkYqeLWEsLaWrEjUfeYNm1afnR0tMrT09MnOjraSKFQ8I87XqlUCl9//fXV3r17u/v6+norlUpOpVJxADBr1qybn3zyiaO3t7ePVqt97HWdnJy0bdq0qR49enShDt8ORVG3keY0fjYkJESIiYnRW/tH0jfij8Sv8VGP7bAzbq2367RkgsAj/ZdBkJk6wnXID2LHoSiqhSvLOIGs3dNhETwKtl2nix2nwaSkpMDb21vsGEhKSlL7+fml6KKt0tJSxsTEhOd5HhEREc7u7u7V8+bNy6tPG+Xl5YyPj4/P+fPnUywsLDhd5KKoliY+Pt4yMDDQ9WGv6bXHhBDyCyEkjxCSdM9z5oSQKEJI+u3/mz3i3LG3j0knhIzVZ866CnXuB5ZIEE0nweuNOjsOmtLrMPVpHpPeKYpq2ozbdIVZ4DAUxm5CReZpseNQz2DZsmWWXl5ePp+lMgEAACAASURBVO7u7r5lZWXs9OnTC+pz/q5du1Senp6+r7/+eh4tSihKP/Q9lGsdgN73PfcBgCOCILgDOHL78X8QQswBzAPQHkAogHmPKmAakkpuBn+7rjh7LRJanm62pA8lt/cuMXZ7QewoFEVRAADb59+B3KI1rh+cB626WOw41FOaN29e3sWLF5MzMjIu/Pnnn1dUKtVjh3/db9CgQeU3btxInDt3br16WSiKqju9FiaCIPwFoOi+pwcC+PX2178CGPSQU3sBiBIEoUgQhGIAUXiwwBFFR9eBqKgtQVLOX2JHaXa4WjXK0g7D2KMnGKlC7DgURVEAAEZqAMe+X4CrLsf1Q5/SJYQpiqL0RIzJ7zaCINzZqekmAJuHHOMAIOuex9m3nxOdj01HmBpYIzqTToLXtfL0I+A1VTBrJnuXUBTVfBhYucOmyzRUXD6J4vjfxY5DURTVLIm6Kpdw67bTM916IoRMIoTEEEJi8vPzdZTs0RjCooPLACTnRqOkivbm6lJJciRkpk5Q2AeKHYWiKOoB5kEjoHTthJsnlqG6IEPsOBRFUc1OnQoTQsj8+x6zhJBNT3nNXEKI3e127AA87NP9dQBO9zx2vP3cAwRB+EkQhBBBEEKsrBpmL4gOLi9BAI8zV/9skOu1BLWlN1CZFQNT3wHNeu8SiqKaLkIIHHrNAyM3Qva+D8Fra8SORFEU1azUtcfEiRAyGwAIIXIAfwBIf8pr/gngzipbYwE8bEzUQQAvEkLMbk96f/H2c42CldIJ7pYhOH31T/BCvebOUY9QkhwJgMDEm+5dQlFU4yUxsoDDi/NQU3AJuSe/EztOs0YIwaJFi2R3Hs+dO9dm+vTp9o87JzIyUhUVFWV05/GQIUNc165d+0yL5zg4OPjn5ORInqWNOwwNDYN00Q5FNVd1LUwmAPC/XZzsAXBMEIRPnnQSIWQLgNMAPAkh2YSQiQAWAuhJCEkH0OP2YxBCQgghPwOAIAhFAD4DcO72f/NvP9dohLkOREFlNi4V/Ct2lCZPEHiUJEfCyDkUMmM7seNQFEU9lqp1Z5gHDUdR3BaUXzkldpxmSy6X4+jRo2x9ioKjR4+qTp48qdTF9XmeB8fRVYEpqiE9tjAhhLQlhLQFEATgWwCv4lZPyV+3n38sQRBGCIJgJwiCVBAER0EQ1giCUCj8H3t3HhdVuf8B/POcMzsM+76DgGyKAi64pIYbamqa5Vbdysz8WZreyrLrLdvM0m7Wtczbamp1s80tq+ueluKGICAqq2yyzMAww2zn+f0xgKgoiAMD+Lxfr3nNmXPOnPMdROZ8z7N8KU2ilIZRSkc2JByU0hRK6Zwm7/2UUhpa//jstj5lO+jjmwS52J7VNLEC7aVT9bVLJtg6FIZhmFbxHPo0pG6huLT7ZZhqWRHw9iASiTBlyhTTG2+8cd0kOUVFRaIxY8b0iImJiYyJiYn89ddf7bKysiRffvml+0cffeQZERER9csvv9gDwP79++379u0b4efn16tp68k//vEPz5iYmMjw8PCoZ555xgcAsrKyJEFBQTH33ntvUHh4ePSFCxckTc87cuTIHtHR0ZGhoaHR77zzjlvDeoVC0fepp57y7dmzZ1RsbGxEQUGBCAAyMzMlffr0iQgPD496+umnG1t78vLyxAkJCT0b6qo0xMowd7qW7kKsvuZ1FYCo+vUUwN3tEVRXIOFlSPBLxp95P0Mb+zwUEqWtQ+qyVOn1tUvCRtg6FIZhmFbhRFL4jXsdFzc9hEu7X0HAve912/Fxq1P34JzaupO9hDt6YEnvli8hZs6cabzvvvtcXn755ZKm65944gn/xYsXl44ZM0aTnZ0tGTNmTNjFixfTH3roocv29vbmFStWlALAhg0b3EpLS8UpKSmZp06dkt17772hjzzySNX333/vcP78eVlqamoGpRQjR44M3bVrl31ISIghPz9f+sknn+QkJSXlXhvPpk2bcj09Pc0ajYb07ds3avbs2VVeXl5mnU7HJSYmat5///1L8+bN83v//ffdV61aVTx//vyAOXPmXF6wYEHFm2++2TgQ9tNPP3VJSkpSv/XWWyUmkwk1NTU2nYyIYTqLmyYmlFJ2pXgTg4Im4WDOf5FS+AvuCplm63C6JMGos9Qu6clqlzAM07XI3ELhOWwRSva8hcqTX8M1boatQ+p2lEolpk2bVrFy5UoPuVzeOKjzjz/+cMjOzm780tBoNLxarW724n7ixIkqnucRHx9fV1FRIQaAX375xeHAgQMOUVFRUQCg1Wq5zMxMWUhIiMHb29uQlJRU29yx3nrrLc8dO3Y4AUBJSYk4PT1d5uXlVSsWi+n06dPVABAfH1/7+++/OwDAiRMn7Hft2nUBAJ544omKV1991Q8ABg4cWPvEE08EGY1G7r777qsaNGiQzho/L4bp6lrst0kIGQNLEcSGOiKXAPxIKe00g9Ftxd8pEr6OYTiS+xNLTNqoOnsPBKMWTqx2CcMwXZBL7DRocg+j9OBa2PknQOYeZuuQrK41LRvt6YUXXiiNi4uLmj59ennDOkopTpw4kaFQKFosOSCTyRr3aSiOSSnFokWLip999tnypvtmZWVJFApFs7PabN++Xbl//35lSkpKplKpFPr3799Tp9NxACASiSjHWfIikUgEk8nU2HzGcdx1MSYnJ2sOHDiQtXXrVsdHH300eMGCBaULFixgfQKZO15LY0z+BWAhgP0AVtU/9gNYSAh5r/3D69wIIUgMnIx81VlcUp+zdThdkip9GySOflD49LF1KAzDMLeMEALf0f8EL1NaphA21tk6pG7H09PTfM8991Rt3ry5cUzHkCFDqt98802PhteHDx+WA4BSqTTX1NTwLR0zOTm5euPGjW4NrSw5OTniS5cu3fRmrUql4h0dHc1KpVI4efKk7PTp03Y32x8A4uLiNBs2bHABgA0bNrg2rD937pzEz8/PuGTJkvKHHnro8okTJxQtHYth7gQt9WkcRykdRyn9mlJ6qP7xNYDxANi8rgD6+SdDxIlZJfg2MFQXo7bgGByjJ3TbvtkMw3R/IoUzfMe8An3FRZQeuOPv2bWLZcuWlahUqsbE4eOPPy44ceKEXXh4eFSPHj2iP/jgA3cAmDp1qmrHjh1OTQe/N2fKlCnV06ZNq+zXr19EeHh41L333ttDpVLdNKGZOnWq2mQykZCQkOhnn33WNzY2ttnuXk2tW7cu/+OPP/YIDw+PunTpkrhh/e7du5WRkZHRkZGRUVu3bnV57rnnSlv3k2CY7o00NGs2u5GQVACPUUqPXbO+P4BPKKW92jm+W5KQkEBTUlI6/LyfHl2KzLK/8Hryboh5SctvYAAAZX9uwOXDHyFsznY2TTDDMF1eyf41qDi+CQGT3oWyx122Due2ZGRkIDIy0tZhIC0tTRsTE5Nh6zgYhrGe06dPu8XGxgY1t62lFpO/AfiAEHKWEPJr/SMDwNr6bQyAxMBJqDWokVq8z9ahdBmUUqjTt8POvx9LShiG6RY8Bi+AzL0nLv36Coyay7YOh2EYpsu5aWJCKT1BKR0Ay7TAL9Q/RlBKB1JKj3dEgF1BT48BcJZ74QiradJq2qJTMKgL2aB3hmG6DU4kgd+41yEYdbi0+5+gtNkx1AzDMMwNtDhvNiHEEcCwpg9CiFN7B9aVcIRDYuBEZJb9hQptka3D6RJU6dvAiRVwCLtjS+EwDNMNSV2D4TV8CWrz/kLFic22DodhGKZLaWlWrocAnAAwHICi/jECwPH6bUy9gUETAQB/5m2zcSSdX2PtkvCRrHYJwzDdjnOvKVD2GIayg+9DV5Zp63AYhmG6jJZaTJYBiKeUPkkpfa3+MQ9AAoCX2j+8rsNV4YOeHv3xZ97PEFjz/U1VZ++FYKhl3bgYhumWCCHwGf0P8HJnFO5cBsHIaucxDMO0RkuJCQHQ3LRdQv02ponEwMmo1Bbj3OVjLe98B1Od3Qaxoy8Uvqx2CcMw3ZNI7gzf5BUwVOahZP+7tg6HYRimS2gpMXkdwAlCyIeEkBfrHx/B0r3r9fYPr2uJ9RkOhdgBh9kg+BsyVBejNv8YnKImgJAWhzgxDMN0WfYB/eGa8CCqUreiOnuPrcPpkn7//XeeEBJ/8uRJWVvev3HjRqfjx4/f8L2rVq1y/+CDD1xvtJ1hmI7V0qxcX8DSbWs/AH39Yx+ABErp5+0dXFcj5qXoFzAOp4v2otagtnU4nZI6YycACqeoCbYOhWEYpt15DJ4PmUcEin57DcaaMluH0+Xs3LlTFBcXp/nyyy9d2vL+H3/80Sk1NbXZwYxGoxHPPffc5QULFlTcXpQMw1hLi7esKaVV9ZXfV9c/vqaUVnVEcF1RYuAkmAQDjhXssnUonQ6lFKr0bVD4xUPi6GPrcBiGYdodx4stUwib9Lj0y3I2hfAt0Gg0OHXqFPfZZ5/l/vDDDy4AsH37duWIESNCG/Z56KGHAtauXesKAPPnz/ft0aNHdHh4eNTcuXP9fvvtN7vff//d6aWXXvKLiIiISk9Pl/bv37/no48+6h8TExP52muveS5evNhn+fLlngCwevVqt5iYmMiePXtGjRkzpkdNTQ1r1meYDiZq6xsJIWc6W+X3zsDfqSf8nSJwJPcnDO8x3dbhdCq6otMwqArgPuAxW4fCMAzTYaQuQfAe8SyKfnsVFSkb4dbvYVuHdEvWpB7CObV1GxXCHV2xuPeQm+7z008/YdCgQebevXvrnZ2dTQcPHlTcaN+SkhJ+586dzhcvXkzjOA7l5eW8m5ubeeTIkaoJEyaoH3nkkcYbqgaDgaSlpWUAwOLFixvvks2aNatqyZIl5QDw9NNP+6xdu9Zt2bJlrJmLYTpQS9MFT7nBYyoArw6KscsZFDgZheos5Fdl2DqUTqUqfRs4sRzKsCRbh8IwDNOhnGImwSEsCaV//Bu6krO2DqdL2LJlC5KTk00AMHXq1MqNGzfesDuXq6urWSqVCg888EDQF1984WRvb3/DpqkZM2ZUNrf++PHj8vj4+J7h4eFRW7dudU1PT2/TuBaGYdqupRaTbwBsQvMzc7H/sDeQ4J+M78+8iyN5PyLAOdLW4XQKltolv8EhfCR4yQ1vejEMw3RLhBB4j1wGbXEaCncuQ8jsTV3mb2FLLRvtobKyEnv27MHx48elK1as6GU2mwkhhE6ZMkUlCFdyDr1eTwBALBbj1KlTGT///LPDd9995/zhhx96/Pnnn+eaO7ZSqWw2aZk7d27wd999dz4xMVG3du1a1/379yvb5cMxDHNDLfWfTAXwDqX0kWsfAFQdEF+XpJAoEet7N44V/AKDuc7W4XQK1ef3WWqXRLHaJQzD3JlEckf4Ja+AQVWAkj1vsfEmN/Hdd9/hwQcfxG+//aa7dOnSmZKSklQ/Pz+D2WzG+fPn5TqdjpSXl/OHDh1yAAC1Ws1VVlbyDzzwgPqjjz4qyMzMVACAvb29ubq6ulVjRbRaLRcQEGDU6/Xk66+/btNge4Zhbk9L/1kXAai+wbZ7rRxLtzIocBJ0xhqcLtpr61A6BdXZbRA7+EDh19fWoTAMw9iMnX8C3AfOgersdhT8/HeY9TW2DqlT2rJlC+699+rLjEmTJlVt3rzZ5Z577qmKiIiInjRpUkh0dLQWAFQqFT927Niw8PDwqMTExJ6vvvpqAQDMmjWrcu3atV6RkZFR6enp0pudc+nSpUX9+/ePTEhIiAgLC2N3FRnGBgilzfXSqt9IyAwAv1JKu8RUegkJCTQlJcXWYQAABCrg5d2T4Grng4VD19s6HJsy1pTg3IYJcB/4ODwGPWHrcBiGYWyKUorKU9+iZP9qSBz9EDBpNaQuwbYO6yoZGRmIjLR9V+S0tDRtTEwMG7DJMN3I6dOn3WJjY4Oa29ZSi0kAgP8SQg4SQl4mhAwghLCK763AEQ6JQZNw7vIxlNcW2jocm1KdbahdMt7WoTAMw9gcIQSufR9A0H0fwayvwcXND6P6/D5bh8UwDGNzLRVYfItSejeAcQBOA3gUlkrwmwkhDxFCPDsiyK5qYMAEEBD8mbfN1qHYzFW1S5z8bB0OwzBMp2HnF4ceszZC6hyEgp+XoOzwR2zcCcMwd7RWDQijlNZQSn+glD5BKe0L4DUA7gC+bNfoujhnhRciPRNxJO9nCNRs63BsQld8BgZVPpyiWaV3hmGYa4mVXgh6YAOcoifi8p8bkP/TYpjr2LgThmHuTK1KTAghgwkhdvXLswHMAfAdpXRMewbXHSQGTYZKV4qM0j9tHYpNqOprlziEjbR1KAzDMJ0SJ5LCZ/RyeN/9PDS5h3Fx80Ooq7ho67AYhmE6XKsSEwAfAtASQmIBLAFwAay1pFV6ew+DvcQJR/J+snUoHU4w1kGdtRvKsLu7zHz9DMMwtkAIgUuf+xE0bT0EQy1yNj+M6uw9tg6LYRimQ7U2MTFRy/RdkwB8QCn9NwBWeKgVRJwY/QLGIbVoHzT6KluH06FqLlhqlziz2iUMwzCtYufbFyGzvoLUNQQF255F6R/rQIU7syswwzB3ntYmJjWEkBcAzAawgxDCARC3X1jdy6DAyTBTE44W7LR1KB2qKn0bxA7eUPjH2zoUhmGYLkOs9EDQ/RvgFDMZ5X99gvwfn4G57kYlxbovnucxdepUWVhYWHRycnJITU3NTa9ZFAqFVQplZWVlScLCwqKtcSyGYW5NaxOTBwDoATxGKS0B4Afg7XaLqpvxcQxFoHMMjuT+hJvVjelOjDVlqM0/CqeoCbDksQzDMExrcSIJfEf/A94jl6E2/y9c3PQg6srP2zqsDiWXy7F169a67OzsdLFYTFevXu1u65gYhmlfrZ2Vq4RSuoZSerD+dT6llI0xuQWDgiahqPo88qrSbR1Kh1Bl7ACowGqXMAzD3AaX3lMQdP/HEEw65Gz5G9TnfrN1SDYxZMgQzfnz56UA8PLLL3uGhYVFh4WFRa9YscLj2n3VajWXmJgYHhUVFRkeHh711VdfOQGWlpCQkJDo6dOnB4aGhkYPHjw4TKPREAA4ePCgomfPnlE9e/aMWrNmzXXHZBimY4hasxMhZAqAtwB4ACD1D0opdWjH2LqVeL/R+C51NY7k/YQglxhbh9OuGmuX+PaFxMnf1uEwDMN0aQqfWITM2oSCbc+hcPtS1PXLhMfg+SAc3yHnX3P6KM6pK616zHBHFyyO7d+qfY1GI3bv3u0wevTo6oMHDyo2b97sevz48QxKKeLj4yOTkpJqBg8erGvYX6FQCDt27Djv4uIiFBcXiwYMGBAxc+ZMFQDk5+fLvvrqq4uDBg3KGzduXMiXX37pPH/+/MrHHnss6L333stPTk7WPPHEE6zoFsPYSGv72KwCMJFS6kgpdaCUKllScmvkYiXifEcipWA3DCZdy2/ownTFaTBU5cEpmg16ZxiGsQaxvTuC7v8Yzr2novzY58j74WmYdGpbh9WudDodpk6dKuvVq1eUn5+fYeHCheX79u2zHzdunMrBwUFwdHQUxo8fX7V3796rJuMRBIEsWrTILzw8PGrEiBHhZWVlksLCQhEA+Pr66gcNGqQDgL59+2pzc3Ol5eXlfE1NDZ+cnKwBgEcffbSi4z8twzBAK1tMAJRSSjPaNZI7QGLQJPyVvx0nL/0PAwK7b8FB1dltICIZHMJZ7RKGYRhr4XgxfEa+CLlnJIr3vIWLmx9EwMTVkLmHtet5W9uyYW0NY0xiYmJu6fpj/fr1LhUVFaIzZ85kSKVS6uvr20un03EAIJFIGgd68jxPG9YzDNM53PQ/JCFkSn03rhRCyDeEkBkN6+rXM7cg1DUO7nb+OJz3o61DaTeCSQ911m44hCWBl9jZOhyGYZhux7nXvQi6fwOoyYCLW/4GdeZuW4fUYUaMGKHZuXOnU01NDVddXc3t3LnTecSIETVN91Gr1bybm5tRKpXSbdu2KYuKiiQ3O6abm5tZqVSad+/ebQ8An3/+uUt7fgaGYW6spRaTpn1xtABGN3lNAXxv9Yi6MUIIEoMm4ef0D1CmyYeHfYCtQ7K6mgv7Ieg1cIruvi1CDMMwtqbw7oWQ2V+hcPvzKNz5InSlGfAcugCEa21HiK5pyJAh2pkzZ1bExcVFAsCDDz54uen4EgCYM2dOZXJycmh4eHhU7969tcHBwXUtHfeTTz7JnTNnThAhBMOHD7/z5mZmmE6CtGb6WkLIYErpHy2ts7WEhASakpJi6zBuSqW7jJd2JWNU+MOYFPOUrcOxurzvn4K+4iLC5mxj0wQzDMO0M8FsROm+Nag8/S3sAgbAb/wbEMmdbvu4GRkZiIyMtEKEtyctLU17q125GIbp3E6fPu0WGxsb1Ny21l45vt/KdUwLnOTuiPYajL/yt8EsmGwdjlUZa8qgyfsTjlHjWVLCMAzTATheDO+k5+Ez+p/QXjqJi5sehK4sy9ZhMQzDtElLY0wSCSFLALgTQhY3ebwMoGPmKeyGBgVNhrquHGdLD9s6FKtSZeysr13CZuNiGIbpSM4xExH8wH9ABTNyvn4Eqoxdtg6JYRjmlrV0W1sCwB6WsSjKJo9qAPe1b2jdV4zXECilLjiS91OHnbPOZEZWVTVKtC12tW0TSilUZ7dB4dsHUmdWu4RhGKajyb2i0WP2V5B7RuPSrpdQsm8NaDdrmWcYpnu76Sg5Sul+APsJIZ9TSvM6KKZuj+fE6B8wHnvPb0F1XQUcZK5WO7Zab0BOjRa51bWWR00t8qprUaKtAwUg5Ti8mtgLd/m4W+2cAKArSYehMhduo/5h1eMyDMMwrSdSuCDovnUo2f8uKk5sQt3lLPiNXwmRwtnWoTEMw7SotdN3aAkhbwOIBiBrWEkpvbtdoroDDAqajP9lb8TR/B0YGf7QLb2XUopSnf6q5CO3uhZ5NbWo0hsb95PyHAKVCvRydcSEYB8EKBXYci4fLxxOxQvxkZgQ7GO1z2OpXSJltUsYhmFsjPBieN/9HOSekSj6/Q1c3DQb/hPfgdzT9oPZGYZhbqa1ickmAN8AmABgHoCHAVxur6DuBF7KYIS4xOJw3o9ICnsQhJDr9jEJAgo0uuuSj7xqLXRmc+N+DhIxgpQKDPVxR6DSDsEOdghysIOXQgbumuMO9nbD0sOpeC3lLFQGA2b3DLrtzyKY9FBn7oZD6N3gpfa3fTyGYRjm9jlF3wOpWygKfl6CnK8fg8+oZXCKGm/rsBiGYW6otYmJK6X0E0LIwibdu4615YSEkJ6wJDkNQgAsp5T+q8k+wwH8BCCnftX3lNIVbTlfZ5YYNAmbTqxARtlpEHFIY/LRkIgUanQwN5nO2VMuRZCDHSaG+CBQaUk+gpR2cJaKm01smqMQifDO4D5YcSwdH6SeR1WdEQt6h7b6/c2x1C6pgVM0G/TOMAzTmcg9IxEyaxMKtj+PS78sh670LLzuWgTCi20dWot4nkdoaKhMEITo0NBQ3bfffpurVCqF1r5/6dKlXitXriyxdlxZWVmSCRMmhGVnZ6db+9gMc6drbWLS0D+omBAyHkARgDZVRqWUZgHoAwCEEB7AJQA/NLPrQUppt6nSRylFld54VfJxUe2LM+YX8eiBcgDlAACeEPjZyxHkYIfhvh6NyUeggwIKkXUKZ0l4Dq8MiIGjRIxN5/KgMhjwQnwkRFzbpvhVpW+HWOkJO/8Eq8THMAzDWI9I4Yyg+9ah9MBay7iTsnPwv+ctiBSdu8C5XC7H1q1b62JiYjImTpwYvHr1aveXX365tKX3CYIASinWrl3r3R6JCcMw7ae1V7qvEUIcASyBpX6JA4BnrHD+JAAXutPAeoFSlGjrkFtdi5wmg89za7SoNlwZ/yHneQQ6KBBsb4BO9z/MiZ+PMGcX+NvL25wg3AqeEPy9b084SyX4z9mLqDYY8erAXpDxtzYLtFFzGZq8I3Dr/wgIx2aQZhiG6YwIJ4LX8MWQeUag6NfXcOGr2QiY+DbkXtG2Dq1VhgwZoklNTZUDwMsvv+y5adMmN8BS+X358uVlWVlZkjFjxoT37dtXc+bMGbs+ffrU6vV6LiIiIio8PFz39ttvX2rayrF8+XJPjUbDr1mzpmj//v2Kxx9/PIjjOAwbNqx6z549jtnZ2elZWVmSmTNnBut0Og4A3nvvvfxRo0bV2u6nwDDdX6sSE0rp9vpFNYARVjz/dABbbrAtkRByGpbWmb9TSjtVk6nBLKBAo71+/EeNFnrzlZZmZ6kYQUo7JPlZWj8aumB5yKXgCMHFChlW738H9nQAgh0md+hnIIRgTnQInKRirD6ZhWcOnMTbQ/rAXtz6lhl1xq762iXdpnGLYRim23KKHAepawgKfv47cr6ZA++RL8A5euJN37Pm9Elkq1RWjSPMyQmLY/u2al+j0Yjdu3c7jB49uvrgwYOKzZs3ux4/fjyDUor4+PjIpKSkGjc3N3N+fr70k08+yUlKSsoFAIVC4ZyZmXkWsHS/utHx58yZE/zhhx/mjhw5snb+/Pm+Det9fHxMBw8ePKdQKOiZM2ekM2bMCElLS2NV6BmmHbXqCpQQEg7gQwCelNIYQkhvABMppa+19cSEEAmAiQBeaGbzCQCBlFINIWQcgB8BhN3gOHMBzAWAgICAtoZzQ1qTCRfVtVd1wcqr0eKSRoumHV29FTIEOdgh3sOlvuuVHYKVCjhKb/i3EAAQ7NIbnvZBOJL7EwYFdWxi0uC+UH84SsR45Wg6ntybgn/d1ReuMmmL72uoXSL3iYXU2fo/e4ZhGMb65B4RCJm1EYU7XkTR7ldQV5IBz+GLwXWycSc6nQ5Tp06VEUKiBgwYULNw4cLyt99+233cuHEqBwcHAQDGjx9ftXfvXuW0adNU3t7ehqSkpFtq0SgvL+dra2u5kSNH1gLAww8/XPnbb785AYDBYCCPPfZY4NmzZ+UcxyEvL6/lL0aGYW5La2+NbwDwLID1AEApTSWEbAbQ5sQEQDKAE5TS6/qLUkqrIqveHAAAIABJREFUmyzvJISsI4S4UUrLm9n3YwAfA0BCQgK9dvvt2ltYhlePnQUAiAhBgFKBMCd7jPL3RKCDHYKUCgQq7SATta0bEyEEiUGT8GPaeyipyYGXMtia4bfaqAAvOEjEeP7waTyxJwXv3dUXvvaKm76nrvQs9BUX4T1yWQdFyTAMw1iDSO6MwCnvo/TgB6g4vhF15efgN+EtiO3crtu3tS0b1tZ0jElr9lcoFDccGC8SiaggXNlcV1fXYp/p119/3dPDw8O4devWHEEQIJfL41sVOMMwbdbawQwKSunRa9bdbjnZGbhBNy5CiBepnyaKENIfljgrbvN8bdLP0wWrBvXGt2MTsW/KCGwek4g3EntjbkwPjAnwQk9nhzYnJQ0GBEwAR0Q4kttxleCbjcPLFR8Mi0e10YS5e1OQraq56f5V6dtAeCkce47qoAgZhmEYayGcCF7DFsFv3BvQlWbg4lezoS0+Y+uwbmrEiBGanTt3OtXU1HDV1dXczp07nUeMGNHsl5VIJKJ6vZ4AgJ+fn6myslJUUlLC63Q6snv3bkcAcHNzM9vZ2Ql79uyxA4CNGzc2zgigVqt5b29vI8/zWLdunau5yTT9DMO0j9YmJuWEkB4AKAAQQu4DUNzWkxJC7ACMAvB9k3XzCCHz6l/eByCtfozJWgDTKaVWbw1pDQ+5DHf5eiBAaddug9IdZK7o5TUUf+Vvh1kwtvyGdhTj6oj1I+LBE4In9x3HqctVze4nmAyoztwNh7AR4KXKDo6SYRiGsRbHiDEImfE5iEiC3G8fR9WZH20d0g0NGTJEO3PmzIq4uLjI+Pj4yAcffPDy4MGDdc3tO2vWrMuRkZFREydODJZKpXTJkiXF/fr1ixw6dGh4aGhoXcN+69evz503b15gREREVG1tLadUKs0AsGjRorItW7a49uzZMyozM1Mml8tbPVUxwzBtQ1pzvU8ICYGlu9QgAFWw1BeZ1dlm00pISKApKSm2DqNNzhQfwEdHFmHuwNWI9bHm/AJtU6Ktw8IDJ1BSW4fXEnthqI/7VdvV535H4fbnETj137APHGijKBmGYRhrMelUKNz5Imrz/gId8W9E9+kPQtp/lsibSUtL07a2K1dbqdVqztHRUQCAF1980au4uFj82WefFbTnORnmTnb69Gm32NjYoOa23fQvDiFkMSFkMYDJAHYCeB3AR7C0dEy1cpx3tCjPQXCUudm8O1cDL4UMH41IQIijPZYeTsWO3KKrtqvSt0Fk7wE7/342ipBhGIaxJpHcCYH3vg+3fg9DMGhhqMqHYLZtK35H+Pbbbx0jIiKiwsLCog8fPmz/+uuvt7lHCMMwt6elWyHK+kcCgCcBOANwAjAPQFz7hnZn4TkRBgTcg/TSP6DWXbZ1OAAAZ6kEHwyLQ5y7M149dhabsiwNZEbNZWhyj8ApajyrXcIwDNONEI6H59CnwcudIBjrYKjMgdmgtXVY7erxxx+vyszMPJudnZ2+b9++8z4+Prc7hpZhmDa6aWJCKX2FUvoKAD8AcZTSv1NKlwCIB8Dmh7WyxKBJEKgZf+Vvb3nnDmInFmH1kD5I8vPA+6nZ+CA1G6qMXQA1s9olDMMw3RQnlkPqEgSAg6EqDyZt8+MNGYZhrKm1nUc9ARiavDbUr2OsyMM+AKFucTiS9xNsNNa/WRKew4qBvXBviC++ysrDO+erIfGOrf/SYhiGYbojTiyD1DUYnMQOxupiGKqLQCkb/80wTPtpbWLyJYCjhJCXCSEvA/gLwOftFdSdLDFwEso0+bhQcdLWoVyFJwTPxUXgoQAl9osisM5pGvRs6kSGYZhujXA8JE7+ENm5waxVwVCZd0eMO2EYxjZalZhQSl8H8AgsM3JVAXiEUvpmewbWmeRrrqsB2W76+o6ETGSHw51kEHxThBDcW7sfM9XbcUQjxqKDJ6Exsq64DMMw3RkhBGKlByROfhBMehgqrow7ESiFUWCtKAzDWEer5wGklJ6glL5X/+hct/Pb0c8FhzBt3z+ws/BIh5xPKpIj3m8MTl76DTqjpkPO2VqCyQB15i+411uBFQNikFquxvx9Kaio09s6NIZhGKad8TIHSxdejoOuqgCl1SqcV2tQqq1r8b1tOh/PY+rUqbKwsLDou+++O7S8vNxms6307ds3wlbnZpg7iW0nKO8CRnjFIdYlFP84+R98cm57h4z9GBQ0GQZzHY4X7m73c90KzcWDMNep4Rw9AaMDvPDOkFjk12jxxN4UFNU2W9+KYRgbo2YKau48Y9aYrk1PxKiU+aBQ7IVKE4GMGuEsEbfLueRyObZu3VqXnZ2d7uTkZHr77bfdW35X+zh58mSmrc7NMHcSka0D6OyUYgU+GPAMVpz+HOuyfkCxrgJLe82GqB2nyQ10joa3Qw8cyf0JQ4I7T7mYqrPbILJzh13AAABAopcb3h8WhyUHT2HunmP4111xCHW0t3GUDMMAAKUUuhQzVP/VQ6gFwAFEAhAJAZEAXJNlIiEgYoBI61+LG9YDXNN9rnq2LDc9DnhLtx+me6GUQmM0obLOAK3JDI4ATjIJHMwakNrL4KABJO07UefAgQNrU1NT5QAgCAKefPJJvz179jgSQuizzz5b/Pjjj1dt375d+corr/g4ODiYsrKyFBMnTqzs1auXbt26dZ56vZ788MMPF6Kjo/WbN292XLlypbfRaOScnZ1N33zzzUV/f3/T4sWLfQoKCiR5eXnSoqIiybx580pfeumlMgBQKBR9tVrtSbVazY0dOzZUrVbzJpOJLF++vGj27Nmqdv3wDHMHYYlJK0h4MV7tOwfecld8en4HyuqqsDJ+HhQiWbucjxCCQYGTsPXMGhRVX4CPQ492Oc+tMNVWQJNzGG4JD15Vu6SXqxM+GpGAhQdP4sm9KXh7SB/0cXOyYaQMw5hrKFRf66E7ZYYkmIMshgc1ANRAG58FA64sq+mVbcaGfdpw4obkR0xApFeWr0uCJNcmSTdKkJrs07BOxBKfjmIWKNQGA95LTUdudQ0ICMQcgYgjAOr/HQQTQMoBcmuF0sOdHPFMn5hW7WsymbB3717lY489Vg4AX375pdOZM2fkGRkZ6cXFxaL+/ftHjh49WgMAmZmZ8rS0tHQPDw9TYGBgL6lUWn7mzJmMV1991WP16tUen376acGoUaM006dPz+Q4DmvWrHFbsWKF14YNGwoB4Pz587LDhw9nqVQqPjIyMubZZ5+9LJVKG5scFQqFsGPHjvMuLi5CcXGxaMCAAREzZ85UcRzrgMIw1sASk1YihOD/IqfAW+GKlWe+wuOHV+G9/gvhJnNsl/P1DxiPH9PW4kjuj5jae0m7nONWqDLra5dEX1+7JMTRHh+PSMDCAyexcP8JvDGoNwZ7u9kgSoZhdKdMqNqih1AHOEwSQzlSDMLd+sU8FSioCdclNFc/A0LTdUaA6q9+LRgs64Qa2uz7bxVnD/AuHEQuBLwLsSw7X1nm7Firze26pNGi2mDEeXUNBApwIJDyPPjmfq5c+11G6HQ6TJ06VVZWVhbbo0ePusmTJ1cDwMGDB5X3339/pUgkgr+/v2nAgAGaQ4cOKRwdHYVevXrVBgYGGgEgICBAn5ycrAaA2NhY3f79+5UAkJOTI5k8ebLf5cuXxQaDgfP3928cKDl69GiVXC6ncrnc5OLiYiwsLBT16NGjcRoyQRDIokWL/P788097juNQVlYmKSwsFAUEBLCZYBjGClhicoumBA6Dh8wZS49/hL8deh3vD1iEYKWP1c9jL3VGb5/hOJq/A5NinoaIa58+vK1BKYUq7WfIvWIgdQludh9vOznW352AZw6exHN/nMZL/aKQHOjdwZEyzJ1L0FKovtVDe8wMsT8H94ekEPu0/S4u4eq7Z0mAxrvjVkYpBRqSFyMF1eP6lhs9IDQs11GYqyhMlRTGYgF16Zbk56q4JWg2YWlMZBwJCM8Sl2tRSnGqXIWvz+XjQNFlvBHiCj+xGC4yMf7Zv69NYmoYYxIYGJg1fPjwsJUrV3o0dK26kaatGxzHQSaT0YZls9lMAGDBggUBCxcuLJk1a5Z6+/btyhUrVvg0936e52Eyma76ZVm/fr1LRUWF6MyZMxlSqZT6+vr20ul0rLmEYayEJSZtMMSzNzYMeg4Lj76HR/54E2v6LUCca0+rnycxcBJOXvodZ4oPoK9vktWP31p1ZZnQV1yAd9ILN93PWSrBv4fF4/nDqXjlaDpUegNmhAd2UJQMc+fSpZtQtckAoYZCOU4Mh7HiLnHxTQgBJADfxuSHUgqhFjBXCjBXWhIWc6XQmLzo8s0Qrp3ckAN4R0uSIqpPWnjn+mVXyzIn7fw/O2sxmAX8XlCCr7MLcE5VAweJGA9FBMGdN8DXXm7r8AAASqVSWLt2bf60adNCn3/++bK77rqrZsOGDe4LFiyoKCsrEx09etR+7dq1BQ1jUFpSU1PDBwQEGAHg888/d72VWNRqNe/m5maUSqV027ZtyqKiIklbPhPDMM1jiUkbRToF4bMhL+Lpv97D/D/X4JU+j2KM7wDrnsNzIJzknjic+6NNExNV+jYQXgLHnqNb3NdOLMKaIX3w8tE0vHc6Gyq9EfNierCuFQzTDgQdhfp7A2oPmyDyJnCbJ4MkwGYzqnY4Qgh4e4C354EbjL0WDBTmSgpzlVCfuND6JEaA/qIA83EzcE0ZDs7O0l2sMXlx5q5KZDj7rt9drLLOgB8vFmLrhUJU1BkQpLTD0vgIjA3whkzEIyMjw9YhXmXw4MG6iIgI3ccff+zy5JNPVh4+fNg+MjIymhBCX3nllcKAgABTampqq461bNmyohkzZvRwdHQ0DRkypCY/P1/a2jjmzJlTmZycHBoeHh7Vu3dvbXBwcPvMlcwwdyjSEdPfdpSEhASakpLSoedUGzRYcuwDnKzMxtOR9+GhHmOt+oW1LX0ddmd9ilfH7oCzwtNqx20twWzEufVjYBc4AP7jW19T00wp3jmRiR8uXsLEYB88FxcBERscyDBWU3fOjKqNepirKOxHiuE4Xgwi7toXy7ZABQqz+uqEpXG5yrJMrynVRMT13cWcCUT1CYwlcbG0uPDOnbe72Hm1Bt+cy8fu/BIYBAGJXq6YHhaA/p4uV313ZWRkIDIy0oaRWqSlpWljYmI6V5bEMMxtOX36tFtsbGxQc9tYi8ltcpTY498Dl+DlU59gbcZ3KNZV4NmYmeCJdS7CE4Mm4pes/+DP/G1IjphjlWPeiobaJU5R99zS+3hC8FxcBJykEnyWkQO1wYgVA2Ig5e+cu7kM0x4EA0X1jwZo9psg8iBwXyyDNIT9v2orwhGInAlEzgCamQCRUgqqRWPCYqpvfWlY1p0xQ6i55gYfudJdjHchEDlfk7y4EHCyjktcBEpxuLgcX2cXIKWsElKew/ggb9wfFoBgB7sOi4NhGKYlLDGxAikvxutxc+Etd8UXF35Bqa4Sb8Q9Abmo1a3DN+Rm54dw9wT8mfczxvR8FJyVEp7WUp3dDpGdG+wDb72bGiEET8T0gJNUjHdPncPig6ewanAs7MTs145h2kJ/0dJKYiqjsB8ugsMkCThJ57wz310QQkDsAIkdD/g3vw81UpiqGlpdmnQZqxJgyBWgO2kGzNccVwZw9gS8PQHX5MHb48pruyvbifzWu49pTSbszC3GN9kFKNBo4S6XYn6vUEwK8YVjOxVFZBiGuR3sCtFKOMLh6ahp8JK74u20zXjiyNt4t/9TcJXe/nTCiYGT8UXKSzhffhzh7v2sEG3rmGorUHPxEFzjZ19Vu+RWPRAWAEeJGK8eO4v5+47j3aF94SJj4wUZprWokUK9wwjN70bwzgRuC2WQhbNWks6CiAnEHgRiDwC4/t+FChRCdUNrS/0AfRWFWUMhaCxdyYyFAswaCtxo0lmuIWGBJVmxI+CUVycvDdsreAO+Ly7ED/mXoDGaEOXigFcHxGCEnwfrUsswTKfGEhMruz/4bnjKXfDC8fV45NAbWDvgGQTZe93WMfv43o1vT9vjcO6PHZqYqDJ/uWHtkls1NtAbDhIxXjiSirl7j2HtXXHwsescM74wTGdmyDej8gs9TCUUdoNFcJwi6dBuQMztIxwB70TAt1B7llLLeBahtj5hqU9cBA3qnynM9duMRYJlnRZAM0NFJ8EHyWIv8PYEMgcefBZBtb0RnH0zLTV2BLySgMjQppo3DMMw1sISk3YwzKsP1g96Fs8cXYtHD72BNf2fQh+XsDYfT8LL0M8/GUdyf4Y2tgYKidKK0d6YKn0b5F7RkLmGWOV4g7zd8P5dcVhy6BTm7jmG9+6KQw9He6scm2G6G2qiqP7FiJrdRnBKAtf5Usij2Z/s7owQS3LAyQjQyklsjUYzDlwox68ZJSgrr4OnIMNgRzfE2znDRS+pT3AAc/WVZOba2i+NOFhaYuwB8ygK02UB4ADwAOEA8KT+uf41xxIZhmGsi33LtZNeziH10wn/C08eeQev9X0cST4JbT5eYuAkHLj4X6QU/oK7QqZZMdLm6cqyoC/PhnfSUqset7ebEz4akYBFB05i3t4UrB7SB73dWriNyDB3GOMlAZUb9TAWCFD0F8FpmgScgl0AdnXldVocKM7B3qIcVNTVYrhPCMb6hyHA/tb/Bqr1Bvx48RK+u1CIyzo9AuwVuH+EP8YFeUMhuvlXu2CgEGqopWWmhsJce6VFpqGlBqgvcinAMp0yBZptmuEATk4gcmNdxBiGuX1suuB2VqWvwZJjHyC16gKeibofs3q0XAukOZRSvLlnBnjC4/m7N1k5yusV730HVanfIXzubojktz9O5lpFtTosPHASZbo6vJnYG4O83ax+DobpaqiZouZ/RlTvMIKTAc4zpJD3YfePurJLtdXYV5SDfUUXkVpZAgrAz84B7jI7nKooBgUQ4+yBsf7hGOUXCmfpzbu45lTX4tvsfOzMK4beLKCfhwumhwcg0csVnBWnqm86XTClFBBgSVLMsCybr6wjIoBXWj8xef311/Hpp59SnufrOI7DunXr8pYuXer3zjvvFNx1111aq5/wGqtWrXJXKBTCggULKtr7XAxzJ2HTBduQs1SJdYlLsPzkf7Dm7Dco1lXgmegHbnk6YUIIBgVNxn9Pr0Kh6hz8nMLbKWJL7RJ15i4oewxrl6QEAHzs5Fg/IgHPHDyJZ/84jX/0i8LYQO92ORfDdAXGUgFVG/Uw5AiQ9+HhNF0KXslaSboaSiku1lRhX9FF7C3KwTl1OQAgzNEVcyISMMInBD0cLDVDSnUa/FZ4HrsKzuGd1EN498wfGOgRgLH+YRjmHQSZSNx4zL9KK/F1dj7+LKmAhOMwJtAL08MCOqQ7LCHE0n2LB9A4mVf7/m4eOXIE27dvx7fffquLj4/PKC4uFun1+g79D/Hcc89d7sjzMQzDEpMOIeMlWBk/D/86+y02XfwNJbpKvBb3OGT8rc1M1c8/GT+ceReH837E/U7PtVO0gCbnEMw61S3XLrlVLjIJ1g2Px/OHT+Plo+lQG4x4IOwG5ZsZppuiAoVmvwnqnwwgYsDlESnk8XyXryx+JxEoRUZVGfYW5WBf8UXka9QAgN4uXng6JhHDvYPhZ3/9TR5PuT1mh/XB7LA+OK+uwC8F2fil8Bz+SMmDQiTGUM8guEg88VdJDXJrtHCVSTA3OgT39vCDs7R7z2xYXFwMNzc3SKWWafe9vb2vm69s/fr1LqtXr/ailJKRI0eqPvzww0urVq1yv3DhgnT9+vWFALB27VrXlJQUuy+//DJ/3bp1Lh9++KGn0WgkcXFxtV9++WWeSCSCQqHo+9hjj5X9+uuvjjKZTNi+fft5f39/0+LFi33s7e3NK1asKF29erXbZ5995m40GklQUJD+u+++y1EqlUIH/1gYpttjXbk62OaLv2FN+jeIcQ7Gu/2ehrP01gayf3p0KTJK/8Qb43ZDzN9+nZTm5P+0GLqSNIQ/vhOEa//cVW82459/pWHfpct4ONwPcwKUoDo1BG0VBJ3K8qxV1T8a1qlAxHLwjt7gHb0szw5eja85uRO7sGM6PVO5gMqv9DBkC5DF8HCeIQHvxPrqdwUmQcCpimLsLbqI/UU5KKurBU84JLj7YJh3MIZ5B8NdfuvFCwVKsfdSHj7LuIDzKhMAHjxnQIKnPeZG9USUs0eH/G1r2pXr3VNZOKeqserxw52UeKZPzxtu12g0GDJkCKqqqujQoUPLZ8yYUTl+/HhN//79e77zzjsFAQEBxsTExIjjx49nuLu7m4YOHRr+f//3f2VJSUmagQMHRuTn56cBwF133RW2bNmyYnd3d9Pf//53v127dl2QSqV09uzZAQMHDqxdsGBBBSEkftOmTednzpypnjdvnp+Dg4N51apVxU0Tk5KSEt7Ly8sMAE8//bSPp6enadmyZWVW/aEwzB2CdeXqRGaGjIKnzBn/OPkfPPLHG3h/wCL423m2+v2JgZNxvPBXpBbvQ7zfGKvHZ9JWoSbnEFzjZt12UkIFEwRddZPEov75qmTD8vyUVg2x3VB8cQ4oOvoX5pb9AL7pQEvCg1M4NT5E7j1ADVqYyi9Cf/EwqLHuqnMTsexKotKYsDRJYpTuHZJ0MUxzKKWo/cME9fcGgADOsyVQDBSxZLqT05tNOFpWiH1FOThQkgu1oQ5SjsdAzwDM9wnGEK8gOEjafsPobKUaX2cX4H8FpRAoxVAfT0S4iJGhKsDh0gwc2Z+OYKUzxvqHYYxfGHzsHKz46ToXe3t7HD9+HJ9//rk+LS3N9PDDD/dYvnx5YcP2Q4cO2Q0cOLDGx8fHBAAPPPBA5f79++0ffPBBlb+/v/5///ufXXR0dN2FCxdko0aN0qxcudI9LS1NERsbGwkAdXV1nIeHhwkAxGIxnT59uhoA4uPja3///ffrfrDHjx+XL1++3Lempoavra3lhw0bpu6YnwTD3FnYlZkNJPkkwE3mhGeOvo+/HXoD/+q/EL2cWzclb0+P/nBReONw7k/tkpioM3cBghlOUVfXLqGUghq0lqSi9kqrRWMLRv06c0PLhk4FqqtGs7O4ACBSO3ByJ3AKZ3BKdyg8w7BELoObsRpbMAD6wIFYHuEKmb2LpfVDprzhRRul1HJudQnM6mKYq0uuLKuLYSzJhKCtuiYADrzS/frEpWmri0RhjR9pl0cpBa2rua71ytxMixY1GyFy8YfINRhit2CIXIMgcg0EEcts/TE6DVOVgKpNBugzzJD25OA8WwqRC2sl6axqjQYcLs3H3qKLOFyaD63JCDuRBEO9AzHcOxiJngGQi9peRd0kCDhQdBlbzuXjTIUaChGPaaH+mBbqB1/7hr9B0VAb6vC/Sxewq+AcPjx7FB+ePYo+rt5I9g9Hkm+P20qIWnKzlo32xPM8BgwYIDz22GNFvXv31m3cuLFVkyhPmzatcsuWLc4RERF1ycnJVRzHgVJKpk2bVvHvf//70rX7i0QiytUXnhSJRDCZTNd92cydOzf4u+++O5+YmKhbu3at6/79+ztm3n6GucOwxMRGYl1C8fmQF/HUX//CE4ffxutxj2OEd1yL7+MIh4GBE7Er42NUaIvgqvBp0/mp2QhBp76uBaPi2OcQy5yhO/gJNE2TD60KMBtuEJSoSWuGM8Se4ZaEQ+EEXu4Ezs75ShKicAIndwQRNd8/eiEAz3P5+Nfpc1iaY8Zbg3xgJ775rykhBLzCGbzCGfCObHYfwaiDUF0KU32yYlaX1CcwxTAUpsKc8RsgmK8+rtwRIgevK60sTRMXBy9wdi5d8g43NembSS6uacVqXGf5/bj2Z9NIJAWvcKr/93UCOBGMJZmoy9xTP4UPABDwTj6WJMUtGCK3K0kL106TK3RGlFJoj5qg+q8BMANOD0hgN0TE6kB0Qiq9DgeKc7G3KAdHLxfAKAhwkcoxxi8Mw32CkeDuCzF3fYX3W1FjMOLnnCL893wBSrR18LWT45k+4ZgQ1PzfPEeJDFOCozElOBqXaquxuzAbv+Sfw5un9uOd1IMY7BmIZP9wDPIKgJTv+l/tWVlZ4JpUqT958qTcz8/PkJmZKQeAoUOH1j733HP+xcXFInd3d9N///tfl/nz55cBwKxZs1RxcXHeZ86cMaxcubIQAMaOHVs9ZcqU0BdffLHU19fXVFpayqvVaj48PPwGX2xX02q1XEBAgFGv15Ovv/7axdvb+0bVYBiGuQ1d/69XFxZg74nPhryAZ46+j2dT1uHvMTMwPTipcTulAqhJD2qsu+oRJwrBLgCHjq/FKOe7QA11oKa6a/bTXf3aVAdq0EEw1ELQVoHWXd9f2EQAowxQUCkMxWctiYWDJ8SePcE3JhdXEhCu/oKUSO2teoE+PTwAjlIxXjt2Fv+3/zjWDOkLF5klkRGogD/KzuDH/IPwkbvh0bDxrRqnw4nl4FyDIHINanY7FcwQNOVXEpfqksYExlRVCH3uMVDDNbNTiqT1iYpXfQJzzXgXB08Qvu13UluDUsHSmqGtqm+taq673NWtW9d9jkYEnNyh8d9X5OwPzrf3df/ejcsKZxCxrNl/e2rSw1SZD1N5DkzluTBW5MBUngN97rGrElzOzgUi12CI3OqTFtdgiN2CwCk9u2TSdyPmaoqqLXrUpZoh6cHBZbYUIg/WStKZlGo12Fdsmdb3ZHkxBFB4K5S4LzgGw7yDEOHsAaOZos4soKi2DjqTGXVmAXqTGXVm85XXZjPq6pd1JrPltdmMOpMAndlcv7+A3Opa6Mxm9HV3wuI+4Rjs4w6+lb/zvnYOeLRnPB4Jj0OWuhy78s9hd2E29hXnQCmW4G6fHkgOCEcfV2+rTiHckTQaDZ566imUlJTIRSJRVFBQkP6LL77ImzRpUg8ACAwMNP7zn/+8NGzYsPCGwe+zZ89WAYC7u7s5NDS0Ljs7Wz5ixAgtAMTHx9e99NJLl5KSksIFQYBYLKZr167Nb21isnTp0qL+/fughSUnAAAgAElEQVRHuri4mOLi4jQajeb2MlOGYZrFBr+3EaUCqFF/5aLfaLnwb22C0HQ/nVGHlQozjkh5TFHX4pHLl0Hqt93IZn+KSgnwfxcA0nTaRsKBiOWWC8ZrHyIZiNQOfNOLzCYJx+VT30CVsR3hc3+BSG77ood/FJfjxSOp8JTLsHJwFFIqTmBLzu/Iry2Fq9QBVfoaKEQyPBY+AdODkiBpxySgoTuTWV1sSV6qS65LYITaa6e6J+CU7uAdvCBqSFquSWA46dVTfVJjnaVbWm1zA/+bGZ+jUzdpmbjm7GJZk2TySjJxdXLRZJ3cAeQ27wK3hApmmNVFMJXnwlRRn7SU58BUkXNVskwkiistLE2fnf3aPdmzNu0JE1Rf6yHoAcd7JLC/m7WSWBOlFHpBaEwG6uoThauWr9tmSRTK63TIr1GjSFuLGqMBoARSXgy5SAoR4SFQoM4koM5svkGn1BvjAMhEPGQ8X//MXbXsqZBhcogvejpbZ5yISRCQcvkSdhWcw76ii9CZTfCU22OsfxjG+oejh4PLLR2v6eD3llBK2+1GQlpamjYmJiajXQ7OMIxN3GzwO0tMWpCb8h+cSvvUcvFHBYBSUNpYBvfWEQ6EcAAhAOHqHwSUcNgtd8cxqROijLWYrK+AuMk+pHHZ8lwMHU7jMvpx3nDj7K9sA8G13w8CJcgT3HHGHAgNlcOPK0cAdxm+XCXExNJFh1KKusvZ4CUKSJz8butnZk1nTR740TASZphhlOyFL6fCIGJCFATUytywm4pwpk4Fb7kLno66H6O8E2x2p52a9DBXl15pabkqcSmGuboUEK6e8ZLIlODt3UGNOktL1o2SUcKBkzs222rBNelKdVXCIb55obbOhFIKobYCporc+laWHBjrl4WaJhPfcKLGMSyWbmFBlmXXIHCSzvV5zRoK1bd66I6bIQ7g4PKwFGIv1krSVmcr1Vh7OhsqvbFJsmFJOG6V5S+EAAGWsuYynoejRAI3uRzOUhlkPAdpkyRCLuItr3nupslG4zaeh5gjNvtbpDMZsb84B7sLsvFnWQHMlCLc0Q3J/mEY7RfWqtnCMjIyENEzHBDMoIK5/tlk6dYpmCEIJtQJddDCCBEnhqtT68ZJ3iqWmDBM98Nm5boNvMQOMpHCcuHP8fVJBQ9w9QkDx1/13LhPw+um21r4krqPUniYTNgBQCtV4m9SGRQ3eE8QFZBRU4Vi3gh/xfWzelEKlJjtccrghdMGL9RQGaQwwYnX4YDJCxQEPAT48tUIFKkQYC6Ah5ALpYM/RLJbu7NmbZRS5AsCDpqMSOOqAcn/IDWOgNQ4Cvfa/4UAcRUACqEmH3dX56GHSImDJl+8cPwjfMTxmO0Rgf7e/eHqGgm5vFVjJa2CiKQQuQRA5NJ8LRZKBQiaisZkxdTQ0lJT1mQyAKfrWrN4hbNl8H87t2bYEiEEvL0beHs3SAMTrtom6DUwVeRZEpb6LmHGyxdQd24/QK+MfeEdvBrHsDQmLq5B4O2cO/rjQHfGhKrNBgi1FA4TxFCOFoPwrJWkrY6WVuD5P1KhlIjQy9UJMhHXmAA0LjdJFKQiHvL6bWKOIK+mCimXC/Hn5TyUaqvBgaCvuzeG+4RguHcwPBXtX6SwI8lFYoz1D8dY/3BU6rX4rfACfsnPwntpR7A27QjilQ4YaSfHEJEJ8jr1VS2xDROYmPs/C2Pp9TfgDByg44E6DhAIwINAQrrv3yaGYToWazHphH4tOoblJ/8DH7kb3h+4CL4K92b3+/b0KvyRsxVvjPsVdhLLIOJSrQ678wuxO78QF6prwBOCQV6eGBvoh8HenpDxPGoMRqRWVOJUeQVOlVcgo1L1/+y9eZQcd3nv/amlq3rfZ98XyRotlmTLsmxjkLxgyTgsCfslvHlznOCQewk4eXNvNm4SQnIPWbgQSELCFpIQCAlgIN5tyQuWbMmWJVuakSXNvnTPdE/ve1X93j+6pzUjjWzJWiyc+Z5Tp/bqqp7qqedTz4YhBJIQ9Pm8bGoIsSlcHcKOi1dNSQgLwyxRMQoYRhHDLFIxihhmdb5QyfPM/AkeiB1nuJjCKSvc6Apxk8ND2VD5enQNGVPjPZ5n6VLGcDkaCHp70VUnVqXIo3NH+Uk+SVaSWVVOcFNhmha7n2BwgFDo1OBwhC/aNa0ITGFxeH6c3TNHOZGO0O4K0uNupMfTQLe7gSaH75K8ORZmBWN+og4r9SE+ijBK9e1kh28prNQGxdtUfYlwEWUVBMl/L5PfZ2Brkwn8oobWcf5Gm7DMRfllhTPyzJYsWyY89Ixtfob/zz+ldPJX+o20W2n+qLSbkCqWhqfa7Miaoz4t2ewYqs6LFcGTuSJPZzIkDAObJHFdoIHtTR3c3NJD0O3/mQsLXFC9SuKyBSsWVc5bBByimGZK8/Kkr589vn6imhfNMtiaGWN7foprKaI5fXWP7HT7Ttas6gNZxcAibxXIGzkMYSBLMg6bB5fmw666LqlnaMVjsqIVvfm0Esr1M6iD8Ve4d/9fo0oqX7j+N1jr7z5jm8nkK/zZ4x/krnW/TVm7gYfGJzk4F0cAG0IBdna2c2t7K3791ctI5jIxHvjne5jo3MUJ1yqOJNL18Ihmu8JVHpXVbkG/o0JQLWGYC1BxCjBOgUahPl8xixhGoQYfRUyztOznF1F4RQszaAuTlzW8VpG15Tn6K/NokoRNdaCqdipygJ8Y7yFuBbnT9SwdlWfJ5Kbrx/G62/EF1vC8sPNIeqbaB0B3cF1hmlJqlIXwO4ejYQmoBIMDOM8CfytaXhXLYP/cMLtnjvJE5CjzpRw2WaHP08RMPkGqUqhv61A0ut1huj1VWOlxN9DtaaDDFUK9BF4gISzMdPQ0WKmOrcKp1gOSzY4a7FoCK2qoBzXY8aoGax0aToOB0nGZzAPNWFkb9k1j2K8eAiv/qnlo1unAUYOMs1bAezXJas0wXybH7CID2OXSf8o9/K28ibUizqfNvbhEGYxTuX3WosIfRdPkoLudfZ5u9ns6yCs6dqvCtZkJbsiMck12Aqd1WiGl+ndmP/O7U5dZVhvk07fTatupy+T2nQP8nKqSuFzPp0UV9BZBCOZZikLJ6hmhnopzafESyeFj0JR5OJHg0dlJUuUSfs3O7e397OxYxfpAE0cHj9DR20yunKJslpAAu82NS/PhsHmQL9M9tQImK1rRm08rYHIB2v/ySzxxwMKuRdG1KLoWQdeiqErqtSKzLlgxS/CdsiAv4D2axKpFoSCGkBmpNPJUwUtc9CFQCchZ1mmTrLVN4VeWr7xkWcZpIFGkUsliLQqJsZCZl5qZlbqYkzuZlbooSdV6+naRodEap0mM0cQkYSWDpurYlCo8qIodW318apm6zLJZo8yD8WGeSAxTtgw2+7t4b8eN3NS4AU11oqp2FHnpQz1XMfj/fnqIF+YSbGsO4bOBZqWRK3OI4iSV/DBWcQKLEkOah2HVhUORuSvQwdv93ShmhUx6lHj8KKnUGKdgJVyHlCqwrF2BldNUMMrsnT3O49NHeDo6RNYoYZcVNrrcbFAteqwEqpnH5+vH5usnrTcQNQVj2RgjmVlGsnNEF4GBIsl0uEJ1z0r3ImhxqpemJ4OZT1QT7xfBihEbwUxHTm0kKSiBdmSnf1nvw+nQICwHIn0P5N8D6hiS/0+RtNPsKMW2yIg904CVTzd+F4xd9SxG8+nLVL1uAAshiBZyDCbiDCXjHE8l0GSFZqerNrhpdlSnfZp+RVY/E0Lw9cER/uHIMDe1hPnstg3Y1TMhNl0u8XSkWtZ33+w4JdPEa9O4OdTM24IhrnW50czzLFLyKhCJsfzLlVeVrCwLPUAdRkQpe9bdJbunXqBCWVK0Yvl8M0k7Pw+GYZnsjU7w4MRxnpgZoWyZuOUS/7t9C129DdgVDZfmw6l5Ud6AprQrYLKiFb35tJJjcgEyLRmBRDK7Gcs61XBPloo1UJlFty1ASxTNFkOSzj8ZczmFZYlf0uG7JcH3yoI7VGiSQhwpt3Gs0kpRaNgp0MAB3uJM0WcrvyYsqYqGXfdhU+yoNUjIHnsEBYXGzR8+AyZsqgNZ1omUZIbSFY4kC7yUCLO/sA4At03l6lCQTeEQ68IhBoJ+bPLZ36QJIdg7d4R/HX6EZ+ZeRpNVdrXfwId6bmOV97WT7l02lc/fvIkvHDrOy/EUI6kyyZJJyfIDfmD9qbvaAq1sYVHiB8USP5opELQKNCoBwo47aOjy4tdU3JSwipNMpY4yOvkNVKpvIh2OMMHgmjqo/FeBFcsyKRRi5HIRoqlxnomN8GwqxmDJoIKEXVTorUTpq0ToMOKoCQtZ1si7mlFVnZmZZ7FqSf6a5uXq0ADbgwOEWjfj9PUzh43R7ByjmTlGs3OMZOZ4MjKEuai6WJPDR4+7gR5PI13uMD01b0vgPI2u06U4AyidAfTOzUuvuVyoJt7XKoUZsRGsUhbF4V++wl3N0DRiTeT2rEPkdRxb4rh3CGTnH5657SUy6OoQEptmMBlnKBHnWGqeRKlaREGRJLo9Pkwh+Gl0kpK5tB+NQ1FPwYrTRbPDRcvCtNNF2O5EfZXf86WQJQR/9eIx/v3EJHd2tfC7WwaWnEOsmOOJmVH2TA9zYG4aU1g02l28s2uAHa29bAq1XLJzPqMaY7mwFGZeK/TOWDQvBJq/bdkS7Et6Pl3ycDMLP2P0ikdJWXuZEy2kWY+JRoEAQrKhoSO48gB2RSta0ZtPKx6Tc5QQglxBMJcQxBIW8aTFXMIilhRkcqe+Q1mGkE8i5JcJB2Qa/DLhQHVes72+f+yDiRi/99z9TGVsSLiwKwpva2tmZ2cH6/06f/DgTrZ1vZMPbv6d8z52ce44J//pgzTv+G1Cmz9wzvvN5PK8GItzKFbNVRnNVN/46bLM2mCAzQ0hNoaDbAgFcaoqBaPEA1P7+PbwI4xkZwjpPt7fvYNf6Np+Tn1IXk1CVHsLJEplUqUKyXKZZKlCsnRqfDwV5XhqjrKloAg7Fhqc5UGryxZuxcRJAZuRxGbMYbdy2MnhtUk0uoO0+FtoD/XQ1biaRm8zymU23i5EhlEkl4vUhhlyuQjZ7Ex9ejaf4KQa4oTazJQaxJJk3KLEgFTkGqed9d5GvO4W3O4WXK5mXK4W7PZTzSZNs0wyeYJ4fJB4/Cjx+CDJ5IklsHIK+KqD3dnCZH6ekcwcI5lZRrMxRmvjwiIPhc/mqIeELfaytDj9ly20BECUBakfl8nuNlBCEsFf1NH7L3GpZSGIFHIMJeJ1CBlKxkmWq2/xFUmi1+tnjT/EgD/EmkCIfl8Ae63ZnhCCZLlEJJ8jks8yk88SKeRq89VlC8dakCJJNNidNDurwNLkXAQuNa/LhXQ9P10Vy+Izzx3h4YkoH17dycc39DOVSzOUnGMoOcfh+Qgvz0cRQIfLx47WXna09jAQaPyZ7dfxRkgIwcj8YfZP3M/zk4+QKydxa36ubb+D6zrvpDuwniODR2np7SFVLlIyq79dt03Dq9nx2LTL8ntTFIX+/n5LkqQSwH333XciGo2qX//610Pf/OY3J15tX6fTuTmfzx+80HM4duyYdtddd606fvz4kQs91opWtKKqVkK5LrFK5SqsxJJVUIklLGIJi/m0YPHX63NLhAMyYX9tXAMXp+PMB2qsUOSRiSkeHJ/kWDKFDISdFabLh7m1vZ3PbP6let+Ob+7/PV6OPMWf3vkwmnJ+yeqRJ/6K+YPfZfXHHrqg3iWJUqkOKS/G4rySSGEBsgR+3SJtTlAUEfp8Dj7afwu3t153SfuOLCfDMvnB+JN85dh9JEpZdjRdxw5fH7nMLJPJGWazMRKlCiVclCQnhhLCUAIUcZIzFcpi+QexJCyccgWvDfy6TtjpJeTy4NdtBHQNn1Yb6zb8uoZft2FXLo0RK4SgVErVIWM58CgW55eevyRTcrQzau9gSPIyZlQD3Fp1Jzc39nF7x7VcHe67IENkKawMMj8/SCJxAqsW869pnjqsLITTeTwdCASzhTQj2QVgqXpaRjJzJMq5+vF1xVb1rCwJCWuk0xVCu8hdsMujJvPfKmFEBa63qvjepSHbL65RLIRgJp9jqAYgg8kqhKROg5ABf5g1gSAD/hD9viD6Bd5XBaNCtJCvQksNViL5XA1gsswW8pinPTP8mr6s12UBYvznGC6Wqxjc+/QLHIql2dhgAznJK6kYOaMKppqssNoX4qbmLra39tLrCVyRYWhXsqKZMfZP3M/+iQeI5SaxyTpXt25na8edDDRtWxI6u7iPSdE0SJeLpMolDMtEliQ8Nh2vZsel2i7Z38HtdrNv377XFcq1AiYrWtGVq5VQrkssXZNoa1Joa1pqFBimYD61CFpqHpaxGRNjUTsLpx3CARmfF5JShiP5KC9kZsjLRQaCfj61cT23dbQS1HW+ecLBl4b+g0Q5wV9s+XW8mosbu9/N/okHeHHqcbZ23nnO5y3MCsnBB3D3vvWCGyoGdJ3tbS1sb2sB4EDsBF8depqDczHipSCy6ESli7E4/FO5yMtzR9kYDrEpHKTZ6XyNo18cqbLC+7p3sKttG984cT/fHn6YZ2IH+W+9b+djmz+OS3VQKmeYmx9kdn6wPk5lqy/mDGyojm4c3rUozh7Kwkm2IpjPZ4jns6QKFqmCk0jKSVHyUJScZw1/sCtyHVICukavz82agIeBgJc2l+OsD3rLMsjn514VPAyjsGQfRbHjdjfjdDYTDF6Fy9WC09lEXHFxIJPh6fgYx9NRMGG1r4WPtaxlR8s6ej2NS87DsgyK5TSFYoJiKUmhVBsXE0zn53guEyVpVnhnuJ+uwGoCvh4C3m40mwtF0erhcAsyzUodVubnq8AyOPivdVix2dyEQmsIBgdoDq1lXcMAnt4b6oncyXKe0cwsI4tCwl5KTPDQ1OFT1y7JtDkDdNVgpcfTWIcXt+38IF5UBOkHKmQerqD4JML/3Y594MIBUwjBdD5bh5ChZJyh5PwSCOnzBnhbS+dFhZDl5FBtdHt8dHt8y643LIt4sXAKXAq5+vRYJsWz0WkK5tJePbqi1LwrblqcLppq8CIhSFUKTOfSHE3EOBpTsYSOkGc5msqxyhdiV8cq1vgbWBNooNcTuCTFEt7syhTnOTD5EPsn7mcscQQJmasat7Jrza+wsXUHDttrl0q2Kyp2h5sGu4u8USFdLpGuFEmViyiyTEBznFNvlIuhn/zkJ56//Mu/bNq9e/eJe++9t3ViYkIbGxvTp6entXvuuSf6+7//+7OLt0+lUvLOnTv7U6mUYhiG9OlPf3r6Ix/5SPLYsWParl27Vm3dujV74MABd1NTU/mhhx464Xa7xVNPPeW8++67uwG2b9+eviwXtqIVrQhY8Zi8IRJCkMoI5pIWs/MmgzMFpmIVKnkbmjj1xkpVBA0BhVDNw9IQkAn7ZZ7L7uePD3+NTlcTX7z+N2hyBPmjh99N0NnMb9z89+d8HpmTTzJ+36fofNfn8fS99YKvy7BM9kQO8u3hRziUOIFLtfPuzpt5f/etNNqDDCaSHIrNczAW53BsnlyNzpqdjlp54iAbwyG6Pe7L8iZ0Jh/jy0M/4IGpfQQ1L/dc9S7e1XnzGcZPqZxhLjG0FFYy4/X1bmczjcEBQr5+7DY3GGWymXFisUFm0xHyOChKTkytCdnVh7C3Y2oNlBQfWVMlXiwxks5Rsaq/Rbcq0+OCDq1AixyjwZpELwyTz8+Qz88hxNI8AV33LwmrWhhXl7Wg634kScISFkcSk+yeOcrumaNM5OJIwIAnzHW+MFe77HhFkUIpSbGUoFCDjgUIKZWXPp9LKIzZfJxUg0QUN0gSMgKHVeGWwjBhqwpILkcjQV8PAW9PDVZ6CHp7cCwK/1pQFVZO1kElHh8kkXhlCawsDQNbi8fTvqTqVNEoV0PBFrwrNW/LeDaOsei7a7B7FoWD1SqGeRoI6Z4zzqs8aZL4VpnKlIVzm4r/vRryMp7O19IChAzWAaQKIekahKiSTJ/Xz5pAqB6S1ecLXBIIuRQSQpCulGuhYjmi+RzT+SzD6QSTuTSxYvGMPBeEjGyFAZV2b4WNYS9r/CHaXJ6618V5EcPF/iuoZBQ4PLOH58bvZ2h2H5Yw6fCt4brOO7m2/Q78jtfOlVvsMfn8wRGOJ3NnbGNaFoawkJDQzvMeXeV38anNPa+6zeJQro6OjtIjjzxy8nQw2b17t/eZZ545lkwmlYGBgfXRaPSQrutiwWNSqVTIZDJyMBi0ZmZm1Ouvv37N6Ojoy8ePH9fWrVu34cknnzx64403Fu68887eu+66K/nxj398fvXq1Wu/8IUvjO/atSv7sY99rP3xxx/3rXhMVrSii6cVj8kVqCkjxYPzkzw6MUWiVMbrs3HrulZ2NLXTiI94zdMylxBMRCxePnHqYS5J63m/+3OMxI/x6eh+fmHNZtYHfoknxv+SuewEDe6OczqHxJEfoziDuLtvuKBryVTy/HD8Kb478hgzhThtzgZ+c90HeWfHW3Av6j6+MRxiYzjER1mFKQQnU+lq6NdcnOeiczw4PgmAX9PYGA7We6ms8nsvSTJrizPMn1zzK3yo9zY+f+S7/OlL/8R3Rh7jk2vfz42N6+vGqa55aG+6jvam6+r7VmHlWB1UZuePMjy5u77e7WyiITjA1d3bq7BiVsimx4nH95Oa/rc6XNjtAfz+PgpanvG8yZThY85oI1pu44jUiiW1AW3Y2UyblqOnWbDaa2cgFKQ/3Irb1YLN5sC0KhRLqSWejOn5I2SnnuJoJs4L2SxHS4KMkJGFoMWa5wZjhg4zijNXhgi8VDt3WVax634cuh+HHiAcWI1DD2DX/dg0L8fKRZ5JT7M/OU5FmHQ4G/lYxw3sattGtlLgtw58iQcVB7/asZWrVZlEaoREeoTB4R9RMU5Vi9M1LwFvdx1YggvgElhFKLSGVaveA4BlVUgmh+v5KvH4IEND38WyqiE+Z8LKAFf5Oljjb13y9zYsk6l8YkkOy0hmjvsnXiS3qNqSW7XT7WlgfaCd7Q1r6X+hjeyDBrJLInSPjmPDuf3bPB1CBhNxjiXjpCvV81YlmX6fn1taO1mzkBPiDZy3gXclyUIwX8wznI4zWMsLeSUVI2/UQvZkhTU+H21OF37VRtmQ2D0jUZKgzZkmX8lz/9gcPx47ueS4TsnEr1QIymXWO2FbyEebv3XZHKf/qjItg2Nzz9W952WzQMDRzG2rPsp1nXfS6u276J+pyDIKly7XxOFw8B//8R/FVwvlevvb3550OBzC4XAYwWCwMjk5qfb19dVrKVuWJX3yk59s37dvn1uWZWZnZ7XJyUkVoK2trXTjjTcWADZv3pwfHR3VY7GYkslklF27dmUBfvmXfzn++OOPL+9CXNGKVnTRtQIml1GT2RwPjU/y4PgkE9kcmixzc2szd3S2c0Nz45JqVt1tS/ctV0QtHGwhNExBiQ+QTMJz+xTgDhq5g6/+W46OxgLhWvL9wtjlYMmD2ygkyQ4/SXDzB1531ZfxbJTvjDzKjyZ+SsEscW3oKn5z3Qd5a/MmlNfIR1AkidV+H6v9Pt7f34sQgolsru5RORSL88R0tYSrU1XYEArWQ7/WBgMXNUdjnb+Hf7jxf7I7cpAvDn6PTzz3f7k+vJZPrn0/q33LQ14VVrbQ3nSqS/npsDI3P8jI5J76epejkcbgAKu63obD5qnBygSp1DBuZ4DrGprZXguz0u0BhGJnIm8xlMxwPCUxnHOxJ6XyaFKG8SIaQzTITxKwJvAZI4TEJB7imEjMKGHGlCYm1EZKkoaKoFcucZtD4mqXm5BjALt+QxVA7IE6hNh1P5ptqcdKCMGhxAnun9zHo6P7SFVyBDQPP9+9nTvbtrHO37Nk+3+++dP8zgt/x5fH9/KBnlv51Lb/jU1WEUKQzUdJpEdJpEdIpEaYT48wOv0Ug8P31fdXFB2/p/MUqNTGPb13LgMrp3JWzoSVq5bkrHi9nXS5w3S5lzbYFEIwV0zXQ8JGM3MMZ2d57uWTXHP4KrJpg+HeGZT3WIS6ln/DK4RgKpdhMDlfD8k6E0IC3NrWXfeG9Hn9VwyEWJaJaZYwar2JzIWS4ka1F9HiebPWn6hcKTJVLDFatBgvw0RFZdrUKFO9JhWTRpFitRWnwZglZMwQtJLIqapncFZq5zH9l5EQ/HzpazTkqz2JLCTykpOM5CWn+MgqQbKyj4zwMIGXl8suvpOwaLGeo884Sa9xAr9UwuVqXuI5XDztdDah/Iw2U3w1CSGYSA7y3MT9HJh4iEwpjsPm4bqOnVzXeSd9oc0XJUn9tTwbb6R0Xa+HfSiKgmEYSwj1K1/5SjAej6svvfTSoK7roq2tbUOhUJABNE1bvK9YWL6iFa3ojdMbBiaSJI0CGcAEDCHEltPWS8AXgDuBPPBLQogXLvd5XqgSpRKPTUzz4PgkL88nkIBrGsJ89KpV7GhvwW07t4elZpNobVBoXeKBtxPJJ/hfT3+T+RSspQW96KJQ3M7BIYPKolBvuw5hv0xzWKavQ8EbexRhGfjX/tx5XY8Qgv3xIb49/AhPRw+jSDI7267nQ723scbXdV7HWixJkuj0uOn0uPm5nk4AZguFJQn1f39kCACbLDMQ8HNzaxPv6OokaL/wnheSJHFLyzXc3HQ13xvdzVdf+TEffvKPeGfHTfzamnfTYA+85jGWg5VyJct0bJDR2CDj88McTk0Qi+yhhE5JsmPaAsi2AVrLGTqLQygzT1IoJeuhSwtqqw3IOgWtn5TSQ1xqY9YKMySux1CrXi9ZMrHIYElpdLXI1oYG7uoa4Kam1dhV7by+k5HMDA9M7eWByWeZLsTQZY0dLZvZ1baN6xvWYjtLCdyA7uFL19/LFwf/nX8ZfpjjqQn+z5Z7COk+PK5mPK5mOlu2LdmnWErVgWW+5mGJxo9wfPwRFnrNSJKM19W6NCQs0Etn163omv3af9kAACAASURBVKcGKyPE40froWDHjn2v3tjTZnMRDF61qFfNAF5vF1gSwbwHX8rN+kQ35ryFERPk9xsYNpNHdjzPNx17yL1UwnlU48am1WwM9uNW/IxkUgwl4xxLzpOpQYhNlunzViFkYAFCfH5srzM/ogoNpyDhXMChUlkeJpbOn1q2AHRnPQckErKfOTnMrBJmTg4TU0JUpGpegQ2DJnJsVlK0KWU6NZMWTUa3OVCUJlS1C1W1I8saSApDeTs/nvDjUQT39qZo1D6CAAQWlrCwhIkQJoZZrvVdKlAxC5hGhpTayFDZx4uZNp4utfG0/lY6bAZr1Xn6SsM4kz+lWIiddgUSDkf4tJDHFtzuU+GPmnZh1QEvp2K5KQ5MPMBzE/cTzYyiyjbWN9/MdR13sq75LdiU8/utv5mVSqWUcDhc0XVd/PjHP/ZMT0+/6pcTDodNj8djPvTQQ+477rgj+81vfjN4uc51RSta0RvvMdkhhDj9CbKgXcCq2nA98Le18RWvomHw1EyUB8cn2ReZxRSCPp+HX98wwNs72mlyOl77IOeoZmeAL9/yK/zPA3/HI3MP0mab4X3Xe1nXfBPp3EKFsKq3ZS5hceiYwYEjBjK30+DpITHZRb9k0hSSXzUUomRWeGjqWb498gjH05MENA93r76L93btIGy/NF7uRoeD2zvauL2j6j5KlcscroHKwbk4X35pkK+8PMTb2lp4V08XWxrDF1wy1CarfLj3du5qv5GvHv8J3x15jIemn+P/6dvJL/btxK5oZCtlkuUiiVKBVLlYn06WiyRPH5eLZCsLRl9TdVj0WHRIFnKlwuGKH2inSzPYFJS5zu+mwxM65cmwV8c21Vn/OyVKOZ6IDPLY9BH2z0YwTSeaHMSlhMmWA1TKgr1TcCg6x1X+IlcFvKwJeFgT8NLpcS77XcWKKR6efo77J/cymBpDRmJrw1ruuepdbG/ZjEs9t3tXlRXuXfcBBnxdfObQP/KLT36GP7/u11nnX/7Nq1330dKwkZaGjUuWG0aRZGa8BivDJNKjzKdGGI/sWwJvTnuYgK+76mXx9tDadQvrNtyNQ/eRmhsjMTZGZmqW4nCWyvMS88US+fIM9hLo5TDSaeEosgccGxW8v+DgVmUTzfOtPDEzwuF4lMcnijw+cRSoFpxucujc2BhmnddLr0unXZeQRblm+I9hxIc4GT03L8Ry4HA6pJ6LZFmr9iNS7SiLehapqh1d99emHfX1iqKjKBqSrGBJMtNlGCuajJVMRgsG40WTcu3dsiZBhy5xoy5os5VpUYoEpDyWWaRiFOoNXGeyxSXNXA2jiCUMxqQN/FT5EF6ivLX0NY6+nOboq91LCz2VFDuSpJArxgiaJW4BMpKPcbmPCbGahypNQCNh/VquCcts8dnotcvIWFRKGfL5WXK5GeLxo4yP7z7je7XZ3GeAyykvTAsOR2hJLtPlVraU5ODUo+yfuJ+T8RcB6A9fw639H2Fz2204Ne8bdm5Xsu6+++75Xbt29a9evXrt1Vdfne/p6Sm+1j5f+9rXRu++++5uSZJWkt9XtKLLrDcs+b3mMdlyNjCRJOkrwB4hxL/W5o8B24UQM2c75qVIfj+WyPKdV2bYGPawqcFLl2f5ikmmEDw/G+PB8Un2TE2TN0waHHbu6Gjnjs42VvkvbYhqxTL408Pf4kcTP2W1rvGt2/562Tfahik4OTTOwccfJu57B/F89bxcDom+DoW+DoXedgVXLbE3Vkzx72O7+ffRPSTKGfo97Xy49zZ2tm1Df4NDI0bSGe4bGeP+sQnS5QrtLifv7OniHd0dhOznVnGpbJokywswUaxOLxpP5ZMMJidJlArIkoYkVM7WPlOTFfy6Hb/mIKDb8Wl2AroDv7Z02r9omSrLCCEYzsyzZ3qE3dMjvJKq/iRW+8LsaO1he2sPvZ5qDH2kkGTP9FEenznKi/FRLAStzgA7apW0NgQ7UCQZw7IYSec4lsgwlEgzlMhwPJmhZFXP3qkqrPZ7WBPw0OtzkDQmeDb2HM/FjmAhWOPr4s62bby9bSsN9gur2HYsNc5v7f8ysVKS39nwi7yz8y0XdDyoVghL56ZJJEdIRqfJRZKU5opYCdDyAZylZhylJpylZjTjNINNFkg+E8OVpqRFycgjJMUgedskeW2WKZedae86pqQQUxWdYu39jYJJIykarTg2kSKFwZTiIKs4kISgzZynrxKltxLFI85u+1ShwXFWcFBqhvgpcNCRZRuSrICkIMnVpq/VbqoCAVjCqjb/EyamqIZlVYylYFBZAB+zWF9XNorMGRqzeIhJIealMPNyCFOqXrMqKgSsOCERI2TNEbJieEUKuebFWgwNC+drW3T+9ena+NlMA9+dCdLnMrl3lYnPbkdVHNjUpdvZlIVGr/oZMCCEoFBKkMnNkMlFauMZpjMxDmVhqOxnmmaEJOMUGTrNk3RZI/TaTXzuZjzOqtdOt3lQZRVJCMxKgWIhXqtsV61uVy5nTvu72XC5ms5aZMLlakJRLtx7u1gVs8RLkafYP34/RyJPYwqDZk8vWzvvZEvHTkLO1tc+yOvU4uT3N1Irnd9XtKI3n67IPiaSJI0ACapxGl8RQvz9aet/AvwfIcTTtfnHgP8phDhw2na/CvwqQGdn57VjY2MX9Tz3TMb53PPDJErVt2sBXeXqsJeNYS+bGjyAySMTUzw8MUmsWMKlqtzS3srOznY2NYRQLmNCphCCe5/6HZ5MzXFNcBV/tfUTeGxnluKNPPF55g9+h9Ufe5CC5WN40uTEhMnwpEmhZk8FggZx+zH2VR4jbhvhLc3r+VDv7VwXWnPFJZmWTJM9UzP8cHiMg7E4iiSxMeznmkYfYbtKqlJa1pORLBXIGcu/jZYAr2avgoRmR5JMRnMTzJcSNNjdvKPjOq4J9dYhw687cCjqRflupnJp9kwPs2d6hMPzEQTg0zQUuUSsNAeU6fM2VWGkdS2rvS3n9LmGZTGayTOUSHM0nuL5uVkmsiWsWn8WCYMGJ1zb0MjWppa6Z+Vi3MPJcpbfff4rPBs7yvu6d/Cb6z541lCwxRKGwEwKjHmBOW9hJhZNzwuMhIDT/4S6AG+JsitFQY+SUceZl46RlE6Q1yMUtXlkRcHv6STg7QFnL6NWAy9nDF5OFylYIGPRRIo2OUOrUqDDVqZNE+i2xeBgR5Z1Jk2L53N5ns9lma5V1+q1O7jG4+Vaj48mm60enmRZBqZVrkNC5SzgUF13al6Is+Hw2SRVjf0FQ191IMt2krKfOeEnItxETAcRw0ZF1Io8SNBhV+hx6vS6HPR7PHS4vNhtzqXAoVSPpyjn1p8Eqv+bvjE4wt8fGeamljCf3bYBu3rp8mtiuSSPTwzyxMwULyZzVEQ1gb5PnaXDOE6w+DKyWHrjOPQAHlcLblczHmcLTnsQm6whI2GZZcrFFPn8qRLd+fwcC2GG9WM4wmcBl+q0pp1Z8e10WcLiROwF9o/fz8HpRylUsvjsYbZ07OK6jjtp962+LP+DV8BkRSta0aXSlQombUKIKUmSGoFHgP8hhHhy0fpzApPFulTlgquJ2UVenEvz4lyaF+ZSRPPV8ByBhYRBl9fObR2NvH9VB17tjfMkTKdP8snHPsaI2k2vp61eTnhBwqzwyj+8A0fr1XS+8y+W7FsxTR44downjkUwEmGC5R4kZGw2QV+7Wveo+D1vbH5gtJDlvtGjDKcTS2AjVS5iWgqScIJwIqEgMBBSDk0tE9Q1/LodX82jsdh7EdAc+GrLAroDj00/oxKYEIJHpvfz14P/wXQhxlsar+aTa99Hj+fc31pWTIvZgkE0VyaSrxDNlUmUTG5s9XB9czXpXAjBsdQ0j88c5ZHJI0zk8kjCgUTVCxTUHdza1sf21h42h1rPuWKZEIKjqVHun9zLw1P7mS+n8agutoW30ekYIF92cCyZ4ZVkhpJZNYQdisLqgKceArYm4KHT43pdsGJYJl8e+j7fOvkgGwP9fG7LxwkKbw0wqqBhzguMGnSYCYGZEqfbfsheCTUooQQklKBcna4NalBGOq3Qw4JK5QyJ9CjR5DAHopO8mMrzStFOgqpHxSXStJrj9Gtp1nsc+B2eRZBQC7Va5G0wjAIVo8jiE0xJLsbUJsaVJmJK1dPktzJ0GlG6zChBK42EhG3BQ6LYawDhWNb4X+pFWMYrscx2qmJnvlxhLJtiJJNgNJPgWDLG8XS83sHbqdpY7Quzxt/AgL+BNf4GOj2+1yxa8XpkCcH/ffEV/u3EBLu6mvm9LWsvSZW9s6lgVNgbnWb39BhPz0ySMyo4VZWt4RBbfBqr9RxGMUomf8r7kslFMMylXi9VseNxtdTypFpwOZrQVDuKpCJZBkY5Vw8Xq/YYitTzmxZks7kWVRILLPEGJStpRooTjBYmyVtFVEmhU2+l29FOk9Zw2TvbO51vp7//1fMGLUuhYjpQFBm/97X7obwerYDJilb05tMVCSZLTkKS/hDICiH+YtGyKyKUa0HpcpnHJ2d4aHySg7E4CJlOt5+Q3U2yKBjNVHs22GSJgaCbTWEvmxq8bAh5cGuXN5Xnz3d/lIlymRetEC7VwRev/w1WeavVpTLDTzL+w0/R8c6/xNu/HYBspcCPJp7mOyOPMZWfo9kR5AM9t7Kr6WZiszonxk1OTpqks9V7Jew/FfbV1apgUy/PA/PIfJR/PXmYx6aGEULQ6fadAgvdUQuXqoZSuW0aJ5MFnp6Z4+X5JIokcXNrM+/u6WJr04U95Etmhe+OPMbXjv+EglniPZ1v5WNXvYug7iVXMYnkKkTyZSK5CtF8hUhuYbpMrGCcbmejKxIlU9DskmnxxhgrHiBSnEeRZK4JdbO9ZS3bW9biUOw8HRllz/QIe2cnKJkGPs3Ozc1d7GjtZWtjO/oyXc4nc3M8MLWPByb3MpaLoskqNzdtZFfbNm5q3IB2WkieYVmM1TwrQ7VQsOPJDMVFsLLK766DypqAly7vmbAiLIGVWfBwVL0cRkIQmZ5nPpIlXAzgqpyWs6KC4q+BR1CuwYaEEpDrMCLZzu9vJ4RgJJNib3SKfdFpDsYilC0LXVa4pqGZrQ2NrHWB24gsqRhWqmSrRv8ir8NSSFi67HRISJoWzyVm2Ts/yUvJCBaCFoefHS1ruaV1HRuCnRcEAoZlMZVLM1qDj5FMgrFsktFMst4tHcBt01jlDVUhJFCDELf/shi6hmXxmf1HeWg8wgdXdfKJjasuu4G9WBXL5MBshN3TYzwxM0GiVESTZbY2trKjtZObWzrw63aEEBRLSTL5peFiC/CSzUUolBJLji1JCm5HQ9Xj4mrB7WzGoXlRZQ1JWFiVEsVivA4uxWKCIiazFIlKRbKSgSQgiEaTcBBGRzlLg9bLoZ6e/0VPT8syaxRM4ca0PFiiGrpmUws0BFfAZEUrWtG56YoDE0mSXIAshMjUph8B/lgI8eCibd4B/HeqVbmuB74ohNj6ase9FGBydD7Bt46d4KczUSqWRafbxc6uDu7oaKPNfarTbapU4XAsw4uxNIfm0gwlcphCIEvQ53OxucFbz1MJ2i9txZSfjnyfbx/8E9573V/wuaH7yRkFPrfl42xrWMfEj3+b3OQLXPWrDzBdSvLdkcf44fjT5IwCGwP9fLj3drY3bz6jyaAQglhCcHKiGvY1NmNimqAq0NlShZT+DoVwQLqoYQaGZbFnZoTvnDjM4fkILlXjXd0DvK93PW2uc0v2HM9kuW9kjP8cnSBZLtPidPLOnk5+rruTsOPcu39bQjBfNOqQMZLKsnvmOCdTaWThRZOClM2lhqZNlmh02mh22mhyaTQ5VVw2E0UpYpKlYKUYz83x5GSWQqEbWQRRZYPrWiR+bUMP/WfJTSoYFfZFJ9gzM8JTkVGylTJO1caNTZ1sb+1hXSDEM3OHeGByH4cSJwC4NnQVd7bfwK0t1y4b4rcgYQmEAaIEoiwQFTBLgplEgYlEnplEgdl0iflMCbkioVsKLqHQpNppke20G060tIyZFLC0CTiSA9SgTNFT5KnyIca1CDetWse2q9aiBiVkj4QkX/j9kymXeW5umn3RafZGp5gtVPun9Hh8bGtq44amVjaFm7AvA3KXQolSjicjg+yeOcqzcyeoWCYh3c1bmwe4pXUdW8I9Zw1tKxoVxrLJmvcjWQeRiVyKinUqxKvB7qLb46fbE6gNfno8AUK68w0JvywYJr+79zB7I3F+bX0fH13TfUWFgZrC4nB8rgop0+PM5HMoksSmcBM7Wjt5W0snTc6zdzOvGAWyucgZnpYFmMnlZ7HE0h+AqntB91FRbcTNDHOlOQCCWpAuZycdjg70i5yn8nrl026hf1XVYyKEhGFqGIYDw6w+v2TZwKYWUZUiNpsNp/3SFK9aAZMVrejNpysRTHqBH9RmVeDbQojPSpJ0D4AQ4u9q5YK/BOykWi74/321MC64NGCyLzLLH+1/gbd3tLOzs501Ad85PVwLhsnL8QyH5tK8GMvwcvxUeEyH286mBi8bG7xsCntpdZ17rPa5qFDJ8rv3v53rOu7k1oGP84lnv8BIdobfHXgvq37yaabX3clDvhBPRA4iSTK3t27hQz23sT7Qe86fUakIxmZMTk5UvSmxRPU+8rqWJtHb9dd3XelyiftGj/Jvwy8TLWRpd3n5QN/V3NV5FS7b6wO7smnyxHSE+4bHODAXQ5Ek3tLSxLt7u9na1IBpCWbzlSUej4Vwq0i+wmy+Uu/OviC3TSZol8iYUWLlSVyayVua+1jrb8CQMqQrSaLFFDP5JNFCkkghhXlavoBPc3J9Qz/bm9fiUzq472SKJ6fSSMAtHT4+cFWYtaEqSAirCgqiXIOGMlRKJkOzcxyaiTA4N4soS+imjGYZBGUb61wtrHa04xR2RFlglZfuf8b4/ItAYUmCsmKRUwxiepmK16Kh1U5vpwt7WEGteT8Wd0tPlbP83gv/wN65l/mFrrfxW+s+dIb35lxlCouhRJy90Wn2Rac4kohhCoHbZmNrQyvbmqpDs/PSvNU9H2UrRZ6ZfYXd00d5OnqMglnGrdq5vmEVV/k6catupnKZOoxE8pm6l01Gos3lpccToKsGHgsQ4rZdGQYtQKpc4beefpEj8RS/fe0A7+5te+2d3kAJITiWnGf39Bh7pscZyaQAWBcIs721k+2tnXR5zq+ASaY4z/HZZxmJHWQ8OUQ0N06mcqrAk45MEJ0AGnaujH42i7Wh6/fp7unDsjxYwgVCRpIMJCmDLGeRpFNharrNjdd9af7GK2CyohW9+XTFgcml0qUAk2zkKMmj/4lygdxQERLDhovBio+jFS+DFS85UX1DGpRLrLWlGbClWWtL06HkudCXxj/K7WOoPMEn/e+hgsSfFad40czTXC4S0ez4bC5+vuttvK97x5IclNerVMaqe1NGpkxK5WrRoLZGmf5Ohb52hZYGGfk1Lmwsk+Tfhl/iJ2NDFEyDa8OtfKj/ajaH2pktlInmy0RyJSL5EqYQ2BW5OqjKkrGuVpc7avOaLGEIiVTJJFaoMDSf5dloghPJHGVTRpFsWGKpcSABIYdKs1Oj2WWjyWnDp4OqFEHKU7RSzFeSRPJJIoUkk9l5ykUD3dTQTRXdsuEwNRpVHy2KnwbFS1j24Jdc+CUXXuHEjY5qKIgyWIsAoVQUJDMGhYKFzZBwChm7kJCN878xTMmiolrIGmh2BZsuI2kSksaZY5uEpIO8ML2wTl88X10mL9oPpZrXkSqVuX9shh8OTzGWyeO2qezsbOZdvW2s8p/ZJ8IUFn879AO+ceJ+rg708bktv3ZOPWMAYoU8+2arILJvdoZ0uYQEDARC3NDUxramNtYFwpc1n+G1JIQgWsjWcz9Opud5eX6GyVya8iLolYFGh5OBQBOrfGG6PQF6PH46XFdOU8azabZQ5JNPHmQim+ePr9/AjvbGN/qUzlujmRR7psfZPTXGYDIOQK/Xz47WTna0drHKF1jyMilXTjGeGGQiOch4cpDxxCDx/FR9fcjZRmdggE7/AB3+ATr8a3DrF1bt7lJICEEkZnH4uIHfdoKOrjVIMjh0CYcuodmWz9+6lFoBkxWt6M2nFTC5AKVeeZTpR/7koh4Tqg3LppVGXrF114ekUivda+VZVRljVWWU1ZVRuowpzl6kdnlN2wy+H85za9LOQEHDAP4x2MCIy89/2/gRdrVtw6FemjespimYmq2CyskJk+m5Wm6CHXrbqyFfve0KHlfVYDQti91TE3z35BCH4nFUdDpdDQR1H9mKIJIrkamYSz5DkSRUWap7oaqvlKXaIFcHsTAtIQsZ3ZTRLRnNkrCbEpol4bAk7BZoFiiGwG6BBxmvLOMWoJgC2RBIFYFiCGymUj2OqaJbCrqp4rBs6KaKar0Og1EByQaSvtTQl2zVadMmmCyVeSVbZN4ysOkSa5odNPrLDBWGeT49xKyVQNLg6sY+trWtY11jN6ougw1OFOLsjo6wZ3qY4Uw1Jn5toJHtLT3saO2hy3NuEHC+EkJwKJbkh8NTPD45S9myWBf08u7eNm7raMZxWkWmR6cP8Icvfh2naufPt3ycjcH+M45ZNk0OxWfZN1sNzzqRql5PSHfUPSLXN7bi1889PO9SybBMJrLV/I+RbIKxTNX7MZZJUDBPhfd4bXrd49Hp9mOJMiPZaZ6be4W5UhpFktkS7mVHy1q2twwQtl/ZvSrGMzk+8eRB0uUKn7tpI1saf/Z700XyWZ6YnmD39BgvxmaxEIR1ldXuMiFGKeefZ74wXd8+7Gqnw1+FkM5AFUJc2qUtF3+hSqYtXjph8NJxg1hCIMuwc8sY69YNYNcuP4ws6LOf/Sxf//rXhaIoRVmW+Zu/+ZuxW265JXcxju10Ojfn8/mDF+NYK1rRis5PK2DyMyAhBNO5Ei/GqpW/Ds2lmchWq8Loisz6kIdNYQ8bG7ysD3nOMOyWO94fP/IePHqIe9/2tctxCWdVMmtyaKTEiXGTaBSMchVIKnqJOTXNhJwiqeaxpFP3osum0OzUaXbqNDl1GhwadkVFQkZJS3iHZEhAuWhhlqrhTZop1eCjCh12qzqtmzKqdf4P1opkUVIsyrKgpFiUZKs+Li+ZF0uWF2WLilL1UuSlIkWlgk1X8LqcqLqCoknIdglVk9A1GbdN5Y6uMH2+s8ezm5bgP0en+cfBaWYydgRlhG2Izc153tOzibc2bcT+Gt2exzIJ9kyPsGdmhCOJWQB6PAG2t/awo7WXq3zhS2KApMoVHhyb4QcnpxjN5HCpCnd0tfDu3jZWL/KinEhP8pv7v0ykEOe313+Yn+96G5O5TD1P5Pm5CAXTQJVkNoYb2dbYyg1NbWe8vb4QWZYgErcYn7FQZFjbp9Z7+iynvFGp53yMLsoBmcill4TsNTpci8KuArVpPwFt+b5IlrA4mphi98xRds8cYTwXR0JiQ7CDW1rWsb1lLe2uK8voH0qk+dRTVTvv8zdvZk3gyoaoc1G2lKh7QCaSg5xIDDNScJGgjzQdCFQcssF6n8L21k5u79qM/xw9fm+0CkXB0eEqjIzPVO/VzhaZDatU1vaqjI4MvaHlgvfu3cu9997Ll770pfy11147ODMzo5ZKJam7u/t1BJueqRUwWdGK3jitgMnPqOKFModqoPJiLMOJZA5B1VuwJuCq56hcHfbg08+MzX/42De478hf8+nbf0CT59XLPl6IMmWDaL7ETL5EJFcimq+GWi1Mx4uVU5WoBHhNOy2mF3/Zib/iQUZGyBaugIk7aKH5TTJyhWgtxyOSK1POCbbFXNw862ZdqlrJKa9aGKpA2Kh2U7cJLJuFaatQUcsU5CJpkSdJnnmRJUWeslyhqFQoKRUqqonTbsPrcuB1Owi4XYTcboIeDxNFk6cjcQ7MxZEE3NDSxM7ODtaFglRMi5JpUTQsiqZFwTAXzZsUF00nS0VeSowxkY2jSDotjkY8Ni9lU9S2M8lUTExLcHtnmLvXddDhOVWpKlPJ89jM89w/uZcX4q8gEKx2bcYlrueVuB3TghtbPXxgdZhrm1znbKBHC1memB5h9/QwB2Mz1YpRTg9vq3lSrg41X/TSsUIIDsdT3Dc8xWMTUUqWxdqAl3f3tXFbRxNOVSWST/Jbz/0LQ8k0brmFfC10rd3lYVtTFUSubWjGqV6cktyGUfXujc2YjM9YTEZNyovMHkmCvnaZnh4LJZhiorAUQKKFbH1bRZJod/nqYVcLENLl9r/uvCig1oBzlt0zR3h85iivpKqFCVd7m9nRuo4dLevo8zS+oYnlB2bn+e2fHsKr2fjiWzfT6Tk7ZF+pypQSjCeOLgnHShQi9fVhV/siL8gAIVc/B+fT7J4e45nIFAXTwG2zcXNzB9tbO7mhqQ27enkrMr6WDENwfNzk8CsGx8dNLKtaZXHDapUN/Sp+76nf/Bvdx+T73/8+3/jGN/izP/uzeijXE0884fzsZz/b8vDDD5/853/+Z//dd9/dm0wmD1qWxerVq9dPTk6+dOTIEf2ee+7pnJ+fV+12u/XVr351bPPmzcWhoSHtgx/8YG8+n5d37tyZ/OpXv9q0ACZ/8Ad/0PSDH/wgWC6XpXe84x3Jz3/+89PHjh3Tdu3atWrr1q3ZAwcOuJuamsoPPfTQCbfb/eYxmla0ojdIK2DyJlG2bPBSPMPBuTSHYmkG57P1ZOxen7PuUdkU9tLo1EkV5vj9B+/ktlUf5V3r/8fr+kxLCGILuR35EpFcsZoYXoOPaL5E7rQwK02WaKp5OppdOo0ODZdqI17K8/xshGPJJELYCGoBHLhQcnY8JTsNhhOnVTU483KFir1Ef1ni6riN9ikbiilhBAWp9XkGe0Y4oU0zU8vviBRSlMzTGqYpGi1OP80O/xnjZqePBrv3NY3vyWyOH4+M8+PRceZLJZocDn6uVtGryel41X0X60R6ki8c/R7PzL1Mm7OBTwy8l1tbG/dqFAAAIABJREFUrq3lZVT4l2PTfO/4DBXLYmdXA+sb0zwTe5anoocoWwZdriZ2td/Azrbr6XBVY/bjhQo/ODHP90/ESZZM+nx2PnBViNu7/OjKuUNFslTgyZlR9syM8OzsBBXLIqg7eGtLNztae9nS0IZNvrh5DQtelPuGpxhO57DJEj7dJF6OY1JGlaBCnGaXzGeu+QU2hTsuyucWS4KJaBVCxmdMpmctFqIBPV4T1//P3pvHSVLX9//POrr6vqbn6rlndnb2mD1d2eVYUQyHGhQEjKBRwIeQxHhEE4yPHH6NfH8SjfpDTfIjeCEERRSDSEQ8QEFuWJZd9p6dc+foOfq+u6o+vz+qp2dmd2fvZVfs1+NRj093dXV1dU9P1+dZr/cRLKD6M+juBJOpPPFxF1q8AYfhRpdKTNiHmXQN4ast0OGz4KPTYwFIi8d3yj+nw2k0Ey07KTvZFh1GIGh1h6wyxOFeVgabkU9DP5LF9NiBCP/nuVdp9bi4/cL11B9HpbszpaNBSJ27tQIgs3khLu3QHKlZ5Q2dFybHeXx0iCcmDpAsFrArCuc1NHNRUxubG1vxaqe3GuNiEkIwNG6yfa/Ozn6dQhE8LoneboU1S1Uaa+XDQu18MLl9yxj7YvlDtjkZLQ06+Js3LN4DKp1Os3nzZmKxmHjTm940fd1110UvvfTSdGdn5+oDBw5sv/nmm1uefvpp71e/+tXhUqkk3XHHHXU/+9nPBs4777yeO++8c2j16tWFxx57zP0P//APzc8+++zet771rd1XXXVV7KMf/ejMbbfdVnfrrbe2ZLPZl3/yk5/4fvSjHwXvvffeISEEF198cfenP/3pia6urmJvb+/qJ554Yuf555+fe8c73tF1+eWXxz/ykY9ET+kHUVVVf4SqgsnrVHndYFcsXQ79SrF9JklWt2ZZTW47a2t9xJM/xyw8y5fffjfqYSoeFQzTcjjKCeWzsDF7fzJXRD+oEpVXU8thVhqNLjshh4amKMjIGEIiUTCt6lblylZT2dIhGTJeTabJrdHo1iqldBtdNtyGirFLQdlmUDMKdgNyimCwocjWlkF+43mGaWUMJAjZPTQ4/YRdQcLOAI1OP42uOfjw2Q4fJnMi0k2TJ8cneLB/iOciU8hYLsqVne2c11h/zAnWz0y+yu07f0Rf6gBrg918sve9rA52IYTgiYm9/Ner+xmIeRGATevn0g4HV3VsZKV/8VKrBcPk10MJfrh3mr54noBd4d3dIa7qriHkPD5nIV0q8kxkmMfH+nk6MkxWL+FWNTY3tnNRUyfnNbThPEm3Il7I89zkmFVBa2KMaMFAEi5k4UIg0eZ18N7udlz2Sb6w/ds4VTtf3PBXrA/1HHG/Qghyhk6skCNRbrw5mSoSiUgkojbycSci60JCQmCS0mJMqRPMaBFitklKcnHB/gKaw3I9PEEajEaYrmVqzE6xJB3TxO610HQ+xe8mdvH42A5emO7HECZ1Di9vKUPK+lDHIaW/T6Ue7B/lSy/tojfk58ub1+E/g81lF1MqH7XgI76LkZg1zoeQek/bgpyQFv/yI0LI0aSbJi9PR/htucLXVD6HIkm8sS7MRU1tXNjURq3j2C9qnKgmoybb91mhWsm0wKbCii6V1UtVOpuPXojkTIMJgGEY3HXXXflXX301ds8999R99rOfPXDffffV/Pu///vIzTff3H7TTTdNDQ4OaoZhSDU1Nfpf/dVfzTQ0NKzr6OioHGyxWJT6+/t3BAKBdZFI5BW73S6i0ajc0tKyNpvNvnzzzTe3/O///m/Q6/UaANlsVv7kJz858Y53vCN56aWX9gwNDb0K8I//+I+NpVJJ+tKXvrRoL7Wqqqrq2FQFk5PQUCrOowf2sb42zOpgA45TFEJyOqSbgr54puKovDKdJF6wEm29NsEbG0I0uOzz3I8CscJCl0GWoNah0ei28jvqnRp+TcOmKCAkCgZE8/qCxoGJ4sGJ6VDrVFHkEjPFGDkjjc8ucVFTM+/q7KLL78apLpzIlyZMss/rpJ8vIWKgqwavhod5IjBExOmgrtSJT28AwGbX6WpRaAyemSuQqWKJ3fE4e+MJsrqBW1VZFvCzLOjHYzv698MUgj2JYZ6f3kteF/i1AHGmmZRGydtiLPG3IOnd9MVkFFnikrYgV3XXU+e041RsOFQFVTp0MiyEYMtkhh/umeapsVT5uX7+bFkty4LHPxEqGDrPTx7gt2MDPDExSKKYxy4rbGpo5aKmLjY3tuPXjn51XDdNdsSmeWZilGcnR9kVm0EAfs3Opvow5zY0c259E5pi49HhCR7cf4D9yQxOVWFDvYtXk78jWprgna1vZoV/CYlinlghT7yYW3A7ns+jlpzUlOqpKTZQU2rAY1h5DgY6aXuUojuO7E3hChQJOjUCdgd+zVlpzBmwOwho1u3DVb+aDYXZvk9n79C8UJil1oRvfijMa61kMcfvI3t4fHwHT0/uo2CU8NucvKlxOd2+RoJ2NwHNRVBzE7C7CWpuHIrthKBKCMH3dg9yx6v7Oa8xxG3nrcFxlLy310LJ/MwCABmO7yKei1Qer/e00RZYSWulQtYynLYTh5CjyRSCnbFpHh8b5rejQ4xkUkjAmlA9mxtbWBmsZXkgdMrclGTa5NU+6/sZmTGtUMRWC6B7OhS042hOeqZDuWY1W5Xru9/9bvCee+4JbdiwIeN2u81HH33U/8ADD/S/733v6zAMQ/rKV75yoLu7u7Bs2bJVU1NT2w7eTyAQWDc1NbXVZrMxH0xuuummlp6envwtt9wyPX/7PXv2aJdffvnSffv27QD47Gc/25BOp5WvfvWrYwfvu6qqqjo+VcHkJPTI8F4+99JvyrkdMisCtawLhVlf28SaUOMxTczOlIQQ9CdS/Mtvv4CpriVDD7FCiQaXnXA5zKrOacOl2FBkGcOUyOpWL49IuZ9HJFukYCz8jjhVmUaXrVxCd66UbqNbA6nAr0Z38r/Du8noJdaGGrluyRouDHce4ioYCZPIs2kyz5dwTjgwMdkaGuB34VfZ0rifJbUNrA91sD7UwZqaNkRRq/RN6R8xyBV4XSonZ0krKdJqmrRskpEhreQoKNMIOQ6SiSJJOBQVu6LgVFUcyrxFVTFNG5GUi9GkhiEkGtyCtfUSy0IKLtWGU1FxKAoOdeHzHIpSuW+T5+BHN022zoxbyfNj/UzmMyiSzIbaJt7S1MlbmjqpdczlFUxk0zwbsRocPj81RrpUQkaiJxBkeaCGdq8Pr00lWSoQL+SJFXMkCnnixTzRfI5YwSRbdILwIiEjyCPkBEgpkAQem0bA5qBO1BIsNeDKBZHSfkTRAkPVZlJba9LSKNHdrNHVqKGqpxYaDpc83Noos6bHSh52Os5czkdeL/LM5D4eG9/JkxO7SeuHv9ptl1UCmpuA3UVAc1fgxVrmACaguQja3fhsTmRJ5uuv7OW+fSNc1tbIP5+z8oyUZE7kpxcAyEhsF/H8ZOXxek+7BR+vEYQcTUII+pNxHh8b5vGxIfYl5jrHt7i9LA+EWB4MWWOgBp92bFUTC0XBrvL3cGC07JjXy6xZqtLbfeTiDUfSmQaTPXv2IMsyhUIhu2rVql0f//jHm+LxuPpnf/ZnsZtuuqnjPe95z8zXv/71sbVr1y6fnp62jYyMbJdlmfXr1y//2Mc+FvnQhz4UM02T5557znneeefl3vrWt3Zfc8010Y985CPRL37xi3X/8i//Ugnl+tznPtf05JNP7vX7/ebAwIBN0zSRTqflKphUVdXpURVMTlKpYoFt0Qm2zoyzdXqcnfHJSsflJb6aMqiEWRcKU+888w3cDtYD227nkX2/5R2rv0EkZyv3ArHAYzpf4qBILWocahk05sCj0aXR4LYRdtnwasqCq6xCCF6eGecHfdt4YnwAWZK5pGUJ1y5Zw8pg/YLthmamGX4+hm2rRvNoCBmZPt84zzTvJrEyRU9LmPWhDlYGmrEfodne2fa9Hctk+dnACA8PDjGdL+DTbHT5nMhyiYFUjJlCDrAa5LV7ffMmICGWeIOkUjAWNZiKGczEBfEEJJMShjH3ORclnZxSwO4pEQgUwZlD17LklRx5Uyev6+QNvZyAb93P6Sa5gh9DDyFhR1DAVCYR8gxIRy5BPR9+ZsHFWb6vmyaJYo6pfIasboVA1TvdhOwuDmQypEqWE6dKEqosKIkihqlb1ZwPkirJBO1O/JrjEOfCodgZSupsmcwwni7i0x00oXKOq4d0TCNfhlOvW6ItLNPWqNDepFAXlF7T8KrDlVtd2qawpkdlaZuCqp45SBFCkNbzxAtZYsUM8WKGWCFDvJi1lkJ5XTFLvJghXsguCjIICbvZi2HUUeOKszyUJ2h3lYGmDDXznRnNjUvVjvtvYQqDTDFJphAjVYyRyCQZnYTpmESyNMh04RWSxm5MeRpJMqn3tFcApC2wgpbAMpy2s++3eL7ihTy74zPsjkfZHZthV3yG8excMYVmt6fyG7EiGGJZIIS/DCuGIegbMXh1n86eQQPdgKBvzrkLBU4eFM80mLz00kt87GMfY2JiQqiqmu/o6Ch873vfG/J6vUZNTc36++67r++qq65KXnfdde2RSMT22GOP9QHs3r1bu+mmm9onJydtuq5L7373u6Nf/vKXx4+U/H7rrbfW33PPPbUALpfLvPfeewdUVRVVMKmqqtOjKpicYuUNnZ2xSV6eHmfrzDjboxNkdWsi1uTyVhyVdaEwbZ5j6xR/qqSbgqFkgT2xHLujOfbEcuyNZSmUo61UWaLeaSvDxlxuR6Nbo8FlOR/2Y7yyXDQMfjXax31929iTmMavObiqcyXXdK6izunGECb7EuO8PDXEzPYsDbuDrB/vwmFqTDkTDHRPIL9BsLynkW5f42mNhT8dEkIwmcuWJxcz7I7NsDM2Q6xgIAk7ElZFnlqnxnkNtby9vZUVwdAx52gIIUimBVNxk+mYoG+iwN6JAkZOwS7m9qEqEArI1AYlagMydUGZ2qBMjV9CLXcGLRkmj4/EuX/vDDujeZyqxOZmF5ubHXjsgryuUzAMcoZegZoK5FRuz0FPTtcplNdlSiWyuo4uTECgSAKvTaXO6aDR6SbgcBLQHATt1hiYHcu33erhw4mKJcGBiJWkPjxuMBIxKqCWlnMUXWlWt7t4e2+QcFA9o1WpZiWEVW54+16dV/sM0lmBXYOVXSqre1Taw2cuH+V4VDJ1EsUssUK2DC0ZpnIZHuzLMJKCzmAGv2OaRKn8eCGLLozD7kuTVfyaE6+q4VFtOBUJhyzQ0FFFEUXkwMhgGgn0UoxiMUqhYGArrcZWWoutuAabvqzy/zRfEgKPWyLglfF7JPyVUSLgkfF7peMKXzrTihfy7IlH2R23QGV3bIaxWVgRsFRpoUvvxJ6oxSwpOOywutv6bjXXn9rv1pkGk1lVGyxWVdXrT1UwOc3STZO9iemKo7J1Zpx40briWGN3LnBUuv2hU1aGdRZCZgFkdzTHvniuEnrlVGV6Ag6W1Tjpj9yLgz6+cOn/h3ocFZsOp2ghy08GdvLj/leJFnJ0eoNct2QNFzV10p+O8PLMIC9PD5IeKLLpQA+bx1cSKLnJa0WSK9PUnOuirTeIfBZ15D6aZiFkdrIwCyPRgvV3lpHo8Pmtq5vlkAyfzcGvRsb42cAwU/k8tQ47l3e08a7OdprcrhM+llemktz5ygEGIiWaFDcb/CF8psNyWlJz/8+SBEGvRG0ZVGoD1u0Zked/BqL8ZjiOKeBNzT7eu6yWdXWuk5rYCCHQhXnClalyecHwxFzFrPFpk7IxSWOtTFujTFtYIeeM8A9bHySerUcSQRyKzCVtjVzZ1czKoO+smfibpmBg1EpA3tWvU9LB55FY1a2ypkelvuYP5/ufLJb4299v5dWZBH+3vodLWzykijEyhTipYox0PsZMPsZULspMIUWskCZZzJHUC2R0g6KQKUkaOtZSQsOQ5uDaYXgJFVupKbYSKrbi0y2n1cSg5JxC8sXwBLM01CmE7fUERAi15CGVgURKkEiZJNKCZEZUvjOzctrBX4aUg+HF75FxO89cA8Fj0eBUnqd2ZBgaVNDzNkzJYFwbY9QxzJQ2QaPbXfnNWR6oYXkgdEqajFbBpKqqqjpdqoLJaywhBIOpuAUq5WU8mwLArWqsCTWwPmQ5KiuD9YdNsj1Y8yFkdyzL7miOvni+AiEuVWZp0MHyoJNlNU6WB520eu0o5corTw8+yL1bPs/fvvm7dIXWntD76kvM8IP923h0ZB9F02BjXTNvqKsjqyfZGh1iR/wAobSXC8dXcXFkLfVpP6ZiovRCzblOHL0K0hkMaTlWzULIztj0XKhFfIbYPAjpLEPI8qAFIkv9wUWdEN00eXpikp/2D/H0hJWIu6mhjiu7Otgcbjih+HwhBC9MJviv7cPsjKZp8Tj4cG8rbwmHiCYF0zHBdNxkOmYtM4mFEzavS8LngygFdqRTTIsCDTUyV6+o4eJ2P9pJwuuxKJk2KxAyPGEwGbW+y4psxci3hRXawjKtDQoO+8LvTbqU45+3fIsnJ4Zpd5zPTMZP3jDpCXi4oquFy9oa8djOnh4SxZJg76DBtn06+0cMhICGkNXMblW3gs9zZiBFCEFBz5IuxkkXYgvGTMG6PZnL8cjkBlKGl+Xag7iM5xbdn0P14LEH8GiB8hjEbQ/gtQdxa+X7WgCjGGJ62stwRGZ0AjIZ6/3LioHNn8LwRMk4J4jZRonraeIFy7UpmXOujE1WaHPX0umto9NbR4ennjZ3LbVKLfmsYgFL2iSREsTTgmTaJJ4SC/rUACgKFqh4LOfF55EIlKHF75XwuSUU5bX93crkBDv6dLbt0xmbtP5xO5ut/KXlnSp5iuyJz7Br3kWS0cxcGFjY5TlpWKmCSVVVVXW6VAWTs0AT2RRbZ8Yr4V8DKSvxUZMVVgbrK47KmppG7IqNwWR+gRNyRAipcdLqmYOQwymvZ/mHn1/KmvCbuf6N//eYrxCaQvDUxBD37d/GC1Oj2GSZNo8LnQRD6QlMBIGSm6sS53LB6HJCET9IYO+WcW1Uca5TkV1nL4wIIYjkMvNO8AshRJEkOr0B6+Rezgvp8deccOO0iWyWnw0M89DgMFO5PKGyi3JFZxtN7uNvSieE4PdjMe58dZi+RJYuv4ubV7VyYVPNgr+xaQpiSWGBSjk0bKoMLvMnaiUMCjad+qDMulYHrXUqdUGZgFc6annRox1nNCEqjQyHx42Ku6PZoLVRqTgizfXyMeVkmMLkW/se5r/2/JQebxeXNlzN4wfi7I2nLReltZEruprprTl7XBRYfNK5eqnKii4Vu3bix2qYJdLFhAUVxRjpQvwQ6MgU46QKsfI2cXSzeNh9KZKKbOvklcJ7KQknl9ZtY5lflKEjiMcewK3NQod1X5UPhXPTFESiJsNjZtkRM8hYKVe4HJQB1ILQxtDiZWyFEKRKeYbSUwykphhITzGYnmIwNcVoJopZbuMqIdHkCtDhraPTU0+Ht44OjwUvPpuTQhHiZYclkRYLHJdEWpDOHnpO9LrKDssssMxzXAJe6aT+ZrMqlgR7Bg2279XZf8CC18aQzOoeld4lR4fXZLFQ+f2adXUPZFKVx8MudyVnZfaCypFg5UhgYgqTkmmgmwYl00CRZLza6SmBXAWTqqp6/akKJmeh4oUcW2cm2DI9zvMTMwwlSwjTjSS8yMKNwDoJOVWJZUEXy2rmQKTNa0c+gYnWj175N367/wd01azlqjWfpLNmzaLbZkpFvt/3Mg8M7CRayKNIghJJII1dVVnv7eDSxFpWDLTh7HOACWqThHujivONKmrw7AtTEUIwkctUEk1nT97xopVBrUgSnb6AdaWxfPJe6g/iUE79lXfdNHlmYpIHB4Z4ZjyCADY21HFFZzsXNjUet4tiCsFjIzN8c8cww6k8K4Jubl7dxqaGwBEn5UIIUhnBdFwwHTPYMVpkYLKEnpNxiLn3rcgQClg5LPNDw0IBGdthIKIyGZ11RMZNMrkyWB/HZPRY9ETkFf5pyzexyQq3veEv8SrNPNg/yi+HJ8gZBt1+D1d2NXNZWyPes6zPxkx8rtdELClQFejpUFi9VGVJi0xJZA/vZMxCx0GP5UqpRV/LafMu7mTYgwse89gDDKVMPvn7VxBC8P++aT0ranzH9J50QzA2aVYg9EDEoFBmn4BXsv7uZQgNBU5NkYKCUWIkM2MBS2qSgfQUQ6kphtLTFEy9sl2N3U2Hp95yWTx1FrR462hwzOUC6roVEhZPzbksFrRY7ksyLSpNOWdl15jLc5kHLbPhYx7X4d+nFe5nsH2fUQn383skVpWT2E823C9VLM7lwJV/80bmwUqj01254DLrsAQ0O6lSnsF9++lcuoSSsOCjZOrl0Sjnk83Jo9pp89Se1LEupiqYVFXV609VMDkJjaRneH56Pw7FVlmcila+reFQ59bZFfWIHZd1U9CfyLMnmmN3LMeeshNSLJfFsisQcBgYUoqZwpQFAlKODm+AdWVHZV0oTNjlPaGTuSkMnh36GT/b8Z8kC9NsaLmUd/V+jFp3M6Yw6U9N8bvxPfxiZD/DqRwCCUERh5rnDbWNvKGmk3OS3dTvClJ4xUTkQfZLuM5RcW1U0ZrPHhgRQjCezVROxrvKJ+bEPAjp8gUWnJC7TxOEHE2RbI6fDQ7z0MAQk7k8NXY7l3e0ckVnO82e43NRdFPwi6FJvr3jABPZAutqffzF6jbW1R3bpHJWg4k89++K8lR/Bq2kssThpk1zYeRk4inB/J+NQCWPRcKhSYxMLJyM+j0S7U2nfjI6X0PpCf72hX9nOBPhEyvew/u6LiGrG/xqZIIH+0fZHUthV2Qubm3gyq5mVtW8tkUpAHSzdJCTMedopPIxYnE3iakeivG1YHoxpQR5x2/IO35JSd2xoKKZKtsOAoqF48LwKQs4lMO4GYvppckotzz1Cj7NxtcuXE+7d/HvYaEoGIkYFUdkdNLEKEdc1QWlBRDqf41D1gxhMp6NM1iGlYHUnMuSLOUq27kUbZ6zUk+Hp5ZObz0t7ppDinIIYbkqFbdlQbiYIJ4yK9/9WSmylV8033EpFAU79s8VSOhdYsFI22kukBAv5Hlh6gAvT4+zJx5lOJ0mUdTnbaEjyPPF9jfS2NUGmMgSqLKKTVbmFmnh/dN1zFUwqaqq15+qYHIS+vnIVj675UfHvL1dVnEoNuyyHZUgmAF0w0+x5CVXciKEdWJWZZMaZ4k6l0HYA61eiUa3DafNAh1VUpnIZhhIxtmbiLI7Pk2mXPmrwemxIKUMK53e4HE5KHk9y6N77uKhvodICC+qaxXjRY1sSQOcSEC9U+Pi5k7+tLWXtlQtuRdMsi/qmAmB5ADnOgtG7EtlpJO42n0qJIRgLJteEMKwOx5dACFLfMGyC1LDikCIbn8N9mPI7XktZQjBsxOTPNg/xFPjE5jAxvo6ruxq501NjdiOw0UpGSYPDUS4a+cBpvMlNjUEuHl1Kytrjq+PQ7Kg89P+GD/eO81UTqfVq3HNklo2Bn2kU9JcHkvcymkxjDM3Gc3oOf7Py9/h8YktvK15E/+05nqcqlVedXcsyU/7R3l0eIKsbrCk7KK87QRdFCEEuVK6DBdWeFT6CE5GphgnV0ovuj+XzVdxK1xaDUpuPbnYWlLRdkxTwe0qsKQjy6qlMi21fuzqyRUqOJJ+OzrJPz+7nRaPi69duJ5658Jwn0xOVCqlDY+bTMyYCGEVWwjXyrQ1ybQ3KrQ2KrhOsIfG6ZYQgmghw0B6ksHUbGjYJEOpaSL5RGU7VVJoddfQMQ9WOssA41QXb4qYLyx0WSyIMSswk8paJaV72i137FSWlM7rRSZyCSZyccaz8XmjtS6SS2Ac5Hj4VBd+rQZNcqObNlJFwWfCSwl3dVqfgyxX+hvN9k16rXrXVMGkqqpef6qCyUloMBXjqfERGlwuah12FFmQN0rkjCJ5o0ReL5EplRjPmIymBZMZhZmsSqJgq0CILOnYbRlsahKUOAYzFEWcgllatMTmIRIANkBDwQHCXgn3kiWB2ybh1xRCDo1ahwOXqlmOjmLDoc65PNFCmq0zQ2yLDZPXS4ATRbgQOLFJ8I62Hj607BzqCh6yL+pkX9DRxwTI4OhVrLyRVQrSKYipPhFlCzp7x1IMRXKMFRLsFuPsSE+SPAhCVswLT1jiD551EHI0TWZzPDxo5aJMZHME7Vq5olcbrZ5j78+Q1w1+sn+Cu3eNkijqXNhcw82rWlniP34n5vGRBD/cM83OaA6PTeZdS2q4ZmnIaqyJFZZS0jkl8fYnKlOY3NX3CP+5+3/o8bXwb+f8Nc2uusrjWV3nV8MRHuwfZVcsiV2R+ZOWBi7vqKfTY5IpJg5yNGZzMuJkKtBhuRym0A97DKqsHdHJOGSd5keRD+/UFYqC3QM62/YubJ5nJc2fePO8xfTT/lG++NIuVtb4+cqb1uGzqSRSVrW0obIjMhO3zhmqAs0NMu1lCG1pkP+gSvMupkypwGDFXZksh4dNMZqNLpjQNzoDFUjpKIeGdXrrCdqP/r9lGFYxCttxfl5CCBLFbAU2xnMWcIxn40TK62LFzILnyEjUOX2EnQHCrgCNzgCNrgBh5+xtPy710GaOO3bupGPp0rlS4bpOcV7xgfmw4lJtuG2nNkxycHCQyy+/nPvuu68CJp/61KeaPB6P8fnPfz6y2POeeOIJ13e+853QXXfdNfLwww977Xa7eckll2QW2/5wam5uXv3iiy/uCofD+mLrn3zySde111675P777+8bHBzUduzY4fzCF74wcWLvdk4PP/yw9ytf+UrD448/3ney+6qqqrNVRwKTs6dszVmqbTPTfO3Vlyv3azQnDc5a3IoPw3AQzzsZz2jo5fOVxybTE7QS0peVx2aPtqijoZuGBTizoFOGnQXwM+/xnD43Rgt5Itk80/m59gjmAAAgAElEQVQCiaLOgbTBgXQOiSyqrINUxBB5dJEHaS4xtMvTQI+3h+FUjmSpSNjpolnegxp7hiUvXUn+V71MDFsTea1LJvBeG843qCie127SMZMqsGc0xYFIntiMST4ho2TsOEtOZDRAw4GfdbSxylHAETRoDNtY2uqiMWzDcZZeqT1W1bucfGjlMq5f0cNzE5P8dGCI7+/dzz17+nhjfS1Xdrbz5ubwUV0Uh6rwvmXNXNHVyA/3jvH9vWN84NEoF7fVclNvK63eY0tYVWWJS9oDXNIeYPt0hvv3zPDDPdP8cM80b27x895lIVaFXGcUSgBkSeaG7rfT7grxL6/czft+9zn+snMz7Q7nAkfjHGeMRiHTl2nj0aFl/HxoHAcT1EnPUSNtQZXmwnzcmr+Sk1HnbqWjZvVhocNjt7axK85T5mbYNYm1y2ysXWYjmTbZsd9Kjn70qSK/fLrIkhaF1T0qyzqUk4ICIQT37BniP7f1cUEwzDX13fzmCYPh8RLJjPXb4dCsIgXrllkheU118mtereq1kNtmpzfYQm+wZcH6kqkzko4yUIYVC14meXlmkLwxV0HCr7kqyfazY6e3nkanvxLqqygSh7tWopsGU/lkBTbGs7GK0zFRBpH5rwVgV2wV6Fjmb6LR6SfsCpbHAHUO3wn1iJIlCbdtIXAYpjnXwLUMK+lSEY9NO+VgcqK68MILsxdeeGEW4LHHHvN6PB7jeMHkaHruueec11577ZL//u//3n/BBRfkLrjgghyQOOoTq6qqqqOqCiZH0YZQK3+57GK2TaXpTxSZSQuSaetkLCghpCxIOTStQKtXZWnATafPpMOr0uF1EXbbjhhmpcoKHlnBYzv5uvNTuUylPPHL0+PsT84gcKNJMsv8tawI1JE3SvxqtJ+CkWBjXQvXdaxh3XQTuRcMcttLSIbMjGuYiVVPsuKSddR3Lz3p41pMpmlyYCZH31iasakiiRmBnlKwZR04DQfgBJzIkoFkz2L68ohAjmCtSluDk1rFTWIKpicVZiImB7YIDmwpASU8PolQvUyoQaa2XibUoPxBwooiSZwfbuD8cANTuXwlF+WfnnuJoF3jHe1WLkqb98guitum8KHeVq7ubuTePWP8aN84j41M846Oem5c2ULYfezfv9W1blbXupnIFHlg3wwP7Y/y2EiClTVOruyuYVnQKtBwrI06j6aSUVgAFZWqUvPGudAp63FTGCxFY4/axZf3/oo2c4ywOYkm2ysVpZqdAZYFZtDU3Qzkmtkaq2UkewUT0hVc0ODhouZ6ltfU0eL1oJwFVb18Hpnz1sqct9bGZHQuaf5/flPApsKKLpXVSxU6m5VjLiZgGIKxaYMfbJlkaEzh7eZGpKjCr/breFwSbWELQtrDCvU1pz436A9JNlmly1dPl69+wXpTmERyiblKYSkLXB4f30mimK1sZ1dstHtqy85KHQHNTWRByFWCqXzykDCrgOYi7AzQ4a3n3PqlhGfdjvLo105fWN/BUmQZtywfAivmGYi82Lhx47INGzakf//73/tSqZRyxx13DL7tbW9LzzoOd9xxx/Ddd99dJ8uyuP/++0O333778Jo1a/I33nhj++joqAbw1a9+dfjSSy/NTExMKFdffXVXJBLRNmzYkD5SJMkrr7zi+PCHP9z5ne98Z+Ciiy7KAnz9618Pvfjii+677757+Oqrr+7wer3GK6+84p6amrLdeuutB2688caYYRhcf/31bU899ZQ3HA4XbTabuOGGG2ZuvPHG2I9//GPfLbfc0up0Os2NGzdWYj4jkYjy/ve/v2N4eNjudDrNO++8c2jTpk25T33qU02Dg4Pa0NCQfXx8XLvttttGnnnmGc9jjz3ma2hoKP3617/us9vtr59wmKr+qFQFk6NoZzTPt7ZH8dpkeoJuLmu3KmMtCzqwKwaD6SSDqThDqQQDqQTPT43x85H9lefbZJlWj48Or59Or5/22dHjP+GSs4upzunmkpZuLmnpBqzykduiE7w8PcbWmXEeHNyFLEm8vaWH69Q1BHe6yf5UJ5YtInvBe6GGfQP0G9t5bPcdPLQtzsb4n/KulX9N0NV4wsdV1A32T6QZGM8yOVUiFQMzbcORd6KZNsCaVKtyCd2Rw6zNIAezNNTZ6Ay76Gp0Y1MWSd7umLtZyAtmJk1mJg1mIibTkyZDfXOhB26vNA9UZGrrFRxncSnjg1XndPChFT1cv3wpz0emeLB/kPv29XPv3v1sqKvlyq523tzUeMS+OH67jY+saefanjDf2zXK/+yf4BdDU1zR1cD1K1qodS4eN3+wGt0af70uzI299TwyGOdHe6f5wvOjgJWnHXZrdPjttHvtdPjsdPjttHo1VDIHQcWhCeHzYaOgZw/7+hISbs1vhUdpQeo9bXTVrLVyNcouhqK4+e7QczwzI9HT8k4+t+7DlbyTw2lvPMVP+0f5xdA4vx3rB/rRZJlWr4sOr5sOn4sOn5sOr5s2r+uMhQjW18j8ySaNt260MTxuQcqO/VbIl8cl0dutsGapSmPtwkTqUklwYNKs5IgciJiUdAA/jfYSa7q0SmhW0PfHDSLHKlmSCbuChF1Bzm/oWfBYvJApJ93PuSyvRId5dHQbAIokU+/wEXYFeEOoowIblZArpx/HEXJZXit97cU4+2Klo294HFoatPGJNwZOah+6rkvbt2/f9cMf/tD/+c9/vultb3vb3tnHli1bVvzgBz84NT/0653vfGfnpz71qchll12W3rdvn3bZZZct7e/v3/GZz3ym6bzzzkt/+ctfHr/vvvv8999//6Ilxt773vd233nnnQOXXXbZokljkUjE9uKLL+7eunWr493vfnf3jTfeGLv77ruDIyMjWl9f347R0VF11apVq2644YaZbDYrffSjH+341a9+tae3t7dw+eWXd83u59Of/nTT2rVrs7/+9a/3P/TQQ97rr7++c/fu3TsBhoaG7E8//fTeLVu2ON761rcu/973vrf/jjvuOHDJJZcsuf/++/0f+MAH4if14VZV1RlSFUyOovPCXu7/0x6aPdphT9L1Ljcb68ML1qWKRQbTCQaTcQtcknH2xaP8dnR4Xq19aHR56PT66ThoORVdewF8mp3Nje1sbmwHIH2gSP5Fg9KDAiMqyGo6zrUKrnNU7MsVpHJYxoX8Gee0v51f7rmLx/ru5eUDv+ZPlv45l/TcgMO2ePx0Oldiz1iK4Yk809M6ubgEGQ1XwYmCClhwoah5TGceI5zEXiMTrtdY2uSmqcaHLJ/4icrukGhqU2hqm5ssFvKC6JTJdGQOWIYPhpV6mdqGPxxYUSSJ8xrrOa+xnulcnocHh/npwDD//NxLBDSNP+04uotS49D45PpO3resie/uPMD/7I/ws4FJrulu5APLm/Hbjz0sw2VTuHppiItb4PGhlxlKFhhNCyZyKrumnDw75sOc91OjEschjeOQxrFLYzjKi1vJ43UEKmFR9Z72SmWpubK2c9Dh0nzI0tHB4A1Nb+Z7+x/h33f9hMH0F/jKOR+lxV132G17Al5uecNyPrZmKXvjKYZSGQaTWQZTGXbHkjx2IMLsZUgJaHI7K6AyCy3tXje+16gssSRZFc/amxTedoHGvmGD7ft0XnhV57ltOrUBid5ulZIOw+MGY1NmpdFmfY1E2hdnR3GSP+0N8uF17VUQOcUK2N2st7tZH+pYsD6nF0mVcoQcXpQjVHL8Y9Zi38X569/znvfEAM4///zMLbfcclSCe+qpp3z79u2rxK+m02klkUjIzz77rPcnP/lJH8C1116b+Iu/+ItFkz8vuOCC5Le//e3aq6++OqEucnHxXe96V1xRFDZs2JCfmZmxATz55JOeq666KqYoCm1tbfq5556bAti6daujpaWlsHr16gLA+9///plvfetbdQDPP/+894EHHugr7zN18803q9FoVAa4+OKLE3a7XWzcuDFnGIZ0zTXXJAF6e3tzAwMDZ55mq6rqBFUFk6PIoyl4tOO7KurVNFbX1LG6ZuHkp2AYjKSTDKQSDKUSDKbiDKQSvDQ1QWFeUmHQ7qhAynyXpcHpPqmJQ/HXJvkXTezLFXzvVHGuUZAdh9+f0+blilUfY3PX1Ty04z/4xZ5v89Tgg1y+8i/pDr6NvrEso5EC0ahJMSGjZO24Sk4k7IAdGYGkZTHdRYxwgUBIoaXBwbJmD0FP6ITfw/HK7pAItyqEWxWs4gFQLMw6KybTkTKs7D8UVuaHgTnPUlipdTq4YUUPH1y+lBciUzw4MFRxUd5QF+LKznbe0hxe1EVpcNn5zBuX8OfLm/n2jhG+v2eM/9kf4bqeMNcta8J9DN3TRxN7ebzvB7ww8kilWZ+ETJM9wFJfALcWRMgtFGgmY9SRKAWIFruI5JYzrc99ri4h0y7b6XDZ8frstPvsdPgcNHs01JOo/CZJEjd0v4MeXxv/uOW/+MCTn+f/ecNfcH79qkWf41AV1tQGWFO7EJTzhsFIygKVweQctLwQiVI050JwauyaBSw+Nx3eOZelzmk/bZN/VZVY0WU1aczlBTv7rVCv371YQpahqU7m3DU22sIywRqTf3pxG9um4/zdecu5eknL0V+gqlMmp6odsarX2aaTdTZORKFQiFgstmBdNBpVOjs7C7P3HQ6HAFBVFcMwjvqPJYRgy5Ytu1wu1wmHOX3zm98cvvHGG9s/+MEPtn//+98fOtw2s8c1+5qnQ7OhWoqioKqqkMv5hrIso+v62XnCqqqqY1AVTI6idMpkJmKi2qwTv6JalVSU8n3VBoqy+NWd+bIrCt3+IN3+4IL1hjCZyGYYTCUYTCUYSFrQ8psDgyRLcwXxnYpagZT5Dkurx3dMpRt9l2v43w2K/+jbmqbJ0FSWvjEFNfaXLM3dQDEisa0vwD4TwAW4UCWdkj2H6bfyP+rqVNobXSwNe3Daj7161GspzX5kWJmJGExPLoQVl0eyXJV5YWBO99nz2y9LEpsa69nUWM9MPs//Do7w04EhPvv8FvyaxjvaW7iis50O3+HLBbd4HPyfTUv5wPJmvrVjmG/vPMCP+ib4wPJmru5uxKkuBBtTmOyY+D2P9d3L3qkXsCkOzmu/gvM7riTkbsJp8x6xpw+US7bmdQaTBQaTBYaSBQaTeV6IpHlkcC4KQZUlWj0a7RVYsYClzWfHeRx5LOfXr+LuN/0zf/fCf/CJ527nr1dcxfVL3n5coOBQFJYGvCwNLPwcDSEYz+QsWJkHLb8cniBdmivs41KVsrviLrsrFrQ0u52ntPyq0yGxYaWNDSttZHICzUalEeZ0rsAnnnyZoWSGW89dzcWtDafsdU+XhC4QkSLmVBFeJ5Hzkioh1diQQiqS4w+rauBrIY/HQzgc5plnnpFXrVpFJBJRfvvb3/pvueWWyWPdh9frNZLJZOXD3bx5c/K2226rv/XWWyMATz/9tPP888/PnXvuuam77ror9KUvfWn8/vvv981/zsGSZZkHH3yw/81vfnPP3/zN3zTdfvvtY8dyLJs3b07fc889oY9+9KMzY2Nj6nPPPee97rrrouvWrcuPjo5qO3bssPf29hbuu+++mtnnbNq0KfXd73439G//9m/jDz/8sDcYDOo1NTXmkV6nqqr+0FUFk6MocsDkiV8UjrqdBS6g2ubBS/m+qs49ptpAKQONumB00qE66XaFUXzl/SiClFlgLJ9kMJtgKG0By0vTEzwy0l95bUWSKnksBy8udS6kRK09dOJTLBnsHU8xOJ5jcqpEJm7lfzjzLmxCZTb/wyEXkZw5cjXTjLKDlLyNljqFa8+5lrZgzyH7/UPTYrBySBjYQbBSCQMrA4vLfebDMkIOBx9cvpQ/X9bNC5NT/LR/iPv7BvjBvn7W14a4oqudi5rDh82P6PK7+ML5y9kdTXPnq8P8x7YhfrB3jBtWtHBFVwOmyPPs0EP8bv99TKaHCTgbuKL341zQ+W7cmv+4jlOSJEJOGyGnjQ0NCyE2UzLKoDK75OlP5HlyNIkxb2La6LJZeSw+O+1eRyWXJWA//E9bq7ueuzb/A59/5bt8Y9cD7IwP8rl1H8Klnlz4pCJJtHhctHhcbGbOKbX6ZRQZTGYYqEBLlhciUX4+NF7ZTpWkeXksc8DS7nUfAoXHq/klhUfSWT7xxMvE8kW++qZ1bGx47dzLY5HIGZjjRcR4wRonyuNUEV7P0zGXjBSyIYdsZVgpLzXWOnynr4Hh2ay7776bD37wg9pXvvKVlQB///d/P9bb23v0E3JZV199dfyaa65Z8sgjjwRuv/324TvvvHPkwx/+cFtPT89KwzCkTZs2pc4///zhf/3Xfx27+uqru7q7u3vf+MY3psPhcPFI+3W5XOIXv/hF3wUXXLDstttuK7nd7qN+O6+//vrYr3/9a293d3dvOBwu9vb2ZgOBgOFyucQ3vvGNocsvv7zb6XSamzZtSqfTaQXgi1/84tj73//+jp6enpVOp9O86667Bo71vVdV1R+qqn1MjqJCXpBOmugl0HXQdYFRAr0krPuHjGDo89aVrOfMHw0dTuRjV1UqTo2iCgzZpCjp5EWJjFkgZeZJGnmKkoEu6eiygUNTCDg1at12at0OVKESnTbIJSTkjIar6EJmbjKdVXPorjyazyQQkmlusLM07KYh4GDWKtbNEk/0388ju75JrpTmvI4ruHzlX+F3LJov+LrRLKzMDwNLxOb+mGcrrMy6KA8NDHEgk8Wn2SoVvToXcVEAXplOcuf2YbZMJfGqBeqlh/GZv6OjZiVv7X4/65vfelwdxU9WRcPkQLpoOSyJvDWmLLelMI9YAnalEgo267K0++w0uKwqeUII7ul/lG/s/DGd3jBfOeejhJ11JAo68WKJeEHHa1PpDriOq3np8ShT0ue5K3PQMprOLpiDN7ocC/NYyvASsM+FAplCUDAEed0kb5jzRkHBMHEoMvFCntu27EQIk9svXMfKmuMDyVMlIQQkDczxAuZ4ATFerIwiPq9thAJSg4YctiM1lsd6DekUNSI80xIFExErIWasxYzqldvkD5rnqlIZVNTDA0zQdso/l127drFixYpTus8T0eupwWIikZD9fr85MTGhnHPOOSueeuqp3W1tbYdviFRVVa9jVRssnmUSQmAaHBZsjBKUZuFnFmhmt6msXwSMys8plQSGDojDn6hMTLJ2K//D6RfU1iq0Njjpafbgdx173HOmmOAXu7/F7/b/EEW2cWnPDfzJ0j9HU4+tN8brRaXiQTkrkyaJ6DxYcVvVwOYDi+s16oZ+sEwheGlymgcHhvjd6Di6EKyrreGKznYuamnCMc9FEUIwEN3Gb/Z9n9+PHmDU/FMyooMGp8Rfrenmkrba0zZpP16ZQhDJlCruymCywEAiz1CyQKo0N8lTZfBpMg5VQpUFWT3HdCGBMBWQDv3uB+02NjUGOLcxwMaGAEHH8UOYYVpwkDcEhTIw5HTTWqeLg0DCJFMymcoVmM4ViRZKJAo6qaJOVjcxBVhp9xKyJCFb2Vzl9ccmCfDbFfx2lYBdIWBX8WsKAYdKYN66gF3FX759PCFzsxKmQEyXKu5HBUImCpCdN/G2y8hhDSlsXzjWvn4g5HgkhICcacHKTAkRnYMXEbXWkTgoN1sCya8e5LaoFsDMQozr+Jy3Kpicem3cuHFZMplUSqWS9IlPfGLi4x//+MyZPqaqqjoTqoLJH6EWwI8uKBUFk5kcJQyWNnrQbKcupnkqPcKDr36drWO/we+o4529f82mtsuPmmNwLBKGwCyBWbRGY95tSQbZBrJNQtbKo81aJ51EsvSp0HxYmc1ZmQ8rTrdUKVscqpcJhmQ8/te2PGs0X+DnQyM8ODDEgXQGn83G29tbubyjiXjqOR7v+z5DsR04bV42d17Fmzrfw86Egzu3D9OXyNLld3FTbytvbq457cddMkwSRZ14wXIzrLG8FHUShRKxgjXOrtNnZ+tCAmRrETKyJCOhYC4Ad4EgR41TZlVNiHafHd002RFNsy+eJaebSEDIoRF2O6h12HHbFIqGIF92KgqHAw7DpGgc/2+sKks4FAmHIuNQrcWuSEiS1TdCFwZ53SCj66RKRYqGgUAAApsMQYdKjUMh5LAA7KmxLEG7g3d3tWEIqfwZ6sTzRvnzM0gUdBY7VLsiVaBlAdDYVUKKTH0aauMmvqiBc1pHjZQQkSLo83boU5DDduTGhRAiBdU/yjClk5EomYioXoGWQwAmpi/87AGc8oLwsAUQE1KRfOqC380qmFRVVVWnS1Uwqeq0SBgCowhmyQKF4andPL77h0zFx2h0LuHc5itpdC7BnLfNfMgwS2LhY8V525SsfZ9oXLmklqFFk+bgxcZBACOhzL+vHX6bhY+dOPyUivNzVixgScREJaxPUcBfI+OvkQjUyPiDMv6QjD8goZzGK8emELw8NcOP+/bxxPgkhpBwM8wSxyDvXbaRzZ3vxD7PBTOF4LGRGb65Y5jhVJ4VQTc3r25jU0PgmCaYQgjSJWMOMool4vnSPPCYBx/ldZnSotU78WoqAU0lYLeVJ8+2ym2/3TbvMWtxqVZvj2zJYDhVZDCZZ388yy8P7COSAUUEERwJqi0EkBE4VBmPTaHGYcOrKXMgoczBhEOR0RRQZBNZMpBlAzCQpBICHShhUsKggCGK6KJASRTJG0VyRoG8UawsOX3h/bxRIGcUyesSpulGMn0g/EjCh2T6kLDKe5vSNA7Xc6wINLEi0M4Kfzsr/B20uOsqFxBMIUiXTOJ5vfy3MIjndeJFa8wnS2jTJdxTBoG4QV1C0JyGxhzIWH93E8GEE4bdgohXIhqQSYUUcrU2HL6Fjox/njMTsCs4VbkKKKdIwhSQ1BeEhx0MMQtcK7DCxYJqBV72r42yomc5qJK1KNIZueBTBZOqqnr9qQomVQGQnzYpJsQcABwCCPMB4lBosNyKuXUnAg2HBQbNWqcc4nwcdP+gx4Q4zHHOfy/z399hwGf+88Ti896jv5dDjvegYz8sDFm3TRnSGZNMSpBOivJokpvXU1ACnB7weGXcPgmPV8Ltk/F4JWzayU8UopkxXh77DTsjz1IwJGTnBczoHUSLJi5VZWNjHW9qbKDJs7CHjWEKno/E+fngJDP5Et1+N29pq6HkNokpJeKlOcBIFOc7HTrGIr87miwRsNvw220Ey2ARtNvwLwIePs12UqWE50sIwb39v+RrOx6gybmE97Rfhk0GQRGjvOgiT7pUYjghcSClEUk7yetWeJddzeLUZlBtEVAiFMxcBR4O7uZ9LHIo2rzFjkPRcM67Pbs4D7rvUDScqrVOQiVZkCmJKHtTQ+yKD7EvdYCSaYW1e1Qny/xtFqgEOljpa6e5FIQJvRx6NReGRXLeP4kqITVo0KhRqFNJhxRiAYVJr0TMNCyoKVhOTKw8zro0i7ky1t9+PrBY7kyw4tKo+OwKyuuEXeyKTLvPct7OhETOWAgrM3MOjIiW6L8ix/KWpQufpFiAIlQQioRQJEwFJJuE3XF6aulUwaSqql5/qoJJVQAMPlBgZsvieXaSDQ7rJBwMBodzGQ5yF0ylxIsT/8vvhn5ATiQ4p+tS3rbqw/gcwUVf/0yqEjJWgZhDgcY4HMAt6v4cCksnAj9/qDIQxLUiCbtO1mFQdBsYXoHsFdj8Ms6gjN+tliFELcOH7ay4av789C4+8+IdJEqLNnaegwDZjkoQQ2+kUKwjUwwghIwsmdQ48zR5C7T7DRpcCk51MdBYuM6haNgV2ykJhTycSqbO/vgBhgZHiQ1FMcZzuKcUWlJB2tM1uHV7ZVvdIRANKo5mN3LYgRQuJ6HX2U7o6rkQgkzJLEPKHKzMgcuh69Kl13M5Lqh1qpUS2HPlsO3UOI49xE0IQdEU5HVjXs7SQbcrYYYmucr9Q7eZDUG8sUbQ1tGNbIBqgmKCakrYBNhMCdWE2aMraOBqOj25hVUwqaqq15+qYFIVALlJEz0rDoEIxWZd/T8dNn2qEOPnu/6L3w88gKY4uWzZh7io+zpsiv3oT36dSRgCUz/IzSmPxyrTFGQzc85KJiXIJAXplFX8YFaqjbKzIuH2Snh8Mm6vhOYosnvqObaOPUY0N47b5mdN01tY3XghLu3w1bnSxSLPRqZ5eiLCRDaHU1XYWFfL5voGmu1OKJlQEpQKOpFkAVnWUA0V0jJ6QlAsLwf3n1DdoAVktIBUXmQ0v4Q9IKEFZRTnsfUHOh2KFVIMpscXwMKsC2GXbYseV1432Dqd5LmJOM9OxBlM5gCod2psagywqTHAOQ0BfNrpr9QuhIC0YV0RjxQXVsCKFGE+KAcU8rWCyWCG/a5JttqHeFrZzYQtCRK4VSfL/W0s97dX3JU2d/1pg6f5svKLDBIFg2RRP65E/7NNhhBkSwaJlEEsbTBq5BnLFZnM6kxldYrz3pxNBo9NxmWTsKsCVQZZMhHCpGDOFkuYA4vj/VgkKIcdKnPhh4qMXVVwKjLX+HQ6unuQJMqFFqz/R1myQvckCRQBsgGKLGF3Vh2Tqqqq6thUBZOqzrgmUgM8uP1rbJ94ghpXmCt6P8aGlsvO+NXx14uEEOQygnhUEJ8xSE4ZpKcN/n/23jxMrrO+8/28Z6mlq6qret837ZK1S5YtGy/YJgYCxo6AAcLmBHwhcZjg3EkyIZd7L4SZYRLWsCTA4IeweYAQAoTNxmADtmRrl7VaS7d6V3dXV3XtZ3nf+eNUV3dLrZastSXX93nOc0qnzql669Sp1vs539+SHpM4GYkhFbqUaMpBilOYZob6SITGaC0hU8NvKDRbgSVRVnFdkDD52JJQ8ODDLUgMG3Tm+O5MMZVcW+1VC3KDBo5pYGsGBUfDmgArobASEitxJqBpPvBFxZnwEvPgxYwIxDyP6xnKFNg2lGDb8DjPDydJ2y6agBXVEW4uVvtaVhVGvxD3wVWoxLQcgjEbeVoFJ6xpf98FiHrfGcnnWqNv1p0NXbkAACAASURBVIpNtnQ4kRrkYLKbg8liGNhEL4XiFxUyAiytbGd5rINl0U6WRzvoCDdcEViZD1JKkXVkKS8qaTmMF+xiAYZiCGPBIZ2WiAkdX8ZHZd5PrVVBSHrhfw6SuJljxJdj1Mgx6ssRNywQGrrQEWhIpc0o1CCAClMQ8Qmifo2agE5thUl90CBsGsXcJo2goRdBYxI6vDwev64RMHR82tzFNuZD8ns4HGbr1q0vGUweeeSR5nA47H7kIx8ZvtgxbNmypfN1r3td8sEHHxw/995llVXW+WguMCk3WCzriqgx0sX7bvk0R0ae5/t7P8Wjz/8NTx79Fn+w6oMsql13tYd3xaSkgukAUJBzwMBZAMFSxW3Fx9bU87GCJGaf6U7MlAFM9rCIA+AAUhNIQ4BPQ/g1tIBAD2poYR3Nb4JPI+Dzni/oigO5CXYn4wzYefAJVjRWc3NDPQ0Fc0ayrbs3X8pP0ItLQICITStv2mqgIiauT8fSDArKwMoWwWVckR1wcTKnfQwNfJVFYDkLwOiXIAfnYtQY8vOGhQ28YWEDjlTsj6dKbsr/2t/LV/b3Uukz2NQQ5ebGKjY1xqgLemWLVUGeFThKlZdO/54jOqLKhAYfYkkIIgYqYqCqfVBjogztzNSwcWB8tjhDQQvNtOjN3FN9C1SDI10Gc6McTw1wIj3EifFBtvUd5TfyEAAB3aQj3EhXuJmuSBNd4SaagjWX7AaEwMtnmBFGeoncXkdKkoUiXMxSiGGqx41dDDWzZzgcABWuQa1VQYNTQaMTpssK4ne8/2YVCkISs8klXGsRCmo4ExrV8RBNYyHc4vWt6VBd61Xsm6zcp0cUvZnCjKajPRMFjsStYgGFAgJoCvnojE6Gg+lUVZp0VgaI+Mqd5csqq6xrQ2UwKeuKakndjfzlXd/g+ZM/4Yf7P8ennv5j1jbfxRtWfoD6cPtVHdts0DB90j8JCJ57MB0KpkPGtG0FVYSHKciYcQf7fCUAvwY+gfBrHjgUAYFKrQQNk9uUCYOFExxOPM9g4TiYgoVN67ih43ailXUIn/dari5I5QTJlCKRVCQTimRckYxL3Gnz1ECQqSph1RqxGkG0WmNDuIENwJ6xOP9+vIfP9vXwyaET/Jf1q3ng7s6Z53ayvOm0XgylxydyqB12KbTIV1xmdMPuNCFq4AYMbMPAQqdQ0LCSYCUk6ZMSa597RkEGvQL8xRAxX9VUuNgkvBihKxcupgtYFY1wQ0WEd7W0MHGqwLHjSUb7suQOFNAzI5wojJKxNWIW+OyZ14oS4PoNXJ+B4/NjN4RwdA/kLKVjKR3X1aAADBWXqaOBOZtZvwRFaSBKA8u5+Rx7TgATnHej7guWOD3PzQRMcHWFoyksTWJpkryQ5HDJ4JLBYUI5TEiHpLSZkE5pv9IivGMDfkE04BVlaKjwszQWpgofkZwfX8aHmNCxEhp2zruWhIBolaCmQy/1L6qu085arEIpxURCMTYsGT3lNW49fsjh8F7v+RKs1IdY0hChZplGrEbDQdGbKsJKcgpctg+lZ0BTdcAoNRmdzGfprPRTG7x2SjV/6EMfavzud79bLYTg7rvvTn7hC1/o379/v/9973tfezweNwKBgPzKV77Ss27duvz04z7xiU/UPvroo3W2bYvOzs7C9773vRORSERu2bKlMxKJuHv27AmNjIyYH/3oR/sefPDBcSkl7373u9uffvrpyubmZss0zes7yamssuaZymBS1hWXJjRu6ngd61ru5pdHv8kvDj/KvsGnuX3hm3nNsvcS8p27I7UcKqDyxYn+NICYGxqmuxCXCBo0pqDBV4QGf9F1iOklWBDFfUoA4ddKgIBZfN4/9Rql1/NrXgfs85g8ZK0Uz3T/G78+9hjjaojarlbuXPhWbu54PUEzPOvQq4vLjHMrvbyVRFySiCuS45LkmOTEEQdr2hzTMCeBJcT9NSt504oVfL3vIB/fsZfBTJb3rVxeasAoTM2r4tQwewNPJRVqYjIsaSbAyBEbdTgLOW9+YBSXCkOUwsREjYlYbCKDBo7PwNZ0Co5OIeW5LvkxycQxrwjBdAmTEqhMBxgREWAKfGqqdPXcRQ9OK4BQUGhZGy3noudtjIKLYTsYrovpOpiuSwjF6qmR4AoNWzNwdJ2MYZDw61iaTt7UcQI6osLEF9DOqPimm4KQCZFZClcIEyzHm9j6AiDmCr+7hHKVZDg/Tl9mmL7MCL2ZU/RnR7GVV3zDpxm0VNTRFqqnraKe1lA99cGqUtnhM15PKtKOS9ZyyeRdsjmXXN6lkJdYlsIuqFJxCmUryAhMKfBJbcYSkAZR6Zs7DPFs0gHN42dXeYsU3qL7wRcU+COCYFgQjApMv/BcHRu0U5L0uDpLCXNvXRkVRKsMFiwrOiyTsHJKloDlxBGHw/u84UzBikZbQ4i19RGqVmjousCVisGMNcNh6Z7I83hPYkYxgQpDK8FKxzRgaQ7P/J1+bVuB7vilnZ93Vmu866bzyzX8zne+U/mTn/wktmPHjkORSEQODw/rAO95z3s6vvSlL/WsWrWq8OSTT4be//73t2/duvXI9GP/8A//cPwv/uIvRgE+8IEPNH/2s5+t/dCHPnQKYHh42Ny+ffuh3bt3Bx544IFFDz744PjXv/712NGjR/1Hjx59oa+vz1y1atUN7373u8uNEMsq6wqpDCZlXTX5jCCvWfYebum8n/848EV+ffQxtvX8mNcsew+3L/xPGNrZu2wX/v4kKnn2CmNACRpKAHBe0DALIJwGHtOfnw+dqU+lT/Lro9/m2Z4fYrk5Ftdu5E1r/pJVTbehiZcewqFpgkhMEIlptC2Y2q6UIp+FRFySjMvSerBPcuyQZ3csYQmLzAV0j8X55NETvP3mNuobDLRzhNoITSBiJsRMWDj7PirrzuK4eBAj92e860EVv3bAL/Caxk3muawwS+Fitm5QkDpWXlAohoslhlyc9PnBqSYlpnTwaS4+5eKTDqbrYDgegOiWe8bUVwZ0L6wq4seNmrhRE2JGyRXSIxqmX0MzoYBk98QEW4cTbDuVoD/t3QRuCfmLneirWF8fPaPUrFKK8VHFUL/LcL/LcL8kl/E+k6ZDKCwIV04VQwhXCkIRzVuHL22/nBoaWEFD6d+OdOlOD3Ig0cPe8V4OjQ/xs9R+rJyBGPVjijBVZh1hI4ZPRFDKR94RJCxn7j42YYOqGoOor1ha2j9VWjro17xyw75i5bdiHxskp1XcKz62FNmUYmJUkoor0glJbsIDU015yd5+HwT8goABpibQBSinCKSjitygJHMpSpBPA8yoCVU+gVaj4yoo2JAvKLJxRbLXYcT1HDWlQ0WloLJGEK3V6GoIsq4+hNnmXVfCUIxb7oxwsO6JPM8Pp/lpd6I0DkMTfGyRpC9VwK9rFFyFVHC1+tY+/vjjlW9/+9tHI5GIBGhoaHCTyaS2a9eu8Jve9KbSXwzLss4Y4Y4dO4If/vCHW1KplJ7JZPQ77rgjOfncfffdl9B1nQ0bNuTHxsZMgKeeeiry5je/OW4YBp2dnfbmzZtTV+IzllVWWZ7KYHIOOYUUdnaMQLQVoZVP1+VQNFDL29b/P9yx8C38275P86/7PslTx7/D/Sv/M2ub75rVLfC9sxGlODO0aZ5Bw+WSUorDI8/xq6PfYv/Qb9E1gw2tr+aVi95GW2zpZXlPIQTBEARDOk1tMyfEtuU5LPERyXC/jtZdDd0GP+22MEyLhmadhlaNhmad2kYN4wK+G1Ghe0nabQFmwy1lS9S4M6MD9mRuhjyZR+1Ol7phFyN9vG7YRcclVafznE/Qa+lUxUxifsGpIYuKgku74dKuu0TyLozbJfemJB3vdZpMRHVgKgRtegEA8/yTwn1o3Bat5rY2z8/qTeWKSfQJftozwvePDWNogjVVEW4M1tDmVOLGNU4NyJKrVREWNLVq1Dd7Z8vrkyNJpxT93S7ZzJkQFqwowkqlmNE3ZxJgfP4z3TvLlcxoljmZjzFLs0wvMVzDVe1Ae+m7AC/YbNySxEUOySiIAppmUeU3aY+F6AjHWBytY3G0jpqA/+L62OigaYqcBWPjM5ue5r1Cal44VrWgttOgppjrUV2nYZrnWcLXPYurZoNrFbc5c/RdOq0EuZNRM7ZpNoRcCJ3+xkkFvYockhwwePrzGuh+wWIzyFIzWIIgZUBeSLLKZUK5BJ1+fDmBrRS/v1CghEACmuaBi6ELzOLiMwTGS7i+L4Vc1yUSiTiHDh06MNd+Dz30UNf3vve9o5s3b8599rOfrXnqqadK5QcDgUDpR3A9FQIqq6xrWeWZ9jmUOPkML/7ibxCaQSDaTrC6i2BVJ8GqLiqqugjEOtDNy1O//eWmluhiHn7F5zkw/Az/tu/TfGXbf2FhzVr+YNUjdFavnLGvvmb20rbXu2y3wPO9P+VXR7/FwMRRwv4qXrPsvbxiwRuJBmqv2rhMn6CuUaeuUWfpKpPbCfCTQ/089lw/i2QtgYkG+n/nAjaaDnUNGg2tOg0tGvVNOj7/xUOkMDVEvQ/qzx4uRsotdb6ehBd7xCbRZ+GbcHilM3u4Ss4QjPoM+sMGlUsjtHT5MOt8iJqiI1NpXNau2G2RIG2RIG/oaGSg3+GFo3kG+xzoM5BKoweYMHNoVQ6tbQY3LgvTUnf2ssYArqPIpKdKT6cnFOmUJJmUDA9Jeo46KDnzeKlLLJ9DxrBJaRZxUWBcFEjrFinDIqc5TBaQEkDltMaYreEAq2oiZ22WGfObBHQNiaI7PcjBRI9XESxxjMMTJ9mTtmAI/JrPK11c6mDfQWe4CUM7uzuolPc5pwBEMnZqJoTEagStXUYp6by6TsM4TwiZTUIX6Drogct3XZRKkE9vHmspXEuRSXjOz8S4IjPuOT/SKTo/QEBTBHSBT1OYSqDb4Hc0TFsQsQyUFITsczuuCkgbkljD5QOTe++9d+JjH/tY80MPPRSfDOVqaGhwW1tbra9+9atVf/RHfzQupWTbtm3BzZs356Yfm81mtfb2drtQKIjHHnusuqmpac4C7XfccUfqy1/+ct3DDz881t/fb27dujXy1re+NX7ZPlxZZZU1Q2UwOYcijWtYePf/R278BLl4N9nRF4kf/xVM6+TsjzQRrOoqLp2ltRmcn80E57tWNNzC0rpNbO35IT868EX+/tfvZGPrq7lv5cPUVDRf7eFdFSXzo/zm+Hf5zYnvkS6M0xJdzNvX/79sbHv1vO0J89plLTRU+/mrZ5/jOf1F/se9NxPJhkohRvuet9n7nDcprKrTaGzRaGjRaWjRCVZc+smc0AREDfSoAQuCSKX41YsOj+2wyMTg3mUGb1quE0gVQ8ak8lyPGhOfX+Ngj8tP9tscH5OEknBXg8m9jQa1ocs3IcvnFMMDxbCsPm9SrRQIoVFfF6BhrUawTtGjT3BiPMFzwwmSQw5iCJZVhbipsYqbGmMEDW1GdSmv8tRpjkbBYcKyvc7sESAMQWkQdk3Cro8q6ada+amUPkKOj5gdpNOZ+dmFpvCHPJelMqoRqdSK/XSK4WIRcU63TEewMNLCwkgLr2u7BfByVnrSQxxMFEsXJ3v44cnf8r/dXwIerCyNtrE82sHSaAcL9AWEMrWMj1DKzyjMgBCNtgUznZALcfGutkrwMwvYVwJN0/6tlCKdVIxOA7Pe4UmHTaFpEKvVqK33EvYdXVDRXPx+FSjlrScfKwWuq7BdhXmZY7ze+MY3TuzcubNi7dq1y03TVPfcc0/yc5/7XP+3v/3t4+9973s7Pv7xjzc5jiMeeOCB+Olg8td//dcDmzZtWl5dXe2sX78+nU6n56Std7zjHYlf/vKXlYsWLVrZ3NxcWLdu3dk7rZZVVlmXXOU+Jhcg6VrkE70erIyfIDt+gtx4N/lEN9KZyg42ArESsFRMc1p84QbEy6TW/8Uqb2d4/MjX+OXRb6CU5JWL3sa9Sx8kaL48HJPexCF+dfRbbO/9GVK5rGy8jbsW/yGLazdeM9V0jicn+OBvt5GyLf7bzTdyc2M94IV/jQxKhvtdhgZcRgYlbjFtqLJK0NjiOSoNLTrhyrl7LrxUHRt1+epWi2OjkmUNGg/e5Kej+ty/SaUUR05JfnLA5rmTXh7JTR06r11hsrj+4kuyplOS4X5ZBBGXRNz7+6zrUNs4CW5nd5lcqTg0ni6VJN4fT83akFATlJyLqN8k5jvTvYj6i3kZPm9bwJil14mlSk7LZKPPzIQXLpae8HrrnP5fTKACL0zstByXycf+wPkVe3CVpCc1xP7BAU70ZUiMgEhGqMm3EJResQeFxAmnCNc6tDYFWNxeRV29cU1CyOWQUt735MGbF8o2WoSVlbd009W5DMPwmvAaBhimwDCubOPTcoPFssq6/lRusHiFpJSkkBoqAUtpiXfjFEr5dmhGkGBVxzSXxVsC0VY0/ewJ3y9njWeH+dGBz/Pcyf8g5Ivy2uX/F+tbXoXPCGLq/uuqqZtULvsGn+ZXR7/Fi6M78OlBNne+gTsXvuWql1S+UI3k8vzF77ZyLJnir9av5r6ujjP2cV1vgjTpqAwPuDPyJaY7KrGaCwOVVF7x2E6LJ484RIOCt2/0cesC/YJeayQt+flBhyeP2GRtWFSr8dobTDZ16OeV96CUIjmupj5vv0t6opgD44P65iKYXUReTspy2D0ygUQR802BR8RnlCqmXU5J97RwsZQ6A2Dc02pYGCZTLktkKt8lXCnwBwSJsalJ9NgpSaFYHFZoEKsW+KsLZEIj9JnH2S/3cSh1gqzrXUh+zWRxZRvLS2FgnXRFmjDL+YMlTcJKd88hFnQtw3HAsWcCpmEIdMP7rgxDYJiXD1bKYFJWWdefymAyD2TnxouQMumweC6LlZ5qNiA0HX9layl/xctn6SIY60T3VVzF0c8fnRw/yPf3fYoXR2d+z6bmx2cE8emB0mIaAfx6AJ8exDQCM547fd+5/u0d67+gClcvRTk7zdaeH/LrY48xmumjuqKJOxa+hVs67qfCd+07RBnb4UNbn2fr8Ah/tHwJ712xdM7JjFKK8THFcN9UhanJhG1/YHLirtPY4pVM1eboAi+l4skXHR7baZG14NXLDd641kfFJWjAmLMVTx11+NkBm6GUorpCcO9yg7uXmISnuRpSqmJxgEn4mspxCFTgFQgoOiLVddo5K5ldD1JKUcgxBS1nAIwshWBNl9CgqmZmE8Kq2tnhTSpJT3qYg8keDiW7OZjo4VCyZwasLKpsZXm0gxWxzjKsFDW987tSCulSgpTTYcX0CaJVl+fmUBlMyirr+tO8AhMhRBvwL0ADXsTql5RSnzltnzuBfwdOFDd9Xyn1kXO99nwGk7PJtbLkEj2nuSzd5JMnUXKq3qQv3DAtf6WrBC9GsOqaCem5VJqsSDWc6sZyc1hOHsudtji50mO7uC44udJjy8njqnOUGp5FHvwEMOcCmlmhJoB/Djiy3QK/6/4+z3b/O3knw4Katdy16A9Z3XQH+jU0OVJe0DnCOPuYHSn5+M69/Kj7JK/taOW/bliLqZ3fhGYyRn5omsMwkfD+fhkG1DVNOSr1TVOJyy+OuDy61eL4mGR5g8Yf3eyn7RyTKOl6+bEvxcGUSrGrz+UnB2z2D0qCOryiXmdJQJAbU5wadLGLfVTClaIEVQ0tOpVVlzZU7XqSbXuQkklJcllFtPrsEHK+kkpyMnOqlLNyqLhkHM9+8WmG56xEO1ge62R5tIMFkeaXFaxMB5PZpJRCSnBsL2/nUhSwmE1lMCmrrOtP8w1MmoAmpdROIUQE2AHcr5Q6MG2fO4H/Wyn1upfy2tcimJxN0rUpTPR57kq82wOWRDe5+AmkM3ULUfdXeu7KdGip7sIfaSrnscwhV9olSJkONXYRYkr/Lj5fcItg48wOQKcfa7t5HDln8ZcZ0oTBhtZX8cqFb6Oj+obL+MkvveTYGHLXdtydO1CjI2hLlqFv2Ih2wyqE78wKWUopHj14hC8dOMyN9bX89803EjYvLIQxm5nuQHjliqF4R71OY0Qo9qQUKgJvucnPrV0zw7YcK00uXvxtTfut5Sf60Y0AVZ23UbPoVcTaN6MZcxcZsAqKUwPeOHp6XBIjElH882r7oblVZ/lincZWnVCk/Nucb5JK0ps55SXXTwOW02FlWbES2PJYBwsjLdctrJwLTK6UymBSVlnXn+YVmJwxACH+HficUurxadvu5GUOJmeTUgorPTzDXfGWE9i5qYqGQvcTjHWUyhtXTOaxxDrKeSxXSK50sN3C7FAzDWxc6XBD463EgvVXe8jnLZXJ4O7ZhbtzO6rbMzbFgoVozS24+/ZCMgF+P9rK1R6kLFqCOM0Z+Y/uk/y3HXvorAzzqVtvpr7i4stuF/Jezsa2F2z6eyUR22u4CFAZzROLDBEyDxNwt+Gk9mBnRkrHzigJHuvEzo4SP/5rnEIS3QwVIeUeYu23oBl+chnvvYb6XYYHJOMjxYpZGtTUazS26ITrBC+kJU8cc0nmFa0xwWtWmNy2wMBXTsCe95odVk6SKd4cMjWDxZFWlsc6isDSyaLK6wNWymBSVlllXS7NWzARQnQCTwMrlVIT07bfCfwr0AcM4EHK/nO93ssBTOaSnU9OS7gvQkuim8LEAF7UHGiGn8qWjcTaNhPruIVAtL0cQlLWeUnZNvLAftyd25GHDnhhWw2N6Os3oq/bgKj2mgEqKZHHjyF3bsfduwfyOaisRF+7Hn3DjYjmltI199zwCH/97POETINP3noTi2PRCx+fdNnfPczXdhr0pkN0+U9yt/ZN9PFx0tYScnI1ObUSiZevFfCNU12VoL5J0dwVo7a1Ad2Y6fBI12ai/3lGX3yC4WMHSeW7yIkN5LUbyVs1AOjFMLLGYhhZXdOZTfhsV/HMCYef7HfoGZdE/HDPUpNXLTOorii7J9eSpJL0ZUa8HivJnlLOSnoarCyKtLA82llMsr82YaUMJmWVVdbl0rwEEyFEGHgK+JhS6vunPVcJSKVUWgjxWuAzSqnFZ3mdh4CHANrb2zf09PRc0nEWXAdHSkLm7E3brgW5do584iS58ROkhvaS6N1KPuGdJ3+kmVj7ZmLtm6lsvRHDF77Ko335SUkHxIVVhrrcmoKM54uQkfcgY90G9PUbZ0DGrMfbNvJgEWYOFmGmvsFzUdZtQKuu4cVEkkd+t42s7fDfN9/Ipoa6OcfkOvnS9TzpFo7GR3ki8xoOGK8mJEe43fo8K3x7qKjunNFjyB/tIp2t4dTAZK7KVH+LYIUolSduaPGSz0uOSL8kmy7ms+h5gmIvAbWdkHmEpq4G6hbfRazjFnQjMPf5VIoDQ5KfHrDZ0euiabC50ys3vKD28hZXKOvySSpJf3ak2BRysjHkXLDihYH55rF7PR/ARAjB29/+dufrX//6HoAPf/jDDel0Wv/kJz85cFUHVlZZZV2U5h2YCCFM4MfAz5VSnzyP/buBjUqp0bn2uxyOyZMDR/ivz/2QpbF61ta0FpcWqv2hS/o+V1r5iX4SJ58lcfIZkn3PI+0sQtMJN64puimbCdUuLeepXAbZ2TgTg7uYGNhFanAXmdEjCM3ADMQwglXFdWxqXdpWXAdiGIHoZQ3Jk4MDuDu24+7aMRWWtWoN+vqNaIsWnxGWdT5S2Qzunt1e+NeJ4wCIroXoGzYytngZj+zcQ/dEmr/ZsIbf72zHyU/M6BM06QZOdwAlOgfD7+C3vBVL+Xll40nuXympqu3ACFSee0xKkYyrUpWs4QFZKtk7qYpQEVhaPUekqkagpMPEwA7Gjj5B/PiTOPkkmhGcykk5D0gZmpD8/KDNr150yDuwtF7j928w2dimvywqcl3vUkrRlx3xwr8S3RxIdnMoeZKUnQXAEHqpGthkkv2ieQQr8wFMAoEANTU1avv27Xubmpqclwomtm1jXmD+WllllXX5NK/ARHi3V78GxJVSf36WfRqBYaWUEkJsAr4HdKhzDPZygEl3aoyf9x1k91g/++IDFKRXzakzXM3amlbWFWGlqaJyXt7xPh9J1yY1tJdkEVQyo4cBMIPVRNtu9hyVtpsxK6qv8kinpJS6Js63UopCaoDUwK4SjEy6VZrhJ9ywikjDKpSS2LlxnHxiap1P4BZSZ31t3R/BDFQVIaaqBDNm0IMXM1hVXHtQo5uhud2NRAJ31w4PHAYHQNPQli5DX38j2g0rZ01kv1B5CfM7cHY+jzXWSz6QZ7y1mv9ZtYb9VPH7+a3cnfw5k6MVuo9grH1GVbp+tYRvHayjZxxWNnlNEltiFw/S6QkvoV4pRUOzTjg6d8UsJR2S/TsYO/o48eO/wsknpkGKl5Oim2fPn8laXgf6nx20GUkr6sKCVy83eeVi45KUMy5r/uh0WJnsYj8dVhZGWkohYMtjHSyOtF4VWJkPYBIOh3nwwQdtYOwf//Ef+6eDyeHDh33vete7OuPxuFFTU+P8y7/8S/fixYutLVu2dPr9fvnCCy9UbNq0Kf30009XPvPMM4erq6vd6urqtX/3d3/X+/DDD4898MADne985zvjK1asyL/tbW/ryuVyGsBnPvOZk6961asyDzzwQOcf/MEfJN7xjnckAO67776uN7/5zeNvf/vbE1f1pJRV1nWg+QYmrwB+A+wDZHHz3wDtAEqpfxJCPAy8H3CAHPCIUuqZc7325c4xsaXLwcQQu8f62DXax554Pynbq4XfEIzMAJWuSM0VaWB2OWRlx0j2bi06Ks/i5L2/w6G6ZcTabyHWvplww6orkkTvOopsXJEek6RHJZkxSXpMkRmThKo12tYaNK80MAPz41wrJcnFj09zRHZjpYcBDyQqm9YSaVpHZfN6QnXLznkOpWvj5JPY+XGc3ExocXKT63HsXKK0jzpLNTChmdPgxYMWwwyjJ/Pog3H04QSGa2A0dOBftQn/ulvRo1WX5rxIh3yyb0b4VXa8m/x4N66dmdrPNflOSGNBEAAAIABJREFU9H62hlZwty/Jf76hjcrahfgjzQjNC3VK5BTf2m7x9DGH6grBOzf5uKljfoTCTUHKpJMyCSmvoGbhPcQ6bj0rpEip2N7rlRs+NCwJGHDnYoNXLzdprCw7l9erlFL0Z0dLOSuHEl4o2EQRVnShsyjSXCxb7MHKokgr/sv893c6mPz8dwWGRuU5jnhpaqzVuPfWuSvdhcNhHn/88ewb3/hGY+/evQc+85nP1E6CyV133bXogQceGP+zP/uzsU9/+tM1P/7xj2NPPPHEsS1btnTG43Hj8ccfP2oYBm9729va77vvvuTChQsLDz74YNfKlSuzjz32WE9HR8fKffv2HRBCoOu6qqioUPv27fO/9a1vXfDCCy8c/I//+I/wpz71qYYnnnji2NjYmL569eoV3d3d+8oOTFllXbzmFZhcTl3p5HepFMcmRtg11seusT52j/UxmvcmWVFfkLXVLR6s1LayNFqPoV17MeRKSTIjh0mcfIbEyWdJDe0F5aKbISpbbyzlpwQqWy7qfey8KkKHJD069Tg7riajdgAIRgXhWo2KKsF4n2RiSKIZ0LTCoG2dQaxZu6ITVOnaZEYOkRrcxcTAblKDu3EKSQDMUB2VTeuobF5HpHkdFdULL3tonFIKaWexc+NT0DJjncDOxrHHB7FTIzhOBlc/e08X3RcuuS9nOjGnr2MIzSiVtfZK8HqPvb48U+9jhupKleImS10Hou3o/XHcXTv4X6MJ/qWpnU3pJB+tixLZcCOqvpFfHHL47i6Lgguvu8HkgdUmAfPqA8lsUtJhon8nY8eeYOz4kzi5cTQjQFXHKzwnpeMVZ4WU46MeoDzb7SIlbGjTec0KkxWNV/b6LuvqSCnFQG50Kmcl0c2hZA/JIsRPwsqyYo+V5dEOFle2XVJYmS9gsnXr1uxXvvKVpGmaKhgMykkwqaqqWjM0NLTX7/erQqEgGhsbV4+Pj+/ZsmVL55133pn6sz/7szGAL37xi9V79+4NdnR0WIFAQD766KN1P/jBD47dd999i/bt23dwbGxM/+M//uP2AwcOBDVNo6enx5/L5XYBLFq06Iann3768De+8Y2qo0eP+r/0pS/1XdKTUFZZL1OVweQKybvzlWDXaD+7xnrZPdZHb8ZzG4K6yarq5pKrsrKqiYBx7d15cQopkv3Pkzy5lcTJZyikBgEIxDqKIV+bqWzZMOuESylFIaPIjCrSox54ZEY9B6SQnroOhQ6hKg9AQjUa4VqNcK0gVK2hnzYJTQ669O5yGDjg4FoQqRO0rTMvm4vi2jnSw/uKELKL1NBeZLHPQSDaTqR5HZVNa6lsXo+/cu7E8CsppRSqpxt3x/O4e3ZBNguhMPq69Yi1a3HrorgznJgph2aGO1MMNVOude43FRqBytZib52ZSejnKrKgCgV+8OxW/mEkQVc2zUM9cX7UfB+9Ri2r6yXvvjVEc/TacRG8nJSdRSflV9i5OJoRINZxK7WLXnVWSIlnJY8fcnjisE2qAB1VGq9ZYXDrAgNzjk73ZV1/UkoxmBsrlS0+MAusLIw0szzawbJiKNjiylYC+oWFYM6XUK6tW7dm6+rqjqxfv37FW97yllGllDgXmLzuda9LPvjgg+MAR48eNd/0pjctbG1tLXz84x/vf/jhh9tf+cpXTpw8edL35S9/ue+RRx5pTqfT2he/+MU+KSXBYHCD4zg7AD70oQ81+nw++a//+q/Vjz76aPeGDRvyV/WElFXWdaK5wOTaql84zyWEoDVURWuoitd3rARgNJ/23JRRz1X58qHfoQBDaCyvaiyFfq2pbqHSN3ey7HyQ4Y9Qs+AuahbchVKKfKKn6KZs5dSBf2No72OgBaiouQtf5e0IcyVWtqoUfuUUpl5L90G4VqO2SydUKwgXISQYE+ed/Btt0ok26Sy728fgAYfe3Q4HfmFx6EmLpuVFF6Xlwu8yO/kJJgZ3Fx2RXWRGDqCkCwgqapdQv/wNniPStA5fqPaC3uNySp4a9ipi7dyBio+BaaKtXOUlsS9ZhtA9F88AOM/xe65MbtbwMulYpVyQQKwN7QInRcLv54E77yDSM8I//naCL7Q3UinTPHzym2zYfwC9dzHO+o3oq9YgAvP/dyM0g2jrJqKtm+i6/a88SDn2BPFjTxI/9ks0w0+swwv3quq8rQQp1RUa/2m9jwdWm/z2uMNPDtj80+8svr3D4lXLTO5ZahILlgHl5SAhBM0VtTRX1HJ380bgTFg5mOzh10O7+ffe3wKgC40FRVgp5axUtl0wrFwtNTQ0uK9//evHv/Wtb9W+9a1vHQNYt25d5itf+UrVn/7pn8b/+Z//uXrjxo3p2Y5dtGiRPT4+bti2LVasWGFt3rw5/fnPf77xH/7hH04CJJNJvbW11dJ1nc997nM1ruuWjn3f+943etNNNy2vra21y1BSVllXRmXH5AorZeXZE+8vhX4dGB/CURIBLKqsK1X+WlfTSl1wfpfudW1FJj4VepUacZgYzpFPmig1FbamaeP4wykidSZV7fVUNoYI1wr84bmTii9UyaGii7Lfc1HCtZ6L0rLSwDzHJK6QPlWCkNTgLrJjxwCF0EzCDSu8/JCmdUSa1mD4I5d87JdCKjWBu3sn7o7tqL5eEAJt8RIPRlauvuQT+VxSMnzYZfiIQy6p6Nho0r7eOMPdeilypeLnBx2+u9vCchVZfx8pfzf/44aFrDn+InLndtTYGBgm2sqV3mdburwEWteKlHSZGNzlJc4f+xV2bmwmpHS8At1XMbW/UrwwKPnJAZtdfS6GBq9YYPCaFQYd1dfWZy/r8kgpxVBurNRjZbJ8ccLy5u260OgKN7MiNjeszCfHZOXKlQd7e3uNJUuWrHr/+98//MlPfnLgyJEjvne+852zJr9Pd0wA7r///i7XdfnRj3504vHHHw/de++9ywYGBnY3Nja6+/bt82/ZsmWhEIK77ror+bWvfa0+m83umjz2tttuW/z6178+8Zd/+Zcjs4+yrLLKeqkqh3LNY+Vdm/3xwRKo7I0PkHO95OXWUGxGQn1bKHZVQoOsXDHnYzL5fNRLRs8lpl07AipiYir0qkbgqxjHzjxHeuhpkn3PeRWmhEa4/oapJPr6FaWk5kstx1IlFyU54OWiNC7zXJSqVi8MKJ/sZWJgZwlGChP9AGhmBZHG1SU3JNxwwznLv15NqUIBuX8f7o7tyBcPg5SIllb0DRvR165HVF5448LZlB6VDB92GD7ikhz0Ys/DdQJfUBA/KfGHBQtvNWlba6C9xJCjg0MuX91aoDehWNOi8+6bfKDneeR32+hLZ/jbjWv5vbYWLzRt5w7c3Tshm4GKkNfEcf0GREfnvAmjO19NQYrnpJQgpf1WahbdQ1XHbTMgZSAp+dlBm6eOOhQcuKFR47U3mKxr1a/ZwhtlXR55sBIvdq7vLgHLuOVV/ZuElckeK8ujHRhDFitWrLjKI7+6DRZTqZS2YsWKFbt37z5YU1PjnvuIssoq63xUBpNrSI6UHE4Os7sIKrvG+klaXpOuGn+oBClra1pYFK1Dv0TJ1Eop8ilVhA81DUIkVnZqP03Hg48aQahWK4VfVVQLdGPukqrp4f2l3inpUwcAhe6vJNZ2E7G2zUTbN+MP11+Sz3O6JoZdenfZ9O+zcW0NMzCCz/whOt9H01IYgVgJQiqb1xGqXYK4zJ2abVfxs4MOPz9oEwsKFtRqdNVoLKjRaY0J9HOEsynXRb54BHfn88gX9oFlQVU1+voN6Os2ojU2XrKxKqWYGPKckaHDDpkx7+9GtFmjcalOw1KDULV3LcZPuhz5tcV4nyQYFSy6zcv5OVd43nhW8s3tFr897lIbErxrk4+N7VPVtiYsi7965nl2jY7xJyuX846lixBCeOfh8EEvZO2FF8CxETW1aOu9JpBa3eW5pi6nPEjZXQz3+iV2dgyh+6nquGUq3Mvn9VJKFxRPHrH52UGHeFbRGBG8eoXJnYuMeVsYoKyrL6UUw/nxqTCw4noSVv6++UE6lnQR0H0EdT8B3UdA96Fd4d5WVwtMfvCDH0T+5E/+pPN973vf8Ic//OFTV/r9yyrrelYZTK5hKaU4kRorQoq3DOe8/zjChp81NcXKXzUtLI814tPnnkxLV5Ed9xyPzGkVsKbnMxsBStDhuSBeDkgwKhCXoPmbnU+Q7N1WAhU7OwZAsHphyU2pbF53wTkKANK1SA/vn6qYNbQbp+Bi2XfhuFuwrcUIzaVuoU3npijV7Vem5KxSiq3dLt/aYTGSVtzQqCEVdMcluWKlX1P3Ep2nYEWjJaahC1B9vbg7i80P02kIVqCvWet1Yu/suqDmh7OOUyrG+yRDhx2GD7vkJxRCQHW7RsNSg/olOsGzlLFVSjF6wuXIr20mhiShasHi2300Lj/zHDvFsK3v7bZwXHj9KpM3rDLxzwK6luvyd9t384vefh5Y0MFfrF2FMe3zqnwed98e5M7tyKMvglKItg7POVqzDhGZn+F3c0lJl9TQHsaOPsHYsV9iZ0dnhRRHKp7v8ap5vTgiqTDhlUsM7l1mUh+5dgoFlHX1NB1WQiOKxgWt5F0LR02ZBX7dLEKKn+AVgJWr6ZiUVVZZl0dlMLnONJhNlkK/do/1cyLlTer9msENVU3FEsUtrKpqIWT6kK5i+LBL726b+EmJmlb10R8RhGtOq4BVo+ELccVCYZRSZMeOTpUkHtyFkg6aEaCyZUMJVALR9jnH5FoZUkN7mBjYzcTgLtLDL5SqRwWrFhQdkbVUNq/DH2nyXJTdDgMvODgFCNVM5aL4Ki7PZz9yyuXrz1u8OCJpr9J4x40+VjV7oWxSKYYmFMfHJCfGXI6PypmwgqTNPkXnRDcdhUEWNFfQvn4RvhUrEMalcXdcRxHvcUs5I1bWc8lqF+g0LNGpX/zSzo1SiuEjLi8+ZZEeVUTqNRbfYVK/yAOU/YMuj24r0JdQrGvVedcm3zl7dkil+KcXDvIvh49ya2MDH715AxWzfH6VTODu2uk1jBzo9xpGLlnquSg3rEL45y5VOh/lQcpexo4+Pg1SfMTab6Fm0T1Ud96O7gvx4imXnx602drtooDlDRprmnVWt+h0VGvlUK+yzqnJHBOlFI5yybsWOadA3rXOgJWoGaIlVHdZxlEGk7LKuv5UBpPrXOOF7IzQr8OJYSSKOivGPdmNLB7twrBMfBFoWWESqS/mgtRoGP75N0FxrSwTA9tJFEsS55O9APgrW4i13Uys/RairTciXauUpD4xsMvrWK8kCJ1Q3bJi2V4PRszg2RsFOpZi6JBD7y6HRL9E6NC4TKdtrUl1+6XpGzGcknx7h8XWbpeqoODN603uWDh3eJPKZLB372Jw94uciEu6gy10Vy2ix6wnJz2YMTVor55yVbpqNNpiGsZLyOtwLMXIMZfhww4jx1ycglcxrX6RTsMSg7qF+kVfJ0oqBg64HP2NRXZcEWoUHK4R/DIuqYt4YVsb2l6aY/X9Y938w669LKmK8olbb6JmjqR+OThQ6mpPIgE+H9qqNR6kLFp8zSXNg9djKDW4x4OU409iZ0aKkLLZc1K6bidhV/DLww47e116xr07EtGAYHWLzpoWndXNOpXzpDlpWfNLcyW/z4AVt4ApDKouUzGQMpiUVdb1pzKYvIzkOoqTBwsc3Z7DGfQhkRyp7OG52AscC/XRGo7SGamhK1JDZ7iGrkg1nZEawub8vXucT/YWQ762kux7DunkvGYnxTt2QvcTaVxZyg+JNKyekST8UpQ6JendbdO/r+iiVBddlFUvzSmwXUWyIBlMufz8oMPOHoUQio56RVXMJe1IEnlJouCSshTu5O9QAY4Ntg1OsSGhpoFpeoumgQIhNTSpIVwdrbgIRPElFEqTSN0tLUqTMG34fhc60iZdKYO2jIGhBDld0h12OBFx6K9wcC8gOsOvCxbGTJZWmyyt9rGsxqQqMDXpt2zJL35hkX/BJeSCUy246TU+6jsuzPH57cAQf7ttB1V+P596xU10Vs49OVJSok4c90Lh9uyGfA4ilejr1nuhcC2t11zSPEyDlGPFcK9JSGnb7CXOd91Oyqlg74DLnn6XfQMuqYJ3SXTVaKwpgsriOu2cuU1lvTw0H6pyQRlMyirrelQZTF4GyoxJenc79O21sXNeh/S2tQYtawy0oORgYohdY/0cSgxxIhXnZDqOMy2mqzYQKoJKDZ2RarqK8FLjD82riZp0bVJDe0j2Pofuq6CyaR2h+uUXlYsym1zbc1FO7nJI9HkuSuUCDd8SyFUrkpYimZckCpJkQZLIu1OPC5KMpQhLHxEZQEOQFRZJPY8UiohPEPPrxPwasYBGxBRo6QnU6AgqHgfXBZ/PS+CurYOKihlQMZuUAsuGbE4jmxdk84JcXuBK70AhFFW6otOClgxUpQQCgeVXTNRJkvWSTFTBRYaKZyzFkXGLvtRUmEd9hc7SapNaw+TYgE48AxtbNO4N6pza4WBlFHULdRbfYRJtfOnOxYH4OH/xu224UvE/b93E2tqa8zpO2Tby0AGvktnB/eC6iPoGz0VZvwGt+vxeZ75JKVkM9/IS563MKYRmlsK9qjpvQzPDnIhLdve77O13eXFEIhUETVjV7Dkpa1p06sLl3JSXq8pgUlZZZV0ulcHkIvTbvhyf3p4koAv8hiCgCwJGcZncZggCulba7j9tn7Nt8+niomK9XaeYO7LLyx0RGtQv1mlbZ1DbNXdYjCMl/dkE3ak43akxTqTG6E57jzPOVBZ82PDTWXRVuiLVJXhpDkUvWUWwKy2r6GZMwsQkUCQLkvH8JFy4JfAwU7A65WdVxiQoNcYMl91hi71hC8eUxAyIGpKo5hIVLtI26M9EyUofzUaKu/3HWKziRO0MlU4W3bJQlgW2BZaFyqQhkwG/H33VGrQNG9EWLr7oJHalFCd7XY6/4JA6ITGT3m89qUNPEPorIFwv6KrVS6FgbVXaJekonrYkR+I2h+IWL5yyOT6ggWXi4JLQc1SGleeqVJp0DBvY+xVuARqW6iy+3Uek7qV99oFMhg/+dhuDmSwfvnEd97S1vKTjVTaDu3eP1/vlxDEARG0dhMOIUBgRDkMo5D0OhUqPmXzO55tXAD8ppSTpoX0lJ8VKDxchpeikdN6O4Y+QKSheGHTZU3RUxjLetdIcFZ6b0qyzolHHN0flvQseo5SQyaAyGcikUZk0Kp2GrLdNpdPF59NQyCOqqhENjYj6BkR9A1pDA4Qj8/L8X8uaD2DysY99jK9+9atK1/W8pml84Qtf6Lnrrrsycx3z53/+58133nln6v7770995CMfqf/gBz84GolE5FzHnI8eeeSR5nA47H7kIx8ZvtjXmq3XSlllvZxU7vx+EYr5NdbW+8i7ioKjyLuKCUtyKqumthW3ywtgPL8uCE4Dl7PCT2mbRkVWEDgpMLoBC7QwRDZqxJZphKIarg6JgiwB0WzwY2gaHeFqOsLV3NG0qLRdKcVIPs2J1Bg96bgHLKk4zw6f4McnXyjtZ2o67eEqusJTDktnpIb2cBUB3byAM31hkkqRthTjOYdE1iaZsUhkbRJ5h0R+CjgSNiQdQcLRyKnZJ71CKSJYxGSBSpmn2cmxzM4StbNErTSmm8XnNtLkLqHGaeGecZNa6wAtheeIOSfoDjTzWNNreTHURXP+FA8N/ZQ1mSMInw98foTPBNOHMn3etkgETB9awI+2ZDnaDTcgzItzfpRSpEYUw4e8HiOpU97/xzWNGg1rDRqW6KR90B2fSrLf2u3wyyPe8boG7VUzc1baLwBWwj6N1XU+ekcE/X0apoLXrjJY2KRzLCk4PGZzOG7zmz6vmbK/Hl6ZDbLmqI+hww6+BRrL7zBpaTq/a6k5FOJLd76Cv3zmOf522w6GcznetnjheU9WRUUI4+ZbMG6+BRkfQ+7aiRzoh3QaFR9FnuyBTBrkWeY3huFBSijkgcsk0ITC0yDGe06Ew1ARuiJ5LUJoRJrWEGlaQ8etHyQ9/EIpcX68++kipNxMzcJ72NB1Bzd1RlBKMZBUJTflicMOPz3gYGqwvFEvhX21RM9skKqU8mA7nS5BxiR0lB6np29PQy7nWX6zye8vnq8worISfHWosVHk89ugUJjaL1iBaGhAq69H1BehpaHBg5hLVKWurCurZ599lh//+Md85zvfyW3YsOHg4OCgUSgUzvmD/vSnPz0w+fif//mfG9773vfGLxZMbNu+mMPLKqusl6AymJxDK+v8rKw7d/6FUgpbQt5RFNwpWMk78oxtBUeRm76t+DjnKAqOJO8q0pZkLDe5TWHbio4JgzUpP/UFAxfFwQqbXTGLE34H7ZRAOyXQlYaGQFPCW6NhINARCAVKKCyjAD4bn65jahqzz90CQHNxgRhQKRS2lNjSxbFdRnKSwVMuT0uJN62II4ijaxqm0DA1HUPTMTXvfS66EpBUKNvLv1COTRadCS2APItzE3BtKt0cMSdHpZOl1clR6eSIOlmiTo6ozBPDplI4xHSXiK7QfaYHBz7Tuwse9oHPB2YIfLHic0OkrQz9Q7UM9N/AiH81ll+y16cxVqn4o1Uudy2uR/c/BPrlL0GslCLRP9V9PTvufRtVbRrL7vHRsESnIjZ1jiJAUxQ2d00dfyqtODEmOT7qwcq2bocnp8FKW2wKVBbUnhtW9g24PLq1wMCEYmObzjs3+Uolazc1TyWpZ2zPWTkctzgct/n+qQxt/QYbT/jZdbzAY7E0yYWSzqZi3kqNj9rg7BP6qN/HZ2/fzEee38U/7j3AUDbHn69Zif4Sz79WXYN296vO2K6UgnyueGd/lgn25LZsBk6eRGYyXg7L2RSsmAYxRaAJnQY005wa/P6LupaE0Ig0ribSuHoapDzB2LEnGO/+DUIziLbdTM2ie2joupPfvyHCa5dpWCmLA7159gwq9sZNvj7g5+vPQ7XIsYpBVlk9rEgfpSI97sHbZG7UGSdWKzpMIURFGJpb0Ka5TyIUhnBo5uc/S7U5pRQkE8jhYdSpIdSpU8jhYdwD++G5bVM7Giaivh5RX49W3+BBS0MDoq7+klWyK+vyaHBwkNraWvzF6nlNTU3OU089VfHQQw+1/+IXvzj2jW98I/ae97xnQSKR2CWlZMmSJSv7+vr2TboR/f395qlTp8w77rhjSVVVlfOBD3xg+KMf/WgLQD6f12zbFv39/ft+85vfVDzyyCNt2WxWq6qqcr75zW92d3R02Js2bVq6cuXK7HPPPRfesmVLfPrYPvGJT9Q++uijdbZti87OzsL3vve9E5FIRG7ZsqUzEom4e/bsCY2MjJgf/ehH+x588MFxKSXvfve7259++unK5uZmyzTNi3ZwyirrelX5L/M5NBnqdq4JgRACnw6+iwyDUUqRsyFVUEzkFePDLomDLk6vRNhgB2CgVdAThrj0oxd8tM5xM0fi4goHiQOawlA+fFYEablk9BRxPU7AD5U+X2mJmOZLggipFBm7QNqxyDgF0naBjF0g5VhId+pOqE/XCRt+QqavuPYTNn0ENHP2HIrinVeVTnl3rvPe3XU0gagIUeE3iOouUV0RNSHmE8R8EA3oxAI6gYAHGMKsBl+jBxqT0GH6LmpiEgP8tmLfbov9OxwWpjU2pkBkBHUhH4moSU3npanoNZukq4ifnOq+XkgrhAY1nToLbvbK+vrD5+kWCEFDRNAQ0bi509umlGIk7bkqJVjpcXjyRe95XUBb1UxYaYtpTBQUX3/OYluPS2NE8Ff3+FnXevbzHDI11jX4WdcwBf9ZW3Kwz6Jvm8OyEyZqJ+wIW/zvaJqMrqgNaiyt9hUT7GfCil/X+ehNG2gIBvnWi8c4lc3x/29aT+ASTEKFEB5MBCug9vxKoyrHmT0kKZNGpTOobHFbPI7s7fUm9u5ZGkzreil0bApiZgLNFOQUJ/bTXBmlFBQKJYiqSOtU+F9BS/tq0vEjjCd3M35yN4me33JcCSKFGmKpKqLZGpZLg+XAW4AxM8q+8GL2RZfzXMUCnjIXoMXuYGHNOKsCCdZUZumqAj08MwSOQOCS/R6EEBCrQo9VwdJlM895NoMaHkaeGkYNe9CiTp7E2bN7ypkRAlFTg6grOiv1DWiT4WHB4CUZ4/Wkbb8uEB+5tHPp6jqNm+48+02/3/u9/8Pem0dJctV3vp8bN9bca196q66uXiW11OpGAoSQEAKBDPKTBbYxiwzDeNDYaMYMxx4MD47tee8Yju1BzDkDGuHzsLE9vIcXjMUitDQtQAgk1K2t972rl1ozq3KL/b4/Iisrq7qq1d2SWkKu7zm37o0bNyIjozIj7/f+vr/f7+38yZ/8Cb/yK7/iXH/99Svf9773Tb797W+v7N69OwXw6KOPZoaGhuqPPvpoKggCsWXLlkrr8Z/5zGdGv/zlL/fs2LFjf19fXwjw/ve/fwrg1ltvHbz++uvLnueJu+++e+V3vvOdg/39/eF9993X9slPfnLZN7/5zaMAvu+L5557bg8kUq6Zc7///e8v/pf/8l/GAe6+++7+L33pS52f/vSnRwFGRkaMJ598cu+uXbvs22+/fejDH/5w8etf/3rh4MGD1sGDB58bHh42rrjiist++7d/e+KlvJ9LWMJrBUvE5AWwa/IpvvDM/8Uty2/l7cveSX/qwrTrYaQoe4qyB9OuouwmhKPszW1PuzT7VASr6rCuBj0+RMBxGw7loZaHnC3I2oJ1tkCXEZW4xrhfZrhW5FS9RCh8hBawrj3Dlq4OrursYnNHJznTRCnF7jMR9+92eXo4TzYqoIsKpfgox70TKBGjC401+RwbCm1saGtjQ6GdoXwe8wKlJ5GKOV2b4kjDj+VoeZIjlYnEp8X1oMEzUrrBqkw7A3qaVW7EqokSK4+dpn90MvmA2jbawGq0TWvQBtcgVqx8RVc7o1jxyP4kIeCUC2/aJHnX1Sa2SzOi15m9EU4hCUCwfLPPdR4UAAAgAElEQVSO9RI4EUdBkrRwZF/E6IGQwAVpNHKMrNfpHpIYL1HoVyEE3VlBd1bj2lWKaqgoeh7HSi4Hx0NOFAUjUzqPHrZ55MDM/yImCRkGbd1H6ekb5Ymyw4HDDgXToWClKJgObWaKvGkvmgw0ZWhsXW2zdTXUp2IO/jhAPiO4tm7hDip2t/vsLgc8dtJlhvZ2zCMrv7V2A71ph/++6zl+99Gf8ufXXUPbK5C3ROg65PKIXP68xs8hD5XKWRIoapVZklM8QTwjhVoMtoNIpxNL4zlIjyMlTrqX/vQg9XSdojxJUT/EcfsAQhwmV9hEe/91tK++gf62HvpTad6h60Sx4uBYw4n+VBf/PN7BP9UgU4TN/ZLNpuTKLkmbc+7Pvxsm/lwldzaAxJQ3G7lupl0JYnRtrvx1Ru6a9M34+nVjd/Rgd1/ZlMJaKsQql7BK45gTY1gTI5ijpzH370W03pdcDq2FsCQSsV7I5V6QWCmlqAQeJb9Oya9T9GqNdo2SN9NXZ8qvESmVyGEbMtjV2Q5WpAvo2i9f6OqXA5lMhl/84hd87Wtf85577rnwzjvvXPPZz352eOXKle5TTz1lP/XUU+mPf/zjI9u3b89GUSSuu+66ygufFT7zmc/02LYdf+pTnxp74okn7AMHDjg33XTTOoA4junq6mou9b3vfe+bXOgcv/jFL5zPfvazy8rlsqxWq/KGG26Ymtl32223laSUbN261Z2YmDAAduzYkf31X//1SV3XGRgYCN7whjeUX9zdWcISXrtYIiYvAAF0WB3ct+9/ct/e/8kV+dfzxq53cUX+OuIo3UIumEc0EpJRO4c1I21C1hbkbEFXRrDeEbSPKqyRxDois4LCVZL+K3RuatOwdcWpWo2d42fYNT7GjvFxhqvJs9iROld0dHDT2l6u6uji8vb2BVeJhRBc1qdzWV+GaVfxo0MhD+/LEk5fTqdxGYM9HnZujBPeCNtPnuRfjh4BQArBmly+QVQSwjKUL2Cdg6xIobE83cbydBvX965p9iulGK+VOXJsH0eHD3OkOMLRyWGetATfs3SwgHUp9HVplttZVrf1tPx4p1lFzCuxpqlUorv/uyd9hkuKDT0af3CzyZrOxj3IwMabLdbdaDaDEuz/YcCBR4PzDkowH4Gb5Bg5szdk/HBEFIBuQ89anZ71ks7VEmlcGBkJ4yiZLM1MlJqTpqQuzptIlfw6QbzwhFbParTrXeTow4q6kMpEZfcxpiY5cKrGVOAueh1p3WwSljbTIW86tDXIyxwic0OK7q02px8XnN4d8bpjFr9+bYbumyRHqiH7ZqRgEwE/bSUrtsOm9Fb2j53mg9/fyX97wyau7Hp1O0kLIRLLgm1DR+d5HaOiqGmJmXUgrybEppb0a4Yxa1VpdeJv+MK0ysRsoI3GJHv0+UZ0r4c48vxXOLrnq+SXX5skc1x9I7qdY32PZH2P5DeuThZfnj4Z8uSJkGdORTx2JPncFFLQllOknIhIi5gOGuSjEWDCixb2MdEE5C2NvKVRsDT6MzpBnMhfm75+TdlsUs7t6ieArqTITdAH9IGtgSVibCLsyMcKPayJOuaIh/bsKTROoLQYZUkiSycyBYEp8HWFKwLqkUs1rFGJ6sTKBxGhCEFEQAhEGFLS1vK5Btg5Mcz3h2cDTkmhsSJdYGAmOmKmo9lO6S9t5MELwbksGy8npJRce+218b/7d//u1ObNm+tf//rXO6677rrKt7/97bxhGOrd73739G/91m8NRFEk/uIv/mL4hc73rW99K/utb32r/fHHH98LoJQSQ0ND9V27du1daPxivim/8zu/s/of/uEfDr7hDW+of+lLX+rYsWNHM065bdvNj+BrKbjQEpZwqbBETF4Aqn4lqbF7uKyexP0vTWh89zB8F4BZ50tDmyUZWQu6OrWmZSNrzfSLZl/GAl0TzbC0J3aGFIeTyFq96yUrthgUVgoOl6f56dgYu46Os2t8jPGGnClvmlzZ0cmvDa7hqs5O1hfa0C/QyTNnC37lMoNbN+nsHYl5eH/Az44KguEVrO1axR9t0Bno8ThcLrK3VGRvscgPT53k2y1kZTCXZ+N5kBUV+Kjjx4mPHCI+fIjssaNs9jw2QyKpWL0GbWCQ2soVHLe0RoSwxNJyqDzOo2cOzub6APqcHO12GlvqONLAlgaW1LF1Y05fUnQc3cBqtGf7zDnbhrY4aTg2GfG3T/g8ezqmNyv4xFssXrdy4fFSF/RfptN/mU5lImZ4V8DwMyEj+87PiuJVFaP7Q87si5g4GqFisNKCZVfo9KzXaV+poTUkg7MrtDWK3uwq7dSc1do6pUa76NWphN6CrwuQM2wKpkPecuhL5dlY6KVgNYiCmaLNmksa0vpC0ag2NVthHDMdzJKg5nU0iFHRT6513K1yYHqMklfHixf2UZBCMLihjzePbCN8dDnP/7TK+NApwrUl1vbYXLMyhaM5TLs2I1Wd4WnBgWIIYR+lCvzeg2VyZpnLOq2mdWVDh0mn8/JJ7i4FhJTJan4u99KeVwgy3Zch2zdhbv5dzpw5xImju9h15gCln+yi9tMjBJkhvNQq6noHU4HGlBcz7TV8zhQYusSOddy6TrGmI9BRSHQrIpuO2dSm6MlJsqbAlBFSi0CExASEyqMeeUz5HiUvKaeCAEPTcGydvJT0SImt69hS4kgdU0pMTSKFjhQ6GpLE206ilIYbxdSCkFoQUQ0jakFIJYyoBCH1IKYeKiYihRdBaBlEygKVeOmBDkqHWCJcrWnxbcW5flAtKcAXuHVBSRcYUtAFdBgKPw7xoxAvipgqhjwxEfFYHKGIgTFgDEPIxvvTW2odXQheMJ74HCSBWhQKpRIpbtzSViT1f1oRYhS9xhHNQ+cQvxkaaEpYnV88wenFYN++fWgtv2k7d+50li9f7t9www2Vf//v//3Ae9/73on+/v6wWCzq4+PjxrZt284yHabT6Whqakrr6+tj//795n/+z/951QMPPLA/k8kogM2bN7uTk5P6Qw89lL755purnueJZ5991tq2bdviKypArVbTVq5cGXieJ77xjW+09/X1ndM7/oYbbijfd999Xb/3e783cfLkSePxxx/PLmaNWcIS/q1jiZi8ABxD0J3RGOqUDZIBNTXC3vLPeKq4ncnwKLYRcGP/ddyy/Fa2dGxFO48wukkiP5+Tz4WELqTaBWvfolNZUeaZ6hh/c3KcZ54Zp9yIBtLtOGzt6uaqzk6u6uxiIJt78c7kDQgh2Ngr2dgrufOaxIry0P6Aex/zcQzB9Wu6ede6fn73colSitO1WoOoTLK3WGTHAmRlQzbLujBkXXGSwaNHME8cT2QkQiB6e5FbX4c2uAZt9SAiX2heSw64HLi8vX/ONfpRyIlqKZGENaKFTfsubhQw4VVxoxA3DKhHQdKOLjyKihRiluDMkB2VganL8csr0GRAd99xurvHeKwseWpvC/GRRpMU2a0EyDJoe6NBzxsk5UOS08/EC1pR3GnFmX0RZ/YGlE7GoARaNoINVar9RU5kijwR1CiN1ymdbFg0GpP71nw0rTA12SKfcuhPF1qsEYmkaoaEzMirXmoZia5ptFtp2q30eR9TD/0WKcx8GUyNQ8v2cHjiMGsPr2X5ngGmD1TZ0fkkT7XtIRJz70VKN2jrzKLH3YyVO5kK0+waS/P4KQvVmMxlTcVgQbKxw+SKLoeNHRZdv+RkZTGEsWK6VSrVtFpEc6RUM/tKXoTfNJZlgetBux4ckMSk/TIpt0haDdNl62wsdNCzehlpx8JokAyER6jKVAOfU0WNM0Wb6XKa0qRFaRL2ajWqcpS6PkZdTqDEXOtczjDJWyZtlkW7bRPGMW4UUvRcamFILQzwogg/igkvYoVaoRAoNJH4ThlSwzA1MprE1iUp3SCjG6SNhh+eYZFBYtZcqNTQylUo1xDlClRdlNJQSJSQxE6WOJvHT+fxUlk8O41nOnhI/DlhHPWZiyFSilgpQhVTCwNqoU+98WzzIp9SEBH7ihkyIoWGrmlIIZEiCTIyk2w1miEeKm6cN5HYng8ipZqWUgHJs7tlvyD57RAk9+2lRqVS4eMf/zhnzpxxdF3fNDAw4P31X//1sWw2G01MTBg33nhjBWDTpk31kZGRUFtgYe7OO+8cf8c73rGup6fHf9Ob3lSempqSv/qrvzoE0NPT4+/YsePgN77xjUN33333ynK5LKMoEnfdddfICxGT//pf/+upa665ZmN7e3t49dVXVyqVyjkfnB/84AdLDz/8cG5oaOjy/v5+b74/zBKWsIRZLOUxeRGIVMTOiSd5YPi7/PDMI9TCKt12D29b9g5uWXYra3Jr544PFKf3hJzYNZu0z1gVMNw3zuOc4PniJF5D6zyQzXJlR1eTiPSlUpd0oqSUYu9ozMP7An52NCKIYahT463rdd4woGO3yIeUUpweHWXPwf3sGTnDvlqNfbrOlJGEepVKMaBpbMjl2bhsORu6e1hbyGMv4mPwUl2/F4dNwuK2EBY3CqiHrdutY5LtWhAxOrKMqYlVoDS03CHC7LO4cW3OeS7026Mh6Is62FrcyGWTa3FCG0/3sMJEKnHGmmBP9jC7c4cZsSbmLITmDXuWaFgOeXO2Pd+Ho2A5ONJ4TU6uWzF5PGLfD31KwzFGVuFcXcNbVaIU1pnyWmVqdcbdOsdLDmFsEIsJQCDidrS4HRG1I1QO0cgwqWkehlzcsvTqhWqshCti4katQBmgHFCLS3KECBCahyZ8pOajyQApAqTmI7QQIULQIgSJRSNWSVLGII4Iw2TiGylJjA6LLM4IFFIDKRSWSmGFXVhBN3rQiVB6YiEwJxDOKDI1gjSnaJ1vxipmyncp+TVq4QKLDwoEgqzpkDMcsoZDSrdI6Ra2NLE0A1Ma6EJHCokmNASCMAYvCqlHEW4Y4kZRUprtpPbCCG8RWeO5oMcxdhxjxxFWFGOTyJRcIfCEmK0vJrSxUmgolIiT/3WjaCgcFZOOFflYUYigM4rpihQpBXYcYymF3VJat+vbrmXDwABak8KfA5aFVmi78Gs/DywlWFzCEl57WEqweAngRnV+PPIoPxj+Lo+P/ZRIhazJDnHLslt5k/UrVPfkGH42JPLAT/vs7jjFw+ZBytJDQ7CuUGiSkCs7Omm3X1qz+ItBxVM8eijkkf0BwyWFY8B1/SFvkUdZeeZ54sOHUOPjyWDDRBsYQAysZnTFKvan0+yrlNlbTORgxUbuASkEq7M51re1sbEhA1ubL7wk0ZNeDOI4ea//786AYk1x7SrJ+7aa9ObOnjAopfDjKLHSNIiOF81YbYLGpCbpn9/nRQFuEJI500b7aCderkawvEKmXTvbx8JKkTXsC5bq/VuBUklQgAM7AqZOx6TbBWvfbNK78WypnRuGfO7nT7Hj1BluG1jO/7Gmn+kgscyM1escnYo4Oa0xVjVww1evE3Iit4kaK+ERUUu7FQKRTL5FAKKOoo4SdWLho/CI8VAiJAlc0JArYSSSJQwgkV8tjoSwCCKEiNBEiFABQnloykMSIjUNU9cxLQdd09E1Da1BCpIVfplIvOqdhPVewloPkZ/I0jTpYqbHMVPjmKkJdCMgZ9gNMp5qWPvmygyzpv2yJn+NVIwXRbhhNEtawlnyMktowtkxYUC9WqVereDW6rieSxgECQmAWVLQaDeJQut267iWbZ3Z9YspoTgqI47pMUdlzDEZc0yPOS1nf+c1Bf2RYFWkMRBJVoUaA5HGqkgjo2a/LwevvJoNqwfO76aYFlr+/AI8XCiWiMkSlvDawxIxucQoekUeOfEQz+2cpm/4dayoryEUEbszZ/hF4Tin0yUu6+hIiEhHF5d3dJAxLl1SwguFimPUmdNEhw+z70iJ7VNd/Dy1gUAzWO2e5C3WMG9cpZEaWo1YtnzRxHFKKUbrdfYUJ5s+K/PJykA2N8fBft0lJCvPnkr8SI4VY4Y6NT74OpP1PQu/l1ipZHLSmHzUG/rw1glKvbHa6s3bdsO5fX4cY2gadote3pY6ti5n21Li6DrWvH1OY7zVGGPr8mWdlL2aoZRidH/E/kd9KmOKbLfG2jcbdK+dS1Aipbjn6ef4/w4e4S3L+vjcNVdjX4JkhxeDWljjWOUoxyqHOVo5wrHyUY5WjnCyNkykQpSSgEO7uZIuexUFo5+U3o2lFRCkqYdQ8v3ER6PhqxEt8sw3NY2cqZMxJGlDkNIFtlRYMsKUIboWYGg+QrgIUUdRw49d3MjFjeqN2sWLXOpRHTeoUg+reHFAfIGGOy3qIBO+ESe4FsPfgohzQIy0TqHLMLF4aDq60BOy0/ApmWmfj5z2lYYu4f+85dKE8XDDoJkw90h5kmOVpD5emZwjBe200wxkkghhN2ldbNywoeHH8spJG5eIyRKW8NrDEjG5BFBKcaxc5umDRSafF7SdymFFBmNmhV2FY+xp/wUl7VkMeYbr+9bxjuXv5PXdb8TQXn2ERIUhavgE8ZHDxIcPER89PBuSNF9AGxykvnIdj5lrefh0iuGSwtbhTYM6b12vs7rj/Cd5M2Rlb7HIntLkWWRFQzCQy7Kxrf28ycqFrmiOVwR7jxWYnEpjGD6d3WfQ05NNaYfXuvLZaF+MnCPxYdFx9FmyYekSS5MEcbzgtQaLZRo/B0xNw5Y6VguxmXnNhNjMEprWcY7Um8TImnfcDOmZIUCvZuuNihWn90QceNSnVlTk+zXW3WCelVfmf+8/xD3PPM8VHW38+RuvJW+9MlGPlFKU/CKHy4fZN3WEg1PDHC2PcKpWZMr3QKVQOAiVwZZtSJFDKQc/kviLfDwEkDctCpZJ3rRosywKlkWh0VewbAqm2exrs6yXbQFAKcX06POcPPh9Ro78kEr1FL4mMbs3YC+7CrN7A4Gu4zWIjRvOkpykeJTKBaanV1GrLieMFaEKCeOQxWJwCQS6pmMIo2Gl0dFn2mLh7Us98daF4FNvf2Ut42Ecc7KW+O41w7pXkvqzfdfSOzgAJM8uU+pYDcd7q+F4b54jYMhLhSVisoQlvPawRExeBMIdPyZ86AEwrSSEp2Mj0inCdJpDaYdnNI1nA/AmOtlUXM5yt41QREx0TJAerHHZoMO69nY002BP/RA/OP19Hjr1ACW/SM7Ic1P/27hl2a1c0XblK7YipTyP+NhR4iOHUIcPEx8/Cg2ne9HVnTipD65BrB5EtLXPuU6lFPvHYh7eF/LToyFBBIMdiS/KG1frOBcYynbmnKP1+hyryt5ikUkv8UecISsZw5hLGBqEwz/PybwWm7T568gGK1BE1JwjqPRJbF1rWCRmJu/nsGTMGZdM5K1Wi0bLmIuZzIdxPMcyM/Ne6w3y4rUQrXqLDt6dp5f35h03M64ehRdFfpoWngbZmSU6yb06q2/+OH2Re9sgQBd7v1oRR4qTz4Yc/HGAO61oX5kQlLYVs8T54eFT/PHPn6I35fDf3/R6lmXO30n/heBGIVOeT7FhrSh6LscrY5yojHGmNsWEW2XaD6hFgji2AAdY+D1bmkabbTdJRN6yKJiJQ3i+pa/NTAhI1jRelZYzpRS18X3NjPPu1AkQkvyybeQGb0Zb/kYqwqHk+Uz5yb1L7mGyPe37zRyJiZwtJGiQlDAOmoQljENCFTTqkKCxb77UrRW6kLNk5SziYswSmgbhSSRoFw8haHlmyJbnimz5Hsz/rpy933oZFgqUUjy/ZzcDa4eSaGFx1KhDwpbnhRBgajpZw6LbyZ7jjBePJWKyhCW89rBETF4Egod/SPTwg3hRyN6UwzPZDM/kcjyXzZAL29k6tZLNU/1YyiBmgm7/SdZXf46pFkl6pmmEls4v2qd5uOs0P86dxtMi+sIMN7vruDnaxCrZA6YJhplkKzdNMIyWzOUzGc1n2nMzmiPPvYqlqtXEGnLkEPHhw6iTJyCOk6gr/cuaREQbGERkz//HpuIpfnw45OF9AScaVpTrBnXeuk5nsPPFSWWUUoy59SZR2Vcs4kVRcxJ8lhWg8cPdagWY+ZGXSH5+WGf7XoEfwVvXSd67xSL3EiUn/GXDLPlJrEOt5GWOpanVEXhBC1QiTWuSpZZx50sWW6EL7Rwk8PzJoiUk0X6L8lM6UV2QG4DBN+l0LTfQNY1d4xP8wWM/RwrBn193LZe1n+3EG6mYsh9Q8jyKvseU5yWTZt+j5Plz+kqeS9Hz8BZ9zzFQR2oejg5506DDStObyrMy08XydOdcEmKar7jv1YUiVopyEDDl+ZQ8vyEj82dLY3uyOs1krcJ0GOOKhS1WAsiZJgXLJGcYLyoaoSKxtkQNwhLGCVmZITDz94UqXDQXhRAiISszsrIZEiN0pCabRKZVYtYa1ypqykGjloWCi7OSzi4UJFZYp6VttzwfrbNIz0JkKPkO1YdPsGHjRjRIIn017nsUx3gz4Y0bhMWUOj1LxGQJS1jCeWKJmLwIPLTnR3x1715OxFlCNMxYcn2lly2lVWTqbQgiOo3jLHN3U5g6jIhDaImMgqFBykY4JlgGGBJhyCS+oiao4fJjeZAH7f08ZZ8mFor1tTxvHevjLSOdtNcu4kdY05rERsyQlQZ5UZUyauRMMk7XEStWoQ0OJkRk1erEKvQioVSSDfrh/SGPHQnxI1jdofHWdYkVJWW+MgQgVorHDkd84ymf8api6wrJ+7eZ9OdfvpVlFcdQc1HVOlRrqEodVa1BtY6q1lGVGtQ9RCaFaMtBWw4xUwo5hP7q9H24UMzI6+ot/jUzpGWu9WfWZ2chfxx3EQJ1PtGSjFjjmuIA102uIRWb7M6c5tGuA8SGR79nkClrdNc11sQGyzydmqF4vMfjsVydychvRDw6G6YGpgwRok6oynjRJErUENQQok7BtFmWbmdVtoeh/HLW5wcYzA6SNwsLnu/VCC+KziIVC23PWDmm/WBRXxZLStosk7xpJrVlUjBN0lEZWTyAGNuJWT5GRrn0dq9lxdCb6V5zE0aq/RK/64aFJ6xS8ktM+SVKfpFSo27dbm2Xg+lFz5fRM+TNAnmzQJvZRt4sUDDbKDT6ClYbWT1PSs9jaTmksFvIf9QkMnO+Cw1Lan3emLN932b7z2eh4P9evYy+1bOJcYVIyFgrUZlpO7qky3l5/GWWiMkSlvDawxIxeRF4ePcjfHnvfi6rhqwrDtJW3YZQaWL9CJHzL0TOD0Arg9AwrTyWkcOUGUxSGJGN6RuYrsSoCoxphVkTmJGFGVpIpYPUEPksoi3HRIfG9uw+HtR2sj86hobGto5ruKXvFq4vvIFUrKMCP5FZeR4qCCDwwfdRvt9oB8kYv9Hf6CPwUX6AsEy01QkREctXIl5mp/uqp/jJkZCH9oUcL8ZYOly3OvFFGey4dA6Ve0YSx/ZD4zGrOzQ+sM3ksr4Ln/Qrz59LKqoJ0VDVOlRa24265sJi3zHTgLSDcGxUpQrT1bn7BZBNI9rys2RlTskjnFcmI/OrEQv5FnlBSFByURM+FD1k0UefDHFOQ6oUY4c++ry8Dr6mmHQUBU9ghwLPgEMrQnavmuKZnmFG1TBj3lFKwSmghhARutBZkVnFQGY1qzKrG/UAKzOrsOWlcXA+X8RKJdafBaRSM9uJw/xM8ahHC5O+xJfFbPitzPiszG7nG3Kz5v7zsP4opahNHGTi4IOJ3Kt0DIRGrv/qJOP84E2YqY6X4c68NAjjgOlgOiEw3uIEppXc+LG/4Lmk0GdJy3wSY7ZRmCE3VhsFI+k35Qv7SjWtNeFci6fb0lcoTrB67bo5yRcXSsQYK4Wj6/SkXvrPuRCCD3zgA+HXv/71pwE++9nP9lQqFfmXf/mXp873HPfff3/Wsqz4bW97WxXgjjvuGHjXu9419eEPf7j4Aq+99bbbbpv8l3/5lyMAQRDQ3d195VVXXVXdvn37wRfzvhbDvn37zHe9611rDxw48PzFHH/DDTcM/eM//uORzs7OC3eCXMISLiHORUx+ufQBrwCuSt/AJ6bewNTpGE2H3ssE3Rsr2G06vncTvns1nlvEd0v4XqnZrrgT+EEJzy+BiCFDUloghYkp0hixjRlamGM6G09obA5zjOmX8URhise8XfzpxONYsc71/gbeZryebYVtGO1tib9HWy6xyLxK81WkLcHbNxi8bb3OwfHEivKTIyGPHAhZWYi5YbXH1r4yllYnCutEoUsYus12FLqU/SlGvQnG/EnGwykmwmkm4yrBOfTiM4jCPrzqhwi9NyC0cezs3zKu7eCenQp2kpCGmRIn+R9m++btn+lbCEm2McgIyIrZ7UYRLe2kNPY3kNIsssIhi0UutsiGJnnfJO/q5KuSzLhCHgnRQw0tlshYRyqJNBz0fDt6oR3Z1nYWeSGbQWivzs/GSwEVxKhJDzXhoooexoSHPumRnvRQky6q6CdZ5lqR0qHdJFirU3QtpkopPM2iumqSExuf45/LipPVLAU5xsYxeONIgetOtLPpcAe3aW3s7FrNU/2vY3e/Ik47pPQUtrQRaHgu7Hdh/zjANPDsK3BX5kKhqAZhQ3rmM+X5LLZe7kjZTGaYN00GspmmRaMwj2C0WRYZ00C+xM8eIQTpzrWkO9ey4tq7EpJy6EEmDj7EkR1/xpFHv/CqJim6ZtBuddBudSQ5KV8ASinqUX1xi4w3S2gOTh9gyi8xHUwt6vif0tNNEtNqkZndnruv18osGMVsT3mKNvuVXfiwLItHHnlEnj59Wu/r6wsv9PggCHjkkUeymUwmmiEm5wvHceJ9+/Y5lUpFZDIZ9c///M+5np6eC8/cewmxY8eOl4UwLWEJlxJLFpMXQPFExHPf91hxlcGyy3UM58J+hJWKCfwynlvCd4tz6xYi07ovDGuzxwMnDdhjwz4LXA3SkWBzxeJ101kGqxlM0phmHstpx8p0YOV6sNp7sDqXo3d0JRYZeX5yJRVHRJG3IEEIQ5cocomCOlE0s9+dRygaJaoTBo3xLf1hWGb4iscAACAASURBVMeNdI7zNg6J2yiJtUjqdPIwOfltAn0PZQnTM0UDf96lSwV5DMyFHIVnPs9RFs39IJr3q0BAbP89sflNEN7iFoyF0DrpEo0/c+r57QuHQlEnokZEuMh5NAV2DCkFTtxSFKQa7VQMmVAnE0oykcSODTSlo2sWUreRZgppptHtNDKVRU/nkOkcupVG6ja67iTjpI00bHTZ2G4pmnbpkjYqpaAWoia8hHw0yEbcsk157jxBCQiyilouZDrrUkxVGE+XOG2Nc8Ia4ZgxzBk1SiWcTbycCTp44+gHuHryNgCe7fw+P+88zbTWhamZmJqFpZlcVrTYesrg6pOC9rogEor9XYpd/YpdyxSlV5dhZA7SutFCKuYSjBnCkbfMV23YZGhYUiYPMnHwISYPPUS9eLRhSdlCx5oGSUl3vtKXeUkQxiHloNwgMEWKfompBpkptpCaKb9EyUv6/HjhhKFSSHJGvml1KVgJablB3czQ+jWJj4yQSWZ5bTYx5aVAJpPhwx/+cABM/I//8T9OtlpM9u3bZ955550Dk5OTekdHR/g3f/M3R9euXevfcccdA5Zlxc8991yqt7c3eOqppzKapqn29vbwi1/84vH77ruvM5vNRk8//XR6bGzM+NM//dPhhawnqVRqy0c+8pHRrVu31j784Q8Xb7/99oFNmza5jz32WGb79u0Ht2/fnvr93//9lZ7nabZtx1/72teOXHnllV4YhvzH//gfl2/fvj0vhFB33nnn+Kc//enRH/3oR6lPfOITK2q1mtbW1hb+3d/93dFVq1YFP/rRj1If/ehHBwBuvPHG6UceeSR/4MCB52u1mvjQhz606plnnklJKfnCF75w4t3vfnf5S1/6Usf9999fqNfr2vHjx613vvOdpa985SvDAMuWLbviySef3NPX1xfefPPNa06fPm16nqd97GMfG/nkJz85fkn+aUtYwnlgScr1IjBzfy6lRSIKPXxvqklaPLeI75Wo1sfZWd7D49WDPB+PEwlFe6Sxsa7Y6CoKCyyDarFMpGPKwZQZpLSICInwG3XQUnxiLtwCLNCQGI1iNmodiUGMpCwFU5piSkaUZEhRC5iUPpOaS1kN4LjvJuW9FY0UvjxAYH2XnPFzemOdnrhAb9RGT1ygJ87TGxUoqDSaEuD5c6RThBGB0Hi44wq+3b2NujR58+Qebh97goJF4seRdhL5VCaV1OkUIuPMttMOZBzEK+RsXA/ryUTDm2SyPsakO0bJG6foTTYnGlPBFNNhhemwQiWqLWrEsZRGOpY4sSAVQSpW2JHCUQpbJVmfW4mOrV6YXwkhZ4mKtOcSGt1GSnMumTsXYoHhWhjVFGYthVFzMKsOei0pVjWFHs2VGvoyoORMMe6UGHEmOe1MMOyMc9qZZNQpMm6XiLTZL4KORkYYpDFIC5O0MJJtYZJmtp0RBim/C3HyZoKxLaCFmG2H0U2Fbkp0S8ewDAzbwrQs0jWN1HAV83AROZlEi1PLM6jLO9CuakfvTSEN0OTL/9xQUQwVH1XxUVUfVfFmtys+VP0k2JehgykRppxTYzb83kwJlj7bbh1jyFeV5U0pRX3yUDO6V714BBBzLSkvI0lRsYIgAj9C+UmdtMPZ9sx+L1pgbAiaQHRn0HoziN4soit93gtIFwM3qlPy5ltkZtvzCc0nOz9D32AvABM/bsMfn5GICTSlIZL0nYBACDAu0B8u26Ox6W3ntshkMhkefPDB2nve8x79mWee2X3PPfd0zhCTm266aej2228vfvzjH5/44he/2HH//fcXHnrooUN33HHHwOTkpP7ggw8e1HWdT3ziE/2ZTCb6kz/5kxFIpFy1Wk27//77D+/atcu+/fbbh44fP/7c/NdOpVJbtm/fvvdzn/tc3z/90z8dufrqqzf++Z//+Ym/+Iu/6Nm+ffvByclJLZvNxoZh8K1vfSv75S9/ufuBBx449PnPf75r+/bt2X/91389bBgGIyMjslAoxK9//evXf+c73znY398f3nfffW0/+MEP8t/85jePrlu3btM999xz/J3vfGflP/yH/7B8hph87nOf69m9e7fzzW9+8+jOnTvtW2+9de2hQ4ee++pXv9r+hS98of/pp5/e7ThOPDQ0dPmjjz66d2hoKGglJiMjI7KnpyeqVCpiy5Ytm370ox/t7e3tXZJ4LeFVgSUp14vAKyGRkrqFo3fjpLvP2rcZuBMoB2W2n36IHwx/l59M/oKfZGBTbgNvbnsd15iDmOUKXmkEvzKOV59MrDJhGS+sIJWBVDqGspFkkUpvlKRf0tJWerLqjtFsz+zT0KmJkDGzxqheZsQsM2LMllGjSFGvzbl+oaAjTNMTZLki6KQ7cOgJfkZbcJAz4mqeNq5gOPpPSBUy6B7nxvph1oQTLRNmH/CTybhlIvJZtGU9qJTDk1oP35jqYzQwuLI94Lcuj1jZtxns171qpW7z4egOju7Qm+qHs4NDnYVIRZSD6XNOOGbkISONthu5C55LU4JMaJALDLKhnlhfIklG6aQ1i7S0SBsWKd3E0pNoZ1IXRCIkilw8d5IonF2V1SId080g6hmkm0G6Wex6FsfNkannyXhZpJo7mZkyK4w4RUZSI4x2JGRjxJlkxCky6hTxjRppIUkpSQpJSmmkkPQryRA66aibVDS732xMnxZG2CgzEfTGoWMPeraHaPw2/OnVeLEBsQnKRjB/EpWFTC8py6WzVqJrtET2+8fg+8coGTbjToHxTI66YyNNgTQ0pCHQTYHUQTME0gDZWkuFTogRBeihjwwDpO8j/QDN89G8AFHzEHUf6gFUPaifQ+HiGIh0Qu6U35ggexHEF7EgZWgJQWkQmGb7XETH1BcmQq2Ep/V850l+hBCkOoZIdQyx4tqPUZs4xMShhxpyry9wbPsXyXVvoX35DRT6rsXQcwsShIWIBF5Luzk2nG0HEQQXHjkLKWbfs6VDEKF+Pjy7XxMJOenNoPVk59TCevE/1bZ06E01ni0LQClF4EJ9KsadVozW9rNSrCeKFG4cLPqZSXov4n6cJ7LZLO9973sn/uzP/qzbcZzmC+3cuTP9ve997xDAXXfdNfnHf/zHy2f2/dqv/VpRP8fi0m233VaSUrJ161Z3YmJiUUfLa6+9tj48PGzdd9997TfffPNU677JyUn5G7/xG6uPHj1qCyFUEAQC4JFHHsl97GMfGzMa/ps9PT3RE088YR84cMC56aab1gHEcUxXV1cwPj4uy+WyfOc731kB+MhHPjLxyCOP5AEee+yxzMc//vFRgC1btrj9/f3+s88+awO86U1vmu7o6IgAhoaG3EOHDllDQ0NzzMef//zne77zne8UAM6cOWM8//zzdm9v7wXJ2ZawhFcCS8TklxRZI8ttK2/ntpW3c6Z+modOPsD3T36Hrxz7OvcJndd3v5FbNt3Km3rejCUvLtJWpCLG3THO1E8zUj/DmfppztROM1I/0eyrR3OJh6lZ9Di99DqDrHP6knaqj95Gu9vuRj9HUskPKMXhiYYvyuFBfuQMsrJNcNM6g+sHddLW2ROXA2OJY/u+0ZgVBcGnXmdy5bKXLh/FqxlSyKYT7PnCjeqzjrjeAk65tXFK9QnGvCIHommm4wqxSKYfRqST9zMUqhlyfppON0tvvY1Ov5+OIE97kCXrpsm7WbJ+as7rRiJizC4x6hTZ3XGAidQUlayPm48ICgJVMElnso3308MycwOXmwXyDY181siha5f+kdW0YNbGqVen8Gpl3GoZr17Fq9UJXI9R1+WUF6BN67RPtNMz3c2q6ToD06ep6z7FlEfZDgmkjqUsjEhiRhpGBEYUoUcRRhRixAHaIjawGEGgmfiaQaCZBDJDoLUR5gxCwyQyTCLLQFkmsWOibANpSaQBTk4j3SnIdGhkOjV0Qy0+8b7QSboXosoeqtUiEEQQXsRkVdfOIi+iMZnH1BGGhgri5BqCxut5ESKI6PRX0unfOfu6+2fu29MsLGKa97rGAq9rSkTKSIhBK5EyNJQpiKVCyZBYRkRaRCQDIi0g0nwi4RMKNym4RHF9Vu4aucRRgBZqmNMOdtnBmnYwyw7WYQfrGQuhZq0nvuPh5ep42fpsna0TWeF5y0iVEsR+htjLE3l5Yi9P7OXmtFU8S757blIENQVaxODrFYgIoUVzaxGDUEhpY6dePgvVpz71qZGrr75602/+5m+elxwpk8mc88Nn23bzS/ZCqpF3vOMdpc997nMrfvCDH+wbHR1tPoD+8A//cNkNN9xQfvDBBw/t27fPvOmmm9Yvdg6llBgaGqrv2rVrb2v/+Pj4RWknTdNsXrSUskmKZnD//fdnd+zYkX3yySf3ZrPZ+Jprrllfr9dffYmNlrCEBbBETF4D6HX6+MDQb/P+NXdysHyAB4a/w4Mnv89PRh4lpad5S99buWXZrVzVsRUpZp+DblRPCEethXi0kJAxd/SshGR5o0CP08vK9Cpe13Vtg3AkxKPX6aVgtr0o64QQgjWdkjWdkg++zuQnh0Me2R/ytZ/5/P2TPq8fSCJ6revSGKso/vcvfH56NKLgCH7njSY3DuloryLJyasRtnTodRx6rF6QISoOUG4IboCqJIVKgCoHqEqIqgTEZQ9VDdG8xSbNiqpRZ9qsMG1OcyZ/GlevEkoXhIskwI5j8pFJr8yz3izgmD0Iw0EIB6IUwnUQMgWag7AdhNWQ271CGdlnMGPBtJ0u8ukgkUjZfiKX0j2U9CFOIuAp3UelPZRyUUyBH+MATg2owayVBkLDw9fr+HqFqlXB16sEeh1f+vh6QKBF+HpEbDkIO4Mw29CNNqTMI7U8UmQRwkATKQQOKBsttogjiQggDhReRRH6itH9Ea3RlK20aBKVdIdJptMm0ymwMuIlsy6qKG6SlLlyp7OlT02Sc9b+aJaEVP2ElBhak6yItHW2JcaQKANiPcZzRykXdzM9+Tyue4pIBBhtPVhdA1jdA2DphLiEcX2OL9yMP1zUQiSafeWkrc4j+MZ8zPhvSWmjSYMmq0g3Sl+yKWINu54lVSskpZrHqRZoG+tExrMLO4HuUktNUUuXqDkVapaibhjURQ6iTgg6UGEnBJ0QtgPz5sFaGYxxMI4icuMIYxyhTyR9+q+BdTT5X878T2eOmzftFy+zz0lPT0/07ne/u/j3f//3ne973/smALZs2VL96le/2va7v/u7k/fee2/7tm3bKgsdm81mo+np6Yt2nrrrrrvGC4VCdM0119Tvv//+ZjiD6elpuXz5ch/g3nvvbbKyt771rdP33ntv57ve9a7pGSnX5s2b3cnJSf2hhx5K33zzzVXP88Szzz5rbdu2zc1ms9EDDzyQueWWWypf+9rXmjGxr7vuusrf/u3ftt92223lZ555xjp9+rS5efNm92c/+9ncFZ8FUCqVZD6fj7LZbLxz50776aef/rexUreE1wSWiMlrCEII1ubWsXbTOu7aeDc7J57kgeHvsv30w3znxLfpsrvZkN/EqDvCSP00Jb8053gpJJ12Fz1OL5vbr2paOXobxKPb6SWlv+Az8SWDYwhuXm9w83qDw+MRj+wP+fHhkEcPhXz01EkiL2JQ03hLr87aTgPjuCQ+oxFbEmHOrLxq89pJjaG9qjTzLwWUH6EqYUIqGsQiaYdzCUdjm0qweJQxS0skQFkDkTHQex3IJO2k6M19ImNASietCWbEhyoI54VSTuo5oZQrNdRYkfjoKajWFpcXGXrTL6jpI9T0DUr6Zn2GGvsvIhO2qvjEI2XUmQrxmTKqVD/bV2PRa9QQGQvSJiJjonWlIWMhMiYibYIpiUc94iMV1IEKBArd1LE2tSO3dML6NL4q47f6lbX4lyXbB/HcElW3iOeVUPHCEi5NmphWAStXwLTbSFkF0ppF5OaJah2E9Q6iWjvTkx0UhztQ0axFVUgP6UygpyYb9QQyNYG0SwjxMvojmo0yf/oUC8xyCms6hTWdRq/YBGYNz57GtUrUzQlqxjiBqiYEol4njFyYFwKaVKMAcBLGnoKxuUNm/KTmBIHQbQwri6N3zwkCMdevaoG+BcdZFz2BV0oR1KFeiqierBMOl2GkjJisok9X6Bip0hfPKnkioVHTU3hOmiDnoNpB6wmQy0ycNh0nr2HnBLqZBnoXfM09e/aQbx+6qOt9OfDpT3/6zF//9V93zWx/5StfOf6hD31o4J577umdcX5f6Lg77rij9J73vGfN9773vcIXv/jF4xf6umvWrAk+85nPjM7v/8M//MMzH/3oR1d//vOf73/b297W/DH9/d///bH9+/dbGzZsuEzXdXXnnXeO/dEf/dHYN77xjUN33333ynK5LKMoEnfdddfItm3b3L/6q786+tGPfnRACMGNN97YTILzB3/wB6Mf+tCHVq1bt26TlJJ77733qOM45/UlvOOOO6b+1//6X12Dg4OXDQ4OuldeeeWShGsJvzRYcn7/NwAvcvnxyKM8cPK7nKwO0+P0tFg6epM61Uen1fWKSGUuBG6geOxIyKr/5zkKro+jYoQfX7xmvpWsmBrCaiEupgRLa6zEajOZ9JpEZ06fNSMFmUeELpL8qLgRkeqFCEZzXwD+IuoFQQup0GfbWQORnkcwGmOEeWmjMymlwPVmc8PMkJf5+WIq9WYbd+HcDwjAsecGOGgQFtIOAhPlC1Q1Rk2HSVjh0SpUWs5naIj2FCJjQsZMVuYz5ux2xkoIR3aWeJyvpUH5EfGeEtHOCaJnJqEWgqmhXdaGvKoDeUU7IvXCuT7CoLJolL/5xGYxEqMUEBXAXwbBMpS/LGn7yyFqTWgYgHkajFNgnkSYw2CeBOMUQlvk/3AB0EKDVK0jKdUOUrVOUtUO7HobWosfkm/UMAK74XQ9i9DyCDIeYSYkzkbE+Zg4r6EKEtFuoKUtpOkgpY2u2wS1caZPPMHU8cdwJw8DkOu7KonuteZmrMzZ/n0vJ+JY4ZUV9SlFfSqmPq1wpxT1adX0+YjmBaqVBtg5gZPXcPKClBWQjmrYbhWzUkErVlEjFdREi9xWE4iOFKI3mzjd92TQerOIngzCmSux3bNnDxs3brwE7/7cWEqwuIQlvPawFJVrCa95JLKRpCS687ghBWnp8+f24TXaQbJPeY26MW5++6x8GOeDJvlZwGpjaqAp1OlxlJCIWKACAW4MdZXEvl0IlkRkdUg3yMV8wjFDMLKNfkd/zVmHAFQYQcMikxCWWjPxpSrXUJN1KPmocoSqK/AlKBPmTGqjJIS0FoADIq0h8iYULLRs+uwobjNWm5TzkkRQUlFMfGA6ISm7JmDKBynQ1ueRWzqRV7Yjcq+MlC1wFdXJmMp4THVCURmPqUzE1Ipz8/k4eUG6QyMzIw3r1Mh0aJipuZ85pRSUA+IzddSZWrNWp+uoYosXiCYQ3TaiN4XW6yR1n4PoSSFsiYoUqtQSQnrCQxUbuWxmwkjPJ+mWhmizEO0WosNO6kbx9VEmRn/IxJGHqE0kaSCyvVcm0b3WvBUr03NR92/GmTyoKfyawq836kbxqrPkwy2fnSPJTNG0bDh5gZNLCIjdaBvO+QVnUX6IGqkmVsCRSrNWo5W5z7S83SArCWnZX6iycdMmkC+dvO9isERMlrCE1x6WiMkSlvAS4CzyM9NuEppogf3RokRHeRGq7kF54mzpCYBtJCvzBQfR7iC6GiudXSlEeyohHL8k0cZeLigvTKRXMxKsRq3GqnOsaKLNQfSkEZ0pRN5EZCTYChX7iBmJ2QLSM+rncJt27HlysoWkZakk/HTaSaLIneP/pWKFOlpukhQ15oIAbU0OeVUH2lUdaJ0XF8jipUQUKmpF1SAscYOwKKoTMXEIKIUd+eQ0l7zuk41dbNfFmHYRbovlxtIQPQ3S0UJCRLf9okifUgqq4WzizUmPeB6JmZ//Bg1EwULlFJ4coxIcoBYewjcnMfq6yV12DfmhmxBaV5NYBHXwq3MJRzCnvXjKJGmAmRY4DYtHk3zMtHMCaby8320VxajxGmqkTHymgjpTJh6poEYq4IYced8yNqxYk4T/bkRkw9AQelKja5fk+bNETJawhNcelsIFvwicmtzN00e/jSHtpOg2hnQa9QLb0sbQneY+eY4IVEuAOI4IIw8/qhOELkHkEkYuQejO7WvUflhvjokvwvn0ZYUG2I1ygRARWFUDu2pgVQzsRrGqBvaogX3EQIvmyVeMCDcT4GUC3HRwVtt3QhbKQflLBwWGK0mVLNJTFqmSSWrKIlWysKuz369YKOo5n1reo3a5T63gJSXvExmLyNwkUGiUhRArCMPEZ6ZRVBhBEDQiTyW1CkIohjAaLj4bTZI9gKEjjCQ8LrrRmPAZjQmfDt064laddDlH57FOuo50kvmHafiHI5Q7KoyvnmBs9Ti1Qn02IpNSxJFPFHnEodes48gnCj2EACF0hCaTInQ0KVv6dIRIak2TzbYQctGoTyISpFyHVOjQrlIsFw6pcpbUtIVs+az6mqRmONSMPNWCTc3SqeXrePkpSI2gnAkQY1CcTO7h8zFEMSpOalrr+EWEpW1vFEALdex6O3atDbuex6pnsL0U9riF7WVpC7bSwbZk8FHgpxBoh3HlMK5u4ukmrjRxdRNX6rhWSGDUQa+DVgW9CoUqSlZA1kBW55RYCwiAKoDbKGd5MVxiOMAAsApM36LLeC+uVUeLJVqkoQUamtJaHOEVsRb//+3deXRUVb4v8O+uOZWqzCFzCGQeTAzRCIjSTIpGQEAEAVGXs41eG5xW622VfrdVnqgveFGgFQVEEWmngAM2iCDdKEhnAsIYCZkIIalMlaSG/f6oKkhCAkGSVMDvZ61aVWefc3btk5OqOr+zJ9gVdkg1oAsM7DpvIqJuYmByHqamchQe+8Z5MXzeQSfPohCqDkFM9wKadmmdbtP7wY/dboPF5ggIHAHCmUCh07TubOMMMlxBh81+4e3TFQoV1EodFOIy/ffVOh/+bdIk4NGqh7HZ6Hx4wdhshKHZC8YaI/wrjNBZ/NplYxM2NOgaUK+rQ4OuHvW6OtTr6p0PR5pN2Y+COwkYm73g1+gH30Y/+DT6wrfRD35NftBZzkyrblG2okZfg1+NJagJPoUaT8fD5GGCXdHhwvX0aFi9QO18tJvx3XnZJp1Nc6Rs82izDOeyRQKtZwcyEnBM+uMJyCsAr2Z/RFddgeiTKRi0axAG7RqIGo8TOBSYh0OBuag0/Nr1sLGibaYXTmPVwa8pGH5NQfBrCoJvUxD8GoPg3ex/uv+HhB11uhpU64txMKQSNfoTjodnJZpVTVDavKFtHQidJRLa1oHQWiKhPRkJjS2pTfGsaFWVokVdghb1MbSof0WL+hha1cdgVzSfc+JOYddCZfeG0uYNpd0bKpvjtSut4zphN6IZSpye0UflfHgCNtEEm6IWammC2lYPna0ZWlsLdFY79BYBvUUD70YPaOztm9hZFRbUa2tQr61Fg87xXK+rcabVoFFlgh12wAb8hnls+5YCuE4xAXWq9gOkCKmASqqgtKugsisdzzYVbL04jwkR/b6wKdcFkNIOi62lk4vtthfn5jYX5G2Wz5t2prbgQrULftoGNqoOwYxSByEU7d+3y4DCDJvdcv4370CpUJ87yOqiXGelOZdVSh00bdJUSi1robogm62QNY6+FfKUGbLGDHmq6czrWvPZF6dGjaOTt68HFH4eEL56R7MxZxo81T3eXENabJBVjWc3wapsdNRCuBg0pzvmutq+i2CDo2nbJdRnxm63wtJsgqW51jHRaXON87XzuakGrU3VsJidaa11sMvOP3tCCuibAxBQkwbfumQYmqIgoIBV2YBmXQms2nLAsxUanTc0el+o9b5QGrwcNSqtFsjWZtham2CzOIbCtVvNsFlbHK8tgKJVB4XVAIXNCJXVCyqrD1S2M0NlSdjQojmFZs1JNOtOoElXCbO2Eo0elbCqmmETVkdA1U1SegC2CAh7DGAbBNgHQlojYLcEoe19M6XGBLW+FmqPBkipg92qh93iAVurFrZWDey2zgdrEEJCrRfQeAho9I6Hus3rM2lwvPY4fxMqc+0xnDr0HWr2b4O1ohpqiy+M2mQYdcnQIRSiTjj6udR1OIcCgLcGClf/Fh9N+35nroE21B0G1egw0AZUfdPn40I6v0spe61MbMpFdPlhU64eIoQCGpUHNCoPdGta7t/grOCnQw1Du1qHNgFOZ02dLNZm1FtOwmJ1LtuaYZf2ToMCvdanW4HCObdRaqHo56N6Xc6ETgUR4gWEeHW6XtrskLXN7QOWU87X5fWwFp5oHxgAjosiP2ew4utxJmhxLXt33R9Ami3tOtu62rHL6vZDAwt/vSP4iA1wBCKuGa8N7p2/pDNSStgsTe2Ci9bmWsdrc83p4KNtEGJtqesyP5XGALXOMayv1jsExqAkaHQ+jjQP39PrNDofqD18oFIbHDu2Whwd/avqYSushdivgqrUADQmAvUSwrsZaKkHampgM5e1aUamhhI6KO2BgFULtGogW1SAWQlY21xYqgDho4DwVUH4qyECtRBBOohAD+h0Gvho1I78nM+ui1IpJaTdcmb+j9MBUNs5QjqmueYLqYTd+qtjvpDWFrQ2GmBp8oW1OQC2lgFoaQxBc10YgEZAUQOIYghFLaAxQYhaQHHmGYpaQNQCohE2IWEG0NKihdLuAWWzDsp6HRSnh/U9M6SvosPy6TR1+20MA4fCO3oULE2nUFfyb5wq3obj1WsdA+DFpDhG94ocDY3Vz9kh/0zHfHmqBfbiBsj6Vkc/tAu9NyjQfih0rbPvhytw0Z4ZYKOrQTfOvD4T9JwekdAZ/FxQkX7nfd2IqOewxuQSJZ1tys/+ce/sB/9Mmr3jmJNELhJQtCigbFRB1ahyPDco2y0rW9rfmZZCwqa3wepphc3TCqm2Q1Wnhsqkhsp8JkiVCgmr0QKLt+NhdT17WSBV/fM7yGZtYHBr4wAAIABJREFUbl+z4Qw+ZBc1iUKhgkbnezqo0Gg7BhhnljU6H6i1Ps5J9nqGbLHBXljj6DyffwpotgFaJZTJjpso9somyEozYG3z9/ZSQxGiP9P5PEQPRZAH4HPujvru5Ah+rJ1/51m68z3YfjJFexf7/ZYJFIVQAZCA3QYBQKHSQePhB60hCGqdd7vAR6HUANLRV0dYFY6HTXHmtVUBRdt0y5n1Cmv77VzbdJpuVUB0d3p4199YSBydbXB2fgcgHGmObKRzGWdqxzQKqH29L/jvdT5KpRIxMTF2IUQLAEyZMuXU3/72t4oef6Nelp2d7b9r1y7PlStXnp5HJTMzM/7VV18tuf7667tsbLpw4cJAvV5vnzt3bnVvle2tt97ye/3114MBwNPT075kyZJfhw0bZgaAF198ccCqVasChRBISEhoWrt2bbFer+/TL+ycnByjVqu1jxs3rtO5WD744APvwsJCj0vx/+L3jDUmfcwRNLSc/lFsf7fw7B/Cs+8odu9H9LfcanN0aO2fFxzUD3k4H855jRV2FbStXtC2erd/bvKGttYLSpsWzdoamDxOwuxTDbOuGk26ajRra9o38Wl0Psr6/pC6S6HUOAIND1/oPIPhFZB4VoDhWtbofKFUe7r1syW0SiiHBEA5JADSYof9gAm2PSdhy6+B0Cgggj2gTPJ1BB+uEbDOM19KfySEgFCqoVCqodZ2XjvYE+w2SzeCnM6CGjNam6phNh1DS30FWurK0FxXBoVaC4VKBwgl7PZW2G2/Yf4XBc5MRtldEhBSBaVdDYVdA4VdDaVNc+Z1h2eFXQOlXQ2b4iZYlU0ABIR0RCLC7oxSICCkAoACQgrYbdZeaUTg4eGB9evXN/+WplwWiwVq9aXd7Pepp56qOv9WFycmJqblxx9/LAoMDLR9/PHHXg8++ODAvLy8/UePHlUvW7YsqKioqMBgMMibb7558N///ne/xx57rNeCpM5s3rzZaDAYbJ0FJhaLBbNmzTIBMPVlmah3ueVXSQgxHsD/g2NMnL9LKV/usF4LYCWADADVAKZLKYv7upwAUF99ABWHN3WjOUL7tAsnTjcX6NicQKPzbdPsoOsmBudsiqDygELZf++C0uWj9y4VqbuEWgFlsu/p2hK6cIrTwY/xovJpNh1H9eF/ovrwd2g8sRcA4DkgCf7RYxGcOh1KlfuHgO7Mvn37oA3rfFb4jvp2OlYgLCzsil27du0LCQmx/vDDD/onnngi4qeffiqaN29e6JEjR7THjh3ThoWFtaxdu7Z4zpw5A/Py8vRKpRILFy4smTBhQn12drb/559/7lNfX6+qrKxU33bbbdWLFi0qB4AlS5b4vfXWW0EWi0UMGTKkceXKlb+qVCrMmjUrMjc317O5uVkxYcKEmtdff73MVZbbb7+9+ptvvvG2Wq1i7dq1R9LT0y/oIkCv16ffe++9J7799ltvnU5nz8nJORQREWGdN29eqMFgsC1YsKByx44dHg8//PBAs9msGDhwYMuaNWuKAwMDbZmZmfEZGRkN27dv96qvr1e+/fbbxePHj2/o7nu3veAfNWpU49y5c0+HvTabTTQ2Niq0Wq3NbDYrwsPDz6ouLigo0D7wwAMDq6urVUqlUq5bt+5IYmJiy8MPPxy+efNmbyGEfPLJJ8vvv//+mpycHOOiRYuCtmzZcggA5syZE3nVVVc1PvbYY9Wd/R31er195cqVgQqFQn788cf+b7zxxrHly5cHaLVae0FBgT4zM7MhNTXV7KqNKisrU91zzz0DS0tLNQDw2muvHbvhhhsaN2zYYJg/f34k4LixsWPHjv2+vr4csaGf6vPARAihBPC/AMYBOA7gZyHEF1LKvW02uxdAjZQyRggxA8ArAKb3dVkBoLG2GEdz3+viYt9RTa90BghnBw/dTFN7QCh6vpMxERG5l847HGFD7kLYkLvQXFeK6kOOIKX8P6sReuUsdxevW0o2tKCpvGev4/QhCkRkac+5jdlsxtSpU3VCiCQAmD9/fvn9999fc659Dh48qNu5c+d+g8Egn3/++SAhBA4cOLB3z549uptvvjn28OHDBQCQl5fnmZ+fX2gwGOzp6elJkyZNMhkMBvsnn3zit2vXrv1arVbOnj078u233/afO3du9WuvvVYaFBRks1qtGD58ePzOnTs9rrnmGjMABAQEWPfu3bvv5ZdfDnz55ZeD1q5d++uF/C3MZrNi2LBhDYsXLy596KGHwhcvXhy4cOHC8rbb3H333YNef/31Y1lZWQ2PP/546NNPPx367rvvlgCA1WoV+fn5+9auXeu9YMGC0PHjxx+4kPd3Wbx4ccCoUaNMADBo0CDLH//4x4pBgwalarVa+3XXXVc3ZcqUszrMzZw5c9ATTzxRMWfOnNqmpiZhs9nEypUrffLz8z327dtXWF5ersrMzEy84YYbzhssdfZ3nDNnTpUrOAOA5cuXB5SXl2t++eWX/SqVCtnZ2afHr3zwwQcj5s2bV3njjTc2HDx4UHPjjTfGHjlypHDRokXB2dnZv95www2NJpNJodfrGZT0Y+6oMckEcEhKeQQAhBAfAZgEoG1gMgnAC87XnwB4UwghpBs6xAQNHodxg8ddFkFDy+oG2I9Zz78hERH1Ak/4YSL8MBEiTEJwsJBz+i1NucaPH19rMBgkAOzYscPw6KOPngCA9PT05tDQ0Nb8/HwdAIwYMaIuODjYBgBZWVk133//vUGlUsmCggJ9WlpaIgA0NzcrBgwYYAWA999/3++9994LsFqtoqqqSp2bm6tzBSYzZ86sAYDMzMymL7744qxqyq6uH1zparVazpgxwwQAGRkZjd999127iufq6mplfX29MisrqwEA7r///upp06YNdq2fNm1aDQAMHz688cknn/xNo4Z8+eWXxtWrVwfs2LFjPwBUVVUpN2zY4HPo0KF8f39/W1ZW1uAlS5b4PfLII6dc+9TU1CgqKys1c+bMqQUAZ/8TuW3bNuPtt99+SqVSISIiwnrNNdc0bN++Xe/t7X3OgOB8f0eXKVOm1KhUZ392fvzxR6+DBw+eHsC9oaFBaTKZFEOHDm144oknIm6//fZTd9xxR010dDQDk37MHd+KYQBK2iwfB3BNV9tIKa1CCBMcszqc7JiZEOIBAA8AQGRkZI8X9nIISIiIqH8RPTjwQW87X81GX1MqldLunGzTbDa3GxbQ09OzWxedHX/bhRCQUopp06ZV/+///m9p23X79+/XvPnmm0G7d+/eFxgYaJs6dWpUc3Pz6ffV6XQSAFQqlbRarWddNAQEBFhra2vbtXirra1VBgUFWV37KRSO7FQqFTrL41zavD9sNttZ+z766KNhmzZt8nYey96O63fu3OnxyCOPDNywYcNBV7D25ZdfekVGRraEhoZaAeDWW2+t3bFjh6FtYHKh1Gr16fMGAC0tLe3Ker6/o4vBYOj0HEsp8csvv+zr2EH/b3/7W8Wtt95q+vzzz72vu+66hA0bNhy80OZ21Hcu+ds1UsplAJYBjlG53Fycfk072+DuIhAREV2U8PDw1h9//FF/++2313388cdd3lm/9tprG1avXu03ceLE+ry8PG15ebkmNTW1eefOnfrt27d7VVZWKj09Pe0bN270+fvf/17s6elpnzJlSsyf//znyrCwMGtlZaXSZDIpa2pqlB4eHnY/Pz9bSUmJ6vvvv/ceOXJkfXfLO2LEiMYnnngi8tixY6rIyEjrDz/8oG9tbVVER0d3awQEf39/m5eXl+3rr782jB8/vuGdd97xHzZsWLf7kSxevLgUQGln6w4ePKiZNm1a9Lvvvns0NTX19CzSUVFRrb/88ouhvr5e4enpad+8ebMxIyOj3Qhivr6+9uDg4NZVq1b53HnnnbVms1lYrVZx/fXX1y9fvjxw7ty51SdOnFD99NNPhuzs7JLW1lZx6NAhD7PZLBobGxXbt2/3uvbaa895HEaj0VZXV9etbkwjRoyoe+mllwb89a9/rQSAHTt2eAwfPtxcWFiozczMNGdmZpp3796tLygo0DEw6b/cEZiUAohosxyOsz8wrm2OC8f4i95wdIInIiKi34GOfUxGjx5tWrJkSelf/vKXsoceeihqwYIFtuHDh3cZIDz11FMn5syZMzAuLi5JqVRi6dKlxR4eHhIAUlNTGydOnBhdUVGhue2226pdw/Y+99xzpWPGjImz2+1Qq9UyOzv72JgxYxpTUlKaoqOjU0JCQlozMjK6HRQAQEREhPWVV14pGT9+fKzdbheenp621atXH1Equz9swIoVK44+/PDDAx977DFFZGRky4cfflh8IWXoynPPPRdSW1urevTRRwcCjtqKgoKCfaNHj26cMGFCTWpqaqJKpUJycnLTvHnzzholbPXq1Ufvv//+gX/9619D1Wq1XLdu3eE777yzdseOHYbExMRkIYR88cUXj0dGRloBYMKECTUJCQnJ4eHhLcnJyV0OlewyderU2ttuuy36q6++8nnjjTeOnWvbZcuWldx3332RcXFxSTabTVxzzTX1w4cPP7Zw4cIBO3bs8BJCyPj4ePNtt93GUbz6sT6fx8QZaBwAMAaOAORnADOllIVttvkjgCuklA85O79PkVLefr68f0/zmBAREfWWC5n5vTf1xszvnc0rQkR9p1/NY+LsMzIXwDdwjDL4rpSyUAixAMAuKeUXAN4BsEoIcQjAKQAz+rqcRERERETUd9zSx0RKuRHAxg5pf2nzuhnAtL4uFxEREV3enJMEsnk4UT+kOP8mREREREREvYuBCRERERERuR0DEyIiIiIicjsGJkRERERE5HYMTIiIiKjfqaiowPz587UREREpycnJiSNHjozJy8u76Gnon3nmmeC2y+np6QkXmycR9QwGJkRERNSvSCkxefJkXH311baSkpKCwsLCfS+//HJpWVmZ2rWNxWL5TXlnZ2eHtF3es2fP/ossLhH1EAYmRERE1K9s2bIFarUaM2bMsLrShg0bZrZarSIjIyN+9OjRMbGxsSkA8MILLwTFxsYmx8bGJi9YsGCAa/uxY8dGJycnJ8bExCS/+uqrAQDwyCOPhLW0tCgSEhKSJk6cOAgA9Hp9OgCYTCbFsGHD4pKSkhLj4uKSVq9e7dO3R01EbpnHhIiIiC4NtZ+0oPW4vUfz1IQr4HNb162yCgoKkJGR0em6vXv36vfs2VOYkJDQum3bNv2aNWv8d+/evU9KiYyMjMQxY8bUX3vtteYPPvigOCgoyNbQ0CDS09OTZs+eXbNkyZLS9957b8D+/fv3dsxXr9fbN2zYcMjPz89eXl6uuuaaaxJmzpxZq1DwHi5RX+GnjYiIiC4ZqampjQkJCa0A8P333xtuvvnmWi8vL7u3t7c9KyurZsuWLUYAeOWVV4Li4+OTMjIyEisqKtSFhYW6c+Vrt9vF448/Hh4XF5c0atSouBMnTmiOHz/OG7hEfYgfOCIiIurSuWo2ektycjI++eQT3HvvvWet0+v1562+ycnJMW7dutW4a9eu/Uaj0Z6ZmRlvNpvPeTN26dKlftXV1ar8/Px9Wq1WhoWFXXG+fYioZ/EDR0RERP3K6NGj0dLSgrVr156+gbpz506PrVu3GtpuN2rUqIaNGzf61NfXK+rq6hQbN270HTVqVH1tba3S29vbZjQa7Xv27NHl5uZ6uvZRqVSypaVFdHxPk8mkDAgIsGi1Wvnll18ay8rKNL17lETUEWtMiIiIqF8RQuDTTz/FXXfdpYyIiEjRarUyPDy8ZcKECbVttxsxYkTTzJkzq4cMGZIIAHfeeWfVtddeax4yZEjzsmXLAgcPHpw8ePDg5rS0tEbXPrNmzapKTExMSklJafriiy+OutLvu+++UzfddFNMXFxcUmpqatOgQYOa++6IiQgAhJTS3WXoMUKIKgC/ursc/VwAgJPuLgSdheel/+E56X94TvrIpk2brggODraef0vAZrOplEplt7a9UBaLRZOenp7bG3kTkXvk5uYGpKWlRXW27rKqMZFSBrq7DP2dEGKXlPIqd5eD2uN56X94TvofnpO+k5ubW5ySktKtILCgoCAxJSVlX2+XiYguf+xjQkREREREbsfAhIiIiIiI3I6Bye/PMncXgDrF89L/8Jz0Pzwn/VBAQECVu8tARJcHBia/M1JK/rD3Qzwv/Q/PSf/Dc9I/BQcHc0ACIuoRDEyIiIiIiMjtGJhc4oQQEUKILUKIvUKIQiHEfznT/YQQm4QQB53Pvs50IYTIFkIcEkLkCSGGONOvFEL8y5lHnhBiujuP61LXU+elTX5eQojjQog33XE8l4OePCdCiEghxLdCiH3O/KLcc1SXvh4+LwudeexzbnPWJHp0fkKIiJMnTwbl5+cn5+fnJ5eVlQ0AAIvFoty3b19sXl5eyr59+2ItFosSAJqamnSFhYUJu3fvHlJaWhrUNq9Tp0555eXlpeTl5aUcP348+ELK8fTTTwfHxMQkx8XFJSUkJCRt3rzZMzMzM/6HH37Q99zRAnq9Pr1jWnFxsXr8+PGDe/J9iOj8GJhc+qwA5kspkwAMBfBHIUQSgGcA/FNKGQvgn85lALgJQKzz8QCAt5zpTQDmSCmTAYwH8IYQwqfvDuOy01PnxeWvAH7oi4JfxnrynKwE8H+llIkAMgGc6JtDuCz1yHkRQgwHcC2AVAApAK4GMLIPj+NyYvX29q654oorChMTE/edPHlyQGNjo66srCzEaDTWp6amFhiNxvqysrJgAFCpVNbIyMhjgYGBlW0zkVLi+PHjkbGxsQdSUlIKa2tr/RobG3XdKcB3333n+c033/jk5+fvPXDgwN4tW7YcGDx4cGtvHGxnoqKiLF9//fWRvno/InJgYHKJk1KWSyl/cb6uB7APQBiASQDed272PoBbna8nAVgpHf4NwEcIESKlPCClPOjMpwyOCy3OC/Mb9dR5AQAhRAaAIADf9uEhXHZ66pw4L5pVUspNzrwapJRNfXksl5Me/KxIADoAGgBaAGoA7S6UqXuklOVqtboVAFQqlV2r1ZpbW1s1JpPJJzAwsBoAAgMDq00mky8AaDQaq9FobBJCtJuxub6+3lOj0bR4eHi0KhQK6ePjc6qmpqZbN7xKS0vVfn5+Vg8PDwkAISEh1qioKEvbbZYuXeoXFxeXFBsbm/zwww+HAcDChQsDH3zwwXDXNtnZ2f5z5syJBICxY8dGJycnJ8bExCS/+uqrAR3fs7y8XHXllVcmfPTRR95FRUWa2NjYZAAoKirSZGRkxCclJSUmJSUlbtq0ybP7f00iuhCX1QSLv3fO5iTpAHYCCJJSljtXVcBxYQs4fvBL2ux23Jnm2hZCiEw4ftwP926Jfx8u5rwIISoBLAIwG8DYvijv78FFflbCAdQKIf4BYBCA7wA8I6W09X7JL28Xc16klP8SQmyB47tMAHhTSslJ/y5Sc3OzxrBRa9TWQhXS6qe1a82DzTADUiKk1U9r/kdtvGtbo1WjERDSrKp1BB82qyrI7qM0qx3beNm0Kpu0Kc2qWm9FmLJJe7+xpIu3xa233lr30ksvhUZFRaWMGDGi7o477jiVlZXV4FpfXFysfuGFF8J27969LzAw0HrdddfFrVq1ymf27Nk1Q4cOTYDj/wKffPKJ37PPPlsOAB988EFxUFCQraGhQaSnpyfNnj27Jjg42AYAJSUlqqysrJgXX3yxbPLkyXVFRUUa13uFhoZat23bdkCv18v8/HztHXfcMbigoID/W0S9gDUmlwkhhAHAegCPSynr2q6TUko47iZ2J58QAKsA3COltPd4QX9neuC8PAJgo5TyeC8V8XenB86JCsB1AJ6Ao7nQYAB393xJf18u9rwIIWIAJMIROIYBGC2EuK6Xivu7YLVaFYcOHYo2aA0NZ3XX6eXuO97e3vaCgoK9b7755q+BgYHWu+66Kzo7O9vftX779u2eQ4cOrQ8NDbWq1WpMnz791NatWw2hoaHWiIiIln/+85+eFRUVysOHD+vGjRvXAACvvPJKUHx8fFJGRkZiRUWFurCwUOc8TjF69Oj4l1566fjkyZPrOpaltbVVzJw5MyouLi5p2rRp0YcPH+5WczQiunCsMbkMCCHUcPygfyCl/IczudLZRKvcGWy42sCXAohos3u4Mw1CCC8AGwA862wiQRehh87LMADXCSEeAWAAoBFCNEgpnwFdsB46JyoA/5FSHnHm+RkcfSPe6YtjuBz10HmZDeDfUsoGZ55fwfH52dYXx3AZEocOHYr28/M75f1IQCUAHMw7lhIfH3hEq9VaWlpa1OVFx+JTU8OLXDucLCkJVSgUtrCwAZUAYKmr86wsOxmakJBwEACqnZ3ffcN9KrpTAJVKhVtuuaX+lltuqU9NTTWvWrXK//x7AdOmTTv14Ycf+iYkJDTfdNNNNQqFAjk5OcatW7cad+3atd9oNNozMzPjzWazAgCUSqW84oorGr/66ivvtrUyLv/zP/8TNGDAAMv69euP2u12eHh4ZHSnHER04VhjcolzjjrzDoB9UsrX2qz6AsBdztd3Afi8Tfoc58g2QwGYnD/8GgCfwtF2+5M+Kv5lq6fOi5RylpQyUkoZBccd+pUMSn6bnjonAH6Go1+Dqw/WaAB7e/0ALlM9eF6OARgphFA5A52RcPRXoQskhBA1NTX+Op2uOTQ09HQ/HS8vr9qqqip/AKiqqvL39vauPVc+BoOhsaWlRWc2mzV2u13U1tb6+fr6nnMfl9zcXG1+fr7Wtbxnzx6P8PDw053fr7vuusadO3cay8vLVVarFevWrfP7wx/+0AAAs2bNqv3mm2981q1b5zdr1qxTAFBbW6v09va2GY1G+549e3S5ubmn+4kIIfDxxx8XHzhwQPfss8+eNXKYyWRShoSEWJRKJZYsWeJvs7HVJlFvYY3Jpe9aAHcCyBdC/MeZ9mcALwP4WAhxL4BfAdzuXLcRwM0ADsExEtc9zvTbAVwPwF8Icbcz7W4ppStPujA9dV6o5/TIOZFS2oQQTwD4p/OiejeA5X12FJefnvqsfAJHkJgPR7Ovr6WUX/bJEVx+rm1ubvasr69XFBQUJAFAaGhoaVhYWPmhQ4ei8/LyAtRqdWtMTMxhAGhtbVXt3bs3yW63KwHIqqqqoJSUlAKVSmWPiIg4dvDgwTgA8PPzO+np6dncnQLU1dUpH3vssci6ujqlUqmUUVFRLe+///6vkyZNigaAgQMHWp5//vnSkSNHxkkpxdixY2tnz55dCwCBgYG2mJiY5oMHD3qMGjWqCQCmTp1qWrZsWeDgwYOTBw8e3JyWltbY9v1UKhU+//zzI+PGjYt5+eWXbZMnTza51j3++OMnpk6dGv3RRx/5jx492uTh4cFmzkS9RDia7hIRERE55ObmFqelpXFGdyLqcbm5uQFpaWlRna1jUy4iIiIiInI7BiZEREREROR2DEyIiIiIiMjtGJgQEREREZHbMTAhIiIiIiK3Y2BCRG4nhPAXQvzH+agQQpS2WW5ybhMlhJBCiP/TZr8AIYRFCPGmc/mFDvv+Rwjh467jIiIiou5jYEJEbielrJZSXimlvBLA2wBeb7Pcds6AowCy2ixPA1DYIbvT+zof3ZrQjYj6F6VSmZGQkJAUHx+flJSUlLhp0ybP8+2j1+vTz7fN9OnTB+7evVvXM6Ukop7ECRaJ6FLSBGCfEOIqKeUuANMBfAwg1L3FIqKeptVq7fv3798LAOvXr/f685//HD5u3Liii8137dq1v1586YioN7DGhIguNR8BmCGEiABgA1DWYf2f2jTj2tL3xSOinmYymZTe3t5W1/J///d/B6WkpCTGxcUl/elPfzrrxoTNZsPs2bMjBw0alDx8+PDYkSNHxqxYscIXADIzM+N/+OEHPdC+hmXFihW+U6dOjQKAqVOnRs2aNSsyLS0tITw8/IqcnBzjtGnTogYPHpzs2oaIeh5rTIjoUvM1gL8CqASwtpP1r0spX+3bIhFdvlpWlEXI0hZ9T+YpwrRN2ntCS875vi0tioSEhKSWlhZx8uRJ9caNGw8AwD/+8Q+vQ4cO6fLy8vZJKTF27NiYr776ynDTTTc1uPZduXKlb0lJiebQoUOFpaWlqpSUlJS77767+kLKaDKZVHv27Nm/Zs0anxkzZsRs3rx5f0ZGhjk1NTVxx44dHsOHDzf/tqMnoq6wxoSILilSylYAuwHMB/CJm4tDRL3E1ZTr6NGjhZ9++unBe+65Z5DdbsfXX3/t9cMPP3glJSUlJScnJx0+fFi3f//+dn1Gtm3bZpgyZUqNUqlEZGSkdejQofUX+v5ZWVm1CoUCQ4YMafL397dkZmaalUol4uLizIcPH9b23JESkQtrTIjoUrQIwFYp5SkhhLvLQnRZO1/NRl8YO3ZsY01Njaq8vFwlpcTjjz9e/uSTT5682Hzbfn+YzeZ2XyY6nU4CgFKphEajka50hUIBq9XKLx6iXsAaEyK65EgpC6WU73ex+k8dhguO6sOiEVEv2LNnj85utyMoKMh600031a1atSrAZDIpAODo0aPq0tLSdjdaR4wY0fDZZ5/52mw2lJSUqHbu3GnsLF9/f3/LL7/8orPZbPj88899++JYiKhrrDEhon5FSvlCh2WD87kYQEon278H4L02+77QcRsiuvS4+pgAgJQSb731VrFKpcKUKVPqCgsLdVdffXUCAOj1evsHH3xwNCws7HTn+Lvuuqvmu+++M8bExCSHhIS0JicnN/n4+Ng6vseLL75YOmnSpBg/Pz9rWlpaU2NjI2/YErmRkFKefysiIiL63cjNzS1OS0u76KZS7mQymRTe3t72iooK5dVXX534448/7o+MjLSef08i6k25ubkBaWlpUZ2tY40JERERXXbGjRsXW1dXp7RYLOLJJ58sZ1BC1P8xMCEiIqLLzk8//XTRkzESUd9iW0oiIiIiInI7BiZEREREROR2DEyIiIiIiMhsvRbcAAAKeklEQVTtGJgQEREREZHbMTAhIiKifkcIkTFp0qRBrmWLxQJfX9+0UaNGxZxrv5ycHKNrm5ycHOOmTZs8e7usRNQzGJgQERFRv+Ph4WEvKiryaGhoEADw6aefegUFBVkuJI/Nmzcbt23bZuidEhJRT2NgQkRERP3S2LFjTevWrfMBgA8//NBv6tSpp1zrtmzZor/yyisTEhMTk9LT0xNyc3O1bfctKirSrFy5MvDtt98OSkhISPr6668Na9as8U5NTU1ITExMGj58eFxJSQmnTSDqR/iBJCIioi61rjwQYS9t0vdknoowfZNmTlzJ+ba78847Tz3//PMh06dPr923b5/+3nvvrd6xY4cBANLS0pp//vnn/Wq1Gp999pnxqaeeCv/mm28Ou/aNj49vnTNnTpXBYLAtWLCgEgCqqqqUM2bM2K9QKPDaa68FLFiwIHj58uXHe/LYiOi3Y2BCRERE/dI111xjPn78uHb58uV+Y8eONbVdd+rUKeX06dMHFRcX64QQ0mKxiPPld/ToUc2tt94aXlVVpW5tbVVERES09F7piehCMTAhIiKiLnWnZqM3jR8/vvb555+P+Pbbb4tOnDhx+rrl6aefDhs5cmT9pk2bDhcVFWlGjx4df7685s6dG/lf//VfFbNmzTLl5OQYFyxYENq7pSeiC8HAhIiIiPqthx9++KSPj48tMzPTnJOTY3Sl19XVKcPDw1sBYOnSpQGd7Ws0Gm11dXVK13J9fb0yMjLSAgDvvfeef2+XnYguDDu/ExERUb8VHR1tee655050TH/66acrXnjhhfDExMQkq9Xa6b5Tp06t3bBhg4+r8/uzzz5bdscdd0QnJycn+vv7d74TEbmNkFK6uwxERETUj+Tm5hanpaWddHc5iOjyk5ubG5CWlhbV2TrWmBARERERkdsxMCEiIiIiIrdjYEJERERERG7HwISIiIiIiNyOgQkREREREbkdAxMiIiIiInI7BiZERETU7xw7dkx1yy23DI6IiEhJTk5OHDlyZExeXp7W3eUiot7Dmd+JiIioX7Hb7Zg4cWLMzJkzq3Nyco4AwL/+9S+PsrIydWpqastvzVNKCaVSef6NicgtWGNCRERE/UpOTo5RpVLJp556qsqVNmzYMPPSpUsDVq1a5eNKmzhx4qDVq1f7ZGdn+48ZMyY6MzMzfuDAgSnz588PAYCioiJNVFRUyuTJk6Pi4uKSDx8+rNHr9emu/VesWOE7derUKAB49913fWNjY5Pj4+OTrrrqqvg+PFwicmKNCREREXWpdfWeCHt5vb4n81SEGJs0s9NLulqfl5fnkZaW1tQx/b777jv5+uuvB91555211dXVyt27dxvWr19/9K233vLPy8vzzM/PLzQYDPb09PSkSZMmmYKCgqzHjh3TvvPOO0fHjBlTfK4yvfzyyyHffvvtgUGDBllOnjzJahUiN2CNCREREV0SsrKyGoqLi3VlZWWqd955xy8rK6tGrVYDAEaMGFEXHBxsMxgMMisrq+b77783AEBISEjrmDFjGs+X91VXXdUwa9asqEWLFgVYrdZePhIi6gxrTIiIiKhL56rZ6C1XXHGF+bPPPvPtbN306dOrly9f7rd+/Xq/FStWFLvShRDttnMt6/V6e2fpAGA2m08vrFmz5tjmzZs9v/jiC++MjIyk3bt37w0ODrb1xPEQUfewxoSIiIj6lQkTJtS3traKV199NcCVtnPnTo+vv/7a8NBDD51cunRpEABkZGQ0u9Zv377dq7KyUtnQ0CA2btzoM3LkyIbO8vb397f88ssvOpvNhs8///x08FNYWKgdPXp04xtvvFHm6+trPXLkiKY3j5GIzsbAhIiIiPoVhUKBL7744vDmzZu9IiIiUmJiYpKffvrpsLCwMEtERIQ1Ojq6efbs2dVt90lNTW2cOHFidHJycvKECRNqrr/++rP6qADAiy++WDpp0qSYIUOGJAQFBVlc6X/605/C4+LikmJjY5OvvvrqhqFDh5p7+ziJqD0hpXR3GYiIiKgfyc3NLU5LSzvp7nJ0pr6+XpGUlJT0n//8Z5+/v78NALKzs/137drluXLlymPuLh8RnVtubm5AWlpaVGfrWGNCREREl4TPPvvMGB8fn3z//fefcAUlRHT5YI0JERERtdOfa0yI6NLGGhMiIiIiIurXGJgQEREREZHbMTAhIiIiIiK3Y2BCRERERERux8CEiIiI+qVVq1b5CCEy9uzZowOAoqIiTWxsbDLgGCJ4zpw5kT3xPgsXLgx88803/XsiLyL67VTuLgARERFRZz766CO/IUOGNKxcudIvPT29rLfe56mnnqrqrbyJqPtYY0JERET9jslkUvz888+GFStWFH/66ad+nW1TWlqqzszMjB84cGDK/PnzQ1zpY8eOjU5OTk6MiYlJfvXVVwNc6Xq9Pv3RRx8Ni4+PT0pLS0soKSlRAcC8efNC//KXvwQBwKJFiwJSUlIS4+Pjk2688cbo+vp6XisR9RHWmBAREVGXWtdsj7CX1+p7Mk9FiE+TZuaIknNts2bNGp8//OEPptTU1BZfX1/rtm3b9AMGDLC23SYvL88zPz+/0GAw2NPT05MmTZpkuv7665s++OCD4qCgIFtDQ4NIT09Pmj17dk1wcLDNbDYrhg0b1rB48eLShx56KHzx4sWBCxcuLG+b56xZs2rmz59/EgAee+yx0Ozs7IBnn332RE8ePxF1jncBiIiIqN/5+OOP/e64444aAJg6deqpVatWnVVrMmLEiLrg4GCbwWCQWVlZNd9//70BAF555ZWg+Pj4pIyMjMSKigp1YWGhDgDUarWcMWOGCQAyMjIaf/31V03HPHfv3u2RkZERHxcXl7R+/Xp/175E1PtYY0JERERdOl/NRm+orKxU/vvf/zYWFRV5zJ07FzabTQgh5Lx589rVXAgh0HE5JyfHuHXrVuOuXbv2G41Ge2ZmZrzZbFYAgEqlkgqF456sSqWC1WptnwGABx54YNAnn3xyaNiwYebs7Gz/rVu3GnvvSImoLdaYEBERUb+yatUq38mTJ58qKyvLLy0tza+oqMgLDw9vPXr0aLsaju3bt3tVVlYqGxoaxMaNG31GjhzZUFtbq/T29rYZjUb7nj17dLm5uZ4X8t5NTU2KyMhIS0tLi/joo4867dtCRL2DNSZERETUr6xbt87vySefrGibNmnSpJqXXnoppG1aampq48SJE6MrKio0t912W/X111/fZDabzcuWLQscPHhw8uDBg5vT0tIaL+S9n3nmmbLMzMxEPz8/65AhQxoaGhqUPXFMRHR+Qkrp7jIQERFRP5Kbm1uclpZ20t3lIKLLT25ubkBaWlpUZ+vYlIuIiIiIiNyOgQkREREREbkdAxMiIiIiInI7BiZERETUkd1ut581lC4R0cVwfq/Yu1rPwISIiIg6KqiqqvJmcEJEPcVut4uqqipvAAVdbcPhgomIiKgdq9V6X0VFxd8rKipSwJuYRNQz7AAKrFbrfV1twOGCiYiIiIjI7XgXhIiIiIiI3I6BCRERERERuR0DEyIiIiIicjsGJkRERERE5HYMTIiIiIiIyO3+P1QCfwBKTOENAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 648x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=ploalc)\n",
+    "g.legend(loc='center right', bbox_to_anchor=(1.5, 0.5), ncol=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fed50d28b38>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=plodeath)\n",
+    "g.legend(loc='center right', bbox_to_anchor=(1.5, 0.5), ncol=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "over10 = deaths2.groupby([\"GEO\", \"ICD10\"], as_index=False).agg({'deaths/100k':'mean'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mental and behavioural disorders due to use of alcohol\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(over10.ICD10[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>0.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>1.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>4.88</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       GEO                                              ICD10  deaths/100k\n",
+       "0  Albania  Mental and behavioural disorders due to use of...         0.20\n",
+       "1  Austria    Drug dependence, toxicomania (F11-F16, F18-F19)         1.99\n",
+       "2  Austria  Mental and behavioural disorders due to use of...         4.88"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "over10.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(34, 3)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "drudru = over10[\"Drug dependence, toxicomania (F11-F16, F18-F19)\"==over10[\"ICD10\"]]\n",
+    "drudru.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(35, 3)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "suff = over10[\"Mental and behavioural disorders due to use of alcohol\"==over10[\"ICD10\"]]\n",
+    "suff.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "drudru = drudru.drop(columns=[\"ICD10\"]).rename(columns={\"deaths/100k\":\"Drugs: Deaths/100k\"})\n",
+    "suff = suff.drop(columns=[\"ICD10\"]).rename(columns={\"deaths/100k\":\"Alcohol: Deaths/100k\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990</td>\n",
+       "      <td>4.8800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>3.2375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020</td>\n",
+       "      <td>0.6400</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k\n",
+       "0   Austria               1.990                4.8800\n",
+       "1   Belgium               0.425                3.2375\n",
+       "2  Bulgaria               0.020                0.6400"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "alcodrug = drudru.merge(suff)\n",
+    "alcodrug.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990</td>\n",
+       "      <td>4.8800</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>3.2375</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020</td>\n",
+       "      <td>0.6400</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization\n",
+       "0   Austria               1.990                4.8800                No\n",
+       "1   Belgium               0.425                3.2375                No\n",
+       "2  Bulgaria               0.020                0.6400                No"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decr = ['Portugal','Czechia','Netherlands']\n",
+    "alcodrug['Decriminalization'] = ['Yes' if i in decr else 'No' for i in list(alcodrug['GEO'])]\n",
+    "alcodrug.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>2.633333</td>\n",
+       "      <td>2.071429</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>32</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>1.680000</td>\n",
+       "      <td>1.540000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>31</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>3.140000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>0.850000</td>\n",
+       "      <td>5.700000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>3.155556</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 GEO  Drugs: Deaths/100k  \\\n",
+       "16                                           Ireland            2.633333   \n",
+       "0                                            Austria            1.990000   \n",
+       "23                                            Norway            1.790000   \n",
+       "32                                    United Kingdom            1.680000   \n",
+       "31                                       Switzerland            1.550000   \n",
+       "12  Germany (until 1990 former territory of the FRG)            0.850000   \n",
+       "6                                            Denmark            0.733333   \n",
+       "3                                            Croatia            0.566667   \n",
+       "8                      European Union - 28 countries            0.555556   \n",
+       "4                                             Cyprus            0.466667   \n",
+       "\n",
+       "    Alcohol: Deaths/100k Decriminalization  \n",
+       "16              2.071429                No  \n",
+       "0               4.880000                No  \n",
+       "23              4.490000                No  \n",
+       "32              1.540000                No  \n",
+       "31              3.140000                No  \n",
+       "12              5.700000                No  \n",
+       "6              13.933333                No  \n",
+       "3               5.444444                No  \n",
+       "8               3.155556                No  \n",
+       "4               0.571429                No  "
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "topdrug= alcodrug.sort_values(by=\"Drugs: Deaths/100k\", ascending=False)\n",
+    "topdrug.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>10.220000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>0.850000</td>\n",
+       "      <td>5.700000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>28</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>0.150000</td>\n",
+       "      <td>5.640000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>5.290000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>France (metropolitan)</td>\n",
+       "      <td>0.280000</td>\n",
+       "      <td>5.160000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>4.650000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 GEO  Drugs: Deaths/100k  \\\n",
+       "6                                            Denmark            0.733333   \n",
+       "7                                            Estonia            0.125000   \n",
+       "12  Germany (until 1990 former territory of the FRG)            0.850000   \n",
+       "28                                          Slovenia            0.150000   \n",
+       "3                                            Croatia            0.566667   \n",
+       "10                                            France            0.290000   \n",
+       "11                             France (metropolitan)            0.280000   \n",
+       "0                                            Austria            1.990000   \n",
+       "18                                            Latvia            0.033333   \n",
+       "23                                            Norway            1.790000   \n",
+       "\n",
+       "    Alcohol: Deaths/100k Decriminalization  \n",
+       "6              13.933333                No  \n",
+       "7              10.220000                No  \n",
+       "12              5.700000                No  \n",
+       "28              5.640000                No  \n",
+       "3               5.444444                No  \n",
+       "10              5.290000                No  \n",
+       "11              5.160000                No  \n",
+       "0               4.880000                No  \n",
+       "18              4.650000                No  \n",
+       "23              4.490000                No  "
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "topalc = alcodrug.sort_values(by=\"Alcohol: Deaths/100k\", ascending=False)\n",
+    "topalc.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time = pd.read_csv(\"time_drug_deaths_1_Data.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time1=time[\":\"!=time[\"Value\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    }
+   ],
+   "source": [
+    "time1[\"deaths/100k\"] = [float(i) for i in time1[\"Value\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time1 = time1[[\"TIME\",\"GEO\",\"ICD10\",\"deaths/100k\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Human immunodeficiency virus [HIV] disease</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>0.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>Human immunodeficiency virus [HIV] disease</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>7.7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                                               GEO  \\\n",
+       "0  1994                                           Czechia   \n",
+       "1  1994                                           Czechia   \n",
+       "2  1994                                           Czechia   \n",
+       "3  1994  Germany (until 1990 former territory of the FRG)   \n",
+       "4  1994  Germany (until 1990 former territory of the FRG)   \n",
+       "\n",
+       "                                               ICD10  deaths/100k  \n",
+       "0         Human immunodeficiency virus [HIV] disease          0.1  \n",
+       "1  Mental and behavioural disorders due to use of...          0.6  \n",
+       "2    Drug dependence, toxicomania (F11-F16, F18-F19)          0.1  \n",
+       "3         Human immunodeficiency virus [HIV] disease          2.5  \n",
+       "4  Mental and behavioural disorders due to use of...          7.7  "
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "time1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mental and behavioural disorders due to use of alcohol\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(time1.ICD10[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hiv = time1[\"Human immunodeficiency virus [HIV] disease\"==time1[\"ICD10\"]]\n",
+    "alc = time1[\"Mental and behavioural disorders due to use of alcohol\"==time1[\"ICD10\"]]\n",
+    "dru = time1[\"Drug dependence, toxicomania (F11-F16, F18-F19)\"==time1[\"ICD10\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed4ec6bef0>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=hiv)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed4eb8fa20>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=alc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed50da6e80>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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zc0tKSuL+++8nNDSUNm3amNO3L1u2jPDwcMLCwujVq9ctvz9wIwX8tGnT2L59O8HBwcydO5fU1FQmTZpEQEAAbdq0YcuWLXmec/z48axdu9Yc39ixY29JHy8iPPfcc/j7+xMQEGCu3YWHh5OYmEjbtm1z1fiioqJYvHgxc+fOJTg4mO3btwNG7bFz5840atQoV21i9uzZ5r+VV199tcDfn/w4OjoSGhpKdHQ0YNQQJkyYkGuRrTvvvJNhw4YB4OHhga+vr/lvrETyKzms8QB8KbgGEYtRQ9gAtDZtHwW8n+N144AFBVzjIWAPsKdBgwZ5F9FlSK4S/tsXRJYOtO7j2xeMc2emi0T/LhKX++5z3rx5Bd55v/vuu/Laa6+JiEhqaqq0bdtWTpw4IVu2bBEPDw85ceKEiBh3QI6OjrJ//37JysqSkJAQmTRpkmRnZ8vatWtl6NChIiISHx9vvtvbtGmTjBgxQkSMO1E/Pz+Ji4uTlJQUadCggZw+fVoSEhKkUaNGkp6eLiIinTp1kv37998SZ4MGDeTatWvmWK7fjYmIzJ49W1599VUREenevbs8/fTTImLctffq1ct8/Zx3wjmf51eDuO7mO8rvv/9eOnfuLElJSRITEyN+fn4yZ84cyc7OlgYNGsju3btFROQf//iH+Pv7i4jIoEGDZPv27eZzhIWFmV+XU867z8cff1xmzJghIiI//PCDBAUFmeMNCQmR5ORk83tp3LixXLt2TS5duiReXl7mGuPUqVNl7ty55mseOXJERER27twpPXv2NL+/QYMG5Xl3ffPnNn36dPnkk09EROTq1avStGlTSUxMlA8//FDq1q0rsbGxIiK3/P6IiHh6epr35axBzJkzRyZNmiQiIocOHZL69etLSkrKLefcunWr+fcsLi5OfH19b6lZrF69Wnr37i2ZmZly4cIFqV+/vpw7dy7X9W+WVw1i1KhRkpWVJX/99Zc0btxYRIyf++TJkyU7O1uysrJk0KBB8tNPP91yvoYNG4q/v78EBQWZa4o5f2dTUlKkR48e8scff4iIyPDhw2Xt2rV5xnbd66+/LnPmzLlle1FrEPbMxbQXaCgiiUqpgcBaoGlRTyIiS4AlYKTasG6I5ZijM7ibhrxWrm2kB8/DlClT2LFjBy4uLuzevZuNGzeyf/9+811SfHw8R48excXFhdDQUHOKbwA/Pz8CAgIAI0tsr169UEoREBBAVFSU+fgJEyZw9OhRlFK52ll79epFlSpVAGjVqhWnTp2ifv36hIWFsX79elq2bElGRob5GjlduXKFypUrW/RRjBgxAoC2bdua47Kmvn37snv3bjp37kzNmjXp1KkTjo6OKKVYsWIFTz31FGlpafTt2xdHR8diX2fHjh3mGkhYWBixsbHmPpjw8HDc3d3Nr+3ZsyeVK1emcuXKVKlShSFDhgAQEBDA/v37SUxM5JdffuGuu+4yH5OWdmOC5V133WVRrBs3bmTdunXmPpvU1FROnz4NGDWmnKngb/79Keh9Xq/RtmjRgoYNG5qXxM15zu7du/PYY48RExPDmjVrGDlyJE5OTreca/To0Tg6OlKrVi26d+/O7t27CQ8PLzSOnIYNG4aDgwOtWrUyr764ceNGNm7cSJs2bQBjMayjR4/SrVu3W47fsmUL3t7eubYdP36c4OBgTp48yaBBgwgMDMzz2h06dODatWv07duXefPmAeDj42Ou8ZWE3QoIEbmW4//fKqX+p5TyBqKB+jleWs+0reIZ8KZtz+9ZE1KuQvIVqOQDGF/k179kABYuXMjly5dp185I1SIivPPOO/Tr1y/XqbZu3Yqnp2eubTlTezs4OJifOzg4mDtjX375ZXr27ElERARRUVH06NEjz+NzpgZ/8MEHeeONN2jRooU59fjNnJycyM7OxsHBwfz/625OH379OnmlH7eWl156iZdeegmAMWPGmJuVOnXqZG6m2Lhxo/mLrm7dupw5c8Z8/NmzZ6lbt26xr1/Un012djZVq1Zl3759Fp0vPyLCmjVraN68ea7tv/322y3nsPScBbn5HOPHj+fTTz9lxYoVfPjhhyU+f35yfp5iGh0oIkyfPp2HH364WOds3Lgx+/bt4/Lly3Tp0oV169YRHh5O69at2bt3r7kJ9bfffmP16tWsX7/efGxqamquG4ListswV6VUbWVaJkwpFWqKJRbYDTRVSvkppVyAe4F19oqzXHPxBGdPSIoxD3kNCwsjNTWVRYsWmV+WnJxs/n+/fv1YtGiR+U7/yJEjJCUlFTuE+Ph48xffsmXLLDqmQ4cOnDlzhs8++4zRo0fn+ZrmzZtz4sQJAGrVqsWlS5eIjY0lLS0t1x9SfipXrkxCQuHp0S2RlZVFbGwsYKRO379/P3379gUwp0pPS0tj1qxZ5r6f8PBwPv74Y0SEnTt3UqVKFerUqVPgdbp27cry5csBo8D29vbGy8urWDF7eXnh5+fHqlWrAOPL7o8//ij0uJs/t379+vHOO++YvzR///33Isdy8zlzvs8jR45w+vTpWwqg6yZOnMjbb78NYO7byKlr166sXLmSrKwsYmJi2LZtmzljsaXx5Kdfv34sXbqUxMREAKKjo80/76Lw9vbmzTffNK+7MmXKFJYtW5ZrJFXOv1EwPpec/W7FZcthrp8DvwLNlVJnlVIPKKUeUUpd7/0cBRxQSv0BzAfuNTWJZQKPA98Dh4AvROQvW8VZ4VWqaaw4l2ZU6JRSrF27lp9++gk/Pz9CQ0OZMGECs2bNAoy791atWpmHZj788MMluut+/vnnmT59Om3atCnSee6++266dOlCtWrV8tw/aNAgtm7dCoCzszOvvPIKoaGh9OnTx6IU4j179uTgwYPmzlZL7N69m3r16rFq1SoefvhhWrc2FnzKyMiga9eutGrVioceeohPP/3U3NQxe/ZsWrZsSWBgIEOGDCEsLAyAgQMH0qhRI5o0acLkyZP53//+V+j1Z8yYQWRkJIGBgUybNo2PPvrIorjzs3z5cj744AOCgoJo3bq1ReuD3/y5vfzyy2RkZBAYGEjr1q15+eWXixxHYGAgjo6OBAUFMXfuXB577DGys7MJCAjgnnvuYdmyZbnu4HOqVasWLVu2zLemOXz4cAIDAwkKCiIsLIz//Oc/ha5eOGTIECIiInJ1Uuelb9++jBkzhk6dOhEQEMCoUaOKfdMxbNgwkpOT2b59O7Vr12blypVMnz6dJk2a0LlzZ1avXp1rEMXPP/9Mnz59inWtXPLrnCiLDz3MtRiys0TO/ykSc+T2XreEBg0aJJs3b853/7lz56R37963MSKtNEpKSpJGjRpJXFycvUO5bfbu3Sv33XdfnvtKzTBXrYxQDuDpDemJkJFi72gKFRcXR7NmzXB3d6dXr175vq5OnTpMnjy52BPltLJv8+bNtGzZkieeeMI82KEiuHz5Mq+99ppVzqUXDCplbLZgUEGyMuHiAfCobqxdrWlauaQXDNKKztHJKBySrxiFhaZpGrqA0K7zrAkIJOu1IjRNM+gCQjM4u4NLJZ3lVdM0M11AaDd4+kB2BqTG2TsSTdNKAV1AaDe4eYGjC46VvM2ph4ODg22SfqKoREqWvjsna6akLsz1hHPnzp1j1KhRVrt+7969uXr1aonj07SC6AJCu8G0VoS7myv7dv3Cvn372LdvH76+vrleZqt0FAX59ttvCQoKKvbM4JwK+oK21Xu74447zPmrrFFAjBs3zqLJc5pWErqA0HLzMCVPS4rJtfnmVMqJiYn06tWLkJAQAgICzLNso6KiaNmyJZMnT6Z169b07duXlBRjfsWxY8fo3bs3QUFBhISEcPz4ccCylMg3p++2JJV4Xqmm80pJfXM67ILSSQ8dOtS8UMu//vUvc3xvvfWWeUGg66kdcrqecjyv6xc15TkYqTg+//zzov1sNa2I7JnNVSvErF2zOHyl5BkZc2pRvQUvhL6Q/wscnEhJTSP4zr7g7IafXyPzanJ79+5l//79VK9enczMTCIiIvDy8uLy5ct07NjRnAHz6NGjfP7557z33nvcfffdrFmzhvvuu4+xY8cybdo0hg8fTmpqKtnZ2WzcuJGjR4+ya9cuRITw8HC2bdt2S8bLn3/+2bz2BBiFzapVq1i6dCnt27fns88+Y8eOHaxbt4433niDtWvX8n//93+EhYWxdOlS4uLiCA0NpXfv3sycOZM9e/awYMECwEhRcfDgQXbs2IG7uzv//e9/UUrx559/cvjwYfr27WtOordr1y4OHDiAh4cH7du3Z9CgQSil+PDDD/ntt98QETp06ED37t3NWTxzcnFxueX6165dY/v27Tg5ObF582ZefPFFc8LEffv28fvvv+Pq6krz5s154oknqF+/PtWqVSMtLY3Y2Fhq1KhRzN8GTSuYLiC0W7i7u7Nv0wqoVBu8biSIy5lKWUR48cUX2bZtGw4ODkRHR5vTHPv5+REcHAzcSKGdkJBAdHQ0w4cPB8DNzQ2wPCXyzem7LUklXlCq6ZvlTIddWDrp61/II0aMYMeOHSilGD58uDmT6IgRI9i+fXueBUReipPyHIyUzufOndMFhGYzuoAoxQq807c1Vy9jTkTlWkY6DnKnUl6+fDkxMTFERkbi7OyMr6+vOY32zWm6rzcx5UUsTImcM333zdfIL5W4FJBq+maWppo2JSDO93lxFCflOVgvpbOm5Uf3QWh586wJ2ZmQkveQ1/j4eHx8fHB2dmbLli2cOnWqwNNVrlyZevXqmZeATEtLIzk52eKUyDnTd1sqv1TThaVrLiid9KZNm7hy5QopKSmsXbuWLl260LVrV9auXUtycjJJSUlERETQtWvXAj+LnNcvTspzEeHChQu3DCDQNGvSBYSWN9fK4OQGSZfynDg3duxY9uzZQ0BAAB9//LFFKbQ/+eQT5s+fT2BgIJ07d+bChQsWp0TOmb7bUvmlmi4slXdB6aRDQ0MZOXIkgYGBjBw5knbt2hESEsLEiRMJDQ2lQ4cOPPjggwU2L918/eKkPI+MjKRjx463rJCmadakk/WVMnZJ1pefpBiIPws1moJrJbuGcv78ecaPH8+mTZvsFsOyZctydS7b05NPPkl4eHiBGW017WY6WZ9mPe7VQTneMuTVarKzjXMnXyk0vYdO352bv7+/Lhw0m9M1iFKmVNUgAOKjjWYmn9bg5GKdc4oY6TyunTNWswNw9oAq9YxlUDVNswldg9Csy9Pb+DfZSrWI9GSIPQZXo4zRUTWaQNWGkJUBl48Y2zPTrXMtTdNKxGY9XEqppcBg4JKI3LJ6tlJqLPACoIAE4FER+cO0L8q0LQvIzK90024DJ1dwqwJJsca8CAfH4p0nKwMSzkNyrNFsVaUeeHgb6T3AuEbiRUi8BKnxUKmWkTzQQd/DaJq92HIIxDJgAfBxPvtPAt1F5KpSagCwBOiQY39PEdGLE5QGnj7Gl3bK1Rs1CktJtpFCPOGC8X/PmlC5Njjc9Kvn4Ahed4BHDbgWfaMw8boD3KreKEg0TbttbFZAiMg2pZRvAft/yfF0J1DPVrFoJeTiCU7uRoeyRw3Lv6xTrxmjoLLSjGGzXvXA2a3gY5xcoXojSEsw+j+uRhnrVHjVBRePEr8VTdMsV1rq7w8AG3I8F2CjUipSKfWQnWKqsJRSPPPMM+bnc/77X2bMWwqZqZCemOcxW7du5ZdfTGV+RioTR49k9cem3EnVG0H1xoUXDjm5VsY3tD+XMzwgIwUu/w1xp42mqmK4nnZb0zTL2b2AUEr1xCggcuaVuFNEQoABwBSlVLc8DzaOf0gptUcptScmxkbDMSsYV1dXvvzySy5fztHC5+RuNAsl3jrLGUwFxM87jBpDzGFjFrZHdfBpYfQvFKGJSETIzs42nnjWgFqtjKap5Ctw6ZARg2SX5C1qmmYBuxYQSqlA4H1gqIjEXt8uItGmfy8BEUBofucQkSUi0k5E2tWsWdPWIVcITk5OPPTQQ8ydO/fGRqXAowYx504xcsRw2rdvT/v27fn555+JOnmSxYv+x9y3/ktw515s33cM3KqwbdcfdO5yJ40aNTKvhQB5p/eOioqiefPmjB8/Hn9/f86cOXPj2g5ODJvwOG0H30/rniNZ8r/5cPG1Z68AACAASURBVOkwpMZTqVIlXnrpJYKCgujYsaM5YeDJkyfNs7P/+c9/mk91/vx5unXrRnBwMP7+/mzfvt22H6amlWF2m6evlGoAfAmME5EjObZ7Ag4ikmD6f19gpp3CtKsLb7xB2iHrpvt2bdmC2i++WOjrpkyZQmBgYK41CPD05slXZvPUw5O5s/8ITp8+Tb++fTi07SseuW84lbyq8uz0V8HFgw++WM/58+fZsWMHhw8fJjw8nFGjRuWb3rtBgwYcPXqUjz76iI4dO94Sz9KlS6levTopKSm0b9eWkUMGUiMrjaSkJDq2C+H//u//eP7553nvvff45z//yZNPPsmjjz7K+PHjWbhwofk8n332Gf369eOll14iKyuL5ORkq3yumlYe2XKY6+dAD8BbKXUWeBVwBhCRxcArQA3gf6aMmNeHs9YCIkzbnIDPROQ7W8Wp5c3Ly4vx48czf/78GxlDHV3YvGM3B4+cgBdmQHYm1+KvkpiYYIw08vDO1ZE8bNgwHBwcaNWqlfnOPr/03g0aNKBhw4Z5Fg4A8+fPN69LceZsNEfjoEb9uri4ODM4tBHEn6Vtm2A2/fAjYKwfcX1NhXHjxvHCC0YLZvv27bn//vvJyMhg2LBh5rTkmqbdypajmEYXsv9B4ME8tp8AgmwVV1liyZ2+LU2dOpWQkBAmTZpk3pYtws6vP8LNzRVwMNKBe/qA8ze39DPkTFV9fcZ+fum9o6Ki8k25vXXrVjZv3syvv/6Kh4cHPXr0IDUtHSr54OzsgvKsAUkxOCadJzPtRo0gr1Tc3bp1Y9u2bXzzzTdMnDiRp59+mvHjxxf5s9G0isDundRa6VW9enXuvvtuPvjgA/O2vn378c4n64w8TT4t2Xf8Ajg4FJpC+zpL03vnFB8fT7Vq1fDw8ODw4cPs3Lkz9wuqNgDv5sYEvPQkkGy6dOnCihUrAMypuwFOnTpFrVq1mDx5Mg8++CB79+619OPQtApHFxBagZ555plco5nmz5/PnoPHCew+hFaBwSxevBiAIUOGEBERQXBwcIEdv5am986pf//+ZGZm0rJlS6ZNm5Z3M5SLh1FoiUBqPPPmzWPhwoUEBAQQHR1tftnWrVsJCgqiTZs2rFy5kieffLKIn4imVRw6WV8pU+qS9ZUlInDpIDg4Q81m9o5G00odnaxPq7iUMuZLZCQZTU2appWILiC08sWjhpEl1lZrWGhaBWJRAaGUmnnTc0el1PL8Xq9pduPgaBQSKXHFTsuhaZrB0hpEfaXUdACllCvGBLejNotK00rC0xsQI4uspmnFZmkBcT8QYCokvga2iMgMm0WlaSXh5AauXpB8Weds0rQSKLCAUEqFKKVCgDbAPOAejJrDNtN2TSudPGsaCQNTrto7Ek0rswqbSf3fm55fBVqZtgsQZougNPtydHQkICDAPPfgo48+wsMj/7UYKlWqZJ74VhJRUVEMHjyYAwcOlPhcuFY2ahJJMcb8CL3gkKYVWYE1CBHpWcBDFw7llLu7O/v27ePAgQO4uLiYJ8OVKeYhryl6yKumFVOhfRBKqX5KqUVKqXWmxyKlVL/bEZxmf127duXYsWMAvPXWW/j7++Pv78/bb799y2sTExPp1asXISEhBAQE8NVXXwFGzaBly5ZMnjyZ1q1b07dvX1JSUgCIjIwkKCiIoKCgXFlXrcK9mpF+Qw951bRiKbCJSSn1NtAMY13ps6bN9YAnlVIDRUTnKbCh7V8c4fKZkjfd5ORdvxJd77ZslnFmZiYbNmygf//+REZG8uGHH/Lbb78hInTo0IHu3bubs7ICuLm5ERERgZeXF5cvX6Zjx46Eh4cDcPToUT7//HPee+897r77btasWcN9993HpEmTWLBgAd26deO5556z6nvFwdFYcCjxEmSmg5OLdc+vaeVcYTWIgSIyUERWiMgO02MFMAgYeBvi0+wgJSWF4OBg2rVrR4MGDXjggQfYsWMHw4cPx9PTk0qVKjFixIhbci6JCC+++CKBgYH07t2b6Ohoc5pvPz8/c2rttm3bEhUVRVxcHHFxcXTrZiwYOG7cOOu/GQ/TIlLJuhahaUVVWCd1qlKqvYjsvml7eyDVRjFpJpbe6Vvb9T6Iolq+fDkxMTFERkbi7OyMr68vqanGr0nO1N+Ojo7mJiabc3Ix1qpIioVKtY1ahaZpFimsBjERWKCUOqiU2mh6HALmm/ZpFUTXrl1Zu3YtycnJJCUlERERQdeuXXO9Jj4+Hh8fH5ydndmyZQunTp0q8JxVq1alatWq7NixA8idltuqPGuCZOkhr5pWRAXWIERkL9BBKVUbqGvaHC0iF2wemVaqhISEMHHiREJDjeXBH3zwwVz9DwBjx45lyJAhBAQE0K5dO1q0aFHoeT/88EPuv/9+lFL07dvXJrHj4glO7kZntUcNPeRV0yxUaLpvpVQVoD85CgjgexGJs3FsRabTfWv5So6FuNNQvTG4edk7Gk2zC6um+1ZKjQf2Yqwt7WF69AQiTfs0rWxwrwYOTnrIq6YVQWGd1C8BbW+uLSilqgG/YQx/zZdSaikwGLgkIv557FcYKTwGAsnARFOzFkqpCcA/TS99XUQ+KvztaFo+lAN4eEPiBchMNWZZa5pWoMI6qRVGSo2bZZv2FWYZRvNUfgYATU2Ph4BFAEqp6sCrQAcgFHjVVChpWvF5egNKZ3nVNAsVVoP4P2CvUmojcMa0rQHQB3itsJOLyDallG8BLxkKfCxGR8hOpVRVpVQdjCatTSJyBUAptQmjoPm8sGsWlYjwz5//Scc6HRnUaBAOSq+hVG45OoN7VaM/onIdPeRVK5rUeEi24kg4Jxeo5GM0fZZShY1i+kgptQ7ox41O6q3AdBGxxidVlxsFDxiztesWsP0WSqmHMGofNGjQoMgBJGQkcCLuBOuOr2PF4RW8EPoCgTUDi3werYzwrGkMd02ONf44Nc0SaQlw5aRxU6GsdGORevXGzUopHV1XaNFlKghW3IZYikVElgBLwBjFVNTjvVy8WD5oOV8f/5q3977N2G/HEt44nCdDnsTHQ3+BlDsunuDsaXRWe9YslX+UWimTkWIUDk6u4N3Uenf86clwLRrizxjNnlXqGlmIS5Fit6copf60wvWjgfo5ntczbctvu004KAeGNhnK+uHreTDgQTac3MDgiMG8t/890rLSbHXZUsvR0ZHg4GD8/f256667SE5OLtLxb7zxhk3iioqKwt//lrEORVepJmSlQ9q1kp9LK9+yMuDKCeNGonoj6zYHuXhAjSZQzdeYyBl7zLhWZun5zilsmOuIfB4jgdpWuP46YLwydATiReQ88D3QVylVzdQ53de0zaY8nT15MuRJvhr2FZ3v6Mz83+czdO1QNp/aTGHzRcqT4qb7FhGys7NtVkBYjVsVcHCGRD3kVStAdpbxhZ2dacyfcXIt/JiiUsoYgl2zpdHUlJYAlw7BtXPG9e2ssBrESiAcGHLTYzBQ6DhBpdTnwK9Ac6XUWaXUA0qpR5RSj5he8i1wAjgGvAc8BmDqnH4N2G16zLzeYX071K9cn7d7vs17fd/D3cmdp7Y+xYMbH+TvK3/frhBKjcLSfUdFRdG8eXPGjx+Pv78/DzzwgDnZ39ixY2+5658zZw4zZswAYPfu3QQGBhIcHMxzzz1nfl1UVBRdu3YlJCSEkJAQfvnlF+u+KeVgjGhKTzCaDzTtZiJw9RRkJBt3+C75L5hlFQ4OULm2UVC4V4XEi0ZBkXzFiMVOCqsv7QfmiMgtS3wppXoXdnIRGV3IfgGm5LNvKbC0sGvYUsc6HVk1ZBVrjqzhnX3vcPf6uxnVdBSPt3mcam62H3W7ZdkSLp06YdVz+jRsRM+JD1n0WkvSfVerVo2jR4/y0Ucf0bFjRwBWrVplTvYXFRWV7/knTZrEe++9R6dOnZg2bdqNGH182LRpE25ubhw9epTRo0dj9RnyHt6QcMHoi6ha9MENWjl3LRrS4sGrnlHjvF2cXIwCybMmxJ+FuFPG72iVekb/2W1WWA1iKpBfQ+1wK8dSKjk5OHFPi3v4Zvg3jG4xmjVH1zAoYhCfHvyUjOwMe4dnE0VN992wYUNz4WCpuLg4EhIS6NSpEwBjxowx78vIyGDy5MkEBARw1113cfDgQeu9uescncCjujFsMSvT+ufXyq7ESzcGMVSqaZ8YXDzBu5lx85KVDpePGDWarPTbGkZhNYh6QJ5/nSJStpMeFVEV1ypMC53GXc3u4j+7/8Os3bP44sgXPN/+ee6se6dNrmnpnb61FTXdt6dn/nc2Tk5OZGdnm59fT/9dkLlz51KrVi3++OMPsrOzcXOz0axnz5rGMMPkWKhcyzbX0MqWlDij9uBWBbzyHFl/+yhlDH91MzU5JV6C1DioVAs8fYxmKRsr7AoNgFVKqe1KqRlKqQ6m9BgVVuOqjVncezELwhaQlZ3Fo5sfZcoPU4iKj7J3aDZlSbrv65ydncnIMGpXtWrV4tKlS8TGxpKWlsb69esBI9V35cqV+e233wBYseLGSOr4+Hjq1KmDg4MDn3zyCVlZNuqsc3YHl0rG3WIFGoSg5SM9ybhLd/aAqg1LzxBoB0fwugN8WhrDYBPOQ8whozCz8e9tgQWEiMwSkTCMXEl/APdjzKz+TCk1XilVIW+7lFJ0r9+diKERPNP2GSIvRjJ83XDm7J5DQnqCvcOziZzpvjt06JBnuu/rHnroIQIDAxk7dizOzs688sorhIaG0qdPn1wpwD/44AMmT55McHAwSUlJVKlitPU+9thjfPTRRwQFBXH48OECaygl5lkTsjOMOzOt4spMM0YsOTqZhrOWwln2Tq5GbDWaGAMtrp40hsbacKBFoem+8zxIqVYYeZT6ikg/q0dVTPZK93055TLv/P4OEUcjqOZWjRCfEIpb0RpZZSQNmtzoNK3uVh1P59vfOXU7JCYmUqlSJQDefPNNzp8/z7x5825vECJw6aCRhsPbPiv4lQvJVyArzdT0UQq/XAuSnQmXjxpzHrybgXMZSOQoAsmX4dp5Yw6Fh7fRJFZIs1NR031bNOtDKdUF2CciSUqp+4AQYJ6I/NeiN1POebt786/O/+Ke5vfwzu/vEHUtqtjnyqycaZ6cl5mdSXJGMk2qNsGxrP3RWeCbb77h3//+N5mZmTRs2JBly5bd/iCUMmoR16KNma22Hs5YHqXEGaNtwFja1asOuFcvPU00BZFsY5Z0ZhrUaFw2Cge48XvrVs3IUJyRbJPP26IahFJqPxAEBGJkaH0fuFtEuls9ohIobwsGJWckczL+JN7u3tTyrJCtebdHdiZc/MvoDKzW0N7RlC3pScbdt7OHUTBcO2d8WTl72G1opsVEjEWkUq4Yo4U8atg7ouITsaiAsOqCQTlkmuYsDAUWiMhCoHQlDSlHrhfaHs4eVHGtQmxqLOm3eXhbheJgGvKactVoZtAsY263dzbaxl0rm4ZmNjQ+x8tH4GrUbR+aabHEC0bhULl22S4cwKLCoTjdCZYWEAlKqenAfcA3SikHwLnIV9MK5ebmRmxsrPmHWcujFgrFhSS9DLhNedQETO26WuGyMiH2uHHnWr2x0bkLpqGZ1Y0RN5VqGc1Plw4ZkxJzDHe2u+QrRkzu1aGSNbIGlW4iQmxsbJGHjFuaeeoeYAzwgIhcUEo1AGYXMUbNAvXq1ePs2bPExNzIE5SQnsC59HNccb+Cq6MN8sFohqQEyIwFr6tlo/3cXkSMocGZaUbK9LiT+b8229EoJDIuGDU196pG85M9ZaYaebicXMHTFS4ctm88t4mbmxv16tUr0jEWFRAicgF4K8fz0xSy3KhWPM7Ozvj5+eXalpaVxtC1Q/Fw9uCLwV/gVIoXGCnTjkXDpyNh+BIIusfe0ZROIvDlZPhzFYz8AAL6WnbcyW3w3XS4eAAa3gn9/w117LDuSszf8MFQo9bwwPdGojwtXxY1MZkyuB5VSsUrpa4ppRKUUjpX8m3i6ujKs+2e5ejVo6w5ssbe4ZRfjXsZbei/LdIT5/Kz5f+MwqHXKxAwyvLj/LrBQz/BoLeMYcVLusPXT97e5V8TL8HyUeDoAmNX6cLBApb2QfwHCBeRKiLiJSKVRcTLloFpufVq0Iv2tduzYN8C4tPi7R1O+aQUdHgYzv0OZ3bZO5rS5/dPYdtsCBkPdz5d9OMdnaD9A/CPvdDhEeN880Pg14WQaeOO7PRk+Pxeo2lpzEo9Ws1ClhYQF0XkkE0j0QqklOKF9i9wLf0ai/5YZO9wyq+g0UYent/0Z5zL8S3GHX/jMKMWUJI+GvdqRhPTo79AvXbw/YuwqDMc3WS9eHPKzjKaxaL3wsj3oW5b21ynHLJowSBgj1JqpVJqdM6Fg25TjJpJ8+rNGdV0FCsOr+B43HF7h1M+uXgad8gH1xnpljW4eBC+GA/ezeGuj4xhrdZQsznctwbGfAGI0fyz/C5jXoU1bXwZDq83CqWWg6177nKuwIlySqkPCzhWROR+64dUfOVholxhrqReYXDEYAK8A1jce3GxU3poBYg7DfOCoFZrqFIK14qoEwSdH789k9ASLsB7vYzJhJN/MCa/2UJmOuxaAj/NMibaNepp9BWUVEYynNhiNGkNmFXy85VDBU2Us3QmdRcR+bmwbfZWEQoIgE8Pfsqs3bNYELaA7vVL1WT28mPzv2zX5FES2ZlGJs/Kd0DvGRBwl+3SPqclwrKBcPkY3L/BKJhsLTEGtv7bun1ADTrAgP+UvRxRt4k1Coi9IhJS2DZ7qygFREZ2BiPXjSQrO4u1Q9fibK0qv1Y2nP4NvnvB6Eyv1x76z4J6Vm5Xz86CFWPg6EYYvRKaWTicVStzip1qQynVSSn1DFBTKfV0jscMoNDiWCnVXyn1t1LqmFJqWh775yql9pkeR5RScTn2ZeXYt67Qd1mBODs483z75zmdcJrlh5bbOxztdmvQAR78EYYtMprD3g+DiEeNzJ7WIALfTYMj3xl33rpwqLAKq5u6AJUwJtRVzvG4BhQ4CFop5QgsxEgL3goYbUoTbiYiT4lIsIgEA+8AX+bYnXJ9n4iEF+E9VQh31r2TbvW68e7+d7mcotNDVDgODhA8Bp6IhDufggOr4Z22sP2/kFH4qn0F2rnI6A/o/ASETrZOvFqZVNiCQT+JyL+AjiLyrxyPt0SksKEGocAxETkhIunACoxkf/kZDXxepOgruOfaPUdqZioLfl9g71A0e3GtbPRFTPkNGveEH2bCwlA49HXxJvsd+toYdtoyHHrPtHa0Whljae9WslJqtlLqW6XUj9cfhRxTFziT4/lZ07ZbKKUaAn5AznO6KaX2KKV2KqWGWRhnheJbxZcxLcfw5dEvORib59LhWkVRvRHcuxzGf2WMblp5H3wcbqQxt9TZPbBmsjE3YcSS27LmsVa6WfobsBw4jPEl/i8gCthtxTjuBVaLSM7FhxuaOk7GAG8rpRrndaBS6iFTQbInZ4K7iuLhoIep5laNWbtmFSudr1bONOoBD2+HgXPgwp+w+E5Y/7SxkE9BrkbBZ/dA5Vpw7+fGet1ahWdpAVFDRD4AMkzNTvcDYYUcEw3Uz/G8nmlbXu7lpuYlEYk2/XsC2ArkuQCyiCwRkXYi0q5mzZqFvpHyxsvFiyfaPMHeS3v5Pup7e4ejlQaOTkbfwRN7IfQhiFwG77SBnYvzXu8i5aoxQS07E8auhkoV7+9Iy5ulBcT136rzSqlBSqk2QPVCjtkNNFVK+SmlXDAKgVtGIymlWgDVgF9zbKumlHI1/d8b6ALoNpR8DG8ynBbVW/BW5FukZNpuAXOtjPGobkwOe/QXI73Edy/Aoi5wbPON12SmwcpxRg3i3s/Au6ndwtVKH0sLiNeVUlWAZ4BnMZYcfaqgA0QkE3gc+B44BHwhIn8ppWYqpXKOSroXWCG520daYqT3+APYArwpIrqAyIejgyMvtH+B80nnWfbXMnuHo5U2Pi3gvi+N+QzZGUZK88/uMSbArfsHRG2Hof8D3y72jlQrZSyaKFdWVJSJcvl5ZuszbDu7ja+Hf01tz9K/StaV1Css+2sZQTWD6NWgl73DqRgy0+C3d+Gn/0B6IiAQ9k/o9py9I9PspMRrUiulmimlflBKHTA9D1RK/dOaQWol93S7pxGEtyLfKvzFdpSRncGnBz9lcMRgPjzwIf/d81/dwX67OLlCl38YKbfb3W/Moej6rL2j0kopS5uY3gOmY+qLEJH9GE1DWilSt1JdJraeyIaTG/j90u/2DidPO6J3MHLdSGbtnkWAdwAP+D/AmYQz/BVbhOGYWslV8oHBbxlzKHTCRy0flhYQHiJyc/asTGsHo5Xc/f734+Phw5u73iRbSs8i8VHxUUz5YQqPbn6UrOwsFoQtYHHvxUzyn4STgxPfnvzW3iFqmnYTSwuIy6Z5CAKglBoFWCnxi2ZNHs4ePN32aQ7GHuSrY1/ZOxwS0hOYs3sOw78aTuTFSJ5p+wxrh66le/3uKKWo4lqFO+veyfcnvy9VBZqmaZYXEFOAd4EWSqloYCrwiM2i0kpkoN9AgmoGMW/vPBLTE+0SQ1Z2FquPrGZwxGA+PvgxQ5sMZf3w9Uz0n3hL9tkBvgO4lHKJyIuRdolV07S8ORW0UymVc+HZbzGGnDoAScBIoHT3hlZQSimmhU5j9DejWfLnEp5uW4z1g0tgz4U9zNo9i8NXDhPiE8Ki3otoVaNVvq/vUb8H7k7ubDi5gfa129/GSDVNK0hhNYjr2VvbAY9iTGirilF7KFVrQWi5+Xv7M7TxUD49+Cmnr52+Ldc8l3iOZ396lknfTyIuLY7Z3WazrP+yAgsHMJrFetTrwaZTm8jIzmOmr6ZpdlFYNtd/mbK51gNCRORZEXkGaAuUwrUYtZyeDHkSZwdn5uyZY9PrJGcks+D3BYSvDeenMz/xWPBjrBu2jv5+/S1eEnWA3wDi0uLYeW6nTWPVNM1ylvZB1ALSczxPN23TSrGaHjWZHDiZLWe28Mu5X6x+fhHhmxPfMGTtEN7d/y5hDcL4evjXPBr0KO5ORUv21qVuFyq7VGbDyQ1Wj1PTtOIpsA8ih4+BXUqpCNPzYcAym0SkWdW4VuNYc2QN/9n1H1aHr8bJwdIfecEOXD7ArF2z2Bezj1Y1WjGn+xza+OSZT9EiLo4u9G7Qm42nNpKamYqbk5tV4tQ0rfgs+rYQkf9TSm0Aupo2TRKR0jkTS8vF1dGVZ9s/y9QtUxm/YTyVXSqX+JxpWWlEXoykhlsNZnaeydAmQ3FQJV87YIDfACKORbA9ejt9GvYp8fk0TSsZi28nRWQvsNeGsWg2ElY/jEmtJxF5KZLEDOsMe33A/wEeDHiQSi6VrHI+gPa121PdrTobTm7QBYSmlQLWaW/QSjWlFE+3u71DXYvDycGJfr79+PLolySmJ1q18NE0rej0moJaqTLQbyBpWWlsObPF3qFoWoWnCwitVAmsGUgdzzo6N5OmlQK6gNBKFQflQH+//uw8t5OrqVftHY6mVWi6gNBKnYF+A8mUTDad2mTvUDStQtMFhFbqNK/WHF8vXz1pTtPsTBcQWqmjlGKg30AiL0ZyMemivcPRtArLpgWEUqq/UupvpdQxpdS0PPZPVErFKKX2mR4P5tg3QSl11PSYYMs4tdJngN8ABOH7qO/tHYqmVVg2KyCUUo7AQmAA0AoYrZTKK63nShEJNj3eNx1bHXgV6ACEAq8qparZKlat9PGt4kvL6i11M5Om2ZEtaxChwDEROSEi6cAKYKiFx/YDNonIFRG5CmwC+tsoTq2UGuA3gAOxB25bunJN03KzZQFRFziT4/lZ07abjVRK7VdKrVZK1S/isSilHlJK7VFK7YmJibFG3Fop0d/XuCf4Luo7O0eiaRWTvTupvwZ8RSQQo5bwUVFPICJLRKSdiLSrWbOm1QPU7KdOpTqE+IToZiZNsxNbFhDRQP0cz+uZtpmJSKyIpJmevo+xEJFFx2oVQ3+//hyLO8aRq0fsHYqmVTi2LCB2A02VUn5KKRfgXmBdzhcoperkeBoOHDL9/3ugr1Kqmqlzuq9pm1bB9G3YF0flyHcndTOTpt1uNisgRCQTeBzji/0Q8IWI/KWUmqmUCje97B9Kqb+UUn8A/wAmmo69AryGUcjsBmaatmkVTA33GnSo04ENJzcgIvYOR9MqFFWe/ujatWsne/bssXcYmpVFHI3glV9eYfnA5QTWDLR3OJpWriilIkWkXV777N1JrWmF6tWwF84OzrqzWtNuM11AaKWel4sXXet25fuo78nKzrJ3OJpWYegCQisTBvgNICYlhsiLkfYORdMqDF1AaGVC9/rdcXdyZ0OUbmbStNtFFxBameDu5E7P+j3ZdGoTGVkZ9g5H04otOSOZRfsWMfPXmUQnlu7pXbqA0MqMgX4DiU+L59fzv9o7FE0rsmzJ5uvjXzMkYgj/++N/fHXsK8Ijwnnn93dIzki2d3h50gWEVmZ0vqMzXi5eejSTVub8GfMn4zaM48UdL1LToyafDPiEb0Z8Q++GvVmyfwlD1g5h/Yn1pW6ujy4gtDLD2dGZPg378OPpH0nJTLF3OJpWqEvJl3hpx0uM+XYM5xLP8XqX1/ls0GcE+wRT27M2s7rN4uMBH+Pt7s307dO5b8N9/Bnzp73DNtMFhFamDPAbQHJmMtvObrN3KJqWr7SsNN7/830GRwxmw8kNPOD/AOuHr2dok6E4qNxfu2182vD5oM+Z2Xkm0QnRjPl2DC/teImYZPtnp9YFhFamtKvVDm93b93MpJVKIsIPp35g6NqhzNs7j051OvHV0K+Y2nYqns6e+R7noBwY3nQ464ev537/+9lwcgODIwbz/p/vk5aVlu9xtqYLCK1McXRwpJ9vP7af3U5CeoK9w9E0syNXjzB542Smbp2Ku5M7S/osYV7YPOp71S/8YJNKLpV4qu1TrB26lg51OjBv7zyGrh3KD6d+1UjntAAAH8lJREFUsEv/hC4gtDJngN8A0rPT+fH0j/YORdO4mnqV13e+zl1f38Xhq4d5qcNLrBqyik53dCr2ORt4NWB+2HyW9FmCu5M7U7dOZfLGybc97b1O1qeVOSLCgC8H4Ovly+I+i+0djlZBZWRn8MXfX7Bw30KSM5K5p/k9PBb8GFVcq1j1OpnZmaw6soqF+xaSkJ7AXc3uYkrwFKq5VbPK+XWyPq1cUUrR37c/O8/v5EqqzgKv3X4/R//MqHWjeHPXm/jX8Gf1kNVM7zDd6oUDgJODE6NbjOab4d9wb/N7WX1kNYMiBrH80HIysm07aVQXEFqZNMBvAFmSxaaoTfYORatAouKjePyHx3lk8yNkZmcyv+d83u3zLk2qNbH5tau4VmF6h+msHrKa1jVa8+auNxm1bhQ/R/9ss2vqJiatTBIRhn01jKquVfloQJGXMq/wYlNiWfzHYg5eOWjvUMoOgYNXDuLq6MrDgQ8ztuVYXBxd7BOKCFvPbGX2ntmcSThD93rdmd19Nu5O7kU+V0FNTE4ljlTT7EApxQC/ASzct5ALSReo7Vnb3iGVCRlZGXx2+DMW/7GY1MxU2tZqi6ODo73DKjNGNR3Fw0EP4+3ubdc4lFL0bNCTLnW7sPzQcv6K/Qs3RzerX0cXEFqZNdBvIAv3LeT7qO+Z0HqCvcMp9bad3cbs3bOJuhZFlzu68Hz752lUtZG9w9JKwMXRhUn+k2x2fpv2QSil+iul/lZKHVNKTctj/9NKqYNKqf1KqR+UUg1z7MtSSu0zPdbZMk6tbGrg1YDWNVrz7clv7R1KqXYi/gSPbH6EKT9MAWBhr4Us6r1IFw5aoWxWg1BKOQILgT7AWWC3UmqdiORs9PwdaCciyUqpR4H/APeY9qWISLCt4tPKhwF+A5izZw6nrp2ioVfDwg+oQK6lX2PRvkWsOLwCNyc3nm33LGNajMHZ0dneoWllhC1rEKHAMRE5ISLpwApgaM4XiMgWEbme53YnUM+G8WjlUD/ffiiUTr2RQ1Z2Fl/8/QWDvxzM8kPLGdpkKOuHr2dC6wm6cNCKxJYFRF3gTI7nZ03b8vMAkPOv3E39f3tnHh9Vleb971NV2XeykrAkQJBAZJdFQDbFDVREcBkV1JZune5puqdnXp3ufl977O7pzR67p+ejYrvg2gKioq3QKvsOCoQkQAhhzUICCdkrtZ33j3sTCgyYpCqpAOf7+dSnbp1776lf3XvrPuc85znPFdklIttE5K6L7SQiC83tdlVUBD65laZrSYlIYWTySD478lm3S5UcCHaW7WTeJ/N4dtuz9Ivtx3sz3+OZ658hPiw+0NI0lyHdYh6EiDwIjAZ+71Xc1wy9egB4XkT6t7avUmqxUmq0Ump0YmJiF6jVdDduTb+VouqiLk9D0J04WXuSH6/7MY+ufpQ6Rx3PTX6O125+jaz4rEBL01zGdKaBKAa8s1T1MsvOQ0RuBH4K3KGUaklbqJQqNt+LgHXAiE7UqrmMuSn9JqxivSrdTA3OBv789Z+588M72VS8ie8P/z4f3fURM9JnICKBlqe5zOlMA7ETyBSRDBEJBu4DzotGEpERwEsYxqHcqzxORELM5QRgAqBn9GhapUdoD8aljmPV0VVXjZvJ+/GVL+97mZvSb2LlXSv57rDvEmrzfzy85uqk06KYlFIuEfk+sBqwAq8qpfJE5D+BXUqplRgupUhgmdnaOa6UugPIAl4SEQ+GEfvNBdFPGs153Jp+Kz/b/DNyTucwLHFYoOV0Kvsq9vGbnb8hpyKH7PhsnpvyHMOTdMCfxv/oVBt+5ExxHV+vPkZ0QhgjZvQhOFTPQ+wq6hx1TH5vMnGhcd1qQDao3kPaPifKAiXXBuEM863T7va4OVh1kISwBBaNXMSs/rO+8YQyTffGXl/H9g+WciIvx291hkZGcc9Pn+3QvjrVRidjr3Oy4+MicjcUYwu24mxyk7+5hOtn92fgmBTEon3BnU1kcCSLRi1iW+m2QEsBQFweYnJqiN1TA0ohChKL3FSNjKE6OxqsHb8mpvSewiPZj1zyCWWa7ofH4yZ37eds+tubNNbW0GfItdiCQ/xSd0h451wLugfhA263h7wNxez4+AgOu5vsSamMmdWPs+UNbHyvgPJjtSRnRDNxXiYpGf5PA6zpfiilKNi2mQ1vv0pNRTmZY69n8oOP4na5Wf/mXyn6eiexKT2Z8vB36DdyjB5Ivko4mZ/LmiWLqThaRNqgwUydv5Dkfp2fAbYtXKoHoQ1EBzmRX8nGZYeoKq2n16A4Js7NJD4tsmW98igO7ihj64rDNNQ4uGZsCuNn9yci1j8tBk33o/xoEWtfX8zJ/bkk9kln6oKF9B4y9Lxtjuz5inVLXqay5CR9h45g6vzHie/VJ0CKNZ1NTUU56996lYJtm4iKT+SGBx/hmvGTulXDQBsIP3K2vIHNyws5mnOa6IRQJtyTScawhIuecIfdxVerjrHni+NYrBZG3dKX4Tf2xhakM2heKTRUn2Xze2+Rs2Y1YZFRTLj3Ia6dPgPLRbKkul0u9n7+KVuWvY2jsZHhM25n/NwHCIuM6mLlms7CabezY+Vydq1cASKMufMeRs+aTVBI94sw0wbCDzgaXez67Ch7vzyB1WZh9G3pDJvWG2tQ2wYIqysa2bKikKLdFUTFhzJhzgD6jUjsVi0JTftwu5zsXvUJW5e/i8vRxIhbZjJuzv2ERkR++85AQ001W5a+Tc4XqwiJiGDCvAcZeuMtWKy68XC5opTiwKZ1bHjndeoqzzBowmQmPbCA6ITuO4lXGwgfUB7F/q2lbPuoiMYaB4Ou78m4O/sREdMxV9HJA5VsXHqIypJ60gbGMnFeJgm9dMvxcqNo907WLfkrVaXFpA8fxZSHv0N8Wu9v37EVKo4dYe2SlzmRl0NC775Mmf84fa/VYauXG2WFBaxZspjSggMk9xvA1PkLSRs0ONCyvhVtIDpIaeFZNi49RMXxWlL6RTNx3kCS06N9rtfj9pC/qYTtK4/Q1OBk8MRUxt7Rj7CowDydStN2zhSfYN0bf+Xonq+I65nGlPnfod+I63yuVylF4Y6trHvzFWoqTjHgunFMfvAxYlN6+kG1pjOpq6pk07tLyFv/JeExsUy6fz5DJk9HLJdH+LE2EO2kttLO1hWFHNpVTkRsCNff3Z/M65L97g6y1zvZ+ckR9q0vJijEypiZGWRPScNqvTwurKsJe10dW99/lz2rP8EWHML1cx9g+M23Y7X5Nzuqy+Hgq79/yPYPluJxuxh5+12Mmz2P4LBwv36PxndcDgdfffoR2z9YitvpZNTtdzJ29r2EhF9e50obiDbidLjZ/Y/j7F59DAWMmNGHkTP6EhTSuT7hypJ6Ni0/xIn8SuJSwplwTyZ9s7vPZK+rGY/Hzb4vV7Ppvbew19UydNrNTLj3QcJjYjv1e+sqz7Dx3SXkb1hDRGwcE++fz5Abpl02rdIrGaUUhTu3sv6tV6k+VUb/0eOY/NCjxKWkBlpah9AG4ltQSlG4q5wtKwqpq2piwKgkxt/dn+j49j8AvKMopTi27wyblh2iuqKRvtnxTLhnAHEpejJUoDiem8O6JYupOH6UXlnZTF2wkKT0rn0KW+mhg6x9fTGlhQdJ7pfJ1AULSbtGZ2gNFBXHj7JuyWKO5+YQ36sPU+Y/TvrQyzuPqDYQl6Cpwclb33sXe3gvwuynGFC1lmR3GUEdcPOcFcV+m4cG8eWYCg5LKA5LOAohLCSNmD43Yukms2adTaepObUWl6PS98o8HnC7iVDhjGmsIvJcMt82oZTC4fZgd3qwO93YnR5CbBYSokKw+TB7/bQ1gq9DQqn3nCJMCdc6hVSPIAQm4kyhOGFR5AYpmkRhtcTQTTL1n4dVuQj2NGBR7kBL6TRqBIKALJeFDLdgCdA1cSHW2Fj6Lnm9Q/vqVBuXIsiCxeIi4vQGXGfyOYTiECEEWYWo0CCiQ21EhwURFWojPNhGa8MQdo+b3Poqiux1hIiF+KBQn28mbpqodYdS37AX+8H9xCddT3zWdIwnuXY9bmcjp4+tobJ4KxZLMOGxGbR6MNqCR+FpqMfT1IgSK9UU83loML3DMrguzImtlXufx6OobXJR2+iixu6k1u6i1u7EY9pii0BklI1auwtrg9A/MZI+PcJpT5oiu0fYWm+hwn4UPPXYQsdjCR2O01qIVQ5jFU/Hfq+PuJQVl8rE6k4nyL4bm7sYofs17JoIoREhgjoipA5LN9ToKz2tNgaFxxBykTkugcIa5XvwTGtc9T0IbxocLvaX1pJfUk1eSQ15JTUcLKvF4TZuDGFBVrJ6RjEkNYbstGiykiJozFnPzhXv4WyytzsOvi2c+PJz1rz8F04rNzEemHzfw2TOmee3+r8Nwwf/Dza/9yaNPvrgldvN2RUrqPjv53FXVREz526SFi3i+PEzrH7pBRrOFmINjmfkXQ8RPGIEucXV5JvnobCiDrdpDaJDbS3nYEhqDENSo8lIiMBmtXC4oo5ffpLP2oMVZCRE8POZWUy9JumSAQYel5u1b3zE3i+Wotx1xKaO4PYfPEFoRCyb3zcnRSaGMWHOgEtOivQ3SikKvypny/uBc322h7oqO1s/OEzBjlNExAQz/u4BDLwuWeci6+ZoF5MPON0eDp2qI6/FaBg3rYSzRUyq3Eycs5rTsRmoMXcyaFB/hqTFkNUzmsgQ/3XOPB4Pe1/8C1vXrKLRaqF3aCTT/vVpEoZ2blrrE3k5rH3d9MEPzmbq/I774Bt27aLs17+mKX8/YSNHkvwf/0FY9hDKa+3GcT15lrKN24ktWI24z2IPTmd1/PU0JSW1GIHm915xYd96k157sJxnP8mnqKKeyQMT+fnMLAYkfXO+Se76r1j7+mIcDcUEh6cy5eGFXDv1/P/K8fwzbFpWeNG0Kp1BxfFaNi4toLSwmoTekUyal0lqZlynfqe/KCuqPi8X2aR5A0nO6JwWrsZ3tIHwI95x8EE9kmkcOZNcSyr5JTWcqXcAhuclIz6CwV43tSGp0cRH+paHqensWTb++hn2HSkAhCF9+jH5Z78gJK6HH37ZOarLy1j/1qsc2r6F6MQkJj/4KJljJ3So5ewsLubUH/5A7WerkORkTt2/kJ3pI8krrSG3pIaK2nPjDn3jw8lOCmfgwR24itaCctFz4A3MXPQ40fHtT3bodHt4Y+sxnv+igAaHm4fH92XR9IHEhAdRfrSUT/70AlUlXyPWCIZOn8e0+XdhsV0kPcaFiRlvSGPMrAxCI/wb5tpQ42D7R4fJ31JKWGQQY+/oR9aEVCyXWStceRQHt5ex9QMzF9m4FMbfpXORdUe0gfAD9vo6ti6/eBy8UopTNU3kFp/raeSV1FB8trGljp4xoee1hIekxZAaE9ruG29lfh5rfv8rjjXUEOr2MO6GGxnx/UVYfAyBdNgb2fHhcnZ9sgKxWBh751xGzZpNUDtTErvcHg6fOE354peJW7kUD/DhoGm8nX4DTbZgrBYhMymyxYBmp0aTlRpNdOi5m+3pk+V88vyLnDmxA7GEM3jy3dz4nXuw2drfMztT18Rznxfwtx3HSQgWHnYW0FS0HpSHtMFTmfkvjxEZ17bZ7N6p3YPDbIyZ1Y/sG1Kx+Dh3xe3ykLPmJLs+PYLL4eHaab247rZ0QsL9a4C6GofdxVefHWPPl0YustG39mXYdJ2LrDuhDYQP+OqDr6p3kF96zmDkFldTdLqe5sMeFx7UYjCab5gZCRFY29BiPLzyA9a99SpnRdEDC1Mf/R7pN9/W7t+oPB72b1rHxndep66qkqxJU5l0/3yi4hO+dV+7083BstoWo5hbXE3ijvU8vO9jEhur2dB7BFum30evazJafuc1KVGEtvEGcWBLDl+88iJNdccJCk3hhn96jOEzxrf7N3o8Hj56ZSVFa5aCpwZH2ABGPLSAW6Z3LKXFmeI6Ni49RPHBKnqkRjBxbia9s9rfk2sJb15+iOryRvpeG8+EOVdeeHN1RQNb3j9M0Z4KI8nlnEwyhnfdeI7m4mgD0UFO5OWwdsnLVBw7Qq+sbKbMf5zkjP4+1+s9GJ5bXENeaTUFZXUtg+HhwVayehpuqezUGAanRjMwOYrgVsJ7PC4Xu57/Azu2baDJaiEjMo5pT/2c2MyBbdLiHWef0t+Is08d2HqcfY3d2TJo3DwWc6j83ODxsIYSnsxdSZ+SQuwZmYT/+N/oP20CNh9b1x6Phw3vfMruT9/B464hOulabvvBE6QNbFua7IIduXy++EXstUexhSSSMGUuL1SEcrKqkVuGpPDT27Po3aP9s1+VUhzZe5rNyw9Rc9pO+tAEJtwzgNikttVVWVrP5mWHOJ5fSWxyOBPnXvkTJE8cqGRTcy6ya+KYNK/zx3M0l0YbiHbiTx98W3G4PBSW15Fb0hy5Y7zXO4yY8iCrkJkUdV7kTlbPaCLMwfCGinI2/OoZ9hcfQ1AMyxzChKf/L8FRrbtOLpypO+mBBQyeNLVlpm5FbdN5A/N5JTUcO9PQsn9SVEiLu2xouIuMD9/A9enHWHv0IOnHPyJm9my/z/ptqG3g0/95nWN7/wFA7+zpzPzho4RHt97ariyp4OM/Leb00W2IJZRBE+9ixuPzsAUHYXe6+evGIv537WHcSvH4pAyenDKg5Xi2B7fTw941J9j16VHcLg/Dpvdm9K3pBIe1Xpe93snOvx9h37qrM8WKx+0hb2MJ2z8uwtHgYsikNMbckUFYpM5FFggCZiBE5BbgT4AV+KtS6jcXrA8B3gBGAWeAe5VSR811TwOPAW7gX5RSq7/t+3w1EP7ywfsLj0dx9Ex9S8ht84260nswPCHivIHwnuWF7Hzxj5Q4Ggl3KybcPIvsxxa2jE+0luun15RZFFQ6WlxgeSU1lHsNHvfpEd5imAab35MUFYrH4aDqjTc4/cKLeBwOejz8EAlPPIE1snNbhKWFJ/n7/7xIddkeLNYohs64l6kP39HyGx1NDla/8A4F2z4G5SC5/0Rm/vBxYpO/6QIqq7bzu1UHWLG7mKSoEP7PLYOYPSKtQ4PC9dVNbPvwMAe2lhEWHcy4O/uRNb5nS5jnN5I0Tkpj7KyMqzZJo73eyY5PjpC7vpjgUCvXzcwge/LVYyi7CwExEGLM6CoAbgJOAjuB+5VS+V7bPAkMVUp9T0TuA2Yrpe4VkcHAu8AYIBX4Ahio1KWnaHY41YbHw/7N69n49muGD37iFCY9sKBNPviuRilFWY2dvGLDaDT3OLwHw1NjQrmtchfxRRtosAkJYuPGJxdRG2RjzRuv0FhZgbt3Nnm9J7O7ykKN3QWA1SIMSIxsGUBvHhfxHjxu1lC3Zg2nfvs7nMePEzltGsn//m8Ep6d35aEg58sdrHvzZZyNpYRE9GLqI9+lrvIsW5e/jttxhvDYAdz83SfoN/Kab63r6+NV/OLjfPaeOMuw3rE8M2swI/p0LKz01NEaNi0toKyohsQ+UUyal4nb5WHTskOcKdZp3i+ksqSeTcsKOLG/irgUw9XWZ8iV7WrrTgTKQIwHnlFK3Wx+fhpAKfVfXtusNrfZKiI2oAxIBJ7y3tZ7u0t9Z0cMhL2+jhW//n+Xfa6b5sFw7yiqY6fOMvfop6R4TuIyW2UhDjcppx1ENbkJsVkJsVmMV5Cx3BYvmmpy4DxxguAB/Ul+6mkiJ07o5F93cTwuN1+8toLcNctRnnoArEFxjJ09n7Gzp7UrssvjUXywu5jfrjpAeW0T/RMjsHTUragUvWoVQ04rwgz7S70N8hItlETS8VnoVypKkVIP2RUeIp1QFwQefYjajCfIwk+fm9KhfQOVaiMNOOH1+SQw9mLbKKVcIlINxJvl2y7YN621LxGRhcBCgD592v9s35DwCGJTejJsxm3n+eAvN+IigpkwIIEJA871euqbXBwou4H8nALsy14iym4nPTKSmKRgIkNsPo2p9Fgwn7h585CgwIZhWmxWZjw+l+vn3Mzqxe8QHBbGzd+9j+DQ9rsFLRZhzqhe3JKdwssbiyg4VeubuBQ40k8RX+JACVT2DCbCKmT6VusVzfEMRY9SB2E1rkBLuaywdVLG6cs+F5NSajGwGIweRHv3FxFu+8FP/K6rOxARYmNU3x6M6jsOZo0LtJxOJbJHNHOe+p5f6ooIsbHoxrZFgWk0VzKd2VwuBryfwdjLLGt1G9PFFIMxWN2WfTUajUbTiXSmgdgJZIpIhogEA/cBKy/YZiUw31y+B1ijjEGRlcB9IhIiIhlAJrCjE7VqNBqN5gI6zcVkjil8H1iNEeb6qlIqT0T+E9illFoJvAK8KSKFQCWGEcHcbimQD7iAf/62CCaNRqPR+Bc9UU6j0WiuYi4VxXR5huxoNBqNptPRBkKj0Wg0raINhEaj0WhaRRsIjUaj0bTKFTVILSIVwLEO7p4AnPajHH+hdbUPrat9aF3t40rU1VcpldjaiivKQPiCiOy62Eh+ING62ofW1T60rvZxtenSLiaNRqPRtIo2EBqNRqNpFW0gzrE40AIugtbVPrSu9qF1tY+rSpceg9BoNBpNq+gehEaj0WhaRRsIjUaj0bTKFWsgRORVESkXkVyvsmEislVE9onIxyISbZYHi8hrZvleEZnSSn0rvesKtC5z3WIRKRCRAyIyp5vout8szxGRVSLi04O9RaS3iKwVkXwRyRORH5rlPUTkcxE5ZL7HmeUiIn8WkUJTw0ivuuab2x8SkfkX+86u1CUiw81jnGeW39sddHnVFy0iJ0XkL91Fl4j0EZF/iMh+s770bqLrd2Yd+81tOvzIxg7oGmReR00i8pML6rpFRA6amp9qlxCl1BX5Am4ARgK5XmU7gcnm8qPAs+byPwOvmctJwFeAxWu/u4F3vOsKtC7gF8AvzWULkBBoXRjp48ubtQC/w3iWuC+6egIjzeUooAAYbNb9lFn+FPBbc/k24DNAgHHAdrO8B1BkvseZy3HdQNdAINNcTgVKgdhA6/Kq70/mtf+X7nAezXXrgJvM5UggPNC6gOuBzRiPNrACW4EpXagrCbgO+BXwE696rMBhoB8QDOwFBrdZhy8nvbu/gHTOv+FVc25gvjeQby7/L/CQ13ZfAmO8LsBN5snx2UD4UdcJIKI7HS8gCKgA+pp/oBeBhX7W+BFwE3AQ6GmW9QQOmssvAfd7bX/QXH8/8JJX+XnbBUpXK/XsxTQYgdYFjAL+BizARwPhx/M4GNjkTy1+0jUeo6EUBoQDu4CsrtLltd0znG8gxgOrvT4/DTzd1u+9Yl1MFyEPuNNcnsu5x5ruBe4QEZsYT7Ab5bXuWeA5oKG76BKR2GZtIvK1iCwTkeRA61JKOYEngH1ACcaf+RV/iTFdCSOA7UCyUqrUXFUGNP/+NAzj2cxJs+xi5YHW5V3PGIxW3uFA6xIRC8Z17/cHtvt4vAYCZ0VkhYjsFpHfi4g10LqUUluBtRg9wFKMm/L+LtR1MXy67q82A/Eo8KSIfIXRbXOY5a9iHLhdwPPAFsAtIsOB/kqpD7qTLgxXTi9gi1JqJEZ39g+B1iUiQRgGYgSGuyQHo8XiMyISCbwPLFJK1XivU0bTKCDx2v7SJSI9gTeBR5RSnm6g60ngU6XUSV+1+FmXDZiEYbiuw3CdLAi0LhEZAGRh/C/TgGkiMinQunyl0x452h1RSh0AZgCIyEDgdrPcBfyoeTsR2YLh85sMjBaRoxjHKklE1imlpgRY1xmMHs0Kc9Uy4DF/auqgruHm+sNm+VIMP6lPmIbnfeBtpVTzbz4lIj2VUqXmzbXcLC/mXE8HjD9ssfmackH5um6gCzEG//8O/FQptc0XTX7UNR6YJCJPYrhZg0WkTinV4fPpJ102YI9Sqsis80OMsYAO91T9pOtBYJtSqs6s8zOMY7ixi3RdjIted23hqupBiEiS+W4BfobhI0dEwkUkwly+CXAppfKVUi8opVKVUunARKDA38ahg7oU8DHnbnjTMZ7fHVBdGBfeYBFpzgx5E+BTN9uMBHkF2K+U+qPXqpVAcyTSfAwfbXP5w2a0yTig2uySrwZmiEicGfkxwywLqC4RCQY+AN5QSi3vqB5/61JK/ZNSqo957f/E1OeLcfDXedwJxHpdY9Pw4dr3o67jwGTT7RqE0bjs8LXfAV0XYyeQKSIZ5rV2n1lH2/DXIEp3ewHvYvgCnRjukMeAH2K0dAuA33BuADYdY/BnP/AFRvrbC+tLxz9RTH7RhTEQvAHDjfMl0Keb6PqeWZ6DYcTifdQ1EaMbnQPsMV+3AfHm7z5kauhhbi8Yg+iHMcZCRnvV9ShQaL4e6Q66MFqeTq869gDDA63rgjoX4HsUkz/P401mPfuA14HgQOvCiBZ6ybz284E/dvHxSsH439YAZ83laHPdbRj/4cMYvdQ269CpNjQajUbTKleVi0mj0Wg0bUcbCI1Go9G0ijYQGo1Go2kVbSA0Go1G0yraQGg0Go2mVbSB0Gg6gIjEi8ge81UmIsVenxvMbdJFRInIL732SxARp5jZUUXkmQv23SPnUqloNAHlqppJrdH4C6XUGcyZ4yLyDFCnlPqD+bnOa9MjGDPQf2Z+nouR48qb/27eV6PpTugehEbTuTQA+0VktPn5XmBpAPVoNG1GGwiNpvP5G3CfiPTGSLZYcsH6H3m5l9Z2vTyNpnW0i0mj6XxWYaSNPwW818p67WLSdEt0D0Kj6WSUUg6Mh8n8K+BzQj6NpqvQPQiNpmt4DlivlKqUjj+qWKPpUrSB0Gi6AKVUHt+MXmrmRyLyoNfnu5RSRztflUZzaXQ2V41Go9G0ih6D0Gg0Gk2raAOh0Wg0mlbRBkKj0Wg0raINhEaj0WhaRRsIjUaj0bSKNhAajUajaRVtIDQajUbTKv8fY0eZ3pHWBE8AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=dru)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "modern = pd.read_excel(\"drugs2011-16.xls\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>EU (28 countries)</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Euro area (19 countries)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>0.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>0.94</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.08</td>\n",
+       "      <td>1.04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.24</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>0.34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>0.22</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.18</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Lithuania</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.89</td>\n",
+       "      <td>0.91</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Hungary</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>Malta</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>Netherlands</td>\n",
+       "      <td>0.11</td>\n",
+       "      <td>0.11</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>2.66</td>\n",
+       "      <td>2.53</td>\n",
+       "      <td>2.25</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>1.42</td>\n",
+       "      <td>1.13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>Poland</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>Romania</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>Slovakia</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.46</td>\n",
+       "      <td>0.44</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>28</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>0.14</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>29</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.22</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.36</td>\n",
+       "      <td>0.29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>30</td>\n",
+       "      <td>Iceland</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>31</td>\n",
+       "      <td>Liechtenstein</td>\n",
+       "      <td>2.7</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>2.16</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>32</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>0.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>33</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.71</td>\n",
+       "      <td>0.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>34</td>\n",
+       "      <td>Montenegro</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>35</td>\n",
+       "      <td>North Macedonia</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>36</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>37</td>\n",
+       "      <td>Serbia</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.22</td>\n",
+       "      <td>0.12</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         geo  2011  2012  2013  2014  2015  2016\n",
+       "0          EU (28 countries)   0.3  0.31  0.31   0.3  0.34  0.34\n",
+       "1   Euro area (19 countries)     :     :     :     :     :     :\n",
+       "2                    Belgium  0.27  0.32  0.25  0.38  0.29  0.48\n",
+       "3                   Bulgaria   0.1  0.04  0.04     :  0.01  0.07\n",
+       "4                    Czechia  0.04  0.04  0.05  0.04  0.06  0.03\n",
+       "5                    Denmark   0.8  0.42  0.45  0.48  0.53  0.61\n",
+       "6                    Germany  0.86  0.94  0.96     1  1.08  1.04\n",
+       "7                    Estonia  0.06     :     :  0.07  0.15     :\n",
+       "8                    Ireland     :  0.04     :     :  0.02     :\n",
+       "9                     Greece  0.04  0.03  0.04     :  0.01  0.01\n",
+       "10                     Spain  0.06  0.07  0.04  0.05  0.05  0.05\n",
+       "11                    France  0.25  0.23  0.24  0.21  0.25  0.36\n",
+       "12                   Croatia  0.12  0.16  0.16  0.26  0.19  0.34\n",
+       "13                     Italy  0.22  0.21  0.18  0.17  0.17  0.14\n",
+       "14                    Cyprus     :     :     :     :     :  0.13\n",
+       "15                    Latvia  0.04     :   0.1   0.1  0.19   0.1\n",
+       "16                 Lithuania  0.03  0.07  0.06     :  0.07  0.11\n",
+       "17                Luxembourg     :     :  0.89  0.91   0.8  1.15\n",
+       "18                   Hungary  0.05  0.05  0.01  0.04  0.08  0.03\n",
+       "19                     Malta     :     :     :     :     :  0.21\n",
+       "20               Netherlands  0.11  0.11  0.16  0.16  0.21  0.27\n",
+       "21                   Austria  2.66  2.53  2.25  1.56  1.42  1.13\n",
+       "22                    Poland  0.01     0  0.02  0.01  0.01  0.02\n",
+       "23                  Portugal  0.06  0.12  0.09  0.05   0.1  0.03\n",
+       "24                   Romania  0.01     0  0.02  0.03  0.01  0.03\n",
+       "25                  Slovenia     :  0.05  0.23     :     :  0.14\n",
+       "26                  Slovakia     :  0.01  0.05  0.02  0.01     :\n",
+       "27                   Finland  0.26   0.5  0.46  0.44  0.32  0.81\n",
+       "28                    Sweden  0.15  0.14  0.16  0.23  0.23  0.26\n",
+       "29            United Kingdom  0.21  0.22  0.26  0.26  0.36  0.29\n",
+       "30                   Iceland     :     :  0.73     :     :     :\n",
+       "31             Liechtenstein   2.7     :     :     :  2.16     :\n",
+       "32                    Norway  0.57  0.63   0.5  0.31  0.64   0.4\n",
+       "33               Switzerland  0.57  0.66  0.63  0.56  0.71  0.81\n",
+       "34                Montenegro     :     :     :     :     :     :\n",
+       "35           North Macedonia     :     :     :     :     :     :\n",
+       "36                   Albania     :     :     :     :     :     :\n",
+       "37                    Serbia  0.21   0.1  0.12   0.2  0.22  0.12"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_columns = [\"geo\", \"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\"]\n",
+    "modern.columns=new_columns\n",
+    "modern.head(40)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.317, 'NaN', 0.332, 0.052, 0.043, 0.548, 0.98, 0.093, 0.03, 0.026, 0.053, 0.257, 0.205, 0.182, 0.13, 0.106, 0.068, 0.938, 0.043, 0.21, 0.17, 1.925, 0.012, 0.075, 0.017, 0.14, 0.022, 0.465, 0.195, 0.267, 0.73, 2.43, 0.508, 0.657, 'NaN', 'NaN', 'NaN', 0.162]\n"
+     ]
+    }
+   ],
+   "source": [
+    "m11=list(modern['2011'])\n",
+    "m12=list(modern['2012'])\n",
+    "m13=list(modern['2013'])\n",
+    "m14=list(modern['2014'])\n",
+    "m15=list(modern['2015'])\n",
+    "m16=list(modern['2016'])\n",
+    "\n",
+    "test = ['1.1', '0.3', ':', '1.2', 0.4]\n",
+    "def unpoint (x):\n",
+    "    s = [float(i) for i in x if i !=':']\n",
+    "    if len(s)!=0:\n",
+    "        return round(sum(s)/len(s), 3)\n",
+    "    else:\n",
+    "        return 'NaN'\n",
+    "\n",
+    "def unpoint_mean (a,b,c,d,e,f):\n",
+    "    #lst = [(sum([float(a[i]), float(b[i]), float(c[i]), d[i], e[i], f[i]])/len([a[i], b[i], c[i], d[i], e[i], f[i]])) if i!= ':' for i in range len(m11)\n",
+    "    #return [([a[i], b[i], c[i], d[i], e[i], f[i]]) for i in range(len(a))]\n",
+    "    #return [([a[i] if a[i]!=':', b[i] if b[i]!=':', c[i] if c[i]!=':', d[i] if d[i]!=':', e[i] if e[i]!=':', f[i]] if f[i]!=':') for i in range(len(a))]\n",
+    "    lst = [([a[i], b[i], c[i], d[i], e[i], f[i]]) for i in range(len(a))]\n",
+    "    return [unpoint(i) for i in lst]\n",
+    "    \n",
+    "\n",
+    "\n",
+    "print(unpoint_mean(m11,m12,m13,m14,m15,m16))\n",
+    "#print(unpoint(test))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>EU (28 countries)</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Euro area (19 countries)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.043</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        geo  2011  2012  2013  2014  2015  2016   Mean\n",
+       "0         EU (28 countries)   0.3  0.31  0.31   0.3  0.34  0.34  0.317\n",
+       "1  Euro area (19 countries)     :     :     :     :     :     :    NaN\n",
+       "2                   Belgium  0.27  0.32  0.25  0.38  0.29  0.48  0.332\n",
+       "3                  Bulgaria   0.1  0.04  0.04     :  0.01  0.07  0.052\n",
+       "4                   Czechia  0.04  0.04  0.05  0.04  0.06  0.03  0.043"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "modern[\"Mean\"]=unpoint_mean(m11,m12,m13,m14,m15,m16)\n",
+    "modern.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"\\nmod = modern\\nmod.loc[mod['2011'].str.startswith(':'), '11'] = None\\nmod.head()\\n\""
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#tst = ['0.3', ':', '0.1']\n",
+    "\"\"\"\n",
+    "premean = modern.drop(columns=[\"geo\"])\n",
+    "def summarize (a,b,c,d,e,f):\n",
+    "    x=[a,b,c,d,e,f]\n",
+    "    x1 = [float(i) for i in x if i!=':']\n",
+    "    return sum(x1)/len(x1)\n",
+    "# df.apply(lambda x: func(x['col1'],x['col2']),axis=1)\n",
+    "modern[\"Mean\"] = modern.apply(lambda x: summarize(modern[\"2011\"],modern[\"2012\"],modern[\"2013\"],modern[\"2014\"],modern[\"2015\"],modern[\"2016\"]), axis=1)\n",
+    "#summarize(tst)\n",
+    "modern.head()\n",
+    "\"\"\"\n",
+    "\n",
+    "\"\"\"\n",
+    "mod = modern\n",
+    "mod.loc[mod['2011'].str.startswith(':'), '11'] = None\n",
+    "mod.head()\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>EU (28 countries)</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>0.548</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 geo  2011  2012  2013  2014  2015  2016   Mean\n",
+       "0  EU (28 countries)   0.3  0.31  0.31   0.3  0.34  0.34  0.317\n",
+       "2            Belgium  0.27  0.32  0.25  0.38  0.29  0.48  0.332\n",
+       "3           Bulgaria   0.1  0.04  0.04     :  0.01  0.07  0.052\n",
+       "4            Czechia  0.04  0.04  0.05  0.04  0.06  0.03  0.043\n",
+       "5            Denmark   0.8  0.42  0.45  0.48  0.53  0.61  0.548"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "modern = modern[(\"NaN\"!=(modern['Mean']))]\n",
+    "modern.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#decr = ['Portugal','Czechia','Netherlands']\n",
+    "#modern['Decriminalization'] = ['Yes' if i in decr else 'No' for i in list(modern['geo'])]\n",
+    "#modern.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICCS</th>\n",
+       "      <th>UNIT</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Flag and Footnotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>139.25</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>38.00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>27.19</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>369.99</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>291.85</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                                               GEO  \\\n",
+       "0  2008                                           Belgium   \n",
+       "1  2008                                          Bulgaria   \n",
+       "2  2008                                           Czechia   \n",
+       "3  2008                                           Denmark   \n",
+       "4  2008  Germany (until 1990 former territory of the FRG)   \n",
+       "\n",
+       "                                                ICCS  \\\n",
+       "0  Unlawful acts involving controlled drugs or pr...   \n",
+       "1  Unlawful acts involving controlled drugs or pr...   \n",
+       "2  Unlawful acts involving controlled drugs or pr...   \n",
+       "3  Unlawful acts involving controlled drugs or pr...   \n",
+       "4  Unlawful acts involving controlled drugs or pr...   \n",
+       "\n",
+       "                               UNIT   Value  Flag and Footnotes  \n",
+       "0  Per hundred thousand inhabitants  139.25                 NaN  \n",
+       "1  Per hundred thousand inhabitants   38.00                 NaN  \n",
+       "2  Per hundred thousand inhabitants   27.19                 NaN  \n",
+       "3  Per hundred thousand inhabitants  369.99                 NaN  \n",
+       "4  Per hundred thousand inhabitants  291.85                 NaN  "
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "precrimes = pd.read_csv(\"crim_off_cat_1_Data.csv\")\n",
+    "precrimes.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>139.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>38.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>27.19</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO   Value\n",
+       "0  2008   Belgium  139.25\n",
+       "1  2008  Bulgaria   38.00\n",
+       "2  2008   Czechia   27.19"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crimes = precrimes.drop(columns=precrimes[[\"ICCS\",\"Flag and Footnotes\", \"UNIT\"]])\n",
+    "crimes.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "crimes = crimes[(\":\"!=(crimes['Value']))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>139.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>38.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>27.19</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO   Value\n",
+       "0  2008   Belgium  139.25\n",
+       "1  2008  Bulgaria   38.00\n",
+       "2  2008   Czechia   27.19"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crimes['Value'] = [float(i.replace(',','')) for i in crimes['Value']]\n",
+    "crimes.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>56.417143</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>177.115556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>269.883000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       GEO       Value\n",
+       "0  Albania   56.417143\n",
+       "1  Austria  177.115556\n",
+       "2  Belgium  269.883000"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crime_mean = crimes.groupby(crimes[\"GEO\"], as_index=False).agg({'Value':'mean'})\n",
+    "crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#decr = ['Portugal','Czechia','Netherlands']\n",
+    "\n",
+    "#crime_mean.loc[(crime_mean['GEO']!=('Portugal') or (crime_mean['GEO']!='Czechia') or (crime_mean['GEO']!='Netherlands')),'Decrimalization'] = 'No'\n",
+    "#crime_mean[\"Decriminalization\"]='No'\n",
+    "#crime_mean.loc[(crime_mean['GEO']==('Portugal') or (crime_mean['GEO']=='Czechia') or (crime_mean['GEO']=='Netherlands')),'Decrimalization'] = 'Yes'\n",
+    "#crime_mean['Decriminalization'] = np.where((crime_mean['GEO']=='Portugal' or crime_mean['GEO']=='Netherlands' or crime_mean['GEO']=='Czechia'), 'Yes', 'No')\n",
+    "#crime_mean['Decriminalization'] = np.where((crime_mean['GEO'] in decr), 'Yes', 'No')\n",
+    "\n",
+    "#crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>56.417143</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>177.115556</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>269.883000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       GEO       Value Decriminalization\n",
+       "0  Albania   56.417143                No\n",
+       "1  Austria  177.115556                No\n",
+       "2  Belgium  269.883000                No"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decr = ['Portugal','Czechia','Netherlands']\n",
+    "crime_mean['Decriminalization'] = ['Yes' if i in decr else 'No' for i in list(crime_mean['GEO'])]\n",
+    "crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>39</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1041.335000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Liechtenstein</td>\n",
+       "      <td>1010.723333</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>38</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>974.664000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              GEO        Value Decriminalization\n",
+       "39    Switzerland  1041.335000                No\n",
+       "21  Liechtenstein  1010.723333                No\n",
+       "38         Sweden   974.664000                No"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sorted_crime_mean = crime_mean.sort_values(by='Value', ascending=False)\n",
+    "sorted_crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2.66</td>\n",
+       "      <td>2.53</td>\n",
+       "      <td>2.25</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>1.42</td>\n",
+       "      <td>1.13</td>\n",
+       "      <td>1.925</td>\n",
+       "      <td>177.115556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425000</td>\n",
+       "      <td>3.237500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>269.883000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>0.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.052</td>\n",
+       "      <td>49.573000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.205</td>\n",
+       "      <td>126.765556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>109.241000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization  2011  \\\n",
+       "0   Austria            1.990000              4.880000                No  2.66   \n",
+       "1   Belgium            0.425000              3.237500                No  0.27   \n",
+       "2  Bulgaria            0.020000              0.640000                No   0.1   \n",
+       "3   Croatia            0.566667              5.444444                No  0.12   \n",
+       "4    Cyprus            0.466667              0.571429                No     :   \n",
+       "\n",
+       "   2012  2013  2014  2015  2016 Drug Deaths: Mean 2011-16  Drug related crimes  \n",
+       "0  2.53  2.25  1.56  1.42  1.13                     1.925           177.115556  \n",
+       "1  0.32  0.25  0.38  0.29  0.48                     0.332           269.883000  \n",
+       "2  0.04  0.04     :  0.01  0.07                     0.052            49.573000  \n",
+       "3  0.16  0.16  0.26  0.19  0.34                     0.205           126.765556  \n",
+       "4     :     :     :     :  0.13                      0.13           109.241000  "
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crime_mean = crime_mean.rename(columns={\"Value\": \"Drug related crimes\"})\n",
+    "modern = modern.rename(columns={'geo':'GEO', 'Mean':'Drug Deaths: Mean 2011-16'})\n",
+    "alls = alcodrug.merge(modern)\n",
+    "alls = alls.merge(crime_mean)\n",
+    "alls.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(28, 12)"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "alls.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>1.925</td>\n",
+       "      <td>177.115556</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425000</td>\n",
+       "      <td>3.237500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>269.883000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>0.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.052</td>\n",
+       "      <td>49.573000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.205</td>\n",
+       "      <td>126.765556</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>109.241000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>41.638000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.548</td>\n",
+       "      <td>419.544000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>10.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.093</td>\n",
+       "      <td>365.880000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>0.340000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>396.871000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>5.290000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.257</td>\n",
+       "      <td>75.882000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>0.028571</td>\n",
+       "      <td>0.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>101.286000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>Hungary</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.450000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>57.196000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Iceland</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>562.196000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>2.633333</td>\n",
+       "      <td>2.071429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>387.311000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>0.387500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.182</td>\n",
+       "      <td>56.924000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>4.650000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.106</td>\n",
+       "      <td>123.566000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Lithuania</td>\n",
+       "      <td>0.310000</td>\n",
+       "      <td>0.980000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.068</td>\n",
+       "      <td>79.516000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>0.350000</td>\n",
+       "      <td>4.462500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.938</td>\n",
+       "      <td>564.701000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Netherlands</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>1.490000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>93.352000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>814.233000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>Poland</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>4.400000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>174.743000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>0.130000</td>\n",
+       "      <td>1.230000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.075</td>\n",
+       "      <td>46.205000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>Romania</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>17.285000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Slovakia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.022</td>\n",
+       "      <td>21.355000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>0.150000</td>\n",
+       "      <td>5.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.14</td>\n",
+       "      <td>81.550000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>0.190000</td>\n",
+       "      <td>0.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.053</td>\n",
+       "      <td>29.752000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>0.300000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.195</td>\n",
+       "      <td>974.664000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>3.140000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.657</td>\n",
+       "      <td>1041.335000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization  \\\n",
+       "0       Austria            1.990000              4.880000                No   \n",
+       "1       Belgium            0.425000              3.237500                No   \n",
+       "2      Bulgaria            0.020000              0.640000                No   \n",
+       "3       Croatia            0.566667              5.444444                No   \n",
+       "4        Cyprus            0.466667              0.571429                No   \n",
+       "5       Czechia            0.000000              1.550000               Yes   \n",
+       "6       Denmark            0.733333             13.933333                No   \n",
+       "7       Estonia            0.125000             10.220000                No   \n",
+       "8       Finland            0.340000              3.780000                No   \n",
+       "9        France            0.290000              5.290000                No   \n",
+       "10       Greece            0.028571              0.220000                No   \n",
+       "11      Hungary            0.000000              4.450000                No   \n",
+       "12      Iceland            0.450000              1.600000                No   \n",
+       "13      Ireland            2.633333              2.071429                No   \n",
+       "14        Italy            0.450000              0.387500                No   \n",
+       "15       Latvia            0.033333              4.650000                No   \n",
+       "16    Lithuania            0.310000              0.980000                No   \n",
+       "17   Luxembourg            0.350000              4.462500                No   \n",
+       "18  Netherlands            0.100000              1.490000               Yes   \n",
+       "19       Norway            1.790000              4.490000                No   \n",
+       "20       Poland            0.040000              4.400000                No   \n",
+       "21     Portugal            0.130000              1.230000               Yes   \n",
+       "22      Romania            0.000000              2.780000                No   \n",
+       "23     Slovakia            0.033333              0.000000                No   \n",
+       "24     Slovenia            0.150000              5.640000                No   \n",
+       "25        Spain            0.190000              0.780000                No   \n",
+       "26       Sweden            0.300000              3.780000                No   \n",
+       "27  Switzerland            1.550000              3.140000                No   \n",
+       "\n",
+       "   Drug Deaths: Mean 2011-16  Drug related crimes  Decr.: 0 or 1  \n",
+       "0                      1.925           177.115556              0  \n",
+       "1                      0.332           269.883000              0  \n",
+       "2                      0.052            49.573000              0  \n",
+       "3                      0.205           126.765556              0  \n",
+       "4                       0.13           109.241000              0  \n",
+       "5                      0.043            41.638000              1  \n",
+       "6                      0.548           419.544000              0  \n",
+       "7                      0.093           365.880000              0  \n",
+       "8                      0.465           396.871000              0  \n",
+       "9                      0.257            75.882000              0  \n",
+       "10                     0.026           101.286000              0  \n",
+       "11                     0.043            57.196000              0  \n",
+       "12                      0.73           562.196000              0  \n",
+       "13                      0.03           387.311000              0  \n",
+       "14                     0.182            56.924000              0  \n",
+       "15                     0.106           123.566000              0  \n",
+       "16                     0.068            79.516000              0  \n",
+       "17                     0.938           564.701000              0  \n",
+       "18                      0.17            93.352000              1  \n",
+       "19                     0.508           814.233000              0  \n",
+       "20                     0.012           174.743000              0  \n",
+       "21                     0.075            46.205000              1  \n",
+       "22                     0.017            17.285000              0  \n",
+       "23                     0.022            21.355000              0  \n",
+       "24                      0.14            81.550000              0  \n",
+       "25                     0.053            29.752000              0  \n",
+       "26                     0.195           974.664000              0  \n",
+       "27                     0.657          1041.335000              0  "
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "allinone = alls.drop(columns=alls[[\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\"]])\n",
+    "allinone[\"Decr.: 0 or 1\"]=[1 if i in decr else 0 for i in list(allinone['GEO'])]\n",
+    "allinone.head(30)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "allinone['Drug Deaths: Mean 2011-16']=[float(i) for i in allinone['Drug Deaths: Mean 2011-16']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>Drugs: Deaths/100k</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>-0.212064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Alcohol: Deaths/100k</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>-0.230574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug Deaths: Mean 2011-16</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>-0.166038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug related crimes</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.240490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Decr.: 0 or 1</td>\n",
+       "      <td>-0.212064</td>\n",
+       "      <td>-0.230574</td>\n",
+       "      <td>-0.166038</td>\n",
+       "      <td>-0.240490</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           Drugs: Deaths/100k  Alcohol: Deaths/100k  \\\n",
+       "Drugs: Deaths/100k                   1.000000              0.113377   \n",
+       "Alcohol: Deaths/100k                 0.113377              1.000000   \n",
+       "Drug Deaths: Mean 2011-16            0.518156              0.254011   \n",
+       "Drug related crimes                  0.477380              0.265929   \n",
+       "Decr.: 0 or 1                       -0.212064             -0.230574   \n",
+       "\n",
+       "                           Drug Deaths: Mean 2011-16  Drug related crimes  \\\n",
+       "Drugs: Deaths/100k                          0.518156             0.477380   \n",
+       "Alcohol: Deaths/100k                        0.254011             0.265929   \n",
+       "Drug Deaths: Mean 2011-16                   1.000000             0.367619   \n",
+       "Drug related crimes                         0.367619             1.000000   \n",
+       "Decr.: 0 or 1                              -0.166038            -0.240490   \n",
+       "\n",
+       "                           Decr.: 0 or 1  \n",
+       "Drugs: Deaths/100k             -0.212064  \n",
+       "Alcohol: Deaths/100k           -0.230574  \n",
+       "Drug Deaths: Mean 2011-16      -0.166038  \n",
+       "Drug related crimes            -0.240490  \n",
+       "Decr.: 0 or 1                   1.000000  "
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr = allinone.corr()\n",
+    "corr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed50e73ba8>"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "sns.heatmap(corr, annot=True)\n",
+    "#allinone.corr().style.background_gradient(cmap='Blues')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "      <th>Badness_index</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>Romania</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>17.285000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.293845</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Slovakia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.022</td>\n",
+       "      <td>21.355000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.469810</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>0.190000</td>\n",
+       "      <td>0.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.053</td>\n",
+       "      <td>29.752000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.576856</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>41.638000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.790434</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>Poland</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>4.400000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>174.743000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.096916</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>Hungary</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.450000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>57.196000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.459428</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>0.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.052</td>\n",
+       "      <td>49.573000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.577796</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>0.028571</td>\n",
+       "      <td>0.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>101.286000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.633436</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>0.130000</td>\n",
+       "      <td>1.230000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.075</td>\n",
+       "      <td>46.205000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.465375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Lithuania</td>\n",
+       "      <td>0.310000</td>\n",
+       "      <td>0.980000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.068</td>\n",
+       "      <td>79.516000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5.407088</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>0.387500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.182</td>\n",
+       "      <td>56.924000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10.360168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>0.150000</td>\n",
+       "      <td>5.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.140</td>\n",
+       "      <td>81.550000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11.417000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>2.633333</td>\n",
+       "      <td>2.071429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.030</td>\n",
+       "      <td>387.311000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11.619330</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>4.650000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.106</td>\n",
+       "      <td>123.566000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13.097996</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.130</td>\n",
+       "      <td>109.241000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>14.201330</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Netherlands</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>1.490000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.170</td>\n",
+       "      <td>93.352000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>15.869840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>5.290000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.257</td>\n",
+       "      <td>75.882000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>19.501674</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.205</td>\n",
+       "      <td>126.765556</td>\n",
+       "      <td>0</td>\n",
+       "      <td>25.986939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>10.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.093</td>\n",
+       "      <td>365.880000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>34.026840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425000</td>\n",
+       "      <td>3.237500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>269.883000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>89.601156</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>0.340000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>396.871000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>184.545015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>0.300000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.195</td>\n",
+       "      <td>974.664000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>190.059480</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.548</td>\n",
+       "      <td>419.544000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>229.910112</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>1.925</td>\n",
+       "      <td>177.115556</td>\n",
+       "      <td>0</td>\n",
+       "      <td>340.947444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Iceland</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.730</td>\n",
+       "      <td>562.196000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>410.403080</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>814.233000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>413.630364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>0.350000</td>\n",
+       "      <td>4.462500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.938</td>\n",
+       "      <td>564.701000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>529.689538</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>3.140000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.657</td>\n",
+       "      <td>1041.335000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>684.157095</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization  \\\n",
+       "22      Romania            0.000000              2.780000                No   \n",
+       "23     Slovakia            0.033333              0.000000                No   \n",
+       "25        Spain            0.190000              0.780000                No   \n",
+       "5       Czechia            0.000000              1.550000               Yes   \n",
+       "20       Poland            0.040000              4.400000                No   \n",
+       "11      Hungary            0.000000              4.450000                No   \n",
+       "2      Bulgaria            0.020000              0.640000                No   \n",
+       "10       Greece            0.028571              0.220000                No   \n",
+       "21     Portugal            0.130000              1.230000               Yes   \n",
+       "16    Lithuania            0.310000              0.980000                No   \n",
+       "14        Italy            0.450000              0.387500                No   \n",
+       "24     Slovenia            0.150000              5.640000                No   \n",
+       "13      Ireland            2.633333              2.071429                No   \n",
+       "15       Latvia            0.033333              4.650000                No   \n",
+       "4        Cyprus            0.466667              0.571429                No   \n",
+       "18  Netherlands            0.100000              1.490000               Yes   \n",
+       "9        France            0.290000              5.290000                No   \n",
+       "3       Croatia            0.566667              5.444444                No   \n",
+       "7       Estonia            0.125000             10.220000                No   \n",
+       "1       Belgium            0.425000              3.237500                No   \n",
+       "8       Finland            0.340000              3.780000                No   \n",
+       "26       Sweden            0.300000              3.780000                No   \n",
+       "6       Denmark            0.733333             13.933333                No   \n",
+       "0       Austria            1.990000              4.880000                No   \n",
+       "12      Iceland            0.450000              1.600000                No   \n",
+       "19       Norway            1.790000              4.490000                No   \n",
+       "17   Luxembourg            0.350000              4.462500                No   \n",
+       "27  Switzerland            1.550000              3.140000                No   \n",
+       "\n",
+       "    Drug Deaths: Mean 2011-16  Drug related crimes  Decr.: 0 or 1  \\\n",
+       "22                      0.017            17.285000              0   \n",
+       "23                      0.022            21.355000              0   \n",
+       "25                      0.053            29.752000              0   \n",
+       "5                       0.043            41.638000              1   \n",
+       "20                      0.012           174.743000              0   \n",
+       "11                      0.043            57.196000              0   \n",
+       "2                       0.052            49.573000              0   \n",
+       "10                      0.026           101.286000              0   \n",
+       "21                      0.075            46.205000              1   \n",
+       "16                      0.068            79.516000              0   \n",
+       "14                      0.182            56.924000              0   \n",
+       "24                      0.140            81.550000              0   \n",
+       "13                      0.030           387.311000              0   \n",
+       "15                      0.106           123.566000              0   \n",
+       "4                       0.130           109.241000              0   \n",
+       "18                      0.170            93.352000              1   \n",
+       "9                       0.257            75.882000              0   \n",
+       "3                       0.205           126.765556              0   \n",
+       "7                       0.093           365.880000              0   \n",
+       "1                       0.332           269.883000              0   \n",
+       "8                       0.465           396.871000              0   \n",
+       "26                      0.195           974.664000              0   \n",
+       "6                       0.548           419.544000              0   \n",
+       "0                       1.925           177.115556              0   \n",
+       "12                      0.730           562.196000              0   \n",
+       "19                      0.508           814.233000              0   \n",
+       "17                      0.938           564.701000              0   \n",
+       "27                      0.657          1041.335000              0   \n",
+       "\n",
+       "    Badness_index  \n",
+       "22       0.293845  \n",
+       "23       0.469810  \n",
+       "25       1.576856  \n",
+       "5        1.790434  \n",
+       "20       2.096916  \n",
+       "11       2.459428  \n",
+       "2        2.577796  \n",
+       "10       2.633436  \n",
+       "21       3.465375  \n",
+       "16       5.407088  \n",
+       "14      10.360168  \n",
+       "24      11.417000  \n",
+       "13      11.619330  \n",
+       "15      13.097996  \n",
+       "4       14.201330  \n",
+       "18      15.869840  \n",
+       "9       19.501674  \n",
+       "3       25.986939  \n",
+       "7       34.026840  \n",
+       "1       89.601156  \n",
+       "8      184.545015  \n",
+       "26     190.059480  \n",
+       "6      229.910112  \n",
+       "0      340.947444  \n",
+       "12     410.403080  \n",
+       "19     413.630364  \n",
+       "17     529.689538  \n",
+       "27     684.157095  "
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "checkstuff = allinone\n",
+    "checkstuff[\"Badness_index\"] = checkstuff[\"Drug Deaths: Mean 2011-16\"]*checkstuff[\"Drug related crimes\"]\n",
+    "checkstuff.sort_values(by=\"Badness_index\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "      <th>Badness_index</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>Drugs: Deaths/100k</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>-0.212064</td>\n",
+       "      <td>0.489576</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Alcohol: Deaths/100k</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>-0.230574</td>\n",
+       "      <td>0.207791</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug Deaths: Mean 2011-16</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>-0.166038</td>\n",
+       "      <td>0.719648</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug related crimes</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.240490</td>\n",
+       "      <td>0.810887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Decr.: 0 or 1</td>\n",
+       "      <td>-0.212064</td>\n",
+       "      <td>-0.230574</td>\n",
+       "      <td>-0.166038</td>\n",
+       "      <td>-0.240490</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.203978</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Badness_index</td>\n",
+       "      <td>0.489576</td>\n",
+       "      <td>0.207791</td>\n",
+       "      <td>0.719648</td>\n",
+       "      <td>0.810887</td>\n",
+       "      <td>-0.203978</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           Drugs: Deaths/100k  Alcohol: Deaths/100k  \\\n",
+       "Drugs: Deaths/100k                   1.000000              0.113377   \n",
+       "Alcohol: Deaths/100k                 0.113377              1.000000   \n",
+       "Drug Deaths: Mean 2011-16            0.518156              0.254011   \n",
+       "Drug related crimes                  0.477380              0.265929   \n",
+       "Decr.: 0 or 1                       -0.212064             -0.230574   \n",
+       "Badness_index                        0.489576              0.207791   \n",
+       "\n",
+       "                           Drug Deaths: Mean 2011-16  Drug related crimes  \\\n",
+       "Drugs: Deaths/100k                          0.518156             0.477380   \n",
+       "Alcohol: Deaths/100k                        0.254011             0.265929   \n",
+       "Drug Deaths: Mean 2011-16                   1.000000             0.367619   \n",
+       "Drug related crimes                         0.367619             1.000000   \n",
+       "Decr.: 0 or 1                              -0.166038            -0.240490   \n",
+       "Badness_index                               0.719648             0.810887   \n",
+       "\n",
+       "                           Decr.: 0 or 1  Badness_index  \n",
+       "Drugs: Deaths/100k             -0.212064       0.489576  \n",
+       "Alcohol: Deaths/100k           -0.230574       0.207791  \n",
+       "Drug Deaths: Mean 2011-16      -0.166038       0.719648  \n",
+       "Drug related crimes            -0.240490       0.810887  \n",
+       "Decr.: 0 or 1                   1.000000      -0.203978  \n",
+       "Badness_index                  -0.203978       1.000000  "
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "checkstuff.corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prerely = allinone.sort_values(by=\"Drugs: Deaths/100k\", ascending=False)\n",
+    "rely = sns.relplot(x=\"GEO\", y=\"Drugs: Deaths/100k\",  hue=\"Decriminalization\", size='Drug related crimes', sizes = (50,250), palette=\"pastel\", data=prerely);\n",
+    "rely.set_xticklabels(rotation=45, horizontalalignment = 'right')\n",
+    "plt.xlabel('Countries',fontsize=12, fontweight=\"bold\")\n",
+    "plt.ylabel('Drugs: Deaths/100k',fontsize=12, fontweight=\"bold\")\n",
+    "rely.fig.set_size_inches(15,5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rely = sns.relplot(x=\"GEO\", y=\"Drugs: Deaths/100k\",  hue=\"Decriminalization\", size='Drug related crimes', sizes = (50,250), palette=\"pastel\", data=allinone);\n",
+    "rely.set_xticklabels(rotation=45, horizontalalignment = 'right')\n",
+    "plt.xlabel('Countries',fontsize=12, fontweight=\"bold\")\n",
+    "plt.ylabel('Drugs: Deaths/100k',fontsize=12, fontweight=\"bold\")\n",
+    "rely.fig.set_size_inches(15,5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x7fed4c377198>"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 502.375x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.relplot(data=allinone, x='Drugs: Deaths/100k', y='Drug related crimes', hue='Decriminalization', alpha=0.75, size='Alcohol: Deaths/100k', palette='bright',  sizes= (50, 200))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 455.5x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.lmplot(x=\"Drug related crimes\", y=\"Drugs: Deaths/100k\", hue=\"Decriminalization\", data=allinone, fit_reg=False)\n",
+    "sns.regplot(x=\"Drug related crimes\", y=\"Drugs: Deaths/100k\", data=allinone, scatter=False, ax=g.axes[0, 0])\n",
+    "plt.rcParams['figure.figsize']=9,7\n",
+    "plt.xlabel('Drug related crimes',fontsize=12, fontweight=\"bold\")\n",
+    "plt.ylabel('Drugs: Deaths/100k',fontsize=12, fontweight=\"bold\")\n",
+    "#plt.savefig('Linear Regression2.png',dpi=300)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x7fed4c28af98>"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x900 with 30 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.pairplot(allinone)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# \n",
+    "tax=[67594323,130411173,193604810,247368473,266529637]\n",
+    "taxy = ['2014','2015','2016','2017','2018']\n",
+    "prehist = pd.DataFrame({'Revenue':tax,'Year':taxy})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "565583916.856951"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tax[0] * (12/11) * (7/13) * (83000000/5250000) * 0.901"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "999150217.7538462"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tax[1] * (7/13) * (83000000/5250000) * 0.9"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1483310698.153846"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tax[2] * (7/13) * (83000000/5250000) * 0.9"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x7fed47418978>"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#sns.distplot(vehicles['Fuel Barrels/Year'], bins=20)\n",
+    "chart = sns.catplot(x=\"Year\", y=\"Revenue\", kind='bar', palette=\"rocket\", data=prehist)\n",
+    "chart.set_xticklabels(rotation=45, horizontalalignment = 'right')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>Drugs: Deaths/100k</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.212064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Alcohol: Deaths/100k</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>0.230574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug related crimes</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.240490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Decr.: 0 or 1</td>\n",
+       "      <td>0.212064</td>\n",
+       "      <td>0.230574</td>\n",
+       "      <td>0.240490</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Drugs: Deaths/100k  Alcohol: Deaths/100k  \\\n",
+       "Drugs: Deaths/100k              1.000000              0.113377   \n",
+       "Alcohol: Deaths/100k            0.113377              1.000000   \n",
+       "Drug related crimes             0.477380              0.265929   \n",
+       "Decr.: 0 or 1                   0.212064              0.230574   \n",
+       "\n",
+       "                      Drug related crimes  Decr.: 0 or 1  \n",
+       "Drugs: Deaths/100k               0.477380       0.212064  \n",
+       "Alcohol: Deaths/100k             0.265929       0.230574  \n",
+       "Drug related crimes              1.000000       0.240490  \n",
+       "Decr.: 0 or 1                    0.240490       1.000000  "
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "allinone2 = alls.drop(columns=alls[[\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\"]])\n",
+    "allinone2[\"Decr.: 0 or 1\"]=[0 if i in decr else 1 for i in list(allinone['GEO'])]\n",
+    "allinone2.corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col0 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col1 {\n",
+       "            background-color:  #a50026;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col2 {\n",
+       "            background-color:  #fee491;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col3 {\n",
+       "            background-color:  #da362a;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col0 {\n",
+       "            background-color:  #a50026;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col1 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col2 {\n",
+       "            background-color:  #ec5c3b;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col3 {\n",
+       "            background-color:  #e0422f;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col0 {\n",
+       "            background-color:  #fee491;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col1 {\n",
+       "            background-color:  #ec5c3b;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col2 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col3 {\n",
+       "            background-color:  #e34933;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col0 {\n",
+       "            background-color:  #da362a;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col1 {\n",
+       "            background-color:  #e0422f;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col2 {\n",
+       "            background-color:  #e34933;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col3 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }</style><table id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Drugs: Deaths/100k</th>        <th class=\"col_heading level0 col1\" >Alcohol: Deaths/100k</th>        <th class=\"col_heading level0 col2\" >Drug related crimes</th>        <th class=\"col_heading level0 col3\" >Decr.: 0 or 1</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row0\" class=\"row_heading level0 row0\" >Drugs: Deaths/100k</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col0\" class=\"data row0 col0\" >1</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col1\" class=\"data row0 col1\" >0.11</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col2\" class=\"data row0 col2\" >0.48</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col3\" class=\"data row0 col3\" >0.21</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row1\" class=\"row_heading level0 row1\" >Alcohol: Deaths/100k</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col0\" class=\"data row1 col0\" >0.11</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col1\" class=\"data row1 col1\" >1</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col2\" class=\"data row1 col2\" >0.27</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col3\" class=\"data row1 col3\" >0.23</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row2\" class=\"row_heading level0 row2\" >Drug related crimes</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col0\" class=\"data row2 col0\" >0.48</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col1\" class=\"data row2 col1\" >0.27</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col2\" class=\"data row2 col2\" >1</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col3\" class=\"data row2 col3\" >0.24</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row3\" class=\"row_heading level0 row3\" >Decr.: 0 or 1</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col0\" class=\"data row3 col0\" >0.21</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col1\" class=\"data row3 col1\" >0.23</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col2\" class=\"data row3 col2\" >0.24</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col3\" class=\"data row3 col3\" >1</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fed4ec578d0>"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "matrix = allinone2.corr().style.background_gradient(cmap='RdYlGn',axis=None).set_precision(2)\n",
+    "matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 648x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['', 'Regular Users according to Survey in 2014']\n",
+    "sizes = [0.869,0.131]\n",
+    "\n",
+    "explode = (0, 0.1)\n",
+    "plt.pie(sizes, explode=explode, shadow=True, autopct='%1.1f%%',  startangle=90, labels=labels)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 648x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['', 'Use within the last 12 months survey 2017']\n",
+    "sizes = [0.93,0.07]\n",
+    "\n",
+    "explode = (0, 0.1)\n",
+    "plt.pie(sizes, explode=explode, shadow=True, autopct='%1.1f%%',  startangle=90, labels=labels)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/your-project/Week 4 - Project/.~lock.Report.odt# b/your-project/Week 4 - Project/.~lock.Report.odt#
new file mode 100644
index 0000000..3b90358
--- /dev/null
+++ b/your-project/Week 4 - Project/.~lock.Report.odt#	
@@ -0,0 +1 @@
+,jan,jan-UX32VD,18.09.2019 19:41,file:///home/jan/.config/libreoffice/4;
\ No newline at end of file
diff --git a/your-project/Week 4 - Project/Canvas_Presentation.pdf b/your-project/Week 4 - Project/Canvas_Presentation.pdf
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index 0000000..e6f1a65
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diff --git a/your-project/Week 4 - Project/Colorado_Marijuana_tax_revenue.png b/your-project/Week 4 - Project/Colorado_Marijuana_tax_revenue.png
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index 0000000..9189626
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diff --git a/your-project/Week 4 - Project/Eurostat_Table_tps00149NoFlagNoDesc b/your-project/Week 4 - Project/Eurostat_Table_tps00149NoFlagNoDesc
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index 0000000..9deeddd
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diff --git a/your-project/Week 4 - Project/Report.odt b/your-project/Week 4 - Project/Report.odt
new file mode 100644
index 0000000..1d5e32a
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diff --git a/your-project/Week 4 - Project/Tax_revenue_Colorado.png b/your-project/Week 4 - Project/Tax_revenue_Colorado.png
new file mode 100644
index 0000000..b12828d
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diff --git a/your-project/Week 4 - Project/canvas_link.odt b/your-project/Week 4 - Project/canvas_link.odt
new file mode 100644
index 0000000..062984f
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diff --git a/your-project/Week 4 - Project/correlation_table.png b/your-project/Week 4 - Project/correlation_table.png
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index 0000000..5b61944
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diff --git a/your-project/Week 4 - Project/crim_off_cat_1_Data.csv b/your-project/Week 4 - Project/crim_off_cat_1_Data.csv
new file mode 100644
index 0000000..1719a2d
--- /dev/null
+++ b/your-project/Week 4 - Project/crim_off_cat_1_Data.csv	
@@ -0,0 +1,411 @@
+"TIME","GEO","ICCS","UNIT","Value","Flag and Footnotes"
+"2008","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","139.25",""
+"2008","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","38.00",""
+"2008","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","27.19",""
+"2008","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","369.99",""
+"2008","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","291.85",""
+"2008","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","573.13",""
+"2008","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","523.93",""
+"2008","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","109.97",""
+"2008","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","31.89",""
+"2008","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","9.57",""
+"2008","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","182.79",""
+"2008","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","58.11",""
+"2008","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","100.34",""
+"2008","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","114.61",""
+"2008","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","57.18",""
+"2008","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","277.59",""
+"2008","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","54.39",""
+"2008","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","44.14",""
+"2008","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","115.05",""
+"2008","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","23.83",""
+"2008","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","150.55",""
+"2008","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","35.33",""
+"2008","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","17.55",""
+"2008","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","71.33",""
+"2008","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","10.01",""
+"2008","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","292.08",""
+"2008","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","868.94",""
+"2008","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","54.72",""
+"2008","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","198.90",""
+"2008","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","34.29",""
+"2008","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","463.13",""
+"2008","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","593.96",""
+"2008","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","762.84",""
+"2008","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","626.72",""
+"2008","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","74.73",""
+"2008","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","20.29",""
+"2008","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","20.60",""
+"2008","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","82.13",""
+"2008","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2008","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","39.52",""
+"2008","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","14.58",""
+"2009","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","139.12",""
+"2009","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","49.04",""
+"2009","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","29.22",""
+"2009","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","347.60",""
+"2009","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","287.60",""
+"2009","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","317.50",""
+"2009","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","483.75",""
+"2009","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","113.93",""
+"2009","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","31.02",""
+"2009","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","9.33",""
+"2009","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","163.88",""
+"2009","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","57.80",""
+"2009","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","88.59",""
+"2009","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","106.67",""
+"2009","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","68.75",""
+"2009","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","452.28",""
+"2009","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","45.03",""
+"2009","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","45.51",""
+"2009","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","112.70",""
+"2009","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","25.18",""
+"2009","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","179.06",""
+"2009","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","40.40",""
+"2009","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","15.79",""
+"2009","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","103.13",""
+"2009","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","11.39",""
+"2009","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","347.78",""
+"2009","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","885.96",""
+"2009","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","60.36",""
+"2009","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","189.79",""
+"2009","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","35.33",""
+"2009","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","403.92",""
+"2009","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,003.12",""
+"2009","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","786.70",""
+"2009","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,113.26",""
+"2009","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","64.49",""
+"2009","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","26.90",""
+"2009","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","20.32",""
+"2009","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","74.98",""
+"2009","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2009","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1.35",""
+"2009","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","16.69",""
+"2010","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","136.07",""
+"2010","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","50.73",""
+"2010","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","28.77",""
+"2010","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","353.89",""
+"2010","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","282.39",""
+"2010","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","223.28",""
+"2010","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","435.06",""
+"2010","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","93.99",""
+"2010","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","30.96",""
+"2010","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","9.08",""
+"2010","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","180.90",""
+"2010","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","55.35",""
+"2010","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","103.89",""
+"2010","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","103.23",""
+"2010","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","70.47",""
+"2010","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","512.68",""
+"2010","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","57.81",""
+"2010","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","43.72",""
+"2010","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","100.84",""
+"2010","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","25.95",""
+"2010","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","190.34",""
+"2010","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","43.08",""
+"2010","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","17.95",""
+"2010","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","85.79",""
+"2010","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","11.58",""
+"2010","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","368.57",""
+"2010","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","964.27",""
+"2010","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","58.30",""
+"2010","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","136.05",""
+"2010","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","41.24",""
+"2010","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","472.25",""
+"2010","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,479.36",""
+"2010","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","905.99",""
+"2010","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,145.32",""
+"2010","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","49.60",""
+"2010","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","28.16",""
+"2010","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2010","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","76.27",""
+"2010","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2010","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","0.99",""
+"2010","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","21.83",""
+"2011","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","125.67",""
+"2011","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","38.80",""
+"2011","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","34.66",""
+"2011","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","414.95",""
+"2011","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","294.77",""
+"2011","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","287.36",""
+"2011","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","384.43",""
+"2011","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","87.98",""
+"2011","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","32.61",""
+"2011","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","9.12",""
+"2011","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","181.05",""
+"2011","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","57.33",""
+"2011","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","111.46",""
+"2011","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","94.81",""
+"2011","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","73.90",""
+"2011","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","574.59",""
+"2011","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","59.98",""
+"2011","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","42.89",""
+"2011","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","95.37",""
+"2011","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","27.70",""
+"2011","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","195.82",""
+"2011","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","39.86",""
+"2011","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","16.14",""
+"2011","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","73.41",""
+"2011","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","14.13",""
+"2011","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","379.40",""
+"2011","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","977.07",""
+"2011","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","55.99",""
+"2011","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","126.58",""
+"2011","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","44.54",""
+"2011","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","544.20",""
+"2011","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,200.59",""
+"2011","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","838.78",""
+"2011","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,158.95",""
+"2011","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","50.98",""
+"2011","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","28.63",""
+"2011","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","26.13",""
+"2011","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","68.14",""
+"2011","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2011","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1.41",""
+"2011","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","29.82",""
+"2012","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","102.16",""
+"2012","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","40.40",""
+"2012","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","36.30",""
+"2012","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","414.67",""
+"2012","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","295.22",""
+"2012","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","348.32",""
+"2012","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","357.45",""
+"2012","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","91.50",""
+"2012","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","30.99",""
+"2012","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","9.04",""
+"2012","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","170.60",""
+"2012","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","57.00",""
+"2012","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","119.49",""
+"2012","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","134.49",""
+"2012","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","100.08",""
+"2012","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","492.14",""
+"2012","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","52.49",""
+"2012","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","48.62",""
+"2012","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","96.50",""
+"2012","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","23.67",""
+"2012","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","200.60",""
+"2012","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","43.99",""
+"2012","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","14.29",""
+"2012","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","85.62",""
+"2012","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","14.04",""
+"2012","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","372.17",""
+"2012","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,026.89",""
+"2012","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","52.77",""
+"2012","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","102.35",""
+"2012","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","50.14",""
+"2012","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","586.40",""
+"2012","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","704.59",""
+"2012","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","885.46",""
+"2012","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,167.39",""
+"2012","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","30.15",""
+"2012","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","28.84",""
+"2012","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2012","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","66.15",""
+"2012","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2012","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1.12",""
+"2012","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2013","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","102.31",""
+"2013","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","41.90",""
+"2013","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","48.66",""
+"2013","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","460.18",""
+"2013","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","314.85",""
+"2013","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","351.32",""
+"2013","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","333.82",""
+"2013","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","95.18",""
+"2013","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","30.59",""
+"2013","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","9.84",""
+"2013","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","62.95",""
+"2013","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","56.26",""
+"2013","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","115.03",""
+"2013","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","80.89",""
+"2013","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","79.21",""
+"2013","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","599.96",""
+"2013","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","54.58",""
+"2013","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","49.36",""
+"2013","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","95.86",""
+"2013","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","322.19",""
+"2013","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","189.00",""
+"2013","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","44.34",""
+"2013","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","12.28",""
+"2013","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","83.15",""
+"2013","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","35.67",""
+"2013","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","417.49",""
+"2013","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,037.84",""
+"2013","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","51.71",""
+"2013","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","668.07",""
+"2013","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","243.40",""
+"2013","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","663.03",""
+"2013","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,172.70",""
+"2013","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","936.12",""
+"2013","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,210.20",""
+"2013","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","27.70",""
+"2013","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2013","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2013","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","78.65",""
+"2013","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2013","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2013","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2014","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","493.09",""
+"2014","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","44.70",""
+"2014","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","53.24",""
+"2014","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","499.23",""
+"2014","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","342.63",""
+"2014","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","307.95",""
+"2014","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","342.03",""
+"2014","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","99.34",""
+"2014","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","28.83",""
+"2014","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","10.46",""
+"2014","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","63.74",""
+"2014","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","53.83",""
+"2014","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","125.87",""
+"2014","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","134.75",""
+"2014","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","87.89",""
+"2014","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","762.26",""
+"2014","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","61.99",""
+"2014","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","44.71",""
+"2014","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","90.28",""
+"2014","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","342.83",""
+"2014","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","167.83",""
+"2014","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","45.56",""
+"2014","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","12.07",""
+"2014","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","80.64",""
+"2014","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","29.71",""
+"2014","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","399.56",""
+"2014","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,018.36",""
+"2014","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","49.21",""
+"2014","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","688.34",""
+"2014","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","269.42",""
+"2014","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","721.59",""
+"2014","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,018.07",""
+"2014","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","888.18",""
+"2014","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","994.96",""
+"2014","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","28.80",""
+"2014","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1.06",""
+"2014","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","61.32",""
+"2014","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","86.99",""
+"2014","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2014","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2014","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2015","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","468.53",""
+"2015","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","55.68",""
+"2015","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","52.66",""
+"2015","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","438.41",""
+"2015","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","348.05",""
+"2015","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","378.90",""
+"2015","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","321.79",""
+"2015","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","99.35",""
+"2015","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","25.98",""
+"2015","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","11.25",""
+"2015","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","67.26",""
+"2015","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","52.28",""
+"2015","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","111.45",""
+"2015","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","177.69",""
+"2015","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","86.40",""
+"2015","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","830.43",""
+"2015","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","61.16",""
+"2015","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","35.71",""
+"2015","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","82.03",""
+"2015","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","385.72",""
+"2015","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","144.76",""
+"2015","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","51.07",""
+"2015","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","21.28",""
+"2015","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","84.20",""
+"2015","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","32.28",""
+"2015","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","428.25",""
+"2015","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","990.61",""
+"2015","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","45.90",""
+"2015","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","660.41",""
+"2015","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","291.46",""
+"2015","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","571.25",""
+"2015","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","738.64",""
+"2015","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","805.15",""
+"2015","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,045.54",""
+"2015","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","29.58",""
+"2015","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","0.82",""
+"2015","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","80.74",""
+"2015","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","80.20",""
+"2015","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2015","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2015","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2016","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","485.98",""
+"2016","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","66.23",""
+"2016","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","52.75",""
+"2016","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","414.96",""
+"2016","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","368.23",""
+"2016","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","429.58",""
+"2016","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","339.27",""
+"2016","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","102.80",""
+"2016","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","26.80",""
+"2016","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","336.36",""
+"2016","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","67.72",""
+"2016","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","58.00",""
+"2016","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","105.27",""
+"2016","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","135.25",""
+"2016","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","79.21",""
+"2016","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","690.85",""
+"2016","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","58.57",""
+"2016","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","48.18",""
+"2016","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","74.78",""
+"2016","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","416.97",""
+"2016","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","159.21",""
+"2016","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","55.56",""
+"2016","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","20.26",""
+"2016","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","69.62",""
+"2016","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","27.51",""
+"2016","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","457.80",""
+"2016","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","949.62",""
+"2016","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","42.22",""
+"2016","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","605.01",""
+"2016","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","295.79",""
+"2016","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","555.14",""
+"2016","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,185.48",""
+"2016","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","694.41",""
+"2016","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","999.96",""
+"2016","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","33.11",""
+"2016","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1.50",""
+"2016","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","113.26",""
+"2016","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","99.20",""
+"2016","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2016","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2016","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","33.08",""
+"2017","Belgium","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","506.65",""
+"2017","Bulgaria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","70.25",""
+"2017","Czechia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","52.93",""
+"2017","Denmark","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","481.56",""
+"2017","Germany (until 1990 former territory of the FRG)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","400.60",""
+"2017","Estonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","441.46",""
+"2017","Ireland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","351.58",""
+"2017","Greece","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","118.82",""
+"2017","Spain","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","27.85",""
+"2017","France","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","344.77",""
+"2017","Croatia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2017","Italy","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","63.28",""
+"2017","Cyprus","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","111.02",""
+"2017","Latvia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","153.27",""
+"2017","Lithuania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","92.07",""
+"2017","Luxembourg","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","454.23",""
+"2017","Hungary","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","65.96",""
+"2017","Malta","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","67.35",""
+"2017","Netherlands","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","70.11",""
+"2017","Austria","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2017","Poland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","170.26",""
+"2017","Portugal","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","62.86",""
+"2017","Romania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","25.24",""
+"2017","Slovenia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","78.61",""
+"2017","Slovakia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","27.23",""
+"2017","Finland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","505.61",""
+"2017","Sweden","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","1,027.08",""
+"2017","England and Wales","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","44.43",""
+"2017","Scotland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","596.43",""
+"2017","Northern Ireland (UK)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","336.11",""
+"2017","Iceland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","641.05",""
+"2017","Liechtenstein","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2017","Norway","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","638.70",""
+"2017","Switzerland","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","951.05",""
+"2017","Montenegro","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","37.12",""
+"2017","North Macedonia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2017","Albania","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","72.55",""
+"2017","Serbia","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","119.41",""
+"2017","Turkey","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2017","Bosnia and Herzegovina","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants",":",""
+"2017","Kosovo (under United Nations Security Council Resolution 1244/99)","Unlawful acts involving controlled drugs or precursors","Per hundred thousand inhabitants","74.46",""
diff --git a/your-project/Week 4 - Project/crim_off_cat_Label.csv b/your-project/Week 4 - Project/crim_off_cat_Label.csv
new file mode 100644
index 0000000..75d1faa
--- /dev/null
+++ b/your-project/Week 4 - Project/crim_off_cat_Label.csv	
@@ -0,0 +1,87 @@
+"DATASET: Recorded offences by offence category - police data [crim_off_cat]"
+
+"LAST UPDATE: 16.07.19 18:06:10"
+
+"EXTRACTION DATE: 12.09.19 12:28:20"
+
+"SOURCE OF DATA: Eurostat"
+
+"TIME"
+"2008"
+"2009"
+"2010"
+"2011"
+"2012"
+"2013"
+"2014"
+"2015"
+"2016"
+"2017"
+
+"GEO"
+"Belgium"
+"Bulgaria"
+"Czechia"
+"Denmark"
+"Germany (until 1990 former territory of the FRG)"
+"Estonia"
+"Ireland"
+"Greece"
+"Spain"
+"France"
+"Croatia"
+"Italy"
+"Cyprus"
+"Latvia"
+"Lithuania"
+"Luxembourg"
+"Hungary"
+"Malta"
+"Netherlands"
+"Austria"
+"Poland"
+"Portugal"
+"Romania"
+"Slovenia"
+"Slovakia"
+"Finland"
+"Sweden"
+"England and Wales"
+"Scotland"
+"Northern Ireland (UK)"
+"Iceland"
+"Liechtenstein"
+"Norway"
+"Switzerland"
+"Montenegro"
+"North Macedonia"
+"Albania"
+"Serbia"
+"Turkey"
+"Bosnia and Herzegovina"
+"Kosovo (under United Nations Security Council Resolution 1244/99)"
+
+"ICCS"
+"Unlawful acts involving controlled drugs or precursors"
+
+"UNIT"
+"Per hundred thousand inhabitants"
+
+"No footnotes available"
+
+"Available flags:"
+"b","break in time series"
+"c","confidential"
+"d","definition differs, see metadata"
+"e","estimated"
+"f","forecast"
+"n","not significant"
+"p","provisional"
+"r","revised"
+"s","Eurostat estimate"
+"u","low reliability"
+"z","not applicable"
+
+"Special value:"
+":","not available"
+
diff --git a/your-project/Week 4 - Project/drug_crimes_vs_deaths.png b/your-project/Week 4 - Project/drug_crimes_vs_deaths.png
new file mode 100644
index 0000000..6f7896b
Binary files /dev/null and b/your-project/Week 4 - Project/drug_crimes_vs_deaths.png differ
diff --git a/your-project/Week 4 - Project/drug_deaths_vs_crimes.png b/your-project/Week 4 - Project/drug_deaths_vs_crimes.png
new file mode 100644
index 0000000..76c33cf
Binary files /dev/null and b/your-project/Week 4 - Project/drug_deaths_vs_crimes.png differ
diff --git a/your-project/Week 4 - Project/drugs2011-16.xls b/your-project/Week 4 - Project/drugs2011-16.xls
new file mode 100644
index 0000000..959b8a1
Binary files /dev/null and b/your-project/Week 4 - Project/drugs2011-16.xls differ
diff --git a/your-project/Week 4 - Project/hlth_cd_asdr/hlth_cd_asdr2_1_Data.csv b/your-project/Week 4 - Project/hlth_cd_asdr/hlth_cd_asdr2_1_Data.csv
new file mode 100644
index 0000000..1182000
--- /dev/null
+++ b/your-project/Week 4 - Project/hlth_cd_asdr/hlth_cd_asdr2_1_Data.csv	
@@ -0,0 +1,1891 @@
+"TIME","GEO","UNIT","SEX","AGE","ICD10","Value","Flag and Footnotes"
+"2011","European Union - 28 countries","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,026.73","d"
+"2011","European Union - 28 countries","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","224.52",""
+"2011","European Union - 28 countries","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,338.42","d"
+"2011","European Union - 28 countries","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,277.89","d"
+"2011","European Union - 28 countries","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","303.45",""
+"2011","European Union - 28 countries","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,300.58","d"
+"2011","European Union - 28 countries","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","837.99","d"
+"2011","European Union - 28 countries","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","148.28",""
+"2011","European Union - 28 countries","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,685.27","d"
+"2011","Belgium","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,023.02",""
+"2011","Belgium","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","211.37",""
+"2011","Belgium","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,373.72",""
+"2011","Belgium","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,284.61",""
+"2011","Belgium","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","267.7",""
+"2011","Belgium","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,482.61",""
+"2011","Belgium","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","840.11",""
+"2011","Belgium","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","155.32",""
+"2011","Belgium","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,667.06",""
+"2011","Bulgaria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,689.88",""
+"2011","Bulgaria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","385.19",""
+"2011","Bulgaria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,075.92",""
+"2011","Bulgaria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,076.46",""
+"2011","Bulgaria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","548.86",""
+"2011","Bulgaria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,382.7",""
+"2011","Bulgaria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,394.04",""
+"2011","Bulgaria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","232.13",""
+"2011","Bulgaria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,190.6",""
+"2011","Czechia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,331.4",""
+"2011","Czechia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","267.08",""
+"2011","Czechia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,725.14",""
+"2011","Czechia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,680.05",""
+"2011","Czechia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","373.91",""
+"2011","Czechia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,072.04",""
+"2011","Czechia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,089.62",""
+"2011","Czechia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","163.72",""
+"2011","Czechia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,911.93",""
+"2011","Denmark","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,111.31",""
+"2011","Denmark","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","211.1",""
+"2011","Denmark","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,827.54",""
+"2011","Denmark","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,341.83",""
+"2011","Denmark","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","259.35",""
+"2011","Denmark","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,810.53",""
+"2011","Denmark","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","945.31",""
+"2011","Denmark","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","162.79",""
+"2011","Denmark","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,175.71",""
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,004.77","d"
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","205.04",""
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,306.19","d"
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,204.94","d"
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","266.58",""
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,078.71","d"
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","842.9","d"
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.73",""
+"2011","Germany (until 1990 former territory of the FRG)","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,729.2","d"
+"2011","Estonia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,326.09",""
+"2011","Estonia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","353.02",""
+"2011","Estonia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,343.13",""
+"2011","Estonia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,882.65",""
+"2011","Estonia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","551.73",""
+"2011","Estonia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,377",""
+"2011","Estonia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,008.38",""
+"2011","Estonia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","182.31",""
+"2011","Estonia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,418.58",""
+"2011","Ireland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,030.07",""
+"2011","Ireland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.71",""
+"2011","Ireland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,519.88",""
+"2011","Ireland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,250.95",""
+"2011","Ireland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","229.79",""
+"2011","Ireland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,466.5",""
+"2011","Ireland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","868.29",""
+"2011","Ireland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.71",""
+"2011","Ireland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,876.02",""
+"2011","Greece","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,022.72",""
+"2011","Greece","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","193.15",""
+"2011","Greece","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,447.37",""
+"2011","Greece","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,235.15",""
+"2011","Greece","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","272.66",""
+"2011","Greece","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,208.52",""
+"2011","Greece","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","845.96",""
+"2011","Greece","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","117.34",""
+"2011","Greece","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,853.86",""
+"2011","Spain","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","889.55",""
+"2011","Spain","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","168.26",""
+"2011","Spain","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,867.17",""
+"2011","Spain","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,155.58",""
+"2011","Spain","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","232.46",""
+"2011","Spain","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,966.44",""
+"2011","Spain","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","693.42",""
+"2011","Spain","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","105.54",""
+"2011","Spain","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,120.31",""
+"2011","France","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","870.97",""
+"2011","France","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","210.7",""
+"2011","France","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,596.71",""
+"2011","France","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,158.04",""
+"2011","France","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","291.58",""
+"2011","France","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,734.93",""
+"2011","France","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","669.23",""
+"2011","France","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","133.59",""
+"2011","France","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,880.48",""
+"2011","Croatia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,451.42",""
+"2011","Croatia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","284.03",""
+"2011","Croatia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,270.64",""
+"2011","Croatia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,815.38",""
+"2011","Croatia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","407.43",""
+"2011","Croatia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,627.68",""
+"2011","Croatia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,198.91",""
+"2011","Croatia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","167.08",""
+"2011","Croatia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,458.5",""
+"2011","Italy","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","917.39",""
+"2011","Italy","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","153.87",""
+"2011","Italy","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,069.38",""
+"2011","Italy","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,169.74",""
+"2011","Italy","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","199.49",""
+"2011","Italy","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,175.15",""
+"2011","Italy","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","746.99",""
+"2011","Italy","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","110.23",""
+"2011","Italy","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,375.66",""
+"2011","Cyprus","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,024.77",""
+"2011","Cyprus","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","133.46",""
+"2011","Cyprus","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,704.29",""
+"2011","Cyprus","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,160.28",""
+"2011","Cyprus","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","175.94",""
+"2011","Cyprus","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,223.85",""
+"2011","Cyprus","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","909.11",""
+"2011","Cyprus","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","92.99",""
+"2011","Cyprus","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,278.23",""
+"2011","Latvia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,576.89",""
+"2011","Latvia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","457.37",""
+"2011","Latvia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,198.47",""
+"2011","Latvia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,204.28",""
+"2011","Latvia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","702.06",""
+"2011","Latvia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,405.73",""
+"2011","Latvia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,215.8",""
+"2011","Latvia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","255.19",""
+"2011","Latvia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,181.36",""
+"2011","Lithuania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,522.52",""
+"2011","Lithuania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","472.54",""
+"2011","Lithuania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,857.06",""
+"2011","Lithuania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,138.39",""
+"2011","Lithuania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","743.9",""
+"2011","Lithuania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,895.16",""
+"2011","Lithuania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,142.83",""
+"2011","Lithuania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","245.4",""
+"2011","Lithuania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,847.63",""
+"2011","Luxembourg","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,029.86",""
+"2011","Luxembourg","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","189.12",""
+"2011","Luxembourg","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,500.63",""
+"2011","Luxembourg","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,347.63",""
+"2011","Luxembourg","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","233.94",""
+"2011","Luxembourg","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,945.17",""
+"2011","Luxembourg","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","850.56",""
+"2011","Luxembourg","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","142.7",""
+"2011","Luxembourg","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,772.77",""
+"2011","Hungary","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,495.13","d"
+"2011","Hungary","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","409.86",""
+"2011","Hungary","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,975.34","d"
+"2011","Hungary","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,939.45","d"
+"2011","Hungary","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","588.54",""
+"2011","Hungary","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,516.31","d"
+"2011","Hungary","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,199.82","d"
+"2011","Hungary","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","252.45",""
+"2011","Hungary","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,110.74","d"
+"2011","Malta","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,036.18",""
+"2011","Malta","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","164.85",""
+"2011","Malta","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,633.22",""
+"2011","Malta","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,260.47",""
+"2011","Malta","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","206.63",""
+"2011","Malta","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,610.96",""
+"2011","Malta","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","872.15",""
+"2011","Malta","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","123.01",""
+"2011","Malta","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,964.75",""
+"2011","Netherlands","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,001.69",""
+"2011","Netherlands","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","171.55",""
+"2011","Netherlands","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,428.7",""
+"2011","Netherlands","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,217.69",""
+"2011","Netherlands","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","195.83",""
+"2011","Netherlands","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,436.14",""
+"2011","Netherlands","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","858.04",""
+"2011","Netherlands","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","147.02",""
+"2011","Netherlands","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,793.25",""
+"2011","Austria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","994.6",""
+"2011","Austria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.72",""
+"2011","Austria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,296.65",""
+"2011","Austria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,249.91",""
+"2011","Austria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","259.75",""
+"2011","Austria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,337.49",""
+"2011","Austria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","817.76",""
+"2011","Austria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","131.73",""
+"2011","Austria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,649.84",""
+"2011","Poland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,325.61",""
+"2011","Poland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","347.08",""
+"2011","Poland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,365.19",""
+"2011","Poland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,761.13",""
+"2011","Poland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","509.27",""
+"2011","Poland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,929.03",""
+"2011","Poland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,028.23",""
+"2011","Poland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.89",""
+"2011","Poland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,468.46",""
+"2011","Portugal","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,014.47",""
+"2011","Portugal","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","212.19",""
+"2011","Portugal","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,326.48",""
+"2011","Portugal","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,302.97",""
+"2011","Portugal","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","305.59",""
+"2011","Portugal","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,420.37",""
+"2011","Portugal","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","805.59",""
+"2011","Portugal","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","126.21",""
+"2011","Portugal","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,610.18",""
+"2011","Romania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,600.13",""
+"2011","Romania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","397.83",""
+"2011","Romania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,563.47",""
+"2011","Romania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,989.14",""
+"2011","Romania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","571.36",""
+"2011","Romania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,841.99",""
+"2011","Romania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,306.74",""
+"2011","Romania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","235.43",""
+"2011","Romania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,729.34",""
+"2011","Slovenia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,099.64",""
+"2011","Slovenia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","219.44",""
+"2011","Slovenia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,733.26",""
+"2011","Slovenia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,440.33",""
+"2011","Slovenia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","299.59",""
+"2011","Slovenia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,149.53",""
+"2011","Slovenia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","880.06",""
+"2011","Slovenia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","137.39",""
+"2011","Slovenia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,945.95",""
+"2011","Slovakia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,471.24",""
+"2011","Slovakia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","330.11",""
+"2011","Slovakia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,182.08",""
+"2011","Slovakia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,881.69",""
+"2011","Slovakia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","484.09",""
+"2011","Slovakia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,651.27",""
+"2011","Slovakia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,188.85",""
+"2011","Slovakia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","186.89",""
+"2011","Slovakia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,325.12",""
+"2011","Finland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,028.94",""
+"2011","Finland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","215.71",""
+"2011","Finland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,386.08",""
+"2011","Finland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,338.42",""
+"2011","Finland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","298.39",""
+"2011","Finland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,631.89",""
+"2011","Finland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","815.19",""
+"2011","Finland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","133.37",""
+"2011","Finland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,629.9",""
+"2011","Sweden","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","966.35",""
+"2011","Sweden","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","152.11",""
+"2011","Sweden","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,327.68",""
+"2011","Sweden","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,169.84",""
+"2011","Sweden","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","185.17",""
+"2011","Sweden","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,234.75",""
+"2011","Sweden","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","818.33",""
+"2011","Sweden","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","118.53",""
+"2011","Sweden","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,707.26",""
+"2011","United Kingdom","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","978.85","d"
+"2011","United Kingdom","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","188.98",""
+"2011","United Kingdom","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,239.59","d"
+"2011","United Kingdom","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,145.76","d"
+"2011","United Kingdom","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","230.47",""
+"2011","United Kingdom","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,924.28","d"
+"2011","United Kingdom","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","848.53","d"
+"2011","United Kingdom","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","148.35",""
+"2011","United Kingdom","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,739.03","d"
+"2011","Iceland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","933.23",""
+"2011","Iceland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.46",""
+"2011","Iceland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,210.09",""
+"2011","Iceland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,079.08",""
+"2011","Iceland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","156.92",""
+"2011","Iceland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,885.95",""
+"2011","Iceland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","813.59",""
+"2011","Iceland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","120.81",""
+"2011","Iceland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,673.51",""
+"2011","Liechtenstein","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","945.45",""
+"2011","Liechtenstein","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.03",""
+"2011","Liechtenstein","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,245.64",""
+"2011","Liechtenstein","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,156.39",""
+"2011","Liechtenstein","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","174.52",""
+"2011","Liechtenstein","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,209.75",""
+"2011","Liechtenstein","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","787.62",""
+"2011","Liechtenstein","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","118.76",""
+"2011","Liechtenstein","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,548.8",""
+"2011","Norway","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","996.31",""
+"2011","Norway","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","172.13",""
+"2011","Norway","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,398.68",""
+"2011","Norway","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,228.68",""
+"2011","Norway","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","210.45",""
+"2011","Norway","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,432.15",""
+"2011","Norway","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","829.24",""
+"2011","Norway","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","132.33",""
+"2011","Norway","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,706.26",""
+"2011","Switzerland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","872.61",""
+"2011","Switzerland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.71",""
+"2011","Switzerland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,869.28",""
+"2011","Switzerland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,087.2",""
+"2011","Switzerland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.54",""
+"2011","Switzerland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,813.58",""
+"2011","Switzerland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","724.09",""
+"2011","Switzerland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","108.81",""
+"2011","Switzerland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,264.06",""
+"2011","Serbia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,786.88",""
+"2011","Serbia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","349.47",""
+"2011","Serbia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,720.79",""
+"2011","Serbia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,094.01",""
+"2011","Serbia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","474.04",""
+"2011","Serbia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,781.56",""
+"2011","Serbia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,549.47",""
+"2011","Serbia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","231.95",""
+"2011","Serbia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,988.45",""
+"2011","Turkey","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,075.76","d"
+"2011","Turkey","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","210.43",""
+"2011","Turkey","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,647.99","d"
+"2011","Turkey","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,325.05","d"
+"2011","Turkey","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","281.58",""
+"2011","Turkey","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,632.69","d"
+"2011","Turkey","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","887.42","d"
+"2011","Turkey","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","141.3",""
+"2011","Turkey","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,967.57","d"
+"2012","European Union - 28 countries","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,035.13","d"
+"2012","European Union - 28 countries","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","220.16",""
+"2012","European Union - 28 countries","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,399.5","d"
+"2012","European Union - 28 countries","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,281.03","d"
+"2012","European Union - 28 countries","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","297.46",""
+"2012","European Union - 28 countries","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,341.41","d"
+"2012","European Union - 28 countries","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","848.99","d"
+"2012","European Union - 28 countries","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.54",""
+"2012","European Union - 28 countries","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,753","d"
+"2012","Belgium","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,051.21",""
+"2012","Belgium","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","208.72",""
+"2012","Belgium","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,529.2",""
+"2012","Belgium","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,322.25",""
+"2012","Belgium","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","268.32",""
+"2012","Belgium","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,673.1",""
+"2012","Belgium","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","860.46",""
+"2012","Belgium","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","149.38",""
+"2012","Belgium","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,795.98",""
+"2012","Bulgaria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,709.05",""
+"2012","Bulgaria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","378.57",""
+"2012","Bulgaria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,201.54",""
+"2012","Bulgaria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,103.81",""
+"2012","Bulgaria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","541.76",""
+"2012","Bulgaria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,552.3",""
+"2012","Bulgaria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,410.57",""
+"2012","Bulgaria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","225.42",""
+"2012","Bulgaria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,303.09",""
+"2012","Czechia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,323.34",""
+"2012","Czechia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","259.04",""
+"2012","Czechia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,716.96",""
+"2012","Czechia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,656.25",""
+"2012","Czechia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","359.29",""
+"2012","Czechia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,010.37",""
+"2012","Czechia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,088.39",""
+"2012","Czechia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","161.71",""
+"2012","Czechia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,913.89",""
+"2012","Denmark","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,087.86",""
+"2012","Denmark","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","203",""
+"2012","Denmark","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,740.75",""
+"2012","Denmark","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,316.32",""
+"2012","Denmark","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","248.55",""
+"2012","Denmark","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,724.27",""
+"2012","Denmark","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","926.58",""
+"2012","Denmark","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","157.23",""
+"2012","Denmark","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,102.65",""
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,003.25","d"
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","199.01",""
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,323.32","d"
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,196.79","d"
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","259.69",""
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,065.34","d"
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","844.11","d"
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","138.52",""
+"2012","Germany (until 1990 former territory of the FRG)","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,756.92","d"
+"2012","Estonia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,317.07",""
+"2012","Estonia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","354.1",""
+"2012","Estonia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,292.39",""
+"2012","Estonia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,897.11",""
+"2012","Estonia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","552.45",""
+"2012","Estonia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,448.14",""
+"2012","Estonia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","989.55",""
+"2012","Estonia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","182.03",""
+"2012","Estonia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,323.15",""
+"2012","Ireland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,039.49",""
+"2012","Ireland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","180.21",""
+"2012","Ireland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,586.77",""
+"2012","Ireland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,273.06",""
+"2012","Ireland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","223.68",""
+"2012","Ireland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,605.12",""
+"2012","Ireland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","870.51",""
+"2012","Ireland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.96",""
+"2012","Ireland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,898.76",""
+"2012","Greece","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,042.72",""
+"2012","Greece","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","193.03",""
+"2012","Greece","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,550.4",""
+"2012","Greece","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,243.72",""
+"2012","Greece","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","273.45",""
+"2012","Greece","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,249.2",""
+"2012","Greece","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","872.3",""
+"2012","Greece","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","116.91",""
+"2012","Greece","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,990.69",""
+"2012","Spain","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","898.41",""
+"2012","Spain","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","164.69",""
+"2012","Spain","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,927.35",""
+"2012","Spain","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,162.19",""
+"2012","Spain","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","227.72",""
+"2012","Spain","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,019.87",""
+"2012","Spain","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","702.85",""
+"2012","Spain","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","103.08",""
+"2012","Spain","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,178.82",""
+"2012","France","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","889.11",""
+"2012","France","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","207.64",""
+"2012","France","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,702.38",""
+"2012","France","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,171.88",""
+"2012","France","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","287.02",""
+"2012","France","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,824.76",""
+"2012","France","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","689.77",""
+"2012","France","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","132.16",""
+"2012","France","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,991.68",""
+"2012","Croatia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,371.21","d"
+"2012","Croatia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","277.55",""
+"2012","Croatia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,886.05","d"
+"2012","Croatia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,751.88","d"
+"2012","Croatia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","400.19",""
+"2012","Croatia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,331.91","d"
+"2012","Croatia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,106.81","d"
+"2012","Croatia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","160.71",""
+"2012","Croatia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,012.49","d"
+"2012","Italy","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","922.61",""
+"2012","Italy","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","151.79",""
+"2012","Italy","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,104.72",""
+"2012","Italy","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,167.48",""
+"2012","Italy","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","196.54",""
+"2012","Italy","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,175.7",""
+"2012","Italy","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","754.92",""
+"2012","Italy","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","109.08",""
+"2012","Italy","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,421.11",""
+"2012","Cyprus","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,055.78",""
+"2012","Cyprus","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.45",""
+"2012","Cyprus","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,850.95",""
+"2012","Cyprus","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,221.25",""
+"2012","Cyprus","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","185.13",""
+"2012","Cyprus","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,498.54",""
+"2012","Cyprus","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","916.04",""
+"2012","Cyprus","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","90.38",""
+"2012","Cyprus","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,324.54",""
+"2012","Latvia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,591.06",""
+"2012","Latvia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","448.89",""
+"2012","Latvia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,306.16",""
+"2012","Latvia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,206.35",""
+"2012","Latvia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","698.99",""
+"2012","Latvia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,429.06",""
+"2012","Latvia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,234.75",""
+"2012","Latvia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","240.84",""
+"2012","Latvia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,337.79",""
+"2012","Lithuania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,506.04",""
+"2012","Lithuania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","457.75",""
+"2012","Lithuania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,833.58",""
+"2012","Lithuania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,107.05",""
+"2012","Lithuania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","725.85",""
+"2012","Lithuania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,808.9",""
+"2012","Lithuania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,132.07",""
+"2012","Lithuania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","232.43",""
+"2012","Lithuania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,845.99",""
+"2012","Luxembourg","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","983.19",""
+"2012","Luxembourg","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","176.17",""
+"2012","Luxembourg","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,314.72",""
+"2012","Luxembourg","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,178.87",""
+"2012","Luxembourg","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","226.58",""
+"2012","Luxembourg","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,110.12",""
+"2012","Luxembourg","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","829.34",""
+"2012","Luxembourg","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","123.82",""
+"2012","Luxembourg","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,741.86",""
+"2012","Hungary","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,502.88","d"
+"2012","Hungary","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","394.08",""
+"2012","Hungary","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,080.25","d"
+"2012","Hungary","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,939.73","d"
+"2012","Hungary","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","561.33",""
+"2012","Hungary","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,630.04","d"
+"2012","Hungary","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,215.09","d"
+"2012","Hungary","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","245.43",""
+"2012","Hungary","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,218.05","d"
+"2012","Malta","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,059.97",""
+"2012","Malta","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","174.75",""
+"2012","Malta","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,714.33",""
+"2012","Malta","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,328.43",""
+"2012","Malta","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","215.27",""
+"2012","Malta","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,923.79",""
+"2012","Malta","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","880.87",""
+"2012","Malta","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","133.83",""
+"2012","Malta","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,964.81",""
+"2012","Netherlands","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,017.48",""
+"2012","Netherlands","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","171.48",""
+"2012","Netherlands","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,509.93",""
+"2012","Netherlands","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,237.16",""
+"2012","Netherlands","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","197.19",""
+"2012","Netherlands","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,530.34",""
+"2012","Netherlands","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","869.56",""
+"2012","Netherlands","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.53",""
+"2012","Netherlands","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,858.51",""
+"2012","Austria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,014.47",""
+"2012","Austria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","188.16",""
+"2012","Austria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,425.68",""
+"2012","Austria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,257.45",""
+"2012","Austria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","250.03",""
+"2012","Austria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,416.28",""
+"2012","Austria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","844.92",""
+"2012","Austria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","128.25",""
+"2012","Austria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,803.47",""
+"2012","Poland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,328.29",""
+"2012","Poland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","345.6",""
+"2012","Poland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,385.01",""
+"2012","Poland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,766.94",""
+"2012","Poland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","506.14",""
+"2012","Poland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,971.79",""
+"2012","Poland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,030.52",""
+"2012","Poland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.81",""
+"2012","Poland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,480.5",""
+"2012","Portugal","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,052.09",""
+"2012","Portugal","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","205.22",""
+"2012","Portugal","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,548.14",""
+"2012","Portugal","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,350",""
+"2012","Portugal","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","294.7",""
+"2012","Portugal","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,706.49",""
+"2012","Portugal","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","839.03",""
+"2012","Portugal","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","123.11",""
+"2012","Portugal","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,794.47",""
+"2012","Romania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,601.82",""
+"2012","Romania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","386.69",""
+"2012","Romania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,618.12",""
+"2012","Romania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,985.6",""
+"2012","Romania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","554.34",""
+"2012","Romania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,894.14",""
+"2012","Romania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,312.71",""
+"2012","Romania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","229.94",""
+"2012","Romania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,782.61",""
+"2012","Slovenia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,090.86",""
+"2012","Slovenia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","215.31",""
+"2012","Slovenia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,705.3",""
+"2012","Slovenia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,409.92",""
+"2012","Slovenia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","294.02",""
+"2012","Slovenia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,016.56",""
+"2012","Slovenia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","884.04",""
+"2012","Slovenia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","134.71",""
+"2012","Slovenia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,977.46",""
+"2012","Slovakia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,461.04",""
+"2012","Slovakia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","322.22",""
+"2012","Slovakia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,162.33",""
+"2012","Slovakia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,862.66",""
+"2012","Slovakia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","466.8",""
+"2012","Slovakia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,625.04",""
+"2012","Slovakia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,186.16",""
+"2012","Slovakia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","186.8",""
+"2012","Slovakia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,311.71",""
+"2012","Finland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,026.98",""
+"2012","Finland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","207.48",""
+"2012","Finland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,410.02",""
+"2012","Finland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,319.31",""
+"2012","Finland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","282.36",""
+"2012","Finland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,600.06",""
+"2012","Finland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","824.03",""
+"2012","Finland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","132.89",""
+"2012","Finland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,677.2",""
+"2012","Sweden","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","975.89",""
+"2012","Sweden","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","149.14",""
+"2012","Sweden","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,388.86",""
+"2012","Sweden","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,173.27",""
+"2012","Sweden","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","180.21",""
+"2012","Sweden","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,272.83",""
+"2012","Sweden","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","834.21",""
+"2012","Sweden","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","117.59",""
+"2012","Sweden","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,792.53",""
+"2012","United Kingdom","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","998.04","d"
+"2012","United Kingdom","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.92",""
+"2012","United Kingdom","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,354.81","d"
+"2012","United Kingdom","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,156.52","d"
+"2012","United Kingdom","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","224.19",""
+"2012","United Kingdom","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,005.38","d"
+"2012","United Kingdom","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","872.79","d"
+"2012","United Kingdom","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.52",""
+"2012","United Kingdom","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,870.97","d"
+"2012","Iceland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","880.54",""
+"2012","Iceland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.21",""
+"2012","Iceland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,924.41",""
+"2012","Iceland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","974.79",""
+"2012","Iceland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","174.76",""
+"2012","Iceland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,277.44",""
+"2012","Iceland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","804.78",""
+"2012","Iceland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","111.11",""
+"2012","Iceland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,668.38",""
+"2012","Liechtenstein","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","847.32",""
+"2012","Liechtenstein","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","144.65",""
+"2012","Liechtenstein","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,748.11",""
+"2012","Liechtenstein","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,056.24",""
+"2012","Liechtenstein","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","156.99",""
+"2012","Liechtenstein","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,768.52",""
+"2012","Liechtenstein","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","706.05",""
+"2012","Liechtenstein","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","131.45",""
+"2012","Liechtenstein","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,078.12",""
+"2012","Norway","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","999.09",""
+"2012","Norway","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","164.43",""
+"2012","Norway","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,444.77",""
+"2012","Norway","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,211.33",""
+"2012","Norway","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","203.2",""
+"2012","Norway","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,373.09",""
+"2012","Norway","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","845.94",""
+"2012","Norway","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","123.67",""
+"2012","Norway","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,827.62",""
+"2012","Switzerland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","881.75",""
+"2012","Switzerland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.37",""
+"2012","Switzerland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,917.53",""
+"2012","Switzerland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,086.66",""
+"2012","Switzerland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","183.86",""
+"2012","Switzerland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,813.57",""
+"2012","Switzerland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","739.38",""
+"2012","Switzerland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","108.79",""
+"2012","Switzerland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,342.57",""
+"2012","Serbia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,745.67",""
+"2012","Serbia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","341.65",""
+"2012","Serbia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,541.76",""
+"2012","Serbia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,052.17",""
+"2012","Serbia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","460.95",""
+"2012","Serbia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,621.05",""
+"2012","Serbia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,509.13",""
+"2012","Serbia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","229.16",""
+"2012","Serbia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,793.11",""
+"2012","Turkey","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","839.38","d"
+"2012","Turkey","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","205.98",""
+"2012","Turkey","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,454.19","d"
+"2012","Turkey","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,033.07","d"
+"2012","Turkey","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","277.42",""
+"2012","Turkey","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,152.53","d"
+"2012","Turkey","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","677.86","d"
+"2012","Turkey","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.21",""
+"2012","Turkey","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,913.89","d"
+"2013","European Union - 28 countries","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,020.93","d"
+"2013","European Union - 28 countries","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","215.33",""
+"2013","European Union - 28 countries","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,346.59","d"
+"2013","European Union - 28 countries","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,265.46","d"
+"2013","European Union - 28 countries","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","289.96",""
+"2013","European Union - 28 countries","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,292.5","d"
+"2013","European Union - 28 countries","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","836.39","d"
+"2013","European Union - 28 countries","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.31",""
+"2013","European Union - 28 countries","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,697.55","d"
+"2013","Belgium","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,034.88",""
+"2013","Belgium","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","202.84",""
+"2013","Belgium","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,469.7",""
+"2013","Belgium","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,298.2",""
+"2013","Belgium","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","255.71",""
+"2013","Belgium","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,601.8",""
+"2013","Belgium","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","849.58",""
+"2013","Belgium","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","150.24",""
+"2013","Belgium","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,736.58",""
+"2013","Bulgaria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,602.3",""
+"2013","Bulgaria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","363.85",""
+"2013","Bulgaria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,714.88",""
+"2013","Bulgaria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,990.33",""
+"2013","Bulgaria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","522.93",""
+"2013","Bulgaria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,048.06",""
+"2013","Bulgaria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,307.15",""
+"2013","Bulgaria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","214.23",""
+"2013","Bulgaria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,818.95",""
+"2013","Czechia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,308.17",""
+"2013","Czechia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","249.83",""
+"2013","Czechia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,677.22",""
+"2013","Czechia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,644.31",""
+"2013","Czechia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","344.85",""
+"2013","Czechia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,008.74",""
+"2013","Czechia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,072.97",""
+"2013","Czechia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","157.32",""
+"2013","Czechia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,852.98",""
+"2013","Denmark","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,073.82",""
+"2013","Denmark","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","199.28",""
+"2013","Denmark","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,684.1",""
+"2013","Denmark","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,299.88",""
+"2013","Denmark","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","247.19",""
+"2013","Denmark","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,645.62",""
+"2013","Denmark","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","910.39",""
+"2013","Denmark","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","151.08",""
+"2013","Denmark","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,044.94",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,066.3",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","201.08",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,638.09",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,311.46",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","261.81",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,644.6",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","888.18",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","140.89",""
+"2013","Germany (until 1990 former territory of the FRG)","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,973.13",""
+"2013","Estonia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,283.74",""
+"2013","Estonia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","331.43",""
+"2013","Estonia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,215.09",""
+"2013","Estonia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,795.06",""
+"2013","Estonia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","506.01",""
+"2013","Estonia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,116.5",""
+"2013","Estonia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","986.01",""
+"2013","Estonia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","180.81",""
+"2013","Estonia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,310.05",""
+"2013","Ireland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,034.34",""
+"2013","Ireland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","173.03",""
+"2013","Ireland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,590.03",""
+"2013","Ireland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,247.79",""
+"2013","Ireland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","215.23",""
+"2013","Ireland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,510.43",""
+"2013","Ireland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","877.65",""
+"2013","Ireland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","131.22",""
+"2013","Ireland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,959.09",""
+"2013","Greece","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","975.51",""
+"2013","Greece","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","187.18",""
+"2013","Greece","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,229.87",""
+"2013","Greece","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,164.69",""
+"2013","Greece","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","264.63",""
+"2013","Greece","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,880.33",""
+"2013","Greece","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","814.34",""
+"2013","Greece","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","114.44",""
+"2013","Greece","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,703.65",""
+"2013","Spain","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","848.31",""
+"2013","Spain","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","159.69",""
+"2013","Spain","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,691.08",""
+"2013","Spain","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,095.84",""
+"2013","Spain","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","218.6",""
+"2013","Spain","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,717.26",""
+"2013","Spain","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","663.2",""
+"2013","Spain","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","102.22",""
+"2013","Spain","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,979.06",""
+"2013","France","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","867.11",""
+"2013","France","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","202.45",""
+"2013","France","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,610.94",""
+"2013","France","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,140.83",""
+"2013","France","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","278.71",""
+"2013","France","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,699.82",""
+"2013","France","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","672.58",""
+"2013","France","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","130.06",""
+"2013","France","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,912.18",""
+"2013","Croatia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,359.13",""
+"2013","Croatia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","267.65",""
+"2013","Croatia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,864.95",""
+"2013","Croatia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,729.72",""
+"2013","Croatia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","381.17",""
+"2013","Croatia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,296.81",""
+"2013","Croatia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,106.63",""
+"2013","Croatia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","159.49",""
+"2013","Croatia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,016.64",""
+"2013","Italy","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","878.27",""
+"2013","Italy","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.26",""
+"2013","Italy","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,904.28",""
+"2013","Italy","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,112.82",""
+"2013","Italy","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","187.27",""
+"2013","Italy","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,933.7",""
+"2013","Italy","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","717.7",""
+"2013","Italy","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","105.07",""
+"2013","Italy","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,246.73",""
+"2013","Cyprus","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","951.52",""
+"2013","Cyprus","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","129.2",""
+"2013","Cyprus","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,346.22",""
+"2013","Cyprus","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,140.4",""
+"2013","Cyprus","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","183.17",""
+"2013","Cyprus","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,092.04",""
+"2013","Cyprus","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","794.57",""
+"2013","Cyprus","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","77.97",""
+"2013","Cyprus","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,752.84",""
+"2013","Latvia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,548.98",""
+"2013","Latvia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","445.95",""
+"2013","Latvia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,102.55",""
+"2013","Latvia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,138.56",""
+"2013","Latvia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","683.27",""
+"2013","Latvia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,146.3",""
+"2013","Latvia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,208.02",""
+"2013","Latvia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","247.66",""
+"2013","Latvia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,172.57",""
+"2013","Lithuania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,510.91",""
+"2013","Lithuania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","456.39",""
+"2013","Lithuania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,864.17",""
+"2013","Lithuania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,128.32",""
+"2013","Lithuania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","718.93",""
+"2013","Lithuania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,946.59",""
+"2013","Lithuania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,135.15",""
+"2013","Lithuania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","234.14",""
+"2013","Lithuania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,854.69",""
+"2013","Luxembourg","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","941.98",""
+"2013","Luxembourg","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","179.76",""
+"2013","Luxembourg","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,088.58",""
+"2013","Luxembourg","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,118.33",""
+"2013","Luxembourg","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","221.21",""
+"2013","Luxembourg","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,821.83",""
+"2013","Luxembourg","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","798.99",""
+"2013","Luxembourg","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.74",""
+"2013","Luxembourg","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,532.88",""
+"2013","Hungary","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,482.81",""
+"2013","Hungary","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","374.35",""
+"2013","Hungary","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,058.73",""
+"2013","Hungary","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,903.41",""
+"2013","Hungary","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","527.67",""
+"2013","Hungary","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,582.74",""
+"2013","Hungary","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,208.06",""
+"2013","Hungary","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","237.93",""
+"2013","Hungary","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,212.97",""
+"2013","Malta","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","975.69",""
+"2013","Malta","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","148.55",""
+"2013","Malta","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,390.33",""
+"2013","Malta","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,196.81",""
+"2013","Malta","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.24",""
+"2013","Malta","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,335.64",""
+"2013","Malta","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","819.07",""
+"2013","Malta","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","102.36",""
+"2013","Malta","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,777.82",""
+"2013","Netherlands","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,003.42",""
+"2013","Netherlands","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","166.98",""
+"2013","Netherlands","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,456.39",""
+"2013","Netherlands","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,213.12",""
+"2013","Netherlands","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","192.56",""
+"2013","Netherlands","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,426.22",""
+"2013","Netherlands","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","859.2",""
+"2013","Netherlands","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","141.22",""
+"2013","Netherlands","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,823.13",""
+"2013","Austria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","997.8",""
+"2013","Austria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","183.65",""
+"2013","Austria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,358.81",""
+"2013","Austria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,242.37",""
+"2013","Austria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","243.8",""
+"2013","Austria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,364.68",""
+"2013","Austria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","826.4",""
+"2013","Austria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","125.21",""
+"2013","Austria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,721.06",""
+"2013","Poland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,308.14",""
+"2013","Poland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","334.68",""
+"2013","Poland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,326.79",""
+"2013","Poland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,729.13",""
+"2013","Poland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","487.71",""
+"2013","Poland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,853.94",""
+"2013","Poland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,019.54",""
+"2013","Poland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","190.67",""
+"2013","Poland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,441.28",""
+"2013","Portugal","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,024.85",""
+"2013","Portugal","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","202.84",""
+"2013","Portugal","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,418.26",""
+"2013","Portugal","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,323.51",""
+"2013","Portugal","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","294.34",""
+"2013","Portugal","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,572.11",""
+"2013","Portugal","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","812.15",""
+"2013","Portugal","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","119.14",""
+"2013","Portugal","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,673.03",""
+"2013","Romania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,520.58",""
+"2013","Romania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","373.23",""
+"2013","Romania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,257.12",""
+"2013","Romania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,889.26",""
+"2013","Romania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","532.06",""
+"2013","Romania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,492.04",""
+"2013","Romania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,241.89",""
+"2013","Romania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","224.12",""
+"2013","Romania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,443.49",""
+"2013","Slovenia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,072.03",""
+"2013","Slovenia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","211.79",""
+"2013","Slovenia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,623.26",""
+"2013","Slovenia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,385.44",""
+"2013","Slovenia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","289.72",""
+"2013","Slovenia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,908.8",""
+"2013","Slovenia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","858.84",""
+"2013","Slovenia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","131.77",""
+"2013","Slovenia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,860.33",""
+"2013","Slovakia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,417.98",""
+"2013","Slovakia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","313.96",""
+"2013","Slovakia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,975.62",""
+"2013","Slovakia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,824.04",""
+"2013","Slovakia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","452.7",""
+"2013","Slovakia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,485.24",""
+"2013","Slovakia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,143.18",""
+"2013","Slovakia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.23",""
+"2013","Slovakia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,101.94",""
+"2013","Finland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","999.37",""
+"2013","Finland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","200.58",""
+"2013","Finland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,296.96",""
+"2013","Finland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,283.03",""
+"2013","Finland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","274.41",""
+"2013","Finland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,446.85",""
+"2013","Finland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","799.79",""
+"2013","Finland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","126.8",""
+"2013","Finland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,578",""
+"2013","Sweden","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","949.94",""
+"2013","Sweden","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","149.48",""
+"2013","Sweden","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,254.43",""
+"2013","Sweden","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,135.75",""
+"2013","Sweden","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","181.19",""
+"2013","Sweden","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,076.37",""
+"2013","Sweden","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","813.88",""
+"2013","Sweden","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","117.19",""
+"2013","Sweden","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,689.97",""
+"2013","United Kingdom","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","991.78",""
+"2013","United Kingdom","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","183.92",""
+"2013","United Kingdom","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,326.76",""
+"2013","United Kingdom","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,169.35",""
+"2013","United Kingdom","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","225.21",""
+"2013","United Kingdom","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,066.96",""
+"2013","United Kingdom","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","856.26",""
+"2013","United Kingdom","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.59",""
+"2013","United Kingdom","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,798.3",""
+"2013","Iceland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","943.31",""
+"2013","Iceland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","142.72",""
+"2013","Iceland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,248.35",""
+"2013","Iceland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,089.78",""
+"2013","Iceland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","164.9",""
+"2013","Iceland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,907.87",""
+"2013","Iceland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","825.89",""
+"2013","Iceland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","119.34",""
+"2013","Iceland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,742.65",""
+"2013","Liechtenstein","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","915.81",""
+"2013","Liechtenstein","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","144.81",""
+"2013","Liechtenstein","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,098.66",""
+"2013","Liechtenstein","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,209.93",""
+"2013","Liechtenstein","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","176.3",""
+"2013","Liechtenstein","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,476.94",""
+"2013","Liechtenstein","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","757.54",""
+"2013","Liechtenstein","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","114.78",""
+"2013","Liechtenstein","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,410.99",""
+"2013","Norway","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","941.11",""
+"2013","Norway","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","153.72",""
+"2013","Norway","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,191.64",""
+"2013","Norway","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,137.01",""
+"2013","Norway","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","185.34",""
+"2013","Norway","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,065.69",""
+"2013","Norway","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","798.44",""
+"2013","Norway","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","120.49",""
+"2013","Norway","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,597.17",""
+"2013","Switzerland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","873.43",""
+"2013","Switzerland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.55",""
+"2013","Switzerland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,886.51",""
+"2013","Switzerland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,075.99",""
+"2013","Switzerland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","181.34",""
+"2013","Switzerland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,769.31",""
+"2013","Switzerland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","731.42",""
+"2013","Switzerland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","105.59",""
+"2013","Switzerland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,314.96",""
+"2013","Serbia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,663.59",""
+"2013","Serbia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","335.12",""
+"2013","Serbia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,147.77",""
+"2013","Serbia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,945.92",""
+"2013","Serbia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","453.56",""
+"2013","Serbia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,106.71",""
+"2013","Serbia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,439.2",""
+"2013","Serbia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","223.5",""
+"2013","Serbia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,457.89",""
+"2013","Turkey","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","884.46","d"
+"2013","Turkey","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","218.77",""
+"2013","Turkey","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,632.55","d"
+"2013","Turkey","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,089.52","d"
+"2013","Turkey","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","294.16",""
+"2013","Turkey","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,372.92","d"
+"2013","Turkey","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","711.17","d"
+"2013","Turkey","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","144.55",""
+"2013","Turkey","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,050.3","d"
+"2014","European Union - 28 countries","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,003.06",""
+"2014","European Union - 28 countries","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","209.44",""
+"2014","European Union - 28 countries","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,279.27",""
+"2014","European Union - 28 countries","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,254.48",""
+"2014","European Union - 28 countries","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","281.78",""
+"2014","European Union - 28 countries","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,269.95",""
+"2014","European Union - 28 countries","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","817.94",""
+"2014","European Union - 28 countries","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.71",""
+"2014","European Union - 28 countries","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,617.77",""
+"2014","Belgium","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","970.63",""
+"2014","Belgium","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","191.8",""
+"2014","Belgium","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,185.8",""
+"2014","Belgium","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,205.39",""
+"2014","Belgium","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","243.38",""
+"2014","Belgium","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,176.74",""
+"2014","Belgium","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","799.67",""
+"2014","Belgium","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","140.44",""
+"2014","Belgium","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,521.11",""
+"2014","Bulgaria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,646.5",""
+"2014","Bulgaria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","382.01",""
+"2014","Bulgaria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,866.58",""
+"2014","Bulgaria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,038.24",""
+"2014","Bulgaria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","538.03",""
+"2014","Bulgaria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,231.4",""
+"2014","Bulgaria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,351.17",""
+"2014","Bulgaria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","234.78",""
+"2014","Bulgaria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,959.85",""
+"2014","Czechia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,237.32",""
+"2014","Czechia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","236.06",""
+"2014","Czechia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,370.75",""
+"2014","Czechia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,564.22",""
+"2014","Czechia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","326.58",""
+"2014","Czechia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,673.48",""
+"2014","Czechia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,007.85",""
+"2014","Czechia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","147.68",""
+"2014","Czechia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,558.8",""
+"2014","Denmark","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,028.33",""
+"2014","Denmark","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","195",""
+"2014","Denmark","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,468.48",""
+"2014","Denmark","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,242.87",""
+"2014","Denmark","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","242.03",""
+"2014","Denmark","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,374.54",""
+"2014","Denmark","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","871.79",""
+"2014","Denmark","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","147.77",""
+"2014","Denmark","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,860.69",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,017.07",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","196.04",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,406.44",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,260.22",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","256.87",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,402.25",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","840.68",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.05",""
+"2014","Germany (until 1990 former territory of the FRG)","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,749.52",""
+"2014","Estonia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,269.27",""
+"2014","Estonia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","331.62",""
+"2014","Estonia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,140.1",""
+"2014","Estonia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,805.54",""
+"2014","Estonia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","515.64",""
+"2014","Estonia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,130.5",""
+"2014","Estonia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","961.79",""
+"2014","Estonia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","171.12",""
+"2014","Estonia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,225.85",""
+"2014","Ireland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","993.55",""
+"2014","Ireland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","166.75",""
+"2014","Ireland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,406.74",""
+"2014","Ireland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,194.52",""
+"2014","Ireland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","208.22",""
+"2014","Ireland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,266.15",""
+"2014","Ireland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","843.76",""
+"2014","Ireland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","125.76",""
+"2014","Ireland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,807.77",""
+"2014","Greece","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","967.28",""
+"2014","Greece","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","185.5",""
+"2014","Greece","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,194.61",""
+"2014","Greece","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,154.06",""
+"2014","Greece","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","262.85",""
+"2014","Greece","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,833.2",""
+"2014","Greece","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","806.54",""
+"2014","Greece","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","113.27",""
+"2014","Greece","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,668.52",""
+"2014","Spain","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","837.46",""
+"2014","Spain","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","156.4",""
+"2014","Spain","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,649",""
+"2014","Spain","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,078.41",""
+"2014","Spain","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","213.47",""
+"2014","Spain","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,649.06",""
+"2014","Spain","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","656.46",""
+"2014","Spain","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","100.7",""
+"2014","Spain","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,950.75",""
+"2014","France","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","829.86",""
+"2014","France","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","195.44",""
+"2014","France","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,448.89",""
+"2014","France","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,086.74",""
+"2014","France","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","267.22",""
+"2014","France","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,469.89",""
+"2014","France","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","645.09",""
+"2014","France","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","127.4",""
+"2014","France","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,782.2",""
+"2014","Croatia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,355.92",""
+"2014","Croatia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","262.73",""
+"2014","Croatia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,868.84",""
+"2014","Croatia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,716.98",""
+"2014","Croatia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","372.55",""
+"2014","Croatia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,267.02",""
+"2014","Croatia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,109.86",""
+"2014","Croatia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","157.65",""
+"2014","Croatia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,040.77",""
+"2014","Italy","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","854.06",""
+"2014","Italy","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","140.22",""
+"2014","Italy","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,800.92",""
+"2014","Italy","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,079.29",""
+"2014","Italy","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","181.05",""
+"2014","Italy","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,787.44",""
+"2014","Italy","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","698.8",""
+"2014","Italy","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","101.14",""
+"2014","Italy","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,166.03",""
+"2014","Cyprus","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","980.1",""
+"2014","Cyprus","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","133.9",""
+"2014","Cyprus","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,473.39",""
+"2014","Cyprus","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,139.73",""
+"2014","Cyprus","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","177.61",""
+"2014","Cyprus","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,111.58",""
+"2014","Cyprus","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","845.27",""
+"2014","Cyprus","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","92.63",""
+"2014","Cyprus","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,952.35",""
+"2014","Latvia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,502.96",""
+"2014","Latvia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","430.06",""
+"2014","Latvia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,932.11",""
+"2014","Latvia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,112.28",""
+"2014","Latvia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","668.55",""
+"2014","Latvia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,072.3",""
+"2014","Latvia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,145.57",""
+"2014","Latvia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","228.58",""
+"2014","Latvia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,931.08",""
+"2014","Lithuania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,449.22",""
+"2014","Lithuania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","425.01",""
+"2014","Lithuania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,677.41",""
+"2014","Lithuania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,049.46",""
+"2014","Lithuania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","670.2",""
+"2014","Lithuania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,743.35",""
+"2014","Lithuania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,086.05",""
+"2014","Lithuania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","216.3",""
+"2014","Lithuania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,676.55",""
+"2014","Luxembourg","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","917.54",""
+"2014","Luxembourg","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","162.03",""
+"2014","Luxembourg","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,036.43",""
+"2014","Luxembourg","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,191.23",""
+"2014","Luxembourg","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","214.37",""
+"2014","Luxembourg","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,223.88",""
+"2014","Luxembourg","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","731.28",""
+"2014","Luxembourg","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","107.44",""
+"2014","Luxembourg","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,306.63",""
+"2014","Hungary","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,455.45",""
+"2014","Hungary","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","370.39",""
+"2014","Hungary","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,934.79",""
+"2014","Hungary","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,872.8",""
+"2014","Hungary","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","523.48",""
+"2014","Hungary","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,443.06",""
+"2014","Hungary","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,180.34",""
+"2014","Hungary","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","233.82",""
+"2014","Hungary","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,087.78",""
+"2014","Malta","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","939.38",""
+"2014","Malta","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","152.37",""
+"2014","Malta","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,188.28",""
+"2014","Malta","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,146.17",""
+"2014","Malta","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","193.19",""
+"2014","Malta","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,080.27",""
+"2014","Malta","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","787.26",""
+"2014","Malta","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","110.7",""
+"2014","Malta","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,580.22",""
+"2014","Netherlands","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","957.96",""
+"2014","Netherlands","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","160.47",""
+"2014","Netherlands","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,250.15",""
+"2014","Netherlands","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,146.49",""
+"2014","Netherlands","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","185.05",""
+"2014","Netherlands","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,115.48",""
+"2014","Netherlands","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","825.93",""
+"2014","Netherlands","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","135.71",""
+"2014","Netherlands","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,675.33",""
+"2014","Austria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","957.15",""
+"2014","Austria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","179.09",""
+"2014","Austria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,169.11",""
+"2014","Austria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,182",""
+"2014","Austria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","233.28",""
+"2014","Austria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,098.51",""
+"2014","Austria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","795.69",""
+"2014","Austria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","126.41",""
+"2014","Austria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,558.61",""
+"2014","Poland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,241.04",""
+"2014","Poland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","316.89",""
+"2014","Poland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,056.11",""
+"2014","Poland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,641.49",""
+"2014","Poland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","459.04",""
+"2014","Poland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,522.86",""
+"2014","Poland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","966.01",""
+"2014","Poland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","182.9",""
+"2014","Poland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,198.82",""
+"2014","Portugal","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","991.4",""
+"2014","Portugal","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.99",""
+"2014","Portugal","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,279.13",""
+"2014","Portugal","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,285.43",""
+"2014","Portugal","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","283.91",""
+"2014","Portugal","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,419.93",""
+"2014","Portugal","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","783.78",""
+"2014","Portugal","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","114.07",""
+"2014","Portugal","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,548.48",""
+"2014","Romania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,516.64",""
+"2014","Romania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","373.89",""
+"2014","Romania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,234.11",""
+"2014","Romania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,886.4",""
+"2014","Romania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","536.22",""
+"2014","Romania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,460.19",""
+"2014","Romania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,234.2",""
+"2014","Romania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","220.83",""
+"2014","Romania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,417.61",""
+"2014","Slovenia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,018.63",""
+"2014","Slovenia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","191.89",""
+"2014","Slovenia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,431.59",""
+"2014","Slovenia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,301.92",""
+"2014","Slovenia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","262.12",""
+"2014","Slovenia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,594.44",""
+"2014","Slovenia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","821.9",""
+"2014","Slovenia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","119.71",""
+"2014","Slovenia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,720.66",""
+"2014","Slovakia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,353.43",""
+"2014","Slovakia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","304.55",""
+"2014","Slovakia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,683.45",""
+"2014","Slovakia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,751.13",""
+"2014","Slovakia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","438.55",""
+"2014","Slovakia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,169.73",""
+"2014","Slovakia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,085.84",""
+"2014","Slovakia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","178.26",""
+"2014","Slovakia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,832.54",""
+"2014","Finland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","994.74",""
+"2014","Finland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","191.68",""
+"2014","Finland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,309.93",""
+"2014","Finland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,261.27",""
+"2014","Finland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","262.56",""
+"2014","Finland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,384.12",""
+"2014","Finland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","803.25",""
+"2014","Finland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","120.98",""
+"2014","Finland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,619.79",""
+"2014","Sweden","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","922.1",""
+"2014","Sweden","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.66",""
+"2014","Sweden","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,127.41",""
+"2014","Sweden","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,104.73",""
+"2014","Sweden","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","175.95",""
+"2014","Sweden","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,938.96",""
+"2014","Sweden","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","786.66",""
+"2014","Sweden","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","114.78",""
+"2014","Sweden","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,560.34",""
+"2014","United Kingdom","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","971.17",""
+"2014","United Kingdom","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","181",""
+"2014","United Kingdom","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,233.15",""
+"2014","United Kingdom","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,145.89",""
+"2014","United Kingdom","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","219.96",""
+"2014","United Kingdom","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,968.3",""
+"2014","United Kingdom","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","837.96",""
+"2014","United Kingdom","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","142.96",""
+"2014","United Kingdom","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,707.08",""
+"2014","Iceland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","882.53",""
+"2014","Iceland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.42",""
+"2014","Iceland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,925.5",""
+"2014","Iceland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,048.39",""
+"2014","Iceland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","170.05",""
+"2014","Iceland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,674.38",""
+"2014","Iceland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","760.89",""
+"2014","Iceland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","120.72",""
+"2014","Iceland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,403.65",""
+"2014","Liechtenstein","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","976.36",""
+"2014","Liechtenstein","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.88",""
+"2014","Liechtenstein","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,441.89",""
+"2014","Liechtenstein","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,106.94",""
+"2014","Liechtenstein","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","170.37",""
+"2014","Liechtenstein","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,973.27",""
+"2014","Liechtenstein","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","890.7",""
+"2014","Liechtenstein","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","103.84",""
+"2014","Liechtenstein","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,139.02",""
+"2014","Norway","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","913.73",""
+"2014","Norway","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.94",""
+"2014","Norway","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,083.33",""
+"2014","Norway","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,114.28",""
+"2014","Norway","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","176.85",""
+"2014","Norway","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,984.16",""
+"2014","Norway","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","770.62",""
+"2014","Norway","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","113.52",""
+"2014","Norway","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,483.27",""
+"2014","Switzerland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","838.86",""
+"2014","Switzerland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.06",""
+"2014","Switzerland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,740.14",""
+"2014","Switzerland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,034.22",""
+"2014","Switzerland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","172.31",""
+"2014","Switzerland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,592.36",""
+"2014","Switzerland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","700.53",""
+"2014","Switzerland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","99.57",""
+"2014","Switzerland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,181.39",""
+"2014","Serbia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,636.11",""
+"2014","Serbia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","333.62",""
+"2014","Serbia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,013.07",""
+"2014","Serbia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,898.37",""
+"2014","Serbia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","449.95",""
+"2014","Serbia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,877.73",""
+"2014","Serbia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,423.13",""
+"2014","Serbia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","224.03",""
+"2014","Serbia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,373.23",""
+"2014","Turkey","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,167","d"
+"2014","Turkey","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","217",""
+"2014","Turkey","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,088.79","d"
+"2014","Turkey","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,434.38","d"
+"2014","Turkey","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","289.09",""
+"2014","Turkey","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,162.35","d"
+"2014","Turkey","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","965.82","d"
+"2014","Turkey","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.66",""
+"2014","Turkey","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,351.59","d"
+"2015","European Union - 28 countries","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,035.96",""
+"2015","European Union - 28 countries","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","210",""
+"2015","European Union - 28 countries","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,445.72",""
+"2015","European Union - 28 countries","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,286.92",""
+"2015","European Union - 28 countries","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","282.22",""
+"2015","European Union - 28 countries","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,434.52",""
+"2015","European Union - 28 countries","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","849.18",""
+"2015","European Union - 28 countries","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","140.32",""
+"2015","European Union - 28 countries","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,775.52",""
+"2015","Belgium","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,001.86",""
+"2015","Belgium","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.48",""
+"2015","Belgium","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,334.92",""
+"2015","Belgium","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,228.98",""
+"2015","Belgium","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","242.98",""
+"2015","Belgium","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,299.38",""
+"2015","Belgium","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","835.52",""
+"2015","Belgium","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.19",""
+"2015","Belgium","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,681.21",""
+"2015","Bulgaria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,660.15",""
+"2015","Bulgaria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","372.03",""
+"2015","Bulgaria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,977.78",""
+"2015","Bulgaria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,060.4",""
+"2015","Bulgaria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","524.72",""
+"2015","Bulgaria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,400.01",""
+"2015","Bulgaria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,361.02",""
+"2015","Bulgaria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","227.41",""
+"2015","Bulgaria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,040.82",""
+"2015","Czechia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,280.12",""
+"2015","Czechia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","234.95",""
+"2015","Czechia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,594.78",""
+"2015","Czechia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,603.65",""
+"2015","Czechia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","324.32",""
+"2015","Czechia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,884.99",""
+"2015","Czechia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,051.18",""
+"2015","Czechia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","147.49",""
+"2015","Czechia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,781.78",""
+"2015","Denmark","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,032.51",""
+"2015","Denmark","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","189.85",""
+"2015","Denmark","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,511.17",""
+"2015","Denmark","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,245.24",""
+"2015","Denmark","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","232.27",""
+"2015","Denmark","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,427.01",""
+"2015","Denmark","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","876.93",""
+"2015","Denmark","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","147.05",""
+"2015","Denmark","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,890",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,057.22",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","200.12",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,595.51",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,301.69",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","261.68",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,595.08",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","876.07",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.27",""
+"2015","Germany (until 1990 former territory of the FRG)","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,917.73",""
+"2015","Estonia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,236.6",""
+"2015","Estonia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","317.4",""
+"2015","Estonia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,031.24",""
+"2015","Estonia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,727.15",""
+"2015","Estonia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","482.38",""
+"2015","Estonia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,865.81",""
+"2015","Estonia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","946.67",""
+"2015","Estonia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","171.31",""
+"2015","Estonia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,147.51",""
+"2015","Ireland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,000.85",""
+"2015","Ireland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","160.61",""
+"2015","Ireland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,469.55",""
+"2015","Ireland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,193.31",""
+"2015","Ireland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","195.86",""
+"2015","Ireland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,311.01",""
+"2015","Ireland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","855.19",""
+"2015","Ireland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","125.79",""
+"2015","Ireland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,866.29",""
+"2015","Greece","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,003.36",""
+"2015","Greece","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","186.75",""
+"2015","Greece","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,374.49",""
+"2015","Greece","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,188.09",""
+"2015","Greece","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","266.28",""
+"2015","Greece","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,993.49",""
+"2015","Greece","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","843.37",""
+"2015","Greece","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","112.94",""
+"2015","Greece","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,858.7",""
+"2015","Spain","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","872.67",""
+"2015","Spain","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","156.19",""
+"2015","Spain","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,830.45",""
+"2015","Spain","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,119.3",""
+"2015","Spain","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","212.62",""
+"2015","Spain","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,862.23",""
+"2015","Spain","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","686.92",""
+"2015","Spain","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","101.1",""
+"2015","Spain","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,105.29",""
+"2015","France","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","858.75",""
+"2015","France","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","196.58",""
+"2015","France","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,592.29",""
+"2015","France","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,118.04",""
+"2015","France","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","269.63",""
+"2015","France","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,620.45",""
+"2015","France","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","670.73",""
+"2015","France","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","127.34",""
+"2015","France","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,913.94",""
+"2015","Croatia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,429.88",""
+"2015","Croatia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","270.12",""
+"2015","Croatia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,217.61",""
+"2015","Croatia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,792.3",""
+"2015","Croatia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","381.81",""
+"2015","Croatia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,615.11",""
+"2015","Croatia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,178.37",""
+"2015","Croatia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","163.07",""
+"2015","Croatia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,369.71",""
+"2015","Italy","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","901.24",""
+"2015","Italy","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.53",""
+"2015","Italy","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,029.25",""
+"2015","Italy","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,123.02",""
+"2015","Italy","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.45",""
+"2015","Italy","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,997.63",""
+"2015","Italy","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","746.61",""
+"2015","Italy","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","104.32",""
+"2015","Italy","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,398.14",""
+"2015","Cyprus","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,047.48",""
+"2015","Cyprus","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.39",""
+"2015","Cyprus","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,779.73",""
+"2015","Cyprus","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,231.28",""
+"2015","Cyprus","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","189.88",""
+"2015","Cyprus","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,530.41",""
+"2015","Cyprus","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","899.62",""
+"2015","Cyprus","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","99.2",""
+"2015","Cyprus","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,203.92",""
+"2015","Latvia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,489.36",""
+"2015","Latvia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","414.97",""
+"2015","Latvia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,924.67",""
+"2015","Latvia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,038.99",""
+"2015","Latvia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","637.24",""
+"2015","Latvia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,825.69",""
+"2015","Latvia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,161.11",""
+"2015","Latvia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","225.45",""
+"2015","Latvia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,023.68",""
+"2015","Lithuania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,489.99",""
+"2015","Lithuania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","422.76",""
+"2015","Lithuania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,895.75",""
+"2015","Lithuania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,073.46",""
+"2015","Lithuania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","661.93",""
+"2015","Lithuania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,900.53",""
+"2015","Lithuania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,129.93",""
+"2015","Lithuania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","219.31",""
+"2015","Lithuania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,889.18",""
+"2015","Luxembourg","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","930.15",""
+"2015","Luxembourg","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","151.31",""
+"2015","Luxembourg","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,145.36",""
+"2015","Luxembourg","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,119.03",""
+"2015","Luxembourg","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","196.79",""
+"2015","Luxembourg","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,926.24",""
+"2015","Luxembourg","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","784.99",""
+"2015","Luxembourg","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","103.61",""
+"2015","Luxembourg","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,597.86",""
+"2015","Hungary","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,500.16",""
+"2015","Hungary","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","371.72",""
+"2015","Hungary","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,158.59",""
+"2015","Hungary","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,908.54",""
+"2015","Hungary","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","517.81",""
+"2015","Hungary","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,649.78",""
+"2015","Hungary","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,230.8",""
+"2015","Hungary","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","240.89",""
+"2015","Hungary","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,317.32",""
+"2015","Malta","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","953.56",""
+"2015","Malta","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","156.6",""
+"2015","Malta","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,243.59",""
+"2015","Malta","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,164.59",""
+"2015","Malta","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","202.5",""
+"2015","Malta","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,136.32",""
+"2015","Malta","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","802.96",""
+"2015","Malta","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","110.01",""
+"2015","Malta","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,663.6",""
+"2015","Netherlands","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","991.75",""
+"2015","Netherlands","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","160.84",""
+"2015","Netherlands","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,421.9",""
+"2015","Netherlands","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,184.42",""
+"2015","Netherlands","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.88",""
+"2015","Netherlands","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,310.72",""
+"2015","Netherlands","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","855.78",""
+"2015","Netherlands","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.65",""
+"2015","Netherlands","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,824.49",""
+"2015","Austria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","989.74",""
+"2015","Austria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","175.02",""
+"2015","Austria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,353.05",""
+"2015","Austria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,222.26",""
+"2015","Austria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","230.23",""
+"2015","Austria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,317.56",""
+"2015","Austria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","820.66",""
+"2015","Austria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","121.16",""
+"2015","Austria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,708.34",""
+"2015","Poland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,273.62",""
+"2015","Poland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","319.7",""
+"2015","Poland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,211.62",""
+"2015","Poland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,681.34",""
+"2015","Poland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","465.43",""
+"2015","Poland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,700.88",""
+"2015","Poland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","991.37",""
+"2015","Poland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","182",""
+"2015","Poland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,332.61",""
+"2015","Portugal","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,005.34",""
+"2015","Portugal","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","190.36",""
+"2015","Portugal","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,369.74",""
+"2015","Portugal","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,286.81",""
+"2015","Portugal","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","271.65",""
+"2015","Portugal","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,477.59",""
+"2015","Portugal","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","806.65",""
+"2015","Portugal","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","116.82",""
+"2015","Portugal","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,654.43",""
+"2015","Romania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,529.56",""
+"2015","Romania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","371.37",""
+"2015","Romania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,310.79",""
+"2015","Romania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,905.02",""
+"2015","Romania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","531.68",""
+"2015","Romania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,574.46",""
+"2015","Romania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,242.95",""
+"2015","Romania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","219.67",""
+"2015","Romania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,467.28",""
+"2015","Slovenia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,041.09",""
+"2015","Slovenia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","198.98",""
+"2015","Slovenia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,517.48",""
+"2015","Slovenia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,327.8",""
+"2015","Slovenia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","272.95",""
+"2015","Slovenia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,682.45",""
+"2015","Slovenia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","839.19",""
+"2015","Slovenia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","122.92",""
+"2015","Slovenia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,796.07",""
+"2015","Slovakia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,390.25",""
+"2015","Slovakia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","312.79",""
+"2015","Slovakia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,838.23",""
+"2015","Slovakia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,768.94",""
+"2015","Slovakia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","449.1",""
+"2015","Slovakia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,217.48",""
+"2015","Slovakia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,127.6",""
+"2015","Slovakia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","183.77",""
+"2015","Slovakia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,023.93",""
+"2015","Finland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","968.81",""
+"2015","Finland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","181.81",""
+"2015","Finland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,217.7",""
+"2015","Finland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,227.32",""
+"2015","Finland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","249.17",""
+"2015","Finland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,265.32",""
+"2015","Finland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","781.76",""
+"2015","Finland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","114.79",""
+"2015","Finland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,535.16",""
+"2015","Sweden","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","926.64",""
+"2015","Sweden","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.52",""
+"2015","Sweden","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,159.49",""
+"2015","Sweden","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,110.72",""
+"2015","Sweden","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","175.31",""
+"2015","Sweden","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,972.29",""
+"2015","Sweden","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","790.19",""
+"2015","Sweden","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","111.03",""
+"2015","Sweden","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,593.87",""
+"2015","United Kingdom","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,002.39",""
+"2015","United Kingdom","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","184.04",""
+"2015","United Kingdom","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,380.72",""
+"2015","United Kingdom","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,175.47",""
+"2015","United Kingdom","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","225.34",""
+"2015","United Kingdom","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,097.82",""
+"2015","United Kingdom","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","868.13",""
+"2015","United Kingdom","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.69",""
+"2015","United Kingdom","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,858.78",""
+"2015","Iceland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","913.05",""
+"2015","Iceland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.06",""
+"2015","Iceland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,108.22",""
+"2015","Iceland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,031",""
+"2015","Iceland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","159.31",""
+"2015","Iceland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,629.51",""
+"2015","Iceland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","823.95",""
+"2015","Iceland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","117.81",""
+"2015","Iceland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,739.02",""
+"2015","Liechtenstein","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","878.16",""
+"2015","Liechtenstein","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","128.91",""
+"2015","Liechtenstein","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,971.19",""
+"2015","Liechtenstein","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,027.97",""
+"2015","Liechtenstein","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.89",""
+"2015","Liechtenstein","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,694.15",""
+"2015","Liechtenstein","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","775.7",""
+"2015","Liechtenstein","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","117.9",""
+"2015","Liechtenstein","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,491.24",""
+"2015","Norway","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","907.15",""
+"2015","Norway","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","139.55",""
+"2015","Norway","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,075.93",""
+"2015","Norway","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,092.07",""
+"2015","Norway","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","167.81",""
+"2015","Norway","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,907.64",""
+"2015","Norway","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","773.62",""
+"2015","Norway","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","109.94",""
+"2015","Norway","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,513.41",""
+"2015","Switzerland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","868.02",""
+"2015","Switzerland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","137.63",""
+"2015","Switzerland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,883.24",""
+"2015","Switzerland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,064.98",""
+"2015","Switzerland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","174.79",""
+"2015","Switzerland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,739.84",""
+"2015","Switzerland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","726.05",""
+"2015","Switzerland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","100.27",""
+"2015","Switzerland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,309.4",""
+"2015","Serbia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,648.17",""
+"2015","Serbia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","334.57",""
+"2015","Serbia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,070.97",""
+"2015","Serbia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,914.27",""
+"2015","Serbia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","451.1",""
+"2015","Serbia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,954.51",""
+"2015","Serbia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,431.96",""
+"2015","Serbia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","224.94",""
+"2015","Serbia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,414.79",""
+"2015","Turkey","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,168.37","d"
+"2015","Turkey","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","210.08",""
+"2015","Turkey","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,124.42","d"
+"2015","Turkey","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,441.48","d"
+"2015","Turkey","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","279.93",""
+"2015","Turkey","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,236.6","d"
+"2015","Turkey","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","963.82","d"
+"2015","Turkey","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","140.92",""
+"2015","Turkey","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,360.93","d"
+"2016","European Union - 28 countries","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,002.25",""
+"2016","European Union - 28 countries","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","205.79",""
+"2016","European Union - 28 countries","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,290.16",""
+"2016","European Union - 28 countries","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,249.59",""
+"2016","European Union - 28 countries","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","275.87",""
+"2016","European Union - 28 countries","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,269.3",""
+"2016","European Union - 28 countries","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","817.84",""
+"2016","European Union - 28 countries","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","138.15",""
+"2016","European Union - 28 countries","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,623.74",""
+"2016","Belgium","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","960.66",""
+"2016","Belgium","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","186.78",""
+"2016","Belgium","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,155.36",""
+"2016","Belgium","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,193.93",""
+"2016","Belgium","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","235.97",""
+"2016","Belgium","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,148.61",""
+"2016","Belgium","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","788.98",""
+"2016","Belgium","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","137.75",""
+"2016","Belgium","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,477.35",""
+"2016","Bulgaria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,601.81",""
+"2016","Bulgaria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","374.31",""
+"2016","Bulgaria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,669.19",""
+"2016","Bulgaria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,007.4",""
+"2016","Bulgaria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","527.81",""
+"2016","Bulgaria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,115.43",""
+"2016","Bulgaria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,300.19",""
+"2016","Bulgaria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","228.16",""
+"2016","Bulgaria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,725.72",""
+"2016","Czechia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,205.97",""
+"2016","Czechia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","226.88",""
+"2016","Czechia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,247.85",""
+"2016","Czechia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,529.49",""
+"2016","Czechia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","310.22",""
+"2016","Czechia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,562.86",""
+"2016","Czechia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","979.42",""
+"2016","Czechia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","145.09",""
+"2016","Czechia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,423.74",""
+"2016","Denmark","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,016.03",""
+"2016","Denmark","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","188.15",""
+"2016","Denmark","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,433.7",""
+"2016","Denmark","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,218.63",""
+"2016","Denmark","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","229.7",""
+"2016","Denmark","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,301.11",""
+"2016","Denmark","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","866.98",""
+"2016","Denmark","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.54",""
+"2016","Denmark","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,841.12",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,016.88",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","196.5",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,403.62",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,258.99",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","255.85",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,400.17",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","837.15",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","137.66",""
+"2016","Germany (until 1990 former territory of the FRG)","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,724.81",""
+"2016","Estonia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,205.93",""
+"2016","Estonia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","309.11",""
+"2016","Estonia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,908.21",""
+"2016","Estonia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,700.65",""
+"2016","Estonia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","467.13",""
+"2016","Estonia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,792.86",""
+"2016","Estonia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","916.59",""
+"2016","Estonia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","169.81",""
+"2016","Estonia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,999.42",""
+"2016","Ireland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","982.98",""
+"2016","Ireland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","157.08",""
+"2016","Ireland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,392.46",""
+"2016","Ireland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,167.44",""
+"2016","Ireland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","194.43",""
+"2016","Ireland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,184.2",""
+"2016","Ireland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","839.91",""
+"2016","Ireland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","120.23",""
+"2016","Ireland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,810.88",""
+"2016","Greece","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","957.87",""
+"2016","Greece","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","186.9",""
+"2016","Greece","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,140.57",""
+"2016","Greece","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,134.03",""
+"2016","Greece","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","260.96",""
+"2016","Greece","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,738.28",""
+"2016","Greece","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","806.37",""
+"2016","Greece","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","118.31",""
+"2016","Greece","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,646.81",""
+"2016","Spain","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","829.03",""
+"2016","Spain","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","152.37",""
+"2016","Spain","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,622.43",""
+"2016","Spain","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,068.02",""
+"2016","Spain","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","207.41",""
+"2016","Spain","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,620.77",""
+"2016","Spain","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","648.4",""
+"2016","Spain","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","98.69",""
+"2016","Spain","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,917.71",""
+"2016","France","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","837.81",""
+"2016","France","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","193.18",""
+"2016","France","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,498.98",""
+"2016","France","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,092.16",""
+"2016","France","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","263.6",""
+"2016","France","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,512.6",""
+"2016","France","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","653.87",""
+"2016","France","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","126.58",""
+"2016","France","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","2,830.65",""
+"2016","Croatia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,336.01",""
+"2016","Croatia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","250.36",""
+"2016","Croatia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,817.8",""
+"2016","Croatia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,695.9",""
+"2016","Croatia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","358.53",""
+"2016","Croatia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,216.82",""
+"2016","Croatia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,088.89",""
+"2016","Croatia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","146.74",""
+"2016","Croatia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,978.28",""
+"2016","Italy","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","843.12",""
+"2016","Italy","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","136.72",""
+"2016","Italy","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,759.31",""
+"2016","Italy","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,059.64",""
+"2016","Italy","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","175.34",""
+"2016","Italy","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,710.17",""
+"2016","Italy","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","692.45",""
+"2016","Italy","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","99.75",""
+"2016","Italy","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,139.23",""
+"2016","Cyprus","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","966.09",""
+"2016","Cyprus","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","130.71",""
+"2016","Cyprus","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,414.71",""
+"2016","Cyprus","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,126.29",""
+"2016","Cyprus","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","177.95",""
+"2016","Cyprus","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,041.25",""
+"2016","Cyprus","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","831.68",""
+"2016","Cyprus","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","85.75",""
+"2016","Cyprus","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,911.03",""
+"2016","Latvia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,476.37",""
+"2016","Latvia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","403.8",""
+"2016","Latvia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,904.15",""
+"2016","Latvia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,071.79",""
+"2016","Latvia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","617.42",""
+"2016","Latvia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","8,075.71",""
+"2016","Latvia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,135.76",""
+"2016","Latvia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","221.4",""
+"2016","Latvia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,910.42",""
+"2016","Lithuania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,454.66",""
+"2016","Lithuania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","416.35",""
+"2016","Lithuania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,741",""
+"2016","Lithuania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","2,054.06",""
+"2016","Lithuania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","658.33",""
+"2016","Lithuania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,815.93",""
+"2016","Lithuania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,090.42",""
+"2016","Lithuania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","209.91",""
+"2016","Lithuania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,725.36",""
+"2016","Luxembourg","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","904.72",""
+"2016","Luxembourg","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","154.38",""
+"2016","Luxembourg","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,002.3",""
+"2016","Luxembourg","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,133.83",""
+"2016","Luxembourg","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","199.79",""
+"2016","Luxembourg","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,989.73",""
+"2016","Luxembourg","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","738.83",""
+"2016","Luxembourg","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","106.87",""
+"2016","Luxembourg","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,347.72",""
+"2016","Hungary","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,425.26",""
+"2016","Hungary","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","356.99",""
+"2016","Hungary","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,835.31",""
+"2016","Hungary","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,847.62",""
+"2016","Hungary","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","504.18",""
+"2016","Hungary","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,393.63",""
+"2016","Hungary","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,146.58",""
+"2016","Hungary","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","224.77",""
+"2016","Hungary","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,951.99",""
+"2016","Malta","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","881.59",""
+"2016","Malta","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","154.64",""
+"2016","Malta","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,882.58",""
+"2016","Malta","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,032.18",""
+"2016","Malta","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","192.98",""
+"2016","Malta","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,496.57",""
+"2016","Malta","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","766.68",""
+"2016","Malta","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","115.34",""
+"2016","Malta","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,455.54",""
+"2016","Netherlands","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","980.25",""
+"2016","Netherlands","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","160.06",""
+"2016","Netherlands","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,366.16",""
+"2016","Netherlands","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,163.57",""
+"2016","Netherlands","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","182.35",""
+"2016","Netherlands","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,214.24",""
+"2016","Netherlands","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","848.82",""
+"2016","Netherlands","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","137.72",""
+"2016","Netherlands","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,784.4",""
+"2016","Austria","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","939.62",""
+"2016","Austria","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","167.59",""
+"2016","Austria","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,126.73",""
+"2016","Austria","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,164.33",""
+"2016","Austria","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","217.88",""
+"2016","Austria","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,071.47",""
+"2016","Austria","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","779",""
+"2016","Austria","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","118.44",""
+"2016","Austria","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,505.92",""
+"2016","Poland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,218.15",""
+"2016","Poland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","312.13",""
+"2016","Poland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,958.41",""
+"2016","Poland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,616.01",""
+"2016","Poland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","455.14",""
+"2016","Poland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,408.33",""
+"2016","Poland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","941.07",""
+"2016","Poland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","176.72",""
+"2016","Poland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,096.45",""
+"2016","Portugal","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,005.01",""
+"2016","Portugal","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","192.21",""
+"2016","Portugal","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,360.4",""
+"2016","Portugal","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,300.95",""
+"2016","Portugal","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","277.65",""
+"2016","Portugal","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,525.33",""
+"2016","Portugal","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","797.31",""
+"2016","Portugal","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","115.29",""
+"2016","Portugal","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,612.87",""
+"2016","Romania","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,476.24",""
+"2016","Romania","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","372.21",""
+"2016","Romania","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,033.92",""
+"2016","Romania","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,851.32",""
+"2016","Romania","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","534.81",""
+"2016","Romania","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,286.13",""
+"2016","Romania","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,188.96",""
+"2016","Romania","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","217.37",""
+"2016","Romania","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,199.88",""
+"2016","Slovenia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,013.64",""
+"2016","Slovenia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","181.62",""
+"2016","Slovenia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,448.38",""
+"2016","Slovenia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,301.61",""
+"2016","Slovenia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","249.35",""
+"2016","Slovenia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,645.56",""
+"2016","Slovenia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","810.72",""
+"2016","Slovenia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","112.1",""
+"2016","Slovenia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,694.8",""
+"2016","Slovakia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,323.64",""
+"2016","Slovakia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","291.6",""
+"2016","Slovakia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,584.09",""
+"2016","Slovakia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,689.03",""
+"2016","Slovakia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","416.1",""
+"2016","Slovakia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,943.94",""
+"2016","Slovakia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,071.34",""
+"2016","Slovakia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","173.87",""
+"2016","Slovakia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,776.27",""
+"2016","Finland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","975.91",""
+"2016","Finland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","183.03",""
+"2016","Finland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,249.09",""
+"2016","Finland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,245.07",""
+"2016","Finland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","251.37",""
+"2016","Finland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,347.27",""
+"2016","Finland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","782.13",""
+"2016","Finland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","114.91",""
+"2016","Finland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,536.53",""
+"2016","Sweden","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","912.91",""
+"2016","Sweden","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","141.32",""
+"2016","Sweden","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,098.21",""
+"2016","Sweden","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,086.5",""
+"2016","Sweden","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","171.41",""
+"2016","Sweden","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,864.17",""
+"2016","Sweden","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","782.75",""
+"2016","Sweden","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","110.54",""
+"2016","Sweden","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,557.78",""
+"2016","United Kingdom","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","987.39",""
+"2016","United Kingdom","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","187",""
+"2016","United Kingdom","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,291.53",""
+"2016","United Kingdom","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,159.18",""
+"2016","United Kingdom","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","226.69",""
+"2016","United Kingdom","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,008.72",""
+"2016","United Kingdom","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","853.55",""
+"2016","United Kingdom","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","148.19",""
+"2016","United Kingdom","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,765.42",""
+"2016","Iceland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","943.47",""
+"2016","Iceland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","134.91",""
+"2016","Iceland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,281.34",""
+"2016","Iceland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,111.09",""
+"2016","Iceland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","161.09",""
+"2016","Iceland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,032.86",""
+"2016","Iceland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","811.93",""
+"2016","Iceland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","107.91",""
+"2016","Iceland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,718.29",""
+"2016","Liechtenstein","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","891.57",""
+"2016","Liechtenstein","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","129.74",""
+"2016","Liechtenstein","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,036.56",""
+"2016","Liechtenstein","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,167.87",""
+"2016","Liechtenstein","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","115.56",""
+"2016","Liechtenstein","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,512.03",""
+"2016","Liechtenstein","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","734.34",""
+"2016","Liechtenstein","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","144.27",""
+"2016","Liechtenstein","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,170.29",""
+"2016","Norway","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","898.51",""
+"2016","Norway","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","140.05",""
+"2016","Norway","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,029.59",""
+"2016","Norway","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,072.85",""
+"2016","Norway","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","167.35",""
+"2016","Norway","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,810.94",""
+"2016","Norway","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","772.91",""
+"2016","Norway","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","111.69",""
+"2016","Norway","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,502.52",""
+"2016","Switzerland","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","812.35",""
+"2016","Switzerland","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","130.08",""
+"2016","Switzerland","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,628.92",""
+"2016","Switzerland","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","989.12",""
+"2016","Switzerland","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","160.7",""
+"2016","Switzerland","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,409.02",""
+"2016","Switzerland","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","686.11",""
+"2016","Switzerland","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","99.26",""
+"2016","Switzerland","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","3,108.74",""
+"2016","Serbia","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,570.96",""
+"2016","Serbia","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","320.81",""
+"2016","Serbia","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,731.8",""
+"2016","Serbia","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,828.25",""
+"2016","Serbia","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","430.43",""
+"2016","Serbia","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","7,598.74",""
+"2016","Serbia","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","1,362.7",""
+"2016","Serbia","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","217.86",""
+"2016","Serbia","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,088.83",""
+"2016","Turkey","Rate","Total","Total","All causes of death (A00-Y89) excluding S00-T98","1,189.55","d"
+"2016","Turkey","Rate","Total","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","214.78",""
+"2016","Turkey","Rate","Total","65 years or over","All causes of death (A00-Y89) excluding S00-T98","5,213.59","d"
+"2016","Turkey","Rate","Males","Total","All causes of death (A00-Y89) excluding S00-T98","1,464.97","d"
+"2016","Turkey","Rate","Males","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","287.09",""
+"2016","Turkey","Rate","Males","65 years or over","All causes of death (A00-Y89) excluding S00-T98","6,327.54","d"
+"2016","Turkey","Rate","Females","Total","All causes of death (A00-Y89) excluding S00-T98","981.13","d"
+"2016","Turkey","Rate","Females","Less than 65 years","All causes of death (A00-Y89) excluding S00-T98","143.14",""
+"2016","Turkey","Rate","Females","65 years or over","All causes of death (A00-Y89) excluding S00-T98","4,440.55","d"
diff --git a/your-project/Week 4 - Project/hlth_cd_asdr/hlth_cd_asdr2_Label.csv b/your-project/Week 4 - Project/hlth_cd_asdr/hlth_cd_asdr2_Label.csv
new file mode 100644
index 0000000..2f1b293
--- /dev/null
+++ b/your-project/Week 4 - Project/hlth_cd_asdr/hlth_cd_asdr2_Label.csv	
@@ -0,0 +1,87 @@
+"DATASET: Causes of death - standardised death rate by residence [hlth_cd_asdr2]"
+
+"LAST UPDATE: 16.08.19 17:00:59"
+
+"EXTRACTION DATE: 10.09.19 10:26:28"
+
+"SOURCE OF DATA: Eurostat"
+
+"TIME"
+"2011"
+"2012"
+"2013"
+"2014"
+"2015"
+"2016"
+
+"GEO"
+"European Union - 28 countries"
+"Belgium"
+"Bulgaria"
+"Czechia"
+"Denmark"
+"Germany (until 1990 former territory of the FRG)"
+"Estonia"
+"Ireland"
+"Greece"
+"Spain"
+"France"
+"Croatia"
+"Italy"
+"Cyprus"
+"Latvia"
+"Lithuania"
+"Luxembourg"
+"Hungary"
+"Malta"
+"Netherlands"
+"Austria"
+"Poland"
+"Portugal"
+"Romania"
+"Slovenia"
+"Slovakia"
+"Finland"
+"Sweden"
+"United Kingdom"
+"Iceland"
+"Liechtenstein"
+"Norway"
+"Switzerland"
+"Serbia"
+"Turkey"
+
+"UNIT"
+"Rate"
+
+"SEX"
+"Total"
+"Males"
+"Females"
+
+"AGE"
+"Total"
+"Less than 65 years"
+"65 years or over"
+
+"ICD10"
+"All causes of death (A00-Y89) excluding S00-T98"
+
+"No footnotes available"
+
+"Available flags:"
+"b","break in time series"
+"c","confidential"
+"d","definition differs, see metadata"
+"e","estimated"
+"f","forecast"
+"n","not significant"
+"p","provisional"
+"r","revised"
+"s","Eurostat estimate"
+"u","low reliability"
+"z","not applicable"
+
+"Special value:"
+":","not available"
+
diff --git a/your-project/Week 4 - Project/hlth_cd_asdr_1_Data.csv b/your-project/Week 4 - Project/hlth_cd_asdr_1_Data.csv
new file mode 100644
index 0000000..d32aa07
--- /dev/null
+++ b/your-project/Week 4 - Project/hlth_cd_asdr_1_Data.csv	
@@ -0,0 +1,721 @@
+"TIME","GEO","UNIT","SEX","AGE","ICD10","Value","Flag and Footnotes"
+"2001","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2001","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2001","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2001","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","10.5",""
+"2001","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2001","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2001","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2001","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.7",""
+"2001","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2001","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.9",""
+"2001","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.8",""
+"2001","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.1",""
+"2001","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2001","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2001","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2001","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2001","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2001","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2001","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2001","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","10.6",""
+"2001","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2001","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2001","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.9",""
+"2001","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.0",""
+"2001","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2001","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.4",""
+"2001","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2001","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"2001","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2001","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2001","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2001","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2001","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.4",""
+"2001","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2001","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2001","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"2001","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2001","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.8",""
+"2001","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2001","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2001","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.8",""
+"2001","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2001","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2001","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2001","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2001","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","7.6",""
+"2001","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.6",""
+"2001","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.5",""
+"2001","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2001","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2001","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3","e"
+"2002","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6","e"
+"2002","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2002","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2002","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2002","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","12.4",""
+"2002","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2002","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.8",""
+"2002","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2002","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.7",""
+"2002","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.5",""
+"2002","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.4",""
+"2002","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2002","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2002","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2002","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2002","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2002","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2002","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2002","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.7",""
+"2002","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2002","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.3",""
+"2002","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2002","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2002","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.1",""
+"2002","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2002","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2002","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.7",""
+"2002","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2002","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2002","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2002","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.8",""
+"2002","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2002","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.8",""
+"2002","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2002","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.5",""
+"2002","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2002","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2002","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2002","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.8",""
+"2002","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2002","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.0",""
+"2002","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2002","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2002","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2002","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"2002","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2002","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2002","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.8",""
+"2002","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2002","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"2002","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2002","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2002","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2002","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","5.6",""
+"2002","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.5",""
+"2002","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.5",""
+"2002","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.9",""
+"2002","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2002","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2002","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.4","e"
+"2003","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6","e"
+"2003","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.0",""
+"2003","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2003","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2003","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2003","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2003","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2003","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","11.5",""
+"2003","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2003","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.0",""
+"2003","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2003","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","11.4",""
+"2003","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.8",""
+"2003","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.3",""
+"2003","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2003","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2003","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2003","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2003","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2003","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2003","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2003","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.6",""
+"2003","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2003","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2003","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2003","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2003","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.7",""
+"2003","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2003","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2003","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.8",""
+"2003","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2003","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.5",""
+"2003","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2003","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2003","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2003","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2003","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2003","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.1",""
+"2003","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2003","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2003","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2003","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2003","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2003","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2003","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2003","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2003","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.7",""
+"2003","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2003","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.6",""
+"2003","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2003","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2003","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.6",""
+"2003","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2003","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2003","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2003","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2003","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2003","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2003","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.4",""
+"2003","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.3",""
+"2003","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2003","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2003","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3","e"
+"2004","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6","e"
+"2004","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.1",""
+"2004","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2004","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2004","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2004","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2004","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","14.3",""
+"2004","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2004","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2004","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2004","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","10.4",""
+"2004","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.4",""
+"2004","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","3.0",""
+"2004","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2004","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2004","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2004","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2004","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.2",""
+"2004","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2004","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2004","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2004","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.7",""
+"2004","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.2",""
+"2004","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2004","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.5",""
+"2004","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.6",""
+"2004","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2004","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2004","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2004","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2004","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2004","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.5",""
+"2004","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2004","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2004","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.1",""
+"2004","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2004","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2004","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.1",""
+"2004","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2004","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.3",""
+"2004","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2004","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.0",""
+"2004","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2004","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.6",""
+"2004","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2004","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2004","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2004","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.8",""
+"2004","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.6",""
+"2004","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.0",""
+"2004","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2004","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2004","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2004","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2004","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.4",""
+"2004","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.5",""
+"2004","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2004","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2004","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2004","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2005","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3","e"
+"2005","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6","e"
+"2005","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.2",""
+"2005","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2005","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2005","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.6",""
+"2005","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","14.3",""
+"2005","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2005","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.9",""
+"2005","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2005","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","14.7",""
+"2005","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.2",""
+"2005","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.4",""
+"2005","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2005","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2005","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2005","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2005","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2005","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.3",""
+"2005","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2005","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2005","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.2",""
+"2005","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2005","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2005","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2005","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2005","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.7",""
+"2005","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2005","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2005","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2005","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.3",""
+"2005","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2005","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2005","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2005","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2005","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2005","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"2005","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.2",""
+"2005","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"2005","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2005","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.1",""
+"2005","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2005","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2005","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2005","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3",""
+"2005","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2005","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.8",""
+"2005","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2005","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.8",""
+"2005","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.6",""
+"2005","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2005","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2005","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2005","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2005","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.0",""
+"2005","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2005","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.0",""
+"2005","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.8",""
+"2005","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.1",""
+"2005","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2005","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3","e"
+"2006","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5","e"
+"2006","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.9",""
+"2006","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2006","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.5",""
+"2006","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2006","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","15.2",""
+"2006","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2006","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2006","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2006","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","11.3",""
+"2006","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.6",""
+"2006","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.9",""
+"2006","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2006","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2006","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2006","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"2006","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2006","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2006","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2006","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2006","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2006","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2006","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2006","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2006","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2006","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2006","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2006","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3",""
+"2006","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2006","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.2",""
+"2006","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2006","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2006","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2006","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.5",""
+"2006","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.2",""
+"2006","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"2006","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2006","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2006","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2006","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.8",""
+"2006","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2006","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2006","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.5",""
+"2006","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2006","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.4",""
+"2006","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2006","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2006","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.6",""
+"2006","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.0",""
+"2006","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2006","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2006","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.6",""
+"2006","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2006","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.4",""
+"2006","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2006","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2006","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2006","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2006","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.1","e"
+"2007","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5","e"
+"2007","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.2",""
+"2007","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2007","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.3",""
+"2007","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2007","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","16.4",""
+"2007","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2007","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2007","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2007","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","17.1",""
+"2007","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2007","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2007","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2007","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2007","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2007","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2007","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"2007","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2007","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.8",""
+"2007","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2007","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2007","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2007","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2007","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.1",""
+"2007","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2007","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2007","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.4",""
+"2007","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2007","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2007","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2007","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2007","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2007","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.1",""
+"2007","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2007","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2007","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2007","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2007","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.4",""
+"2007","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2007","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.8",""
+"2007","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2007","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.5",""
+"2007","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2007","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2007","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.7",""
+"2007","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.9",""
+"2007","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2007","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2007","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.7",""
+"2007","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2007","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.0",""
+"2007","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2007","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2007","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2007","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2007","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.1","e"
+"2008","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6","e"
+"2008","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.6",""
+"2008","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2008","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2008","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2008","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2008","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2008","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","16.6",""
+"2008","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2008","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2008","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"2008","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","12.3",""
+"2008","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2008","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.3",""
+"2008","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2008","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.2",""
+"2008","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2008","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2008","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2008","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.7",""
+"2008","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2008","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2008","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2008","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"2008","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2008","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2008","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2008","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.2",""
+"2008","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2008","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2008","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.4",""
+"2008","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.5",""
+"2008","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.2",""
+"2008","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2008","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2008","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2008","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2008","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2008","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2008","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.0",""
+"2008","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2008","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3",""
+"2008","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2008","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2008","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.9",""
+"2008","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2008","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2008","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"2008","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2008","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.7",""
+"2008","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2008","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.3",""
+"2008","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2008","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2008","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3","e"
+"2009","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5","e"
+"2009","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.6",""
+"2009","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2009","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2009","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2009","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","14.2",""
+"2009","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2009","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2009","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"2009","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","8.8",""
+"2009","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.1",""
+"2009","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2009","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2009","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2009","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2009","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2009","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2009","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.4",""
+"2009","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2009","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2009","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2009","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2009","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2009","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2009","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2009","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2009","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.8",""
+"2009","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.3",""
+"2009","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2009","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.2",""
+"2009","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.5",""
+"2009","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2009","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2009","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2009","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2009","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.8",""
+"2009","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.0",""
+"2009","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.2",""
+"2009","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2009","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3",""
+"2009","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2009","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2009","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.7",""
+"2009","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2009","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2009","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2009","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2009","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.0",""
+"2009","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2009","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.2",""
+"2009","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2009","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.5",""
+"2009","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2009","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","European Union - 28 countries","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.9","e"
+"2010","European Union - 28 countries","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5","e"
+"2010","Belgium","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3",""
+"2010","Belgium","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","Bulgaria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2010","Bulgaria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2010","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Denmark","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2010","Denmark","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2010","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2010","Estonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.8",""
+"2010","Estonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Ireland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2010","Ireland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Greece","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2010","Greece","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Spain","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"2010","Spain","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2010","France","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2010","France","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2010","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","Croatia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.2",""
+"2010","Croatia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","Italy","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2010","Italy","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2010","Cyprus","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"2010","Cyprus","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2010","Latvia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2010","Latvia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Lithuania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2010","Lithuania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2010","Luxembourg","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.9",""
+"2010","Luxembourg","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Hungary","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.1",""
+"2010","Hungary","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Malta","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.2",""
+"2010","Malta","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2010","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2010","Austria","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.3",""
+"2010","Austria","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","2.3",""
+"2010","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2010","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2010","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2010","Romania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2010","Romania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Slovenia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.9",""
+"2010","Slovenia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Slovakia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2010","Slovakia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Finland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.3",""
+"2010","Finland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","Sweden","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.9",""
+"2010","Sweden","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","United Kingdom","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2010","United Kingdom","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.5",""
+"2010","Iceland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2010","Iceland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"2010","Liechtenstein","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2010","Liechtenstein","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","5.0",""
+"2010","Norway","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2010","Norway","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.5",""
+"2010","Switzerland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.7",""
+"2010","Switzerland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"2010","North Macedonia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"2010","North Macedonia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2010","Albania","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"2010","Albania","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
diff --git a/your-project/Week 4 - Project/hlth_cd_asdr_Label.csv b/your-project/Week 4 - Project/hlth_cd_asdr_Label.csv
new file mode 100644
index 0000000..87e3aef
--- /dev/null
+++ b/your-project/Week 4 - Project/hlth_cd_asdr_Label.csv	
@@ -0,0 +1,89 @@
+"DATASET: Causes of death - standardised death rate per 100 000 inhabitants - annual data [hlth_cd_asdr]"
+
+"LAST UPDATE: 17.04.19 09:11:17"
+
+"EXTRACTION DATE: 10.09.19 17:53:01"
+
+"SOURCE OF DATA: Eurostat"
+
+"TIME"
+"2001"
+"2002"
+"2003"
+"2004"
+"2005"
+"2006"
+"2007"
+"2008"
+"2009"
+"2010"
+
+"GEO"
+"European Union - 28 countries"
+"Belgium"
+"Bulgaria"
+"Czechia"
+"Denmark"
+"Germany (until 1990 former territory of the FRG)"
+"Estonia"
+"Ireland"
+"Greece"
+"Spain"
+"France"
+"France (metropolitan)"
+"Croatia"
+"Italy"
+"Cyprus"
+"Latvia"
+"Lithuania"
+"Luxembourg"
+"Hungary"
+"Malta"
+"Netherlands"
+"Austria"
+"Poland"
+"Portugal"
+"Romania"
+"Slovenia"
+"Slovakia"
+"Finland"
+"Sweden"
+"United Kingdom"
+"Iceland"
+"Liechtenstein"
+"Norway"
+"Switzerland"
+"North Macedonia"
+"Albania"
+
+"UNIT"
+"Rate"
+
+"SEX"
+"Total"
+
+"AGE"
+"Total"
+
+"ICD10"
+"Mental and behavioural disorders due to use of alcohol"
+"Drug dependence, toxicomania (F11-F16, F18-F19)"
+
+"No footnotes available"
+
+"Available flags:"
+"b","break in time series"
+"c","confidential"
+"d","definition differs, see metadata"
+"e","estimated"
+"f","forecast"
+"n","not significant"
+"p","provisional"
+"r","revised"
+"s","Eurostat estimate"
+"u","low reliability"
+"z","not applicable"
+
+"Special value:"
+":","not available"
+
diff --git a/your-project/Week 4 - Project/legend_ordered_drug_deaths_counrty.png b/your-project/Week 4 - Project/legend_ordered_drug_deaths_counrty.png
new file mode 100644
index 0000000..1afcc1b
Binary files /dev/null and b/your-project/Week 4 - Project/legend_ordered_drug_deaths_counrty.png differ
diff --git a/your-project/Week 4 - Project/ordered_drug_deaths_country.png b/your-project/Week 4 - Project/ordered_drug_deaths_country.png
new file mode 100644
index 0000000..eb62529
Binary files /dev/null and b/your-project/Week 4 - Project/ordered_drug_deaths_country.png differ
diff --git a/your-project/Week 4 - Project/pie13.png b/your-project/Week 4 - Project/pie13.png
new file mode 100644
index 0000000..e0ad9b3
Binary files /dev/null and b/your-project/Week 4 - Project/pie13.png differ
diff --git a/your-project/Week 4 - Project/pie7.png b/your-project/Week 4 - Project/pie7.png
new file mode 100644
index 0000000..e2b43a4
Binary files /dev/null and b/your-project/Week 4 - Project/pie7.png differ
diff --git a/your-project/Week 4 - Project/time_drug_deaths_1_Data.csv b/your-project/Week 4 - Project/time_drug_deaths_1_Data.csv
new file mode 100644
index 0000000..abe40b7
--- /dev/null
+++ b/your-project/Week 4 - Project/time_drug_deaths_1_Data.csv	
@@ -0,0 +1,307 @@
+"TIME","GEO","UNIT","SEX","AGE","ICD10","Value","Flag and Footnotes"
+"1994","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.1",""
+"1994","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"1994","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1994","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","2.5",""
+"1994","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.7",""
+"1994","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.7",""
+"1994","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.2",""
+"1994","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.4",""
+"1994","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"1994","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","2.7",""
+"1994","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"1994","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1994","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1994","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.7",""
+"1994","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1994","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","6.3",""
+"1994","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"1994","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"1995","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1995","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.5",""
+"1995","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"1995","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","2.3",""
+"1995","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.4",""
+"1995","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.7",""
+"1995","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.0",""
+"1995","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"1995","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"1995","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","2.6",""
+"1995","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"1995","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1995","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1995","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"1995","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"1995","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.9",""
+"1995","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.8",""
+"1995","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1996","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1996","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"1996","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"1996","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.8",""
+"1996","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.4",""
+"1996","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.8",""
+"1996","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","5.9",""
+"1996","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"1996","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"1996","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","2.0",""
+"1996","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"1996","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1996","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1996","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"1996","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1996","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","10.3",""
+"1996","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"1996","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1997","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1997","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.4",""
+"1997","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"1997","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.9",""
+"1997","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.5",""
+"1997","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.6",""
+"1997","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","2.2",""
+"1997","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.6",""
+"1997","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"1997","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.1",""
+"1997","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"1997","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"1997","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease",":",""
+"1997","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"1997","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"1997","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.9",""
+"1997","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"1997","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"1998","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1998","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"1998","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"1998","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.7",""
+"1998","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.3",""
+"1998","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.2",""
+"1998","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.7",""
+"1998","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"1998","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.6",""
+"1998","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.8",""
+"1998","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"1998","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"1998","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease",":",""
+"1998","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol",":",""
+"1998","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"1998","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.1",""
+"1998","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"1998","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1999","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"1999","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"1999","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)",":",""
+"1999","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.7",""
+"1999","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","7.0",""
+"1999","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.3",""
+"1999","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.7",""
+"1999","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.3",""
+"1999","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"1999","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.8",""
+"1999","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.8",""
+"1999","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1999","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"1999","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"1999","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"1999","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.9",""
+"1999","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.7",""
+"1999","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2000","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"2000","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.9",""
+"2000","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2000","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.7",""
+"2000","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.2",""
+"2000","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.2",""
+"2000","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.7",""
+"2000","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2000","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2000","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.8",""
+"2000","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.9",""
+"2000","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2000","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2000","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.7",""
+"2000","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2000","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.7",""
+"2000","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","0.6",""
+"2000","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2001","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"2001","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2001","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2001","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.6",""
+"2001","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2001","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2001","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.7",""
+"2001","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2001","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2001","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.7",""
+"2001","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.4",""
+"2001","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2001","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2001","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2001","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","9.3",""
+"2001","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2001","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2002","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease",":",""
+"2002","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2002","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.6",""
+"2002","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.8",""
+"2002","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2002","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.7",""
+"2002","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2002","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2002","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2002","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.8",""
+"2002","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2002","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2002","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.5",""
+"2002","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2002","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","9.2",""
+"2002","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2002","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2003","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease",":",""
+"2003","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.6",""
+"2003","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2003","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.6",""
+"2003","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","6.0",""
+"2003","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2003","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.6",""
+"2003","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2003","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2003","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2003","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2003","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2003","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2003","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2003","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2003","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.9",""
+"2003","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2003","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease",":",""
+"2004","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2004","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2004","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.6",""
+"2004","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2004","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.7",""
+"2004","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.6",""
+"2004","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2004","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2004","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2004","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2004","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2004","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2004","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2004","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.3",""
+"2004","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2004","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"2005","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","2.6",""
+"2005","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2005","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.6",""
+"2005","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.9",""
+"2005","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2005","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.4",""
+"2005","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.3",""
+"2005","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2005","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2005","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2005","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2005","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.3",""
+"2005","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2005","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","8.1",""
+"2005","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2005","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2006","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"2006","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2006","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.6",""
+"2006","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2006","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2006","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.4",""
+"2006","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.9",""
+"2006","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2006","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2006","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2006","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2006","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2006","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"2006","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2006","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","6.6",""
+"2006","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.0",""
+"2006","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2007","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.0",""
+"2007","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2007","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2007","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2007","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.8",""
+"2007","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.2",""
+"2007","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.0",""
+"2007","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2007","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.4",""
+"2007","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2007","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2007","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2007","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2007","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2007","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","7.3",""
+"2007","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.2",""
+"2007","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.1",""
+"2008","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.7",""
+"2008","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2008","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2008","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.6",""
+"2008","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"2008","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","1.1",""
+"2008","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.1",""
+"2008","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2008","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2008","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2008","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2008","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.4",""
+"2008","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.2",""
+"2008","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2008","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","6.6",""
+"2008","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2008","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.1",""
+"2009","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2009","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2009","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.5",""
+"2009","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","1.0",""
+"2009","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.8",""
+"2009","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2009","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.4",""
+"2009","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.4",""
+"2009","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.5",""
+"2009","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2009","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.2",""
+"2009","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.4",""
+"2009","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2009","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","6.1",""
+"2009","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2009","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
+"2010","Czechia","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.1",""
+"2010","Czechia","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.3",""
+"2010","Czechia","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.5",""
+"2010","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","5.7",""
+"2010","Germany (until 1990 former territory of the FRG)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.9",""
+"2010","France (metropolitan)","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.7",""
+"2010","France (metropolitan)","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","4.8",""
+"2010","France (metropolitan)","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.3",""
+"2010","Netherlands","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2010","Netherlands","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.1",""
+"2010","Netherlands","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.1",""
+"2010","Poland","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","0.3",""
+"2010","Poland","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","3.9",""
+"2010","Poland","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.0",""
+"2010","Portugal","Rate","Total","Total","Human immunodeficiency virus [HIV] disease","5.9",""
+"2010","Portugal","Rate","Total","Total","Mental and behavioural disorders due to use of alcohol","1.4",""
+"2010","Portugal","Rate","Total","Total","Drug dependence, toxicomania (F11-F16, F18-F19)","0.2",""
diff --git a/your-project/Week 4 - Project/time_drug_deaths_Label.csv b/your-project/Week 4 - Project/time_drug_deaths_Label.csv
new file mode 100644
index 0000000..6a582a6
--- /dev/null
+++ b/your-project/Week 4 - Project/time_drug_deaths_Label.csv	
@@ -0,0 +1,67 @@
+"DATASET: Causes of death - standardised death rate per 100 000 inhabitants - annual data [hlth_cd_asdr]"
+
+"LAST UPDATE: 17.04.19 09:11:17"
+
+"EXTRACTION DATE: 10.09.19 18:44:02"
+
+"SOURCE OF DATA: Eurostat"
+
+"TIME"
+"1994"
+"1995"
+"1996"
+"1997"
+"1998"
+"1999"
+"2000"
+"2001"
+"2002"
+"2003"
+"2004"
+"2005"
+"2006"
+"2007"
+"2008"
+"2009"
+"2010"
+
+"GEO"
+"Czechia"
+"Germany (until 1990 former territory of the FRG)"
+"France (metropolitan)"
+"Netherlands"
+"Poland"
+"Portugal"
+
+"UNIT"
+"Rate"
+
+"SEX"
+"Total"
+
+"AGE"
+"Total"
+
+"ICD10"
+"Human immunodeficiency virus [HIV] disease"
+"Mental and behavioural disorders due to use of alcohol"
+"Drug dependence, toxicomania (F11-F16, F18-F19)"
+
+"No footnotes available"
+
+"Available flags:"
+"b","break in time series"
+"c","confidential"
+"d","definition differs, see metadata"
+"e","estimated"
+"f","forecast"
+"n","not significant"
+"p","provisional"
+"r","revised"
+"s","Eurostat estimate"
+"u","low reliability"
+"z","not applicable"
+
+"Special value:"
+":","not available"
+
diff --git a/your-project/Week 4 - Project/week4-project.ipynb b/your-project/Week 4 - Project/week4-project.ipynb
new file mode 100644
index 0000000..17bf420
--- /dev/null
+++ b/your-project/Week 4 - Project/week4-project.ipynb	
@@ -0,0 +1,4706 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import scipy.stats as st\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deaths = pd.read_csv(\"hlth_cd_asdr_1_Data.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "      <td>Total</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>1</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                            GEO  UNIT    SEX    AGE  \\\n",
+       "0  2001  European Union - 28 countries  Rate  Total  Total   \n",
+       "1  2001  European Union - 28 countries  Rate  Total  Total   \n",
+       "2  2001                        Belgium  Rate  Total  Total   \n",
+       "\n",
+       "                                               ICD10 Value Flag and Footnotes  \n",
+       "0  Mental and behavioural disorders due to use of...     :                NaN  \n",
+       "1    Drug dependence, toxicomania (F11-F16, F18-F19)     :                NaN  \n",
+       "2  Mental and behavioural disorders due to use of...     :                NaN  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>UNIT</th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Flag and Footnotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>717</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>North Macedonia</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>718</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>719</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>Rate</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     TIME              GEO  UNIT    SEX    AGE  \\\n",
+       "717  2010  North Macedonia  Rate  Total  Total   \n",
+       "718  2010          Albania  Rate  Total  Total   \n",
+       "719  2010          Albania  Rate  Total  Total   \n",
+       "\n",
+       "                                                 ICD10 Value  \\\n",
+       "717    Drug dependence, toxicomania (F11-F16, F18-F19)   0.1   \n",
+       "718  Mental and behavioural disorders due to use of...     :   \n",
+       "719    Drug dependence, toxicomania (F11-F16, F18-F19)     :   \n",
+       "\n",
+       "    Flag and Footnotes  \n",
+       "717                NaN  \n",
+       "718                NaN  \n",
+       "719                NaN  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.tail(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(720, 8)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                            GEO  \\\n",
+       "0  2001  European Union - 28 countries   \n",
+       "1  2001  European Union - 28 countries   \n",
+       "2  2001                        Belgium   \n",
+       "\n",
+       "                                               ICD10 Value  \n",
+       "0  Mental and behavioural disorders due to use of...     :  \n",
+       "1    Drug dependence, toxicomania (F11-F16, F18-F19)     :  \n",
+       "2  Mental and behavioural disorders due to use of...     :  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths1= deaths[[\"TIME\", \"GEO\", \"ICD10\",\"Value\"]]\n",
+    "deaths1.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/pandas/core/indexing.py:494: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  self.obj[item] = s\n"
+     ]
+    }
+   ],
+   "source": [
+    "deaths1.loc[deaths1['Value'].str.startswith(':'), 'Value'] = ''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                            GEO  \\\n",
+       "0  2001  European Union - 28 countries   \n",
+       "1  2001  European Union - 28 countries   \n",
+       "2  2001                        Belgium   \n",
+       "\n",
+       "                                               ICD10 Value  \n",
+       "0  Mental and behavioural disorders due to use of...        \n",
+       "1    Drug dependence, toxicomania (F11-F16, F18-F19)        \n",
+       "2  Mental and behavioural disorders due to use of...        "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths1.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deaths2=deaths1[\"\"!=deaths1[\"Value\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO                                              ICD10 Value\n",
+       "4  2001  Bulgaria  Mental and behavioural disorders due to use of...   1.1\n",
+       "5  2001  Bulgaria    Drug dependence, toxicomania (F11-F16, F18-F19)   0.1\n",
+       "6  2001   Czechia  Mental and behavioural disorders due to use of...   1.1"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths2.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>1.1</td>\n",
+       "      <td>1.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO                                              ICD10 Value  \\\n",
+       "4  2001  Bulgaria  Mental and behavioural disorders due to use of...   1.1   \n",
+       "5  2001  Bulgaria    Drug dependence, toxicomania (F11-F16, F18-F19)   0.1   \n",
+       "6  2001   Czechia  Mental and behavioural disorders due to use of...   1.1   \n",
+       "\n",
+       "   deaths/100k  \n",
+       "4          1.1  \n",
+       "5          0.1  \n",
+       "6          1.1  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deaths2[\"deaths/100k\"] = [float(i) for i in deaths2[\"Value\"]]\n",
+    "deaths2.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Mental and behavioural disorders due to use of alcohol'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "just = [i for i in deaths2[\"ICD10\"]]\n",
+    "just[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    }
+   ],
+   "source": [
+    "plodeath=deaths2[\"Drug dependence, toxicomania (F11-F16, F18-F19)\"==deaths1[\"ICD10\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    }
+   ],
+   "source": [
+    "ploalc=deaths2[\"Mental and behavioural disorders due to use of alcohol\"==deaths1[\"ICD10\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fed4c29a2b0>"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 648x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=ploalc)\n",
+    "g.legend(loc='center right', bbox_to_anchor=(1.5, 0.5), ncol=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fed50d28b38>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=plodeath)\n",
+    "g.legend(loc='center right', bbox_to_anchor=(1.5, 0.5), ncol=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "over10 = deaths2.groupby([\"GEO\", \"ICD10\"], as_index=False).agg({'deaths/100k':'mean'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mental and behavioural disorders due to use of alcohol\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(over10.ICD10[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>0.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>1.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>4.88</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       GEO                                              ICD10  deaths/100k\n",
+       "0  Albania  Mental and behavioural disorders due to use of...         0.20\n",
+       "1  Austria    Drug dependence, toxicomania (F11-F16, F18-F19)         1.99\n",
+       "2  Austria  Mental and behavioural disorders due to use of...         4.88"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "over10.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(34, 3)"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "drudru = over10[\"Drug dependence, toxicomania (F11-F16, F18-F19)\"==over10[\"ICD10\"]]\n",
+    "drudru.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(35, 3)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "suff = over10[\"Mental and behavioural disorders due to use of alcohol\"==over10[\"ICD10\"]]\n",
+    "suff.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "drudru = drudru.drop(columns=[\"ICD10\"]).rename(columns={\"deaths/100k\":\"Drugs: Deaths/100k\"})\n",
+    "suff = suff.drop(columns=[\"ICD10\"]).rename(columns={\"deaths/100k\":\"Alcohol: Deaths/100k\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990</td>\n",
+       "      <td>4.8800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>3.2375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020</td>\n",
+       "      <td>0.6400</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k\n",
+       "0   Austria               1.990                4.8800\n",
+       "1   Belgium               0.425                3.2375\n",
+       "2  Bulgaria               0.020                0.6400"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "alcodrug = drudru.merge(suff)\n",
+    "alcodrug.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990</td>\n",
+       "      <td>4.8800</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>3.2375</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020</td>\n",
+       "      <td>0.6400</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization\n",
+       "0   Austria               1.990                4.8800                No\n",
+       "1   Belgium               0.425                3.2375                No\n",
+       "2  Bulgaria               0.020                0.6400                No"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decr = ['Portugal','Czechia','Netherlands']\n",
+    "alcodrug['Decriminalization'] = ['Yes' if i in decr else 'No' for i in list(alcodrug['GEO'])]\n",
+    "alcodrug.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>2.633333</td>\n",
+       "      <td>2.071429</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>32</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>1.680000</td>\n",
+       "      <td>1.540000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>31</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>3.140000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>0.850000</td>\n",
+       "      <td>5.700000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>European Union - 28 countries</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>3.155556</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 GEO  Drugs: Deaths/100k  \\\n",
+       "16                                           Ireland            2.633333   \n",
+       "0                                            Austria            1.990000   \n",
+       "23                                            Norway            1.790000   \n",
+       "32                                    United Kingdom            1.680000   \n",
+       "31                                       Switzerland            1.550000   \n",
+       "12  Germany (until 1990 former territory of the FRG)            0.850000   \n",
+       "6                                            Denmark            0.733333   \n",
+       "3                                            Croatia            0.566667   \n",
+       "8                      European Union - 28 countries            0.555556   \n",
+       "4                                             Cyprus            0.466667   \n",
+       "\n",
+       "    Alcohol: Deaths/100k Decriminalization  \n",
+       "16              2.071429                No  \n",
+       "0               4.880000                No  \n",
+       "23              4.490000                No  \n",
+       "32              1.540000                No  \n",
+       "31              3.140000                No  \n",
+       "12              5.700000                No  \n",
+       "6              13.933333                No  \n",
+       "3               5.444444                No  \n",
+       "8               3.155556                No  \n",
+       "4               0.571429                No  "
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "topdrug= alcodrug.sort_values(by=\"Drugs: Deaths/100k\", ascending=False)\n",
+    "topdrug.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>10.220000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>0.850000</td>\n",
+       "      <td>5.700000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>28</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>0.150000</td>\n",
+       "      <td>5.640000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>5.290000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>France (metropolitan)</td>\n",
+       "      <td>0.280000</td>\n",
+       "      <td>5.160000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>4.650000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 GEO  Drugs: Deaths/100k  \\\n",
+       "6                                            Denmark            0.733333   \n",
+       "7                                            Estonia            0.125000   \n",
+       "12  Germany (until 1990 former territory of the FRG)            0.850000   \n",
+       "28                                          Slovenia            0.150000   \n",
+       "3                                            Croatia            0.566667   \n",
+       "10                                            France            0.290000   \n",
+       "11                             France (metropolitan)            0.280000   \n",
+       "0                                            Austria            1.990000   \n",
+       "18                                            Latvia            0.033333   \n",
+       "23                                            Norway            1.790000   \n",
+       "\n",
+       "    Alcohol: Deaths/100k Decriminalization  \n",
+       "6              13.933333                No  \n",
+       "7              10.220000                No  \n",
+       "12              5.700000                No  \n",
+       "28              5.640000                No  \n",
+       "3               5.444444                No  \n",
+       "10              5.290000                No  \n",
+       "11              5.160000                No  \n",
+       "0               4.880000                No  \n",
+       "18              4.650000                No  \n",
+       "23              4.490000                No  "
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "topalc = alcodrug.sort_values(by=\"Alcohol: Deaths/100k\", ascending=False)\n",
+    "topalc.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time = pd.read_csv(\"time_drug_deaths_1_Data.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time1=time[\":\"!=time[\"Value\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jan/.local/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \"\"\"Entry point for launching an IPython kernel.\n"
+     ]
+    }
+   ],
+   "source": [
+    "time1[\"deaths/100k\"] = [float(i) for i in time1[\"Value\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "time1 = time1[[\"TIME\",\"GEO\",\"ICD10\",\"deaths/100k\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICD10</th>\n",
+       "      <th>deaths/100k</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Human immunodeficiency virus [HIV] disease</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>0.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Drug dependence, toxicomania (F11-F16, F18-F19)</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>Human immunodeficiency virus [HIV] disease</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>Mental and behavioural disorders due to use of...</td>\n",
+       "      <td>7.7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                                               GEO  \\\n",
+       "0  1994                                           Czechia   \n",
+       "1  1994                                           Czechia   \n",
+       "2  1994                                           Czechia   \n",
+       "3  1994  Germany (until 1990 former territory of the FRG)   \n",
+       "4  1994  Germany (until 1990 former territory of the FRG)   \n",
+       "\n",
+       "                                               ICD10  deaths/100k  \n",
+       "0         Human immunodeficiency virus [HIV] disease          0.1  \n",
+       "1  Mental and behavioural disorders due to use of...          0.6  \n",
+       "2    Drug dependence, toxicomania (F11-F16, F18-F19)          0.1  \n",
+       "3         Human immunodeficiency virus [HIV] disease          2.5  \n",
+       "4  Mental and behavioural disorders due to use of...          7.7  "
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "time1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mental and behavioural disorders due to use of alcohol\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(time1.ICD10[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hiv = time1[\"Human immunodeficiency virus [HIV] disease\"==time1[\"ICD10\"]]\n",
+    "alc = time1[\"Mental and behavioural disorders due to use of alcohol\"==time1[\"ICD10\"]]\n",
+    "dru = time1[\"Drug dependence, toxicomania (F11-F16, F18-F19)\"==time1[\"ICD10\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed4ec6bef0>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=hiv)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed4eb8fa20>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=alc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed50da6e80>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x='TIME', y='deaths/100k', hue = 'GEO', data=dru)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "modern = pd.read_excel(\"drugs2011-16.xls\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>EU (28 countries)</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Euro area (19 countries)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>0.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>0.94</td>\n",
+       "      <td>0.96</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.08</td>\n",
+       "      <td>1.04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.24</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>0.34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>0.22</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.18</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Lithuania</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.89</td>\n",
+       "      <td>0.91</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Hungary</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>Malta</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>Netherlands</td>\n",
+       "      <td>0.11</td>\n",
+       "      <td>0.11</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>2.66</td>\n",
+       "      <td>2.53</td>\n",
+       "      <td>2.25</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>1.42</td>\n",
+       "      <td>1.13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>Poland</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>Romania</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>Slovakia</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.46</td>\n",
+       "      <td>0.44</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>28</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>0.14</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>29</td>\n",
+       "      <td>United Kingdom</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.22</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.36</td>\n",
+       "      <td>0.29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>30</td>\n",
+       "      <td>Iceland</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>31</td>\n",
+       "      <td>Liechtenstein</td>\n",
+       "      <td>2.7</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>2.16</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>32</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.64</td>\n",
+       "      <td>0.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>33</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>0.66</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>0.56</td>\n",
+       "      <td>0.71</td>\n",
+       "      <td>0.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>34</td>\n",
+       "      <td>Montenegro</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>35</td>\n",
+       "      <td>North Macedonia</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>36</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>37</td>\n",
+       "      <td>Serbia</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.22</td>\n",
+       "      <td>0.12</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         geo  2011  2012  2013  2014  2015  2016\n",
+       "0          EU (28 countries)   0.3  0.31  0.31   0.3  0.34  0.34\n",
+       "1   Euro area (19 countries)     :     :     :     :     :     :\n",
+       "2                    Belgium  0.27  0.32  0.25  0.38  0.29  0.48\n",
+       "3                   Bulgaria   0.1  0.04  0.04     :  0.01  0.07\n",
+       "4                    Czechia  0.04  0.04  0.05  0.04  0.06  0.03\n",
+       "5                    Denmark   0.8  0.42  0.45  0.48  0.53  0.61\n",
+       "6                    Germany  0.86  0.94  0.96     1  1.08  1.04\n",
+       "7                    Estonia  0.06     :     :  0.07  0.15     :\n",
+       "8                    Ireland     :  0.04     :     :  0.02     :\n",
+       "9                     Greece  0.04  0.03  0.04     :  0.01  0.01\n",
+       "10                     Spain  0.06  0.07  0.04  0.05  0.05  0.05\n",
+       "11                    France  0.25  0.23  0.24  0.21  0.25  0.36\n",
+       "12                   Croatia  0.12  0.16  0.16  0.26  0.19  0.34\n",
+       "13                     Italy  0.22  0.21  0.18  0.17  0.17  0.14\n",
+       "14                    Cyprus     :     :     :     :     :  0.13\n",
+       "15                    Latvia  0.04     :   0.1   0.1  0.19   0.1\n",
+       "16                 Lithuania  0.03  0.07  0.06     :  0.07  0.11\n",
+       "17                Luxembourg     :     :  0.89  0.91   0.8  1.15\n",
+       "18                   Hungary  0.05  0.05  0.01  0.04  0.08  0.03\n",
+       "19                     Malta     :     :     :     :     :  0.21\n",
+       "20               Netherlands  0.11  0.11  0.16  0.16  0.21  0.27\n",
+       "21                   Austria  2.66  2.53  2.25  1.56  1.42  1.13\n",
+       "22                    Poland  0.01     0  0.02  0.01  0.01  0.02\n",
+       "23                  Portugal  0.06  0.12  0.09  0.05   0.1  0.03\n",
+       "24                   Romania  0.01     0  0.02  0.03  0.01  0.03\n",
+       "25                  Slovenia     :  0.05  0.23     :     :  0.14\n",
+       "26                  Slovakia     :  0.01  0.05  0.02  0.01     :\n",
+       "27                   Finland  0.26   0.5  0.46  0.44  0.32  0.81\n",
+       "28                    Sweden  0.15  0.14  0.16  0.23  0.23  0.26\n",
+       "29            United Kingdom  0.21  0.22  0.26  0.26  0.36  0.29\n",
+       "30                   Iceland     :     :  0.73     :     :     :\n",
+       "31             Liechtenstein   2.7     :     :     :  2.16     :\n",
+       "32                    Norway  0.57  0.63   0.5  0.31  0.64   0.4\n",
+       "33               Switzerland  0.57  0.66  0.63  0.56  0.71  0.81\n",
+       "34                Montenegro     :     :     :     :     :     :\n",
+       "35           North Macedonia     :     :     :     :     :     :\n",
+       "36                   Albania     :     :     :     :     :     :\n",
+       "37                    Serbia  0.21   0.1  0.12   0.2  0.22  0.12"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_columns = [\"geo\", \"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\"]\n",
+    "modern.columns=new_columns\n",
+    "modern.head(40)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.317, 'NaN', 0.332, 0.052, 0.043, 0.548, 0.98, 0.093, 0.03, 0.026, 0.053, 0.257, 0.205, 0.182, 0.13, 0.106, 0.068, 0.938, 0.043, 0.21, 0.17, 1.925, 0.012, 0.075, 0.017, 0.14, 0.022, 0.465, 0.195, 0.267, 0.73, 2.43, 0.508, 0.657, 'NaN', 'NaN', 'NaN', 0.162]\n"
+     ]
+    }
+   ],
+   "source": [
+    "m11=list(modern['2011'])\n",
+    "m12=list(modern['2012'])\n",
+    "m13=list(modern['2013'])\n",
+    "m14=list(modern['2014'])\n",
+    "m15=list(modern['2015'])\n",
+    "m16=list(modern['2016'])\n",
+    "\n",
+    "test = ['1.1', '0.3', ':', '1.2', 0.4]\n",
+    "def unpoint (x):\n",
+    "    s = [float(i) for i in x if i !=':']\n",
+    "    if len(s)!=0:\n",
+    "        return round(sum(s)/len(s), 3)\n",
+    "    else:\n",
+    "        return 'NaN'\n",
+    "\n",
+    "def unpoint_mean (a,b,c,d,e,f):\n",
+    "    #lst = [(sum([float(a[i]), float(b[i]), float(c[i]), d[i], e[i], f[i]])/len([a[i], b[i], c[i], d[i], e[i], f[i]])) if i!= ':' for i in range len(m11)\n",
+    "    #return [([a[i], b[i], c[i], d[i], e[i], f[i]]) for i in range(len(a))]\n",
+    "    #return [([a[i] if a[i]!=':', b[i] if b[i]!=':', c[i] if c[i]!=':', d[i] if d[i]!=':', e[i] if e[i]!=':', f[i]] if f[i]!=':') for i in range(len(a))]\n",
+    "    lst = [([a[i], b[i], c[i], d[i], e[i], f[i]]) for i in range(len(a))]\n",
+    "    return [unpoint(i) for i in lst]\n",
+    "    \n",
+    "\n",
+    "\n",
+    "print(unpoint_mean(m11,m12,m13,m14,m15,m16))\n",
+    "#print(unpoint(test))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>EU (28 countries)</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Euro area (19 countries)</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.043</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        geo  2011  2012  2013  2014  2015  2016   Mean\n",
+       "0         EU (28 countries)   0.3  0.31  0.31   0.3  0.34  0.34  0.317\n",
+       "1  Euro area (19 countries)     :     :     :     :     :     :    NaN\n",
+       "2                   Belgium  0.27  0.32  0.25  0.38  0.29  0.48  0.332\n",
+       "3                  Bulgaria   0.1  0.04  0.04     :  0.01  0.07  0.052\n",
+       "4                   Czechia  0.04  0.04  0.05  0.04  0.06  0.03  0.043"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "modern[\"Mean\"]=unpoint_mean(m11,m12,m13,m14,m15,m16)\n",
+    "modern.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"\\nmod = modern\\nmod.loc[mod['2011'].str.startswith(':'), '11'] = None\\nmod.head()\\n\""
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#tst = ['0.3', ':', '0.1']\n",
+    "\"\"\"\n",
+    "premean = modern.drop(columns=[\"geo\"])\n",
+    "def summarize (a,b,c,d,e,f):\n",
+    "    x=[a,b,c,d,e,f]\n",
+    "    x1 = [float(i) for i in x if i!=':']\n",
+    "    return sum(x1)/len(x1)\n",
+    "# df.apply(lambda x: func(x['col1'],x['col2']),axis=1)\n",
+    "modern[\"Mean\"] = modern.apply(lambda x: summarize(modern[\"2011\"],modern[\"2012\"],modern[\"2013\"],modern[\"2014\"],modern[\"2015\"],modern[\"2016\"]), axis=1)\n",
+    "#summarize(tst)\n",
+    "modern.head()\n",
+    "\"\"\"\n",
+    "\n",
+    "\"\"\"\n",
+    "mod = modern\n",
+    "mod.loc[mod['2011'].str.startswith(':'), '11'] = None\n",
+    "mod.head()\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>geo</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>EU (28 countries)</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.42</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.53</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>0.548</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 geo  2011  2012  2013  2014  2015  2016   Mean\n",
+       "0  EU (28 countries)   0.3  0.31  0.31   0.3  0.34  0.34  0.317\n",
+       "2            Belgium  0.27  0.32  0.25  0.38  0.29  0.48  0.332\n",
+       "3           Bulgaria   0.1  0.04  0.04     :  0.01  0.07  0.052\n",
+       "4            Czechia  0.04  0.04  0.05  0.04  0.06  0.03  0.043\n",
+       "5            Denmark   0.8  0.42  0.45  0.48  0.53  0.61  0.548"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "modern = modern[(\"NaN\"!=(modern['Mean']))]\n",
+    "modern.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#decr = ['Portugal','Czechia','Netherlands']\n",
+    "#modern['Decriminalization'] = ['Yes' if i in decr else 'No' for i in list(modern['geo'])]\n",
+    "#modern.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>ICCS</th>\n",
+       "      <th>UNIT</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Flag and Footnotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>139.25</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>38.00</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>27.19</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>369.99</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Germany (until 1990 former territory of the FRG)</td>\n",
+       "      <td>Unlawful acts involving controlled drugs or pr...</td>\n",
+       "      <td>Per hundred thousand inhabitants</td>\n",
+       "      <td>291.85</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME                                               GEO  \\\n",
+       "0  2008                                           Belgium   \n",
+       "1  2008                                          Bulgaria   \n",
+       "2  2008                                           Czechia   \n",
+       "3  2008                                           Denmark   \n",
+       "4  2008  Germany (until 1990 former territory of the FRG)   \n",
+       "\n",
+       "                                                ICCS  \\\n",
+       "0  Unlawful acts involving controlled drugs or pr...   \n",
+       "1  Unlawful acts involving controlled drugs or pr...   \n",
+       "2  Unlawful acts involving controlled drugs or pr...   \n",
+       "3  Unlawful acts involving controlled drugs or pr...   \n",
+       "4  Unlawful acts involving controlled drugs or pr...   \n",
+       "\n",
+       "                               UNIT   Value  Flag and Footnotes  \n",
+       "0  Per hundred thousand inhabitants  139.25                 NaN  \n",
+       "1  Per hundred thousand inhabitants   38.00                 NaN  \n",
+       "2  Per hundred thousand inhabitants   27.19                 NaN  \n",
+       "3  Per hundred thousand inhabitants  369.99                 NaN  \n",
+       "4  Per hundred thousand inhabitants  291.85                 NaN  "
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "precrimes = pd.read_csv(\"crim_off_cat_1_Data.csv\")\n",
+    "precrimes.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>139.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>38.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>27.19</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO   Value\n",
+       "0  2008   Belgium  139.25\n",
+       "1  2008  Bulgaria   38.00\n",
+       "2  2008   Czechia   27.19"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crimes = precrimes.drop(columns=precrimes[[\"ICCS\",\"Flag and Footnotes\", \"UNIT\"]])\n",
+    "crimes.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "crimes = crimes[(\":\"!=(crimes['Value']))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>TIME</th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>139.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>38.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>27.19</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   TIME       GEO   Value\n",
+       "0  2008   Belgium  139.25\n",
+       "1  2008  Bulgaria   38.00\n",
+       "2  2008   Czechia   27.19"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crimes['Value'] = [float(i.replace(',','')) for i in crimes['Value']]\n",
+    "crimes.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>56.417143</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>177.115556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>269.883000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       GEO       Value\n",
+       "0  Albania   56.417143\n",
+       "1  Austria  177.115556\n",
+       "2  Belgium  269.883000"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crime_mean = crimes.groupby(crimes[\"GEO\"], as_index=False).agg({'Value':'mean'})\n",
+    "crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#decr = ['Portugal','Czechia','Netherlands']\n",
+    "\n",
+    "#crime_mean.loc[(crime_mean['GEO']!=('Portugal') or (crime_mean['GEO']!='Czechia') or (crime_mean['GEO']!='Netherlands')),'Decrimalization'] = 'No'\n",
+    "#crime_mean[\"Decriminalization\"]='No'\n",
+    "#crime_mean.loc[(crime_mean['GEO']==('Portugal') or (crime_mean['GEO']=='Czechia') or (crime_mean['GEO']=='Netherlands')),'Decrimalization'] = 'Yes'\n",
+    "#crime_mean['Decriminalization'] = np.where((crime_mean['GEO']=='Portugal' or crime_mean['GEO']=='Netherlands' or crime_mean['GEO']=='Czechia'), 'Yes', 'No')\n",
+    "#crime_mean['Decriminalization'] = np.where((crime_mean['GEO'] in decr), 'Yes', 'No')\n",
+    "\n",
+    "#crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Albania</td>\n",
+       "      <td>56.417143</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>177.115556</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>269.883000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       GEO       Value Decriminalization\n",
+       "0  Albania   56.417143                No\n",
+       "1  Austria  177.115556                No\n",
+       "2  Belgium  269.883000                No"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decr = ['Portugal','Czechia','Netherlands']\n",
+    "crime_mean['Decriminalization'] = ['Yes' if i in decr else 'No' for i in list(crime_mean['GEO'])]\n",
+    "crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Value</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>39</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1041.335000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Liechtenstein</td>\n",
+       "      <td>1010.723333</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>38</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>974.664000</td>\n",
+       "      <td>No</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              GEO        Value Decriminalization\n",
+       "39    Switzerland  1041.335000                No\n",
+       "21  Liechtenstein  1010.723333                No\n",
+       "38         Sweden   974.664000                No"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sorted_crime_mean = crime_mean.sort_values(by='Value', ascending=False)\n",
+    "sorted_crime_mean.head(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "      <th>2011</th>\n",
+       "      <th>2012</th>\n",
+       "      <th>2013</th>\n",
+       "      <th>2014</th>\n",
+       "      <th>2015</th>\n",
+       "      <th>2016</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2.66</td>\n",
+       "      <td>2.53</td>\n",
+       "      <td>2.25</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>1.42</td>\n",
+       "      <td>1.13</td>\n",
+       "      <td>1.925</td>\n",
+       "      <td>177.115556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425000</td>\n",
+       "      <td>3.237500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>0.48</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>269.883000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>0.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.052</td>\n",
+       "      <td>49.573000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.26</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>0.205</td>\n",
+       "      <td>126.765556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>:</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>109.241000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization  2011  \\\n",
+       "0   Austria            1.990000              4.880000                No  2.66   \n",
+       "1   Belgium            0.425000              3.237500                No  0.27   \n",
+       "2  Bulgaria            0.020000              0.640000                No   0.1   \n",
+       "3   Croatia            0.566667              5.444444                No  0.12   \n",
+       "4    Cyprus            0.466667              0.571429                No     :   \n",
+       "\n",
+       "   2012  2013  2014  2015  2016 Drug Deaths: Mean 2011-16  Drug related crimes  \n",
+       "0  2.53  2.25  1.56  1.42  1.13                     1.925           177.115556  \n",
+       "1  0.32  0.25  0.38  0.29  0.48                     0.332           269.883000  \n",
+       "2  0.04  0.04     :  0.01  0.07                     0.052            49.573000  \n",
+       "3  0.16  0.16  0.26  0.19  0.34                     0.205           126.765556  \n",
+       "4     :     :     :     :  0.13                      0.13           109.241000  "
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crime_mean = crime_mean.rename(columns={\"Value\": \"Drug related crimes\"})\n",
+    "modern = modern.rename(columns={'geo':'GEO', 'Mean':'Drug Deaths: Mean 2011-16'})\n",
+    "alls = alcodrug.merge(modern)\n",
+    "alls = alls.merge(crime_mean)\n",
+    "alls.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(28, 12)"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "alls.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>1.925</td>\n",
+       "      <td>177.115556</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425000</td>\n",
+       "      <td>3.237500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>269.883000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>0.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.052</td>\n",
+       "      <td>49.573000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.205</td>\n",
+       "      <td>126.765556</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>109.241000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>41.638000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.548</td>\n",
+       "      <td>419.544000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>10.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.093</td>\n",
+       "      <td>365.880000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>0.340000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>396.871000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>5.290000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.257</td>\n",
+       "      <td>75.882000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>0.028571</td>\n",
+       "      <td>0.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>101.286000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>Hungary</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.450000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>57.196000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Iceland</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.73</td>\n",
+       "      <td>562.196000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>2.633333</td>\n",
+       "      <td>2.071429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>387.311000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>0.387500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.182</td>\n",
+       "      <td>56.924000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>4.650000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.106</td>\n",
+       "      <td>123.566000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Lithuania</td>\n",
+       "      <td>0.310000</td>\n",
+       "      <td>0.980000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.068</td>\n",
+       "      <td>79.516000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>0.350000</td>\n",
+       "      <td>4.462500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.938</td>\n",
+       "      <td>564.701000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Netherlands</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>1.490000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>93.352000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>814.233000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>Poland</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>4.400000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>174.743000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>0.130000</td>\n",
+       "      <td>1.230000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.075</td>\n",
+       "      <td>46.205000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>Romania</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>17.285000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Slovakia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.022</td>\n",
+       "      <td>21.355000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>0.150000</td>\n",
+       "      <td>5.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.14</td>\n",
+       "      <td>81.550000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>0.190000</td>\n",
+       "      <td>0.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.053</td>\n",
+       "      <td>29.752000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>0.300000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.195</td>\n",
+       "      <td>974.664000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>3.140000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.657</td>\n",
+       "      <td>1041.335000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization  \\\n",
+       "0       Austria            1.990000              4.880000                No   \n",
+       "1       Belgium            0.425000              3.237500                No   \n",
+       "2      Bulgaria            0.020000              0.640000                No   \n",
+       "3       Croatia            0.566667              5.444444                No   \n",
+       "4        Cyprus            0.466667              0.571429                No   \n",
+       "5       Czechia            0.000000              1.550000               Yes   \n",
+       "6       Denmark            0.733333             13.933333                No   \n",
+       "7       Estonia            0.125000             10.220000                No   \n",
+       "8       Finland            0.340000              3.780000                No   \n",
+       "9        France            0.290000              5.290000                No   \n",
+       "10       Greece            0.028571              0.220000                No   \n",
+       "11      Hungary            0.000000              4.450000                No   \n",
+       "12      Iceland            0.450000              1.600000                No   \n",
+       "13      Ireland            2.633333              2.071429                No   \n",
+       "14        Italy            0.450000              0.387500                No   \n",
+       "15       Latvia            0.033333              4.650000                No   \n",
+       "16    Lithuania            0.310000              0.980000                No   \n",
+       "17   Luxembourg            0.350000              4.462500                No   \n",
+       "18  Netherlands            0.100000              1.490000               Yes   \n",
+       "19       Norway            1.790000              4.490000                No   \n",
+       "20       Poland            0.040000              4.400000                No   \n",
+       "21     Portugal            0.130000              1.230000               Yes   \n",
+       "22      Romania            0.000000              2.780000                No   \n",
+       "23     Slovakia            0.033333              0.000000                No   \n",
+       "24     Slovenia            0.150000              5.640000                No   \n",
+       "25        Spain            0.190000              0.780000                No   \n",
+       "26       Sweden            0.300000              3.780000                No   \n",
+       "27  Switzerland            1.550000              3.140000                No   \n",
+       "\n",
+       "   Drug Deaths: Mean 2011-16  Drug related crimes  Decr.: 0 or 1  \n",
+       "0                      1.925           177.115556              0  \n",
+       "1                      0.332           269.883000              0  \n",
+       "2                      0.052            49.573000              0  \n",
+       "3                      0.205           126.765556              0  \n",
+       "4                       0.13           109.241000              0  \n",
+       "5                      0.043            41.638000              1  \n",
+       "6                      0.548           419.544000              0  \n",
+       "7                      0.093           365.880000              0  \n",
+       "8                      0.465           396.871000              0  \n",
+       "9                      0.257            75.882000              0  \n",
+       "10                     0.026           101.286000              0  \n",
+       "11                     0.043            57.196000              0  \n",
+       "12                      0.73           562.196000              0  \n",
+       "13                      0.03           387.311000              0  \n",
+       "14                     0.182            56.924000              0  \n",
+       "15                     0.106           123.566000              0  \n",
+       "16                     0.068            79.516000              0  \n",
+       "17                     0.938           564.701000              0  \n",
+       "18                      0.17            93.352000              1  \n",
+       "19                     0.508           814.233000              0  \n",
+       "20                     0.012           174.743000              0  \n",
+       "21                     0.075            46.205000              1  \n",
+       "22                     0.017            17.285000              0  \n",
+       "23                     0.022            21.355000              0  \n",
+       "24                      0.14            81.550000              0  \n",
+       "25                     0.053            29.752000              0  \n",
+       "26                     0.195           974.664000              0  \n",
+       "27                     0.657          1041.335000              0  "
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "allinone = alls.drop(columns=alls[[\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\"]])\n",
+    "allinone[\"Decr.: 0 or 1\"]=[1 if i in decr else 0 for i in list(allinone['GEO'])]\n",
+    "allinone.head(30)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "allinone['Drug Deaths: Mean 2011-16']=[float(i) for i in allinone['Drug Deaths: Mean 2011-16']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>Drugs: Deaths/100k</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>-0.212064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Alcohol: Deaths/100k</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>-0.230574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug Deaths: Mean 2011-16</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>-0.166038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug related crimes</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.240490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Decr.: 0 or 1</td>\n",
+       "      <td>-0.212064</td>\n",
+       "      <td>-0.230574</td>\n",
+       "      <td>-0.166038</td>\n",
+       "      <td>-0.240490</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           Drugs: Deaths/100k  Alcohol: Deaths/100k  \\\n",
+       "Drugs: Deaths/100k                   1.000000              0.113377   \n",
+       "Alcohol: Deaths/100k                 0.113377              1.000000   \n",
+       "Drug Deaths: Mean 2011-16            0.518156              0.254011   \n",
+       "Drug related crimes                  0.477380              0.265929   \n",
+       "Decr.: 0 or 1                       -0.212064             -0.230574   \n",
+       "\n",
+       "                           Drug Deaths: Mean 2011-16  Drug related crimes  \\\n",
+       "Drugs: Deaths/100k                          0.518156             0.477380   \n",
+       "Alcohol: Deaths/100k                        0.254011             0.265929   \n",
+       "Drug Deaths: Mean 2011-16                   1.000000             0.367619   \n",
+       "Drug related crimes                         0.367619             1.000000   \n",
+       "Decr.: 0 or 1                              -0.166038            -0.240490   \n",
+       "\n",
+       "                           Decr.: 0 or 1  \n",
+       "Drugs: Deaths/100k             -0.212064  \n",
+       "Alcohol: Deaths/100k           -0.230574  \n",
+       "Drug Deaths: Mean 2011-16      -0.166038  \n",
+       "Drug related crimes            -0.240490  \n",
+       "Decr.: 0 or 1                   1.000000  "
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "corr = allinone.corr()\n",
+    "corr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fed50e73ba8>"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "sns.heatmap(corr, annot=True)\n",
+    "#allinone.corr().style.background_gradient(cmap='Blues')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>GEO</th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Decriminalization</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "      <th>Badness_index</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>Romania</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>17.285000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.293845</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>Slovakia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.022</td>\n",
+       "      <td>21.355000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.469810</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>0.190000</td>\n",
+       "      <td>0.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.053</td>\n",
+       "      <td>29.752000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.576856</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>Czechia</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>41.638000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.790434</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>Poland</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>4.400000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>174.743000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.096916</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>Hungary</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.450000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>57.196000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.459428</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>Bulgaria</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>0.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.052</td>\n",
+       "      <td>49.573000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.577796</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>0.028571</td>\n",
+       "      <td>0.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>101.286000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.633436</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>0.130000</td>\n",
+       "      <td>1.230000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.075</td>\n",
+       "      <td>46.205000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.465375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>Lithuania</td>\n",
+       "      <td>0.310000</td>\n",
+       "      <td>0.980000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.068</td>\n",
+       "      <td>79.516000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5.407088</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>0.387500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.182</td>\n",
+       "      <td>56.924000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>10.360168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>Slovenia</td>\n",
+       "      <td>0.150000</td>\n",
+       "      <td>5.640000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.140</td>\n",
+       "      <td>81.550000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11.417000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>2.633333</td>\n",
+       "      <td>2.071429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.030</td>\n",
+       "      <td>387.311000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11.619330</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>Latvia</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>4.650000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.106</td>\n",
+       "      <td>123.566000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13.097996</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>Cyprus</td>\n",
+       "      <td>0.466667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.130</td>\n",
+       "      <td>109.241000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>14.201330</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>Netherlands</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>1.490000</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>0.170</td>\n",
+       "      <td>93.352000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>15.869840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>France</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>5.290000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.257</td>\n",
+       "      <td>75.882000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>19.501674</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>Croatia</td>\n",
+       "      <td>0.566667</td>\n",
+       "      <td>5.444444</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.205</td>\n",
+       "      <td>126.765556</td>\n",
+       "      <td>0</td>\n",
+       "      <td>25.986939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>Estonia</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>10.220000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.093</td>\n",
+       "      <td>365.880000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>34.026840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>Belgium</td>\n",
+       "      <td>0.425000</td>\n",
+       "      <td>3.237500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>269.883000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>89.601156</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>0.340000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>396.871000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>184.545015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>0.300000</td>\n",
+       "      <td>3.780000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.195</td>\n",
+       "      <td>974.664000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>190.059480</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>Denmark</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>13.933333</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.548</td>\n",
+       "      <td>419.544000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>229.910112</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>1.990000</td>\n",
+       "      <td>4.880000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>1.925</td>\n",
+       "      <td>177.115556</td>\n",
+       "      <td>0</td>\n",
+       "      <td>340.947444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>Iceland</td>\n",
+       "      <td>0.450000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.730</td>\n",
+       "      <td>562.196000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>410.403080</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>1.790000</td>\n",
+       "      <td>4.490000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>814.233000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>413.630364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>Luxembourg</td>\n",
+       "      <td>0.350000</td>\n",
+       "      <td>4.462500</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.938</td>\n",
+       "      <td>564.701000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>529.689538</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>1.550000</td>\n",
+       "      <td>3.140000</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.657</td>\n",
+       "      <td>1041.335000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>684.157095</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            GEO  Drugs: Deaths/100k  Alcohol: Deaths/100k Decriminalization  \\\n",
+       "22      Romania            0.000000              2.780000                No   \n",
+       "23     Slovakia            0.033333              0.000000                No   \n",
+       "25        Spain            0.190000              0.780000                No   \n",
+       "5       Czechia            0.000000              1.550000               Yes   \n",
+       "20       Poland            0.040000              4.400000                No   \n",
+       "11      Hungary            0.000000              4.450000                No   \n",
+       "2      Bulgaria            0.020000              0.640000                No   \n",
+       "10       Greece            0.028571              0.220000                No   \n",
+       "21     Portugal            0.130000              1.230000               Yes   \n",
+       "16    Lithuania            0.310000              0.980000                No   \n",
+       "14        Italy            0.450000              0.387500                No   \n",
+       "24     Slovenia            0.150000              5.640000                No   \n",
+       "13      Ireland            2.633333              2.071429                No   \n",
+       "15       Latvia            0.033333              4.650000                No   \n",
+       "4        Cyprus            0.466667              0.571429                No   \n",
+       "18  Netherlands            0.100000              1.490000               Yes   \n",
+       "9        France            0.290000              5.290000                No   \n",
+       "3       Croatia            0.566667              5.444444                No   \n",
+       "7       Estonia            0.125000             10.220000                No   \n",
+       "1       Belgium            0.425000              3.237500                No   \n",
+       "8       Finland            0.340000              3.780000                No   \n",
+       "26       Sweden            0.300000              3.780000                No   \n",
+       "6       Denmark            0.733333             13.933333                No   \n",
+       "0       Austria            1.990000              4.880000                No   \n",
+       "12      Iceland            0.450000              1.600000                No   \n",
+       "19       Norway            1.790000              4.490000                No   \n",
+       "17   Luxembourg            0.350000              4.462500                No   \n",
+       "27  Switzerland            1.550000              3.140000                No   \n",
+       "\n",
+       "    Drug Deaths: Mean 2011-16  Drug related crimes  Decr.: 0 or 1  \\\n",
+       "22                      0.017            17.285000              0   \n",
+       "23                      0.022            21.355000              0   \n",
+       "25                      0.053            29.752000              0   \n",
+       "5                       0.043            41.638000              1   \n",
+       "20                      0.012           174.743000              0   \n",
+       "11                      0.043            57.196000              0   \n",
+       "2                       0.052            49.573000              0   \n",
+       "10                      0.026           101.286000              0   \n",
+       "21                      0.075            46.205000              1   \n",
+       "16                      0.068            79.516000              0   \n",
+       "14                      0.182            56.924000              0   \n",
+       "24                      0.140            81.550000              0   \n",
+       "13                      0.030           387.311000              0   \n",
+       "15                      0.106           123.566000              0   \n",
+       "4                       0.130           109.241000              0   \n",
+       "18                      0.170            93.352000              1   \n",
+       "9                       0.257            75.882000              0   \n",
+       "3                       0.205           126.765556              0   \n",
+       "7                       0.093           365.880000              0   \n",
+       "1                       0.332           269.883000              0   \n",
+       "8                       0.465           396.871000              0   \n",
+       "26                      0.195           974.664000              0   \n",
+       "6                       0.548           419.544000              0   \n",
+       "0                       1.925           177.115556              0   \n",
+       "12                      0.730           562.196000              0   \n",
+       "19                      0.508           814.233000              0   \n",
+       "17                      0.938           564.701000              0   \n",
+       "27                      0.657          1041.335000              0   \n",
+       "\n",
+       "    Badness_index  \n",
+       "22       0.293845  \n",
+       "23       0.469810  \n",
+       "25       1.576856  \n",
+       "5        1.790434  \n",
+       "20       2.096916  \n",
+       "11       2.459428  \n",
+       "2        2.577796  \n",
+       "10       2.633436  \n",
+       "21       3.465375  \n",
+       "16       5.407088  \n",
+       "14      10.360168  \n",
+       "24      11.417000  \n",
+       "13      11.619330  \n",
+       "15      13.097996  \n",
+       "4       14.201330  \n",
+       "18      15.869840  \n",
+       "9       19.501674  \n",
+       "3       25.986939  \n",
+       "7       34.026840  \n",
+       "1       89.601156  \n",
+       "8      184.545015  \n",
+       "26     190.059480  \n",
+       "6      229.910112  \n",
+       "0      340.947444  \n",
+       "12     410.403080  \n",
+       "19     413.630364  \n",
+       "17     529.689538  \n",
+       "27     684.157095  "
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "checkstuff = allinone\n",
+    "checkstuff[\"Badness_index\"] = checkstuff[\"Drug Deaths: Mean 2011-16\"]*checkstuff[\"Drug related crimes\"]\n",
+    "checkstuff.sort_values(by=\"Badness_index\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Drug Deaths: Mean 2011-16</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "      <th>Badness_index</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>Drugs: Deaths/100k</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>-0.212064</td>\n",
+       "      <td>0.489576</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Alcohol: Deaths/100k</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>-0.230574</td>\n",
+       "      <td>0.207791</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug Deaths: Mean 2011-16</td>\n",
+       "      <td>0.518156</td>\n",
+       "      <td>0.254011</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>-0.166038</td>\n",
+       "      <td>0.719648</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug related crimes</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>0.367619</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.240490</td>\n",
+       "      <td>0.810887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Decr.: 0 or 1</td>\n",
+       "      <td>-0.212064</td>\n",
+       "      <td>-0.230574</td>\n",
+       "      <td>-0.166038</td>\n",
+       "      <td>-0.240490</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.203978</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Badness_index</td>\n",
+       "      <td>0.489576</td>\n",
+       "      <td>0.207791</td>\n",
+       "      <td>0.719648</td>\n",
+       "      <td>0.810887</td>\n",
+       "      <td>-0.203978</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           Drugs: Deaths/100k  Alcohol: Deaths/100k  \\\n",
+       "Drugs: Deaths/100k                   1.000000              0.113377   \n",
+       "Alcohol: Deaths/100k                 0.113377              1.000000   \n",
+       "Drug Deaths: Mean 2011-16            0.518156              0.254011   \n",
+       "Drug related crimes                  0.477380              0.265929   \n",
+       "Decr.: 0 or 1                       -0.212064             -0.230574   \n",
+       "Badness_index                        0.489576              0.207791   \n",
+       "\n",
+       "                           Drug Deaths: Mean 2011-16  Drug related crimes  \\\n",
+       "Drugs: Deaths/100k                          0.518156             0.477380   \n",
+       "Alcohol: Deaths/100k                        0.254011             0.265929   \n",
+       "Drug Deaths: Mean 2011-16                   1.000000             0.367619   \n",
+       "Drug related crimes                         0.367619             1.000000   \n",
+       "Decr.: 0 or 1                              -0.166038            -0.240490   \n",
+       "Badness_index                               0.719648             0.810887   \n",
+       "\n",
+       "                           Decr.: 0 or 1  Badness_index  \n",
+       "Drugs: Deaths/100k             -0.212064       0.489576  \n",
+       "Alcohol: Deaths/100k           -0.230574       0.207791  \n",
+       "Drug Deaths: Mean 2011-16      -0.166038       0.719648  \n",
+       "Drug related crimes            -0.240490       0.810887  \n",
+       "Decr.: 0 or 1                   1.000000      -0.203978  \n",
+       "Badness_index                  -0.203978       1.000000  "
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "checkstuff.corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prerely = allinone.sort_values(by=\"Drugs: Deaths/100k\", ascending=False)\n",
+    "rely = sns.relplot(x=\"GEO\", y=\"Drugs: Deaths/100k\",  hue=\"Decriminalization\", size='Drug related crimes', sizes = (50,250), palette=\"pastel\", data=prerely);\n",
+    "rely.set_xticklabels(rotation=45, horizontalalignment = 'right')\n",
+    "plt.xlabel('Countries',fontsize=12, fontweight=\"bold\")\n",
+    "plt.ylabel('Drugs: Deaths/100k',fontsize=12, fontweight=\"bold\")\n",
+    "rely.fig.set_size_inches(15,5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rely = sns.relplot(x=\"GEO\", y=\"Drugs: Deaths/100k\",  hue=\"Decriminalization\", size='Drug related crimes', sizes = (50,250), palette=\"pastel\", data=allinone);\n",
+    "rely.set_xticklabels(rotation=45, horizontalalignment = 'right')\n",
+    "plt.xlabel('Countries',fontsize=12, fontweight=\"bold\")\n",
+    "plt.ylabel('Drugs: Deaths/100k',fontsize=12, fontweight=\"bold\")\n",
+    "rely.fig.set_size_inches(15,5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x7fed4c377198>"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 502.375x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.relplot(data=allinone, x='Drugs: Deaths/100k', y='Drug related crimes', hue='Decriminalization', alpha=0.75, size='Alcohol: Deaths/100k', palette='bright',  sizes= (50, 200))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 455.5x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.lmplot(x=\"Drug related crimes\", y=\"Drugs: Deaths/100k\", hue=\"Decriminalization\", data=allinone, fit_reg=False)\n",
+    "sns.regplot(x=\"Drug related crimes\", y=\"Drugs: Deaths/100k\", data=allinone, scatter=False, ax=g.axes[0, 0])\n",
+    "plt.rcParams['figure.figsize']=9,7\n",
+    "plt.xlabel('Drug related crimes',fontsize=12, fontweight=\"bold\")\n",
+    "plt.ylabel('Drugs: Deaths/100k',fontsize=12, fontweight=\"bold\")\n",
+    "#plt.savefig('Linear Regression2.png',dpi=300)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x7fed4c28af98>"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x900 with 30 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.pairplot(allinone)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# \n",
+    "tax=[67594323,130411173,193604810,247368473,266529637]\n",
+    "taxy = ['2014','2015','2016','2017','2018']\n",
+    "prehist = pd.DataFrame({'Revenue':tax,'Year':taxy})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "565583916.856951"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tax[0] * (12/11) * (7/13) * (83000000/5250000) * 0.901"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "999150217.7538462"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tax[1] * (7/13) * (83000000/5250000) * 0.9"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1483310698.153846"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tax[2] * (7/13) * (83000000/5250000) * 0.9"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x7fed47418978>"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#sns.distplot(vehicles['Fuel Barrels/Year'], bins=20)\n",
+    "chart = sns.catplot(x=\"Year\", y=\"Revenue\", kind='bar', palette=\"rocket\", data=prehist)\n",
+    "chart.set_xticklabels(rotation=45, horizontalalignment = 'right')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Drugs: Deaths/100k</th>\n",
+       "      <th>Alcohol: Deaths/100k</th>\n",
+       "      <th>Drug related crimes</th>\n",
+       "      <th>Decr.: 0 or 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>Drugs: Deaths/100k</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.212064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Alcohol: Deaths/100k</td>\n",
+       "      <td>0.113377</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>0.230574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Drug related crimes</td>\n",
+       "      <td>0.477380</td>\n",
+       "      <td>0.265929</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.240490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>Decr.: 0 or 1</td>\n",
+       "      <td>0.212064</td>\n",
+       "      <td>0.230574</td>\n",
+       "      <td>0.240490</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Drugs: Deaths/100k  Alcohol: Deaths/100k  \\\n",
+       "Drugs: Deaths/100k              1.000000              0.113377   \n",
+       "Alcohol: Deaths/100k            0.113377              1.000000   \n",
+       "Drug related crimes             0.477380              0.265929   \n",
+       "Decr.: 0 or 1                   0.212064              0.230574   \n",
+       "\n",
+       "                      Drug related crimes  Decr.: 0 or 1  \n",
+       "Drugs: Deaths/100k               0.477380       0.212064  \n",
+       "Alcohol: Deaths/100k             0.265929       0.230574  \n",
+       "Drug related crimes              1.000000       0.240490  \n",
+       "Decr.: 0 or 1                    0.240490       1.000000  "
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "allinone2 = alls.drop(columns=alls[[\"2011\",\"2012\",\"2013\",\"2014\",\"2015\",\"2016\"]])\n",
+    "allinone2[\"Decr.: 0 or 1\"]=[0 if i in decr else 1 for i in list(allinone['GEO'])]\n",
+    "allinone2.corr()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col0 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col1 {\n",
+       "            background-color:  #a50026;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col2 {\n",
+       "            background-color:  #fee491;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col3 {\n",
+       "            background-color:  #da362a;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col0 {\n",
+       "            background-color:  #a50026;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col1 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col2 {\n",
+       "            background-color:  #ec5c3b;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col3 {\n",
+       "            background-color:  #e0422f;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col0 {\n",
+       "            background-color:  #fee491;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col1 {\n",
+       "            background-color:  #ec5c3b;\n",
+       "            color:  #000000;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col2 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col3 {\n",
+       "            background-color:  #e34933;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col0 {\n",
+       "            background-color:  #da362a;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col1 {\n",
+       "            background-color:  #e0422f;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col2 {\n",
+       "            background-color:  #e34933;\n",
+       "            color:  #f1f1f1;\n",
+       "        }    #T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col3 {\n",
+       "            background-color:  #006837;\n",
+       "            color:  #f1f1f1;\n",
+       "        }</style><table id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Drugs: Deaths/100k</th>        <th class=\"col_heading level0 col1\" >Alcohol: Deaths/100k</th>        <th class=\"col_heading level0 col2\" >Drug related crimes</th>        <th class=\"col_heading level0 col3\" >Decr.: 0 or 1</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row0\" class=\"row_heading level0 row0\" >Drugs: Deaths/100k</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col0\" class=\"data row0 col0\" >1</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col1\" class=\"data row0 col1\" >0.11</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col2\" class=\"data row0 col2\" >0.48</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row0_col3\" class=\"data row0 col3\" >0.21</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row1\" class=\"row_heading level0 row1\" >Alcohol: Deaths/100k</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col0\" class=\"data row1 col0\" >0.11</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col1\" class=\"data row1 col1\" >1</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col2\" class=\"data row1 col2\" >0.27</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row1_col3\" class=\"data row1 col3\" >0.23</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row2\" class=\"row_heading level0 row2\" >Drug related crimes</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col0\" class=\"data row2 col0\" >0.48</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col1\" class=\"data row2 col1\" >0.27</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col2\" class=\"data row2 col2\" >1</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row2_col3\" class=\"data row2 col3\" >0.24</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74level0_row3\" class=\"row_heading level0 row3\" >Decr.: 0 or 1</th>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col0\" class=\"data row3 col0\" >0.21</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col1\" class=\"data row3 col1\" >0.23</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col2\" class=\"data row3 col2\" >0.24</td>\n",
+       "                        <td id=\"T_f26dbbf2_d878_11e9_9380_c48508455a74row3_col3\" class=\"data row3 col3\" >1</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fed4ec578d0>"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "matrix = allinone2.corr().style.background_gradient(cmap='RdYlGn',axis=None).set_precision(2)\n",
+    "matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 648x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['', 'Regular Users according to Survey in 2014']\n",
+    "sizes = [0.869,0.131]\n",
+    "\n",
+    "explode = (0, 0.1)\n",
+    "plt.pie(sizes, explode=explode, shadow=True, autopct='%1.1f%%',  startangle=90, labels=labels)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Bbos3pX4D/FNbc6O6mEjgaWQZcPGmVGjuJ37/AZvLPW3CkStd1yOFzxjzg9h1C9uBS4GdsWNOOXOMvtVlwBPxptTVY/T4IuNGYRlg8abUsTabeciY0DdNKKSWWTIsa20/8BVgKdBQMXdpQ7i6Yc4Yfssa4KfxptR18abUUOdvigSCwjKg5vzTb95qc9nHTDiyzHUtEhzGmOtj1y3cBLwOaI8lVozVqHKwNwOPxJtSahYugaSDWwEz+8M3VGLtz8Ox2te7rkWCJa+582JgVtm0RDpSNyUxjiXMA+6ON6X+E2/ZvOw4fm+Ro6KRZYDMet9PlppQeL2CUo6EMeam2HULnwIuATqrFp01XqPKfGHgM8Ad8abUWO7+FRlVCsuAmPW+n3w0XDXhgVB5bJbrWiSwmoH5QCLaMCsbmTBzicNazgQejTelrnBYg8iIKSwL3JyP3lg1+4PX/TlSO/mrJhyJuq5HAusOv7lzI9Bddfy5LzPuFwiuB26IN6V+HG9KVTuuReSQFJYFbNb7fnwamKfDVfWvdF2LBN4XYonkbOCkcM2kvdFJcwppYtg1eAsZnOq6EJGDUVgWqFnv+8m/hqsn3hMqj01zXYsE3kBz51cBfdVLzk+aUMGtXHEs8Pd4U+qtrgsRGUqh/cGUvFnv+0mVCUdvjtRO1nJhMlqaY4nkFGBFqKJ6W9nUYwp1BFcGXBtvSh3T1tz4GdfFiOTTyLKATHtz8zwTLV8TrqpXUMqosNa2Ar8Bzgdy1UsuWG7C0UJv07Yy3pT6abwppWP0UjAUlgViyuWffkXZ1Pmrw5W1c13XIsVjUHPn7WUzjjvddU0jdDXw53hTqt51ISKgsHQulkiaKZf/x0cq48v+ECqP1bmuR4rHUTZ3LgTn4TWXjrsuRERh6VAskQzXnHLx1yuPWf4VEykrc12PFJchmjuf4bqmI7AIuE8zZcU1haUjsUSyojZ5+a8r48s+aEJh/R5kVFlrdwOj1dzZtal4K/5c4roQKV16k3YglkjW1Z3xplsrZi2+1HUtUpzGqLmzSzHgt/Gm1EdcFyKlSWE5zqpPuGBm/Vlvvat8esLFupxSAqy1aSC/ufOsUW7u7EoI+Fq8KfX1eFNK710yrvSCG0e1yy9eULfijXeVTZl3outapHgZY344Ts2dXfkQcH28KRV2XYiUDoXlOKk7/Q0n15566d+iDTOPcV2LFC+/ufP/Y39z5wlj3NzZlSuAnykwZbwoLMdBzbKLkjUnvToVqZs6w3UtMvrW7ciy7Ltd+y61X9jDf9/Xe8BtrLV86E89HPuNTk78ny4e3pLdd99Tvt/Fif/TxaqNGQAyOcsF1+4l3W8PuxZjzC8GNXc+62h/vgL2JuCn2iUr40EvsjFWtfjlZ9eeeumvInVTtMZrkTpuUphH3lvNI++t5qF3VxGLGl638MDFZ/70dIbWXVlaP1jN919bwT+mugH43kP9fP1VFfzxqhj/b1UfAP/zQD9vOTFKLHp4TUGstRbIb+5cHq6dPJ7NnV24CviJAlPGml5gYyi24PQL65KX/yg6cdZs17XI+LjtuSzzG0LMrT/wT+umpzJcfWIZxhhOnxWhvQe2dOaIhiDdD+l+SzQE7T2W36/v5+qlh7/SmzHm5th1C9eS19zZfReucfFW4McKTBlLWkh9jMQSybNrk5d/vWzqfB2jLCE3PNHPm5a8NOg2d1pm1+0Prlm1hs2dlvefVsbVv+umNwvfe00Fn72zl0+eVU7oyELuC+xv7tzuuLnzeLsa6AHe47oQKU76T2wMxBLJ5TUnv+brFbMWL3Rdi4yfvqzl5nUZ3rB45P+DzqkLccc1Vax6p7f7dlNnjkWTQrz1d91c8es063dmR/pQhdjceby9O96UanZdhBQnheUoiyWSS6pPeMW3KuedvNR1LTK+/tSa4eTpIaZWv/TPamaNYWPH/gk7m/ZYZtYcmGWfur2Hz51bzjda+njXSVG+dEEFn7mzd/BDHcxAc+dlBdjceTx9It6U+oTrIqT4KCxHUSyRPDa28MxvVSZOT7quRcbfLw6yCxbg4uMiXPtYH9Za7tuUoa4cptfs//O7sy3DjOoQiYlh0v0QMt4l3T+ib53f3Lm/QJs7j6fmeFPq3a6LkOKisBwlsURyTuX8U79Ztfics0pv75fs7bPc+myW1y/aH5bffbCP7z7ozXB9dSLCMfUhjv1mF//w+x6+01i573bWWj53dy//frbXZvLdp0T58J97aLw+zcdXjGh9/fzmzrsKuLnzePqfeFPqCtdFSPEw3mxzORqxRHJaxZwTv11zymsvMaGwTpIOuPqNd/1xzoNfXQ90nD03POtjZ5S/03VNB2OtbTXGLIxdt/AK4Pza5ZfGK+aeeL7rugpEP3BeW3Pj310XIsGnkeVRiiWSDWXTj/tyzcmNr1VQyngLcHPn8RAFfh1vSs10XYgEn8LyKMQSydpw7eRP1556yWUmHD38E+NEjkIRNHceD1OB38SbUuWuC5FgU1geoVgiGSMU/mhd8g1vDEUrKoe/h8joMsZ8rQiaO4+HJPBt10VIsCksj0AskSwD3ld76qWXR2onaRk7GXd+c+fvMtDcedHZiQA3dx4P74w3pf7RdRESXArLwxRLJA3wxspjT2usmHV8Ka2QIgXEGPPtA5o7x5cVWxuusfD1eFMq6E2wxRGF5eFLRibMvKx6yQXa5SVO+M2dv86+5s6nF0tz57GmCT9yxBSWhyGWSM420fL31K1445kmHBnRCXAio+2lzZ2Xa1Q5ctPwJvzo71cOi8JyhGKJZBXwgboVV64IV9ZMcl2PlKYSau48ljThRw6bwnIEYolkCHhb1ZLzzyybPPc41/VI6Sqx5s5j6V3xptR7XRchwaGwHJkLyqYlGmOJFVrzVZwp0ebOY+kbmvAjI6WwHEYskVwQqqx9e+2pl55pQiGt0CPOlHBz57ESBX4Rb0rVuC5ECp/C8hBiieQEjPlA/cvetCJUVlnruh4pefnNnbMl1tx5rMwGvuy6CCl8CsuDiCWSEeDd1SdcuDxSN3Wu63qk5Km589h5d7wpdZ7rIqSwKSwP7tJw7ZRTK+efstx1ISKoufNYMsAP4k0prasrB6WwHEIskVwGXFx32uuXmlBEC6SLa2ruPPbmAc2ui5DCpbAcJJZI1gL/EFv08gmRuinHuq5HBPiimjuPi/fHm1Ivd12EFCaFZZ6BdV9DlTW1sQVnnOu6HhFrbSvwa+B8IFe15PxTTDiqdlNjwwA/jDel1EVIXkJheaBFwFm1p112QihSpuMX4pwx5sv5zZ3LZyxUc+exdSzweddFSOFRWPpiiWQF8I6KucuqyibNWeq6HhG/ufNPGWjufPy5J4Si5dVuqyoJH443pdQoQQ6gsNyv0UTKJlefcIF2v0pByGvu/CpMaGvF7CV6Ax8fIeBH8aZUhetCpHAoLIFYIjkXeE3t8kuPDZXHGlzXIzKouXOZmjuPu+OAz7guQgpHyYelv/jA28umzq8om7FAx4OkIKi5c0H4WLwpdbLrIqQwlHxYAudgTLzm5Ne83JiQng9xTs2dC0YYLYUnvpIOB//ctStqll00Mxyrm+G6HhFQc+cCc168KXWh6yLEvZINS/+cyreEKmrCFXOX6s1ICoKaOxek5nhTSuvwlriSDUvgVGBZzUmvXmDCUc16k4Kg5s4F6STgStdFiFslGZaxRLIGeFu4dkpX2bRj1dBZCoKaOxe0z8abUlonuoSVZFgCFwIVNctepQWppWC8pLnzQjV3LiDzgXe7LkLcKbmwjCWSE4GLopPjfdFJc09yXY9IngObOzeouXOB+Xe18SpdJReWeM1zbfUJF7xczXOlgAxq7nzOGXp9FpypwD+5LkLcKKmwjCWSM4Bzy6YvyEXqpy92XY9Inub9zZ0ndmmvR8H653hTapLrImT8lVRY4s0w7KtadPZZ+qddCsjDrOz4C/ubO5+uY+kFqwb4N9dFyPgrmbCMJZLzgFPLpiVykfppi1zXI5JnUHPn+WruXNj+Md6UirsuQsZXSYSlvwDB64DuqsVnv1yjSikUau4cSGXAf7ouQsZXSYQlEAdOLJt6rNWxSikkau4cWG+ON6Xmui5Cxk+phOUlaFQpBUbNnQMtDHzQdREyfoo+LGOJZBxYFmmY1ReZMEOjSikYau4ceO+KN6X0z02JKPqwxBtV9lQdd8bJOm9NCoWaOxeFOuAdrouQ8VHUYRlLJOcCJxGObI9Onqfz1qRgqLlz0fhwvClV1O+j4in2X/IrgN7YgjOOC0XLtUyVFAQ1dy4qx+D9wyNFrmjDMpZI1gKnA9sqZi9Z7roekQGDmztXqrlz0H3IdQEy9oo2LPH6VYaik+bWhasnznNdjAiAtTbDoObOETV3Drpz402p41wXIWOrKMMylkiG8JYO2xVbsOIUzeuRQmGMuf7A5s6na1RZHN7jugAZW0UZlkACmGQiZd1lk+PLXBcjAgdr7jxlgeOyZHS8Ld6UqnBdhIydYg3Lc4He2HEvW2wiZTHXxYiAmjsXuQbgja6LkLFTdGEZSyTr8WYZbiufdfwprusRyaPmzsXtva4LkLFTdGGJN7GHsinHNESqG7R2oxQKNXcufiviTSn9A1SkiiosY4lkGG9iz47KxOk6XUQKiZo7lwbtii1SRRWWwHFAg4lW9JVNmrvUdTEiPjV3Lh2vd12AjI1iC8vzgJ7K+acmTCSqmWlSKNTcuXQcH29KaYZzESqasIwlkg3AycD2sqnzdYKwFAQ1dy5JGl0WoaIJSyAJWIyx0fppCdfFiICaO5eo17kuQEZfUYRlLJE0eA10d1XMPmGWzq2UQqDmziXr1HhTapbrImR0FUVYAlP8y97ymYt0vEAKgpo7lyyDRpdFp1jC8jjAAkQaZup4pTjnN3f+HmruXKp03LLIFEtYngF0Rhtm1Ycrqie7LkbEb+7cx77mzku1YHppOSvelJrkuggZPYEPy1giWQ0sANor5i7VqFKcG7q5c62aO5eWMGoKXVQCH5Z4HUYAbHTyXB2vFOfU3Fl82hVbRIohLJcDvaGKmvJwdUPcdTFS2tTcWfJcEG9K1bguQkZHoMMylkhGgFOAXRXzTppvTCjQP48En5o7S55y4NWui5DREfRwmQeUAf3lWrVHHMtr7rwINXcWz/muC5DREfSwPAHIYkImUjdVq/aIU3nNnS9FzZ3FoxWbikRgw9JftWcFsLt85qIZJlJW6bomKXlq7iyDHR9vStW6LkKOXmDDEpgKTALSZZPnznRdjJS8O9XcWYYQwjuFSAIuyGG5CH/VnnDd1BmOaxH5gpo7y0FoV2wRCHJYLgc6AcJVExSW4tJqNXeWQ1jhugA5eoEMy1giGcI7NtRpymLRUHmVlpUSl5rV3FkOQSPLIhDIsAQmA1EgUz59wXQdGxJXrLVPo+bOcmgN8aaUTiEKuKCG5Qy8NjhEJ83W5B5xxhjzJTV3lhHQrtiAC2pYzgNyAJHaKTpeKU6oubMcBoVlwAU1LBeyb3JPvcJSnFBzZzkM2uMQcIELy1giGcYbWXaFKmsrTFmswXVNUnrU3FkO05J4U0p7HQIscGEJTMGrO+tP7nFdj5QgNXeWwxRGixMEWhDDct/knkjDTO2ClXGn5s5yhJa7LkCOXBDD8hggCxCpnaKZsDLu1NxZjtB81wXIkQviKiOL2D+5Z7rjWqTEWGszxpj85s45NXeWEZrnugA5coEaWcYSySgwB+gy0YpIqKyy3nVNUlqMMb9Qc2c5QnHXBciRC1RY4nUaMUAuOmGGglLGld/cuZl9zZ2PVXNnORxz402poL3nii9ov7h9k3vCtZMVljKujDG/P7C588vV3FkORxnee5gEUBDDMgcQrm5QWMp4yE/Dfc2dIw2zspGGGcc7qkmCK+66ADkyQQzLHoBwZa3CUsZcb5aJ/tU7WdlxH35z5+rjzznDmFDQ/n7EPU3yCaig/bFPww/LUGWNwlLGmrF234xxNXeW0RB3XYAcmcCEZSyRNHir93hhWR5TWMpYm1JbznrU3FlGj0aWARWkP/hKvAPkGQATrah1W46UgMqTpodvA+7La+68Tc2d5SjEXRcgRyZIYVmPP7kHwETKqhzWIsVvIvDUqTPC9xC96aMAAB6VSURBVABbgStQc2c5ehpZBlRgdsPihSUA4eqJMU2ukDFWBdxU/rk9W9TcWUbR7HhTKkiDFPEFKXBq8esN10yscVyLFL+1/gXU3FlGTxiY5boIOXxBC0sAwrF6vWHJmMlGYx3Ab25e15+LJZJVqLmzjC41gAigIIXlZKAPIFRZo7CUMdM5bfkjN6/rX+1/qubOMtq0ZyyAghSWDQyEZUW1wlLGXCyRLEfNnWX0KSwDKEgHmifih6UJR6OOa5HScCpQXXlscoKaO8soUlgGUJBGlhMYCEvNhJUxFkskI3htuHZWzj/1LNf1SFFRWAZQIEaWsUQyhPcCawcgFAo7LUhKgdfcec6Jau4so01hGUBBGaFF8Lo/WAA0spQxZG3OMNDcecEKHauU0aawDKBAjCzxzk2yA58Yo5GljJ1s584pwMSyacem1dxZxoBWHwugoIzQDqzTmKDULQGUad9yPGruLGNHExQDKCihEyJvZElIu2Fl7OT6eiapubOMIYVlAAUldA7Y7ardsDKWTCjUr+bOMoYUlgEUlDeDQbth9SYmYydUWWvV3FnGkMIygIISOgdM8NExSxlLZZPnnaTmzjKGFJYBFJTQGTyy1G5YGTMmEq1wXYMUNYVlAAUyLHUsSUQCLDf8TaTQBCV0DhxJamQpIsG1x3UBcviCEpaDdsOik99EJKg6XBcghy+QYWmzmT5XhYiIHCWNLAMoKGF5wG5Xm+lNuypEROQoKSwDKChheeDIsr+321UhIiJHSbthAygoYXnAblfb16OwFJGg0sgygIISlmnYP6kn19et3bAiElQKywAKSlgeMJLM9aU1shSRoNJu2AAKUljuqzXXu1dhKSJBpZFlAAUiLNOtLVmgB79Zda67U7thRSSoNLIMoECEpa+TfWG5RyNLEQkqjSwDKGhhGQXIptsVliISVArLAApSWO7BD0vb35uxuWy/43pERA5Xuq25MeO6CDl8QQrLDvzdsAA206/RpYgEzQuuC5AjE6Sw3DeyBLDZPoWliATNetcFyJEJUli2kz+y7O/b67AWEZEjobAMqCCFZRqwA5/kujt2OKxFRORIKCwDKkhh2U1eh/FM167tDmsRETkSra4LkCMTpLA8YLdrpv1FhaWIBI1GlgEVpLDcSd5i6v3b27Y5rEVE5HB1AxtdFyFHJkhh2Q5k8BtBZ/fu7raZPi17JyJB8XRbc6Md/mZSiAITlunWFgtsAmID27LdnRpdikhQaBdsgAUmLH1tQNXAJ7nuDh23FJGgUFgGWNDC8jmgfOCTTKdmxIpIYCgsAyxoYbkdyA58kunYqrAUkaBQWAZYEMNy/4zYHW0KSxEJCoVlgAUtLNvxRpbejNjOnXs1I1ZEAmBXW3OjVh0LsECFZbq1JQdsJn9GbE+XXoAiUujuc12AHJ1AhaWvjbywzKU7dPqIiBS6u1wXIEcniGH5LPkzYvdse9FhLSIiI6GwDLgghuV28hZU793SusFhLSIiw0kDD7ouQo5OUMNy/4zYbc/uyPX3qreliBSqVW3Njf2ui5CjE8Sw3A30kdcIOtu1U6NLESlU2gVbBAIXlv6M2LVA3cC2zO4XFJYiUqgUlkUgcGHpe5S8NWJ7t7S2uStFROSgetFpI0UhqGHZBuxrddP3Yus2m+nvdleOiMiQHmhrbuxxXYQcvaCG5WbyelsCZDp3tDmrRkRkaNoFWyQCGZbp1pYMsI6845b9O55/2l1FIiJDUlgWiUCGpe9RoHrgk56Njz/jsBYRkcGywD2ui5DREeSwfIa845aZ3S905Hr2ap1YESkUD7c1N3a5LkJGR5DDciPe+ZbRgQ397Vs0uhSRQvFX1wXI6AlsWKZbW7LAI8CEgW19W5/RcUsRKRS/cV2AjJ7AhqVvNVAx8EnP849tsLlsxmE9IiIAz7U1Nz7kuggZPUEPywNGkravuz/TsVXdyEXEtd+6LkBGV6DDMt3asgvYSv5qPpuefNRdRSIigHbBFp1Ah6XvfvKOW6afuf9pm+lLO6xHRErbZrTEXdEphrB8hLyVfMhmcv07N61xV46IlLjftjU32uFvJkFSDGHZBuwgb1ds94ZHtCtWRFz5hesCZPQFPizTrS0WuA1oGNjWu/GJzbnevbvcVSUiJeqZtubGVa6LkNEX+LD0Pcygn6VvW9tjjmoRkdJ1nesCZGwURVimW1u2Ac8C9QPbup+5X2EpIuPt564LkLFRFGHpu438LiQ7N+7O7t290WE9IlJa7m9rbmx1XYSMjWIKy8eBHHk/U++LT2t0KSLjRaPKIlY0YZlubenEW/5u0r5t61etsblc1l1VIlIietAs2KJWNGHpuxuoHPgkl27vzuzZpsXVRWSs/bytuVEtAotYsYXlWqCXvLZdvZvX6pxLERkz1loLfM11HTK2iios060tfcDfgcn7tq2756lcX3e7u6pEpJgZY/7c1tz4pOs6ZGwVVVj67iNvZInN2Z6NT9zrrhwRKXJfcV2AjL1iDMtngd1AbGDD3jW3r85l+va6K0lEitSjbc2Nt7kuQsZe0YVlurUlB/yRvFmxtr830/fCuhZ3VYlIkfqq6wJkfBRdWPruBfqAsoENXU/c9oDNZvrclSQixcRa+wI6XaRkFGVYpltb0sCfgKkD23Lde3r6tj37oLuqRKSYGGO+1dbc2O+6DhkfRRmWvjsBC0QGNnQ9cfsqLVIgIkfLWrsX+K7rOmT8FG1Ypltb2vHWi502sC27Z1tX/86NOu9SRI6KMebHbc2Nu13XIeOnaMPSdxvez7jv59y79s57/ZOIRUQOm7U2B/y36zpkfBV1WPqtu1aRd+yyf3vbzkz7i0+5q0pEgswYc1Nbc+MzruuQ8VXUYen7M96sWDOwIb3+nr+7K0dEgsofVX7WdR0y/oo+LNOtLRuBx8hbAq9305MvZDp3POeuKhEJImPMtW3Njatd1yHjr+jD0vcH8rqRAKTX3XuHk0pEJJCstWngU67rEDdKJSyfxlsGr2FgQ8+GR57v3/3CGncliUiQGGO+1Nbc+ILrOsSNkgjLdGuLBf4PqMnf3vlw6haby+qkYhE5JGtzW4Avu65D3CmJsPStATYDEwY2ZNq37Ond/NQ97koSkSAwJvSvbc2Nadd1iDslE5b+Aus/B+rJmxnbufoP96jfpYgcjM3lVgPXuq5D3CqZsPStA1qA6QMbbH9vJt163y3uShKRQmZCoY+2NTdqIZMSV1Jh6R+7/BXez72vQXT6qbvX6lQSERnM2txNbc2Nd7quQ9wrqbAESLe2bAduIm90CdD16C1/sjaXc1OViBQaa23GmNDHXdchhaHkwtJ3K9BB3uzYvq1Pb+/b9twD7koSkQLzrbbmxqddFyGFoSTDMt3a0gP8DJiUv73zod/fYTN9mvEmUuKszbUbY/7TdR1SOEoyLH2PAE8CUwY25Lr39HS3rb7dXUkiUgiMCX1cLbgkX8mGpX8qyfV4y+CFB7Z3PXbLw9n0ni3OChMRp2w28+e25sYfuq5DCkvJhiXsW2T9FmDGvo3W2q4n/ppSz0uR0mOzmT0mHLnGdR1SeEo6LH1/AHrJW2i9d+MTm3tfeEptvERKjM32v6etuXGr6zqk8JR8WKZbWzqBG8hrEA2w54Hf3aHdsSKlI9eb/r/nv3r5Da7rkMIUcV1AgbgXOB+v5+V2ALKZXOfDv/9d3RlXvtuEwnqexsGeB2+i69G/gIXqpa+k9tRLaL/rZ6SfbgFjCMfqmfjqjxCpmfiS+3Y9fhsdq7z3uboVV1J9wvnYTD/bfvtZsp07qDmpkZqTGwHY+edvUr3sIsqnHTuuP58ULpvp2xEqj13jug4pXCU/sgRIt7ZkgP8FKoCyge19W5/Z3rPhsducFVZC+ra30fXoX5h29VeZ/o5v0v3M/fTvfoHa5GXMeMe3mPH2b1I5/1Q67v3FS+6b7e6k457rmfbWrzLt6q/Rcc/1ZHu66H7uYcpnLWb6O75F1xpvknPftmexuZyCUvax1mKzmbe0NTd2uK5FCpfC0pdubdmEtzt2Zv72zod/f1+mc2ebk6JKSP/OTZRNP45QtAITClM+ewnp9fcSKo/tu43t7yFvDfx9ep57mIr4SYQrawhXVFMRP4meZx/ChMLY/l7IZsGfrtV+98+pP+st4/RTSRDY3vSPnv/aG/7iug4pbArLA92O18prWv7GPff/5nc209ftpqTSUDZpLr2b1pDt3kOuv4fuZx8ku2cHALvvupZN37mGvU/eMWTQZTp3Eq7dv75EuGYimc6dVMw7iUzHNrb87GPULn8t6dYWyqbOH3I3rpSmXH/vxlBF1ftd1yGFz+gMiQPFEsnJwOeAdmBfQMYWnLGg+oQL3uSssBLQ+egtdK1OYaIVRCfNwYSjNFzw7n1f71h1IzbTT/1ZVx1wv46W32KzfdSfcSUA7ff8AhMppy75+n23sdkMW2/8D6a8/t9o//t1ZPdsp2rJ+cQSyfH54aTgWJvL2Uzfiue/ctn9rmuRwqeR5SD+Qus/xVtofd8+v/T6e9f3vvj0fc4KKwE1Sy9k+jVfZ9pVXyRUUU204YA94lQdfw7p9S/t1R2pmbhvFAqQ7dz5ktFj5+oU1UvOo/eFdYTKq5h0ySfY88DvxuYHkUCwvemvKChlpBSWQ1vlXw54t95z36/+mk136HSSMZLd6/XgzuzZRnr9KqoWn03/rs37vp5ubSHaMOsl96uYdzLdbavJ9nR5E3vaVlMx7+T9j9vTRffTD1C15DxspheMAWO861KScn3dT4Yqqj/pug4JDu2GPYhYIlkNfAZvKbz2ge3RiXMm1J/1lveacKTsoHeWI/Lidf9CrrsTQmEmnPcuKuPL2P67/6J/1yYwISK1k2l45fuJ1Eyid0srXY/8iYkXfQiArsduoWPVrwCoW/FGqk98xb7H3XXb/xJLJKmYcyI208e233yWbOdOqk+6iNpTXuvkZxV3cpm+TnK5xc9/9bJNrmuR4FBYHkIskZwP/BvwAtA/sL1q8dnHVy06+3JnhYnIEbG5bC7Tse2izd971y2ua5Fg0W7YQ0i3tjyDdzrJAfv+9j5555qeTU+qe7pIwPTv3PQFBaUcCYXl8G7Fa+c1I3/jnpZf39G/c+NjbkoSkcPVv/uFW9vv+um/u65DgklhOQy/ldeP8E4jqc//WvvdP78507Vrg5PCRGTEsnt3P9e3pfWSdGuLjjvJEVFYjkC6taUD+DpQA+xbUsZm+7Ptd//shlzP3h0HvbOIOJXr3dvet/WZ87ff/CUtLCJHTGE5QunWlmeBb+N1J4kObM+lO3o67rvxepvpSzsrTkSGlMv09fZsWvu6rTd++jnXtUiwKSwPQ7q15WHgemA2ec9d/86NuztXp35hc9mMs+JE5AA2l831bnziw9t+9ek7XNciwaewPHy3+Je5+Rt7nn98096n7v6dTsURKQy9G9d8q/PhP3zfdR1SHBSWh8mfIHADsJpBp5Sk1971ZM/zj/3VSWEisk/vi0+n9jz4fx/VhB4ZLQrLI+D3v/w+sBnvGOY+nQ/edE/f9raHnBQmIvTt2PBgxz3XX+bPZBcZFQrLI5RubUkD3wB6gQn5X2v/+3V/zOzZ/oyTwkRKWN+2Zx/ruPeGC9KtLVr4V0aVwvIopFtbdgJfxTudpGrfF3LZ3O67rr0x07XreVe1iZSa3hefXtt+7w0X7X3yrg7XtUjxUVgepXRry/N4I8wpwL7F1W3v3r7df/vhzzOdOzRlXWSM9W5pXdex6pevSz91zwuua5HipLAcBenWlseBn+BN+AkPbLd93f27//bD6zMd21pd1SZS7PygvDy97t51rmuR4qWwHD13ADfjnVKyPzD7ezO7//bDX/a3b3nKVWEixap3y/p1Hat+eVl6/aonXNcixU0tukZRLJE0wKXA64Dngf2LFITCoQlnX/O6aMPMJY7KEykqvVvWP9Wx6sbL0+tXrXFdixQ/heUo8wOzEXgjsJG8PpgYY+pf/raLyybNWeaoPJGioKCU8aawHAN+YL4CeAuwCejL/3r9WW9tLJsyb7mL2kSCrveFdU913PcrBaWMK4XlGIolkucC1wAv4J2PuU/dy978yvJpx57uoi6RoPKD8rL0+lVPuq5FSovCcozFEsmzgHcBW4Ce/K/VrXjj+eUzFp7ppDCRgOne8OgjnQ/9/ioFpbigsBwHsUQyCbwPeBGvifQ+tae9/uUVs5ec66QwkQCwuWxm7xO3351uXfWBdGuLglKcUFiOk1gieTLwIWA7sDf/a1WLz10SO+6Mi00oHB3yziIlKtfX07Xngd/d3vdi678qKMUlheU4iiWSJwIfAXYBXflfK5tx3LTaUy6+IlRWWe+kOJECk927e1v7Pb+4Jdu547/SrS1rXdcjpU1hOc5iieRi4J+ATuCANSzDVRMq61725jdEaibOc1KcSIHo27Hh2Y57b7jJ9vd+Jd3astl1PSIKSwdiieR84MNAOd7En/1MyNSdccWF5dMSmikrJcdaS0/b6tWdD//hBuC76daWPa5rEgGFpTOxRLIBb9LPfLzFCw7ovVd1/HknxhaseK0JhSMu6hMZbzaX7e96/NZ7u5++/0fAL9KtLf3D3klknCgsHYolkmXAm4Dz8RpJH3AuZvnMRdNrTn7NFaGyyjoX9YmMl1xfd+ee+397R9/WZ/4b+Fu6tUVvTFJQFJaO+av9nA28DWhn8HHM6omxujOufEOkZmLcQXkiYy7TtWtrxz3X/yXbtetL6dYWrcojBUlhWSBiiWQC79SSKN75mPuFwqG6M668sHzq/KSL2kTGgrXW9m5a89ieh35/K9n+r6ZbW7YMfy8RNxSWBSSWSE4E3g/Mw+tacsAvp2rJ+SfGjk02mnCkbKj7iwRFrje9u/PhP9zX+8JTtwPfS7e2dLquSeRQFJYFJpZIlgNXAecwxCLskYZZ9bWnXnpppLphroPyRI5a39ZnH+lo+fVa29+TAm7URB4JAoVlAfKPY54LXI23gMFLps/XnPza0yvmnni+ZstKUOT6ezq7Hv/rXT3PPbwFuBb4uybySFAoLAtYLJFcAHwQqMDrXHLAL6tsyjGTak557evDsbrpLuoTGan+XZue7Fh146O5nq41wA/SrS1bXdckcjgUlgUulkhOAN4KLMdbwOCAhdgJhUO1yy85s3zm4pebUCjsoESRg7KZ/u69T911V3rdPS8AvwRuS7e2ZFzXJXK4FJYB4O+WPQPv9JIcg2fL4o8yT2q8OFw9YfZ41ycylEzHtmc67rvxoWzXrvXA99OtLRtd1yRypBSWARJLJCcDbweOZ4iG0gDVyy46tTJ+0gWaMSuu2GymL/3M/X/f+/hfNwI3A39It7b0DXc/kUKmsAyYWCIZxlvE4M1AhiFGmZH6abW1yy9pjNRNXTDe9UnpstbSv3PjY50P3fxktmvXRrzR5NOu6xIZDQrLgIolklPxZssuYYim0gCx4152XOzY5AWhiupJ412flJZsun1z12O33tm7eW0GuBX4Tbq15SWvSZGgUlgGWCyRDAErgLcAYbwJQAf+Qk3IVJ9wwUkV8WXnhKIVNeNfpRSzXH9vV/ezD9y294nbd+L1aP2+lqyTYqSwLAL+jNk3AacD2/F6ZR7ARCsi1UtfmayYtfhME45WjHeNUlxsLtvfu2X9fZ0P/+Ep29ddBvwVuEkr8UixUlgWCX/G7Il4M2YbgK0MsWs2FKurqFl20VllU+efpgUN5HBZm8v1b9+wuvORPz2Y7dxRCawFrk+3tjzvujaRsaSwLDJ+268zgcvxFjPYArxkObFI/fTa6qWvPDc6cfZSY4wZ5zIlgPp3b1nb9fitd/VvbyvH65DzM+CRdGtLbpi7igSewrJIxRLJKuA84GIghHeqSXbw7cqmHju5+oTzL9DMWTmYTOeOZ/c+eecdvZvWWLxj4jcBf023tvQ4Lk1k3Cgsi5x/PPPVeA2m+/Fmzr7kl14xd+mc2MKzzo9UN8wZ5xKlANlcLtu/e/MT6XX33Ne3Zb3Bax33N7xzJnc7Lk9k3CksS0QskZwOXAokgTSwbajblc9cNL3y2ORp0YaZS3RMs/TYTH9339ZnHux68o77s3u2VQJVwAPAb9VvUkqZwrLExBLJecAbgcV4x52GHCWEqxtiVYtefnLZtAWnhsoqasezRhl/ud69O3s2PXnf3ifveNT2ddfjheQ6vBZazzguT8Q5hWUJ8mfOLsY73WQ20IHXCuylTMjEjnvZwoq5S5PqoVl8Ml27NvQ89/C96fX3PgtMwdvd+hjwJ2CdWmiJeBSWJcxfOu9E4CIggXdMcxveMnovUTYtMSW2YMVp0YmzTzShcHT8KpXRZG0ul9n1wpp066pVvZvX7gYm4x3HvhO4Pd3astlthSKFR2EpAyPN2cA5wFlABG9xg/RQtw/F6iqqFp19UvmM404LlVXWj1uhclSy3Z1b+7e3rUmvX/VIpuNFA0wA9gJ/BO5Jt7Z0uK1QpHApLOUAsUSyFjgNaATq8ZYw28UQM2gxxlQec+ox5TMXLopMmLEwFCmrGtdiZVi5nq4dfTs2PNH93Oo1/due3QlMAmJ459/eDKxOt7a8pHuNiBxIYSlDiiWSEbzjmhcBC/F2zW7lILtoMcZUzF02p3zW4kXRCTMXaVKQO7ne9K6+HRvW9LQ98kTfi63b8PYUDByPfAJvJLlOiwmIjJzCUoYVSyRn4u2iPQdvwfZdeCPOgyqfdfzMitlLFkUnzl4UKo81jHmRJS7X193Rv+P5J3qef2xN7+a1W/B+TxPxVnHKAn8Hbku3tmxyWadIUCksZcRiiWQ1cCpwITANb9dsO7DnUPcrm5aYUjH3xEXRiXMWhytrpox9paUh15ve3b/7hXU9zz++pnfj45vwVmqaiLebNQusBu4BntJqOyJHR2Eph82fEDQVOB5vQtBcvODcg3caykFfVNFJcxsq5i5dGJ0wfW64umGOOqCMjLWWXG/XtuyeHc/379y4oXfz2g2Zjq2deAE5AagGcsCjeAG5Nt3aMuQELRE5fApLOWqxRHIS3vHNs4D5gMFrE9aO9wY+NGNM2bTElLKpx86JNsyYG66eODcULa8ej5oLnbXW5rr3bMl0bNvQv/P5DT0b1zyfS7cPdJEZmMlag/ePyRrgLryAPOTucRE5MgpLGVWxRLIeb0LQmcAivDf2brzjnC9ZyH2waMOs+rKp82dGJkyfEa6ZNDNcWTvdhCNlY1p0AbC5XDabbt+c6di6oX/7hg09m9ZstL17+/JuUgnUAQPPxTq88yKfTLe2HHI3uIgcPYWljBn/GOdCYAWwFC84Dd7koA5GEJ4YY8qmzJ9UNiU+M1wzeUqooro+VFE1IVRWOcGEo+VjWP6YsLlcNte7d0eue8+O7N727ZnO7dszu17Y3r9jwy6b7c9/PqrwwjGM95ztBh7HG0W2pltb2se/epHSpbCUceH32ZwNzMNbNeg4vFMaBkaencBhTUIJxeoqohNmTAjXTKoPV02YEI7V1ofKqyeEyqvqTVlFvauF4G2mvzvXl96d693bnuvu3J1Nd+zOdu1qz7S/uKt/16Z2bG7wH53BO+ZY518P4XWHeQRvBPk8sFtLz4m4o7AUJ/zzOGcAc4ATgAV4YWHxAmMv3oShlzSuHqlw7ZTqaP20CaGK6koTjkZNJBolHI2YcDRqwpGoCUeihCJRE45ETCgSJRSOmlA4SjgSNSYUsTaXIdvfa7P9vTbT32szfQOXPpvp7c319/bavu7enH+xvenebPeeHtuXPlTNBu90jph/GbARb3JOK7Ah3drSeaQ/t4iMPoWlFAR/hm0tXoDOxpswlMA7VjfwIg0BfXgj0G6gl0PMvHUsgheKlf5H8GoNATvxRovP+JeNmrkqUtgUllKw/ACtwZv5WQ80ANPxAnUq3jmFlv2jUYMXoN14Kw1l8Wbj5hjJ8dFDC+EdP4wM8XHg+kAtIb+OrXjLyj3nX98O7Ei3tvQNfnARKWwKSwksv2tKHfvDdCJekM7AOwZYBpT7H6N4YToQaDCyUenAMcR+9o9o0/5lr3/pwgvDgf6gu4FuHWMUKR4KSykJ/ig1jBea+ZfIoOsZvFFh/qUv3doy9Jq4IlISFJYiIiLDCLkuQEREpNApLEVERIahsBQRERmGwlJERGQYCksREZFhKCxFRESGobAUEREZhsJSRERkGApLERGRYSgsRUREhqGwFBERGYbCUkREZBgKSxERkWEoLEVERIahsBQRERmGwlJERGQYCksREZFhKCxFRESGobAUEREZhsJSRERkGApLERGRYSgsRUREhqGwFBERGYbCUkREZBgKSxERkWEoLEVERIahsBQRERmGwlJERGQYCksREZFhKCxFRESGobAUEREZhsJSRERkGApLERGRYSgsRUREhqGwFBERGYbCUkREZBgKSxERkWEoLEVERIahsBQRERmGwlJERGQY/x9J1ScMzDlkUAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 648x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels = ['', 'Use within the last 12 months survey 2017']\n",
+    "sizes = [0.93,0.07]\n",
+    "\n",
+    "explode = (0, 0.1)\n",
+    "plt.pie(sizes, explode=explode, shadow=True, autopct='%1.1f%%',  startangle=90, labels=labels)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}