Ob

05_AdvancedPandas/Train.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print('hey')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(\"\"\"\"Shuffle, Shuffle, Shuffle\", say it together!\n",
+    "Change colors and directions,\n",
+    "Don't back down and stop the player!\n",
+    "      Do you want to play Taki?\n",
+    "      Press y\\\\n \"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "numbers = \"123456789\"\n",
+    "numbers[-1:-10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "encrypted_message = \"!XgXnXiXcXiXlXsX XnXoXhXtXyXpX XgXnXiXnXrXaXeXlX XmXaX XI\"\n",
+    "encrypted_message[::-2]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "numbers = \"123456789\"\n",
+    "numbers[0:10:1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "import pandas as pd\n",
+    "url = 'https://s3.eu-west-1.amazonaws.com/data.cyber.org.il/virtual_courses/introdata/colab/youth_survey_preprocessed.csv'\n",
+    "music = pd.read_csv(url)\n",
+    "music.head"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "import pandas as pd\n",
+    "url = 'https://s3.eu-west-1.amazonaws.com/data.cyber.org.il/virtual_courses/introdata/colab/youth_survey_preprocessed.csv'\n",
+    "music = pd.read_csv(url)\n",
+    "music.head"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Base Installations\n",
+    "import sys\n",
+    "import pandas as pd\n",
+    "import numpy as np \n",
+    "import matplotlib as plt\n",
+    "\n",
+    "# Load Data\n",
+    "df = pd.read_csv(r'C:\\Users\\bruch\\Desktop\\spotify_tracks1.csv')\n",
+    "df.head # Checking that the data loaded + Understanding about what the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_rename = df.rename(columns= {\n",
+    "    'popularity':'pop'})\n",
+    "df_rename.head"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.shape \n",
+    "print (f'Total rows    : 521260 \\nTotal columns : 18')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_pop = df.sort_values('popularity', ascending=False) # Sortinggggg\n",
+    "df_pop.popularity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.describe()\n",
+    "df.info()\n",
+    "df.memory_usage()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_pop[['popularity']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "plt.figure()\n",
+    "plt.bar(['pop','rk','instrument'], [14,12,4])\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": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}