star_wars_rating.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analysis on Star Wars Survey"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "star_wars = pd.read_csv(\"star_wars.csv\", encoding=\"ISO-8859-1\")"
   ]
  },
  {
   "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>RespondentID</th>\n",
       "      <th>Have you seen any of the 6 films in the Star Wars franchise?</th>\n",
       "      <th>Do you consider yourself to be a fan of the Star Wars film franchise?</th>\n",
       "      <th>Which of the following Star Wars films have you seen? Please select all that apply.</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Unnamed: 6</th>\n",
       "      <th>Unnamed: 7</th>\n",
       "      <th>Unnamed: 8</th>\n",
       "      <th>Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.</th>\n",
       "      <th>...</th>\n",
       "      <th>Unnamed: 28</th>\n",
       "      <th>Which character shot first?</th>\n",
       "      <th>Are you familiar with the Expanded Universe?</th>\n",
       "      <th>Do you consider yourself to be a fan of the Expanded Universe?ÂÃ¦</th>\n",
       "      <th>Do you consider yourself to be a fan of the Star Trek franchise?</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Household Income</th>\n",
       "      <th>Education</th>\n",
       "      <th>Location (Census Region)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>...</td>\n",
       "      <td>Yoda</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "      <td>Response</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.292880e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>Very favorably</td>\n",
       "      <td>I don't understand this question</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>High school degree</td>\n",
       "      <td>South Atlantic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.292880e+09</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>$0 - $24,999</td>\n",
       "      <td>Bachelor degree</td>\n",
       "      <td>West South Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.292765e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>Unfamiliar (N/A)</td>\n",
       "      <td>I don't understand this question</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>$0 - $24,999</td>\n",
       "      <td>High school degree</td>\n",
       "      <td>West North Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.292763e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Very favorably</td>\n",
       "      <td>I don't understand this question</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>$100,000 - $149,999</td>\n",
       "      <td>Some college or Associate degree</td>\n",
       "      <td>West North Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3.292731e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Somewhat favorably</td>\n",
       "      <td>Greedo</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>$100,000 - $149,999</td>\n",
       "      <td>Some college or Associate degree</td>\n",
       "      <td>West North Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3.292719e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>Very favorably</td>\n",
       "      <td>Han</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>$25,000 - $49,999</td>\n",
       "      <td>Bachelor degree</td>\n",
       "      <td>Middle Atlantic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.292685e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>Very favorably</td>\n",
       "      <td>Han</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>High school degree</td>\n",
       "      <td>East North Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3.292664e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>Very favorably</td>\n",
       "      <td>Han</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>High school degree</td>\n",
       "      <td>South Atlantic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3.292654e+09</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Star Wars: Episode I  The Phantom Menace</td>\n",
       "      <td>Star Wars: Episode II  Attack of the Clones</td>\n",
       "      <td>Star Wars: Episode III  Revenge of the Sith</td>\n",
       "      <td>Star Wars: Episode IV  A New Hope</td>\n",
       "      <td>Star Wars: Episode V The Empire Strikes Back</td>\n",
       "      <td>Star Wars: Episode VI Return of the Jedi</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>Somewhat favorably</td>\n",
       "      <td>Han</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>18-29</td>\n",
       "      <td>$0 - $24,999</td>\n",
       "      <td>Some college or Associate degree</td>\n",
       "      <td>South Atlantic</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RespondentID Have you seen any of the 6 films in the Star Wars franchise?  \\\n",
       "0           NaN                                           Response             \n",
       "1  3.292880e+09                                                Yes             \n",
       "2  3.292880e+09                                                 No             \n",
       "3  3.292765e+09                                                Yes             \n",
       "4  3.292763e+09                                                Yes             \n",
       "5  3.292731e+09                                                Yes             \n",
       "6  3.292719e+09                                                Yes             \n",
       "7  3.292685e+09                                                Yes             \n",
       "8  3.292664e+09                                                Yes             \n",
       "9  3.292654e+09                                                Yes             \n",
       "\n",
       "  Do you consider yourself to be a fan of the Star Wars film franchise?  \\\n",
       "0                                           Response                      \n",
       "1                                                Yes                      \n",
       "2                                                NaN                      \n",
       "3                                                 No                      \n",
       "4                                                Yes                      \n",
       "5                                                Yes                      \n",
       "6                                                Yes                      \n",
       "7                                                Yes                      \n",
       "8                                                Yes                      \n",
       "9                                                Yes                      \n",
       "\n",
       "  Which of the following Star Wars films have you seen? Please select all that apply.  \\\n",
       "0           Star Wars: Episode I  The Phantom Menace                                    \n",
       "1           Star Wars: Episode I  The Phantom Menace                                    \n",
       "2                                                NaN                                    \n",
       "3           Star Wars: Episode I  The Phantom Menace                                    \n",
       "4           Star Wars: Episode I  The Phantom Menace                                    \n",
       "5           Star Wars: Episode I  The Phantom Menace                                    \n",
       "6           Star Wars: Episode I  The Phantom Menace                                    \n",
       "7           Star Wars: Episode I  The Phantom Menace                                    \n",
       "8           Star Wars: Episode I  The Phantom Menace                                    \n",
       "9           Star Wars: Episode I  The Phantom Menace                                    \n",
       "\n",
       "                                    Unnamed: 4  \\\n",
       "0  Star Wars: Episode II  Attack of the Clones   \n",
       "1  Star Wars: Episode II  Attack of the Clones   \n",
       "2                                          NaN   \n",
       "3  Star Wars: Episode II  Attack of the Clones   \n",
       "4  Star Wars: Episode II  Attack of the Clones   \n",
       "5  Star Wars: Episode II  Attack of the Clones   \n",
       "6  Star Wars: Episode II  Attack of the Clones   \n",
       "7  Star Wars: Episode II  Attack of the Clones   \n",
       "8  Star Wars: Episode II  Attack of the Clones   \n",
       "9  Star Wars: Episode II  Attack of the Clones   \n",
       "\n",
       "                                    Unnamed: 5  \\\n",
       "0  Star Wars: Episode III  Revenge of the Sith   \n",
       "1  Star Wars: Episode III  Revenge of the Sith   \n",
       "2                                          NaN   \n",
       "3  Star Wars: Episode III  Revenge of the Sith   \n",
       "4  Star Wars: Episode III  Revenge of the Sith   \n",
       "5  Star Wars: Episode III  Revenge of the Sith   \n",
       "6  Star Wars: Episode III  Revenge of the Sith   \n",
       "7  Star Wars: Episode III  Revenge of the Sith   \n",
       "8  Star Wars: Episode III  Revenge of the Sith   \n",
       "9  Star Wars: Episode III  Revenge of the Sith   \n",
       "\n",
       "                          Unnamed: 6  \\\n",
       "0  Star Wars: Episode IV  A New Hope   \n",
       "1  Star Wars: Episode IV  A New Hope   \n",
       "2                                NaN   \n",
       "3                                NaN   \n",
       "4  Star Wars: Episode IV  A New Hope   \n",
       "5  Star Wars: Episode IV  A New Hope   \n",
       "6  Star Wars: Episode IV  A New Hope   \n",
       "7  Star Wars: Episode IV  A New Hope   \n",
       "8  Star Wars: Episode IV  A New Hope   \n",
       "9  Star Wars: Episode IV  A New Hope   \n",
       "\n",
       "                                     Unnamed: 7  \\\n",
       "0  Star Wars: Episode V The Empire Strikes Back   \n",
       "1  Star Wars: Episode V The Empire Strikes Back   \n",
       "2                                           NaN   \n",
       "3                                           NaN   \n",
       "4  Star Wars: Episode V The Empire Strikes Back   \n",
       "5  Star Wars: Episode V The Empire Strikes Back   \n",
       "6  Star Wars: Episode V The Empire Strikes Back   \n",
       "7  Star Wars: Episode V The Empire Strikes Back   \n",
       "8  Star Wars: Episode V The Empire Strikes Back   \n",
       "9  Star Wars: Episode V The Empire Strikes Back   \n",
       "\n",
       "                                 Unnamed: 8  \\\n",
       "0  Star Wars: Episode VI Return of the Jedi   \n",
       "1  Star Wars: Episode VI Return of the Jedi   \n",
       "2                                       NaN   \n",
       "3                                       NaN   \n",
       "4  Star Wars: Episode VI Return of the Jedi   \n",
       "5  Star Wars: Episode VI Return of the Jedi   \n",
       "6  Star Wars: Episode VI Return of the Jedi   \n",
       "7  Star Wars: Episode VI Return of the Jedi   \n",
       "8  Star Wars: Episode VI Return of the Jedi   \n",
       "9  Star Wars: Episode VI Return of the Jedi   \n",
       "\n",
       "  Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.  \\\n",
       "0           Star Wars: Episode I  The Phantom Menace                                                                                              \n",
       "1                                                  3                                                                                              \n",
       "2                                                NaN                                                                                              \n",
       "3                                                  1                                                                                              \n",
       "4                                                  5                                                                                              \n",
       "5                                                  5                                                                                              \n",
       "6                                                  1                                                                                              \n",
       "7                                                  6                                                                                              \n",
       "8                                                  4                                                                                              \n",
       "9                                                  5                                                                                              \n",
       "\n",
       "   ...         Unnamed: 28       Which character shot first?  \\\n",
       "0  ...                Yoda                          Response   \n",
       "1  ...      Very favorably  I don't understand this question   \n",
       "2  ...                 NaN                               NaN   \n",
       "3  ...    Unfamiliar (N/A)  I don't understand this question   \n",
       "4  ...      Very favorably  I don't understand this question   \n",
       "5  ...  Somewhat favorably                            Greedo   \n",
       "6  ...      Very favorably                               Han   \n",
       "7  ...      Very favorably                               Han   \n",
       "8  ...      Very favorably                               Han   \n",
       "9  ...  Somewhat favorably                               Han   \n",
       "\n",
       "  Are you familiar with the Expanded Universe?  \\\n",
       "0                                     Response   \n",
       "1                                          Yes   \n",
       "2                                          NaN   \n",
       "3                                           No   \n",
       "4                                           No   \n",
       "5                                          Yes   \n",
       "6                                          Yes   \n",
       "7                                          Yes   \n",
       "8                                           No   \n",
       "9                                           No   \n",
       "\n",
       "  Do you consider yourself to be a fan of the Expanded Universe?ÂÃ¦  \\\n",
       "0                                           Response                   \n",
       "1                                                 No                   \n",
       "2                                                NaN                   \n",
       "3                                                NaN                   \n",
       "4                                                NaN                   \n",
       "5                                                 No                   \n",
       "6                                                 No                   \n",
       "7                                                 No                   \n",
       "8                                                NaN                   \n",
       "9                                                NaN                   \n",
       "\n",
       "  Do you consider yourself to be a fan of the Star Trek franchise?    Gender  \\\n",
       "0                                           Response                Response   \n",
       "1                                                 No                    Male   \n",
       "2                                                Yes                    Male   \n",
       "3                                                 No                    Male   \n",
       "4                                                Yes                    Male   \n",
       "5                                                 No                    Male   \n",
       "6                                                Yes                    Male   \n",
       "7                                                 No                    Male   \n",
       "8                                                Yes                    Male   \n",
       "9                                                 No                    Male   \n",
       "\n",
       "        Age     Household Income                         Education  \\\n",
       "0  Response             Response                          Response   \n",
       "1     18-29                  NaN                High school degree   \n",
       "2     18-29         $0 - $24,999                   Bachelor degree   \n",
       "3     18-29         $0 - $24,999                High school degree   \n",
       "4     18-29  $100,000 - $149,999  Some college or Associate degree   \n",
       "5     18-29  $100,000 - $149,999  Some college or Associate degree   \n",
       "6     18-29    $25,000 - $49,999                   Bachelor degree   \n",
       "7     18-29                  NaN                High school degree   \n",
       "8     18-29                  NaN                High school degree   \n",
       "9     18-29         $0 - $24,999  Some college or Associate degree   \n",
       "\n",
       "  Location (Census Region)  \n",
       "0                 Response  \n",
       "1           South Atlantic  \n",
       "2       West South Central  \n",
       "3       West North Central  \n",
       "4       West North Central  \n",
       "5       West North Central  \n",
       "6          Middle Atlantic  \n",
       "7       East North Central  \n",
       "8           South Atlantic  \n",
       "9           South Atlantic  \n",
       "\n",
       "[10 rows x 38 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['RespondentID',\n",
       "       'Have you seen any of the 6 films in the Star Wars franchise?',\n",
       "       'Do you consider yourself to be a fan of the Star Wars film franchise?',\n",
       "       'Which of the following Star Wars films have you seen? Please select all that apply.',\n",
       "       'Unnamed: 4', 'Unnamed: 5', 'Unnamed: 6', 'Unnamed: 7', 'Unnamed: 8',\n",
       "       'Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.',\n",
       "       'Unnamed: 10', 'Unnamed: 11', 'Unnamed: 12', 'Unnamed: 13',\n",
       "       'Unnamed: 14',\n",
       "       'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.',\n",
       "       'Unnamed: 16', 'Unnamed: 17', 'Unnamed: 18', 'Unnamed: 19',\n",
       "       'Unnamed: 20', 'Unnamed: 21', 'Unnamed: 22', 'Unnamed: 23',\n",
       "       'Unnamed: 24', 'Unnamed: 25', 'Unnamed: 26', 'Unnamed: 27',\n",
       "       'Unnamed: 28', 'Which character shot first?',\n",
       "       'Are you familiar with the Expanded Universe?',\n",
       "       'Do you consider yourself to be a fan of the Expanded Universe?ÂÃ¦',\n",
       "       'Do you consider yourself to be a fan of the Star Trek franchise?',\n",
       "       'Gender', 'Age', 'Household Income', 'Education',\n",
       "       'Location (Census Region)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1187, 38)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1186, 38)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars = star_wars[pd.notnull(star_wars['RespondentID'])]\n",
    "star_wars.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far we removed one row with 'RespondentID' being NaN. From looking at the columns, we will need to adjust the column names with the tag 'Unnamed'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert yes and no answers to boolean values\n",
    "yes_no = {\n",
    "    \"Yes\": True,\n",
    "    \"No\": False\n",
    "}\n",
    "\n",
    "star_wars['Have you seen any of the 6 films in the Star Wars franchise?'] = star_wars['Have you seen any of the 6 films in the Star Wars franchise?'].map(yes_no)\n",
    "star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'] = star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'].map(yes_no)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     936\n",
       "False    250\n",
       "Name: Have you seen any of the 6 films in the Star Wars franchise?, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars['Have you seen any of the 6 films in the Star Wars franchise?'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     552\n",
       "False    284\n",
       "Name: Do you consider yourself to be a fan of the Star Wars film franchise?, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far converting from yes/no to boolean worked. We can already see, that not everybody went through all the questions, as the question 'Have you seen any of the 6 films in the Star Wars franchise?' was answered by 1186 people and the later question 'Do you consider yourself to be a fan of the Star Wars film franchise?'was answered by 836 people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "# converting seen answer to Boolean\n",
    "seen_map = {\n",
    "    \"Star Wars: Episode I  The Phantom Menace\": True,\n",
    "    np.nan: False,\n",
    "    \"Star Wars: Episode II  Attack of the Clones\": True,\n",
    "    \"Star Wars: Episode III  Revenge of the Sith\": True,\n",
    "    \"Star Wars: Episode IV  A New Hope\": True,\n",
    "    \"Star Wars: Episode V The Empire Strikes Back\": True,\n",
    "    \"Star Wars: Episode VI Return of the Jedi\": True\n",
    "}\n",
    "\n",
    "for col in star_wars.columns[3:9]:\n",
    "    star_wars[col] = star_wars[col].map(seen_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename the columns of the movies\n",
    "new_names = {\n",
    "   \"Which of the following Star Wars films have you seen? Please select all that apply.\": \"seen_1\",\n",
    "        \"Unnamed: 4\": \"seen_2\",\n",
    "        \"Unnamed: 5\": \"seen_3\",\n",
    "        \"Unnamed: 6\": \"seen_4\",\n",
    "        \"Unnamed: 7\": \"seen_5\",\n",
    "        \"Unnamed: 8\": \"seen_6\"\n",
    "}\n",
    "\n",
    "star_wars = star_wars.rename(columns=new_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True     673\n",
      "False    513\n",
      "Name: seen_1, dtype: int64\n",
      "False    615\n",
      "True     571\n",
      "Name: seen_2, dtype: int64\n",
      "False    636\n",
      "True     550\n",
      "Name: seen_3, dtype: int64\n",
      "True     607\n",
      "False    579\n",
      "Name: seen_4, dtype: int64\n",
      "True     758\n",
      "False    428\n",
      "Name: seen_5, dtype: int64\n",
      "True     738\n",
      "False    448\n",
      "Name: seen_6, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "for col in star_wars.columns[3:9]:\n",
    "    print(star_wars[col].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we renamed the columns of the movies to the specific episodes and converted the answers to boolean values. This will make data picking and analysis a lot easier.\n",
    "The same will be done in the following operations with the ranking of the 6 movies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "star_wars[star_wars.columns[9:15]] = star_wars[star_wars.columns[9:15]].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename the columns of the ranking\n",
    "rank_names = {\n",
    "   \"Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.\": \"rank_1\",\n",
    "        \"Unnamed: 10\": \"rank_2\",\n",
    "        \"Unnamed: 11\": \"rank_3\",\n",
    "        \"Unnamed: 12\": \"rank_4\",\n",
    "        \"Unnamed: 13\": \"rank_5\",\n",
    "        \"Unnamed: 14\": \"rank_6\"\n",
    "}\n",
    "\n",
    "star_wars = star_wars.rename(columns=rank_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>rank_1</th>\n",
       "      <th>rank_2</th>\n",
       "      <th>rank_3</th>\n",
       "      <th>rank_4</th>\n",
       "      <th>rank_5</th>\n",
       "      <th>rank_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1157</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1158</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1159</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1160</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1161</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1162</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1163</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1164</th>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1165</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1166</th>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1167</th>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1168</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1169</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1170</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1171</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1172</th>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1173</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1174</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1175</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1176</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1177</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1178</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1179</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1180</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1181</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1182</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1183</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1184</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1186 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      rank_1  rank_2  rank_3  rank_4  rank_5  rank_6\n",
       "1        3.0     2.0     1.0     4.0     5.0     6.0\n",
       "2        NaN     NaN     NaN     NaN     NaN     NaN\n",
       "3        1.0     2.0     3.0     4.0     5.0     6.0\n",
       "4        5.0     6.0     1.0     2.0     4.0     3.0\n",
       "5        5.0     4.0     6.0     2.0     1.0     3.0\n",
       "6        1.0     4.0     3.0     6.0     5.0     2.0\n",
       "7        6.0     5.0     4.0     3.0     1.0     2.0\n",
       "8        4.0     5.0     6.0     3.0     2.0     1.0\n",
       "9        5.0     4.0     6.0     2.0     1.0     3.0\n",
       "10       1.0     2.0     3.0     4.0     5.0     6.0\n",
       "11       NaN     NaN     NaN     NaN     NaN     NaN\n",
       "12       NaN     NaN     NaN     NaN     NaN     NaN\n",
       "13       3.0     4.0     5.0     6.0     1.0     2.0\n",
       "14       4.0     5.0     6.0     2.0     3.0     1.0\n",
       "15       4.0     2.0     5.0     3.0     1.0     6.0\n",
       "16       4.0     6.0     5.0     3.0     1.0     2.0\n",
       "17       4.0     1.0     2.0     3.0     5.0     6.0\n",
       "18       1.0     2.0     3.0     4.0     5.0     6.0\n",
       "19       6.0     5.0     2.0     3.0     1.0     4.0\n",
       "20       6.0     5.0     1.0     4.0     3.0     2.0\n",
       "21       6.0     5.0     4.0     1.0     2.0     3.0\n",
       "22       3.0     4.0     5.0     1.0     2.0     6.0\n",
       "23       6.0     5.0     4.0     3.0     1.0     2.0\n",
       "24       6.0     1.0     4.0     2.0     3.0     5.0\n",
       "25       1.0     2.0     6.0     3.0     4.0     5.0\n",
       "26       NaN     NaN     NaN     NaN     NaN     NaN\n",
       "27       4.0     6.0     5.0     2.0     3.0     1.0\n",
       "28       6.0     5.0     4.0     2.0     3.0     1.0\n",
       "29       6.0     5.0     4.0     2.0     1.0     3.0\n",
       "30       4.0     6.0     5.0     2.0     1.0     3.0\n",
       "...      ...     ...     ...     ...     ...     ...\n",
       "1157     3.0     4.0     5.0     6.0     2.0     1.0\n",
       "1158     NaN     NaN     NaN     NaN     NaN     NaN\n",
       "1159     2.0     3.0     4.0     5.0     1.0     6.0\n",
       "1160     NaN     NaN     NaN     NaN     NaN     NaN\n",
       "1161     3.0     4.0     2.0     5.0     6.0     1.0\n",
       "1162     3.0     4.0     5.0     6.0     1.0     2.0\n",
       "1163     4.0     5.0     6.0     1.0     2.0     3.0\n",
       "1164     5.0     6.0     2.0     1.0     4.0     3.0\n",
       "1165     5.0     4.0     3.0     6.0     1.0     2.0\n",
       "1166     5.0     6.0     4.0     3.0     1.0     2.0\n",
       "1167     6.0     5.0     1.0     4.0     3.0     2.0\n",
       "1168     3.0     4.0     5.0     6.0     1.0     2.0\n",
       "1169     NaN     NaN     NaN     NaN     NaN     NaN\n",
       "1170     4.0     5.0     6.0     3.0     1.0     2.0\n",
       "1171     NaN     NaN     NaN     NaN     NaN     NaN\n",
       "1172     6.0     2.0     1.0     5.0     3.0     4.0\n",
       "1173     2.0     3.0     4.0     1.0     6.0     5.0\n",
       "1174     5.0     3.0     6.0     4.0     2.0     1.0\n",
       "1175     1.0     2.0     3.0     4.0     5.0     6.0\n",
       "1176     1.0     3.0     4.0     6.0     2.0     5.0\n",
       "1177     2.0     1.0     3.0     4.0     5.0     6.0\n",
       "1178     1.0     2.0     3.0     4.0     5.0     6.0\n",
       "1179     NaN     NaN     NaN     NaN     NaN     NaN\n",
       "1180     3.0     4.0     5.0     6.0     1.0     2.0\n",
       "1181     3.0     4.0     5.0     2.0     1.0     6.0\n",
       "1182     5.0     4.0     6.0     3.0     2.0     1.0\n",
       "1183     4.0     5.0     6.0     2.0     3.0     1.0\n",
       "1184     NaN     NaN     NaN     NaN     NaN     NaN\n",
       "1185     4.0     3.0     6.0     5.0     2.0     1.0\n",
       "1186     6.0     1.0     2.0     3.0     4.0     5.0\n",
       "\n",
       "[1186 rows x 6 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars[star_wars.columns[9:15]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we've cleaned up our data we can start analyzing the data. We begin with computing the most favourite of all of the star-Wars movies, by simply applying the mean to the ranking columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "rank_1    3.732934\n",
       "rank_2    4.087321\n",
       "rank_3    4.341317\n",
       "rank_4    3.272727\n",
       "rank_5    2.513158\n",
       "rank_6    3.047847\n",
       "dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking_mean = star_wars[star_wars.columns[9:15]].mean()\n",
    "ranking_std = star_wars[star_wars.columns[9:15]].std()\n",
    "ranking_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\B.Ellinger\\Miniconda3\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:424: MatplotlibDeprecationWarning: \n",
      "Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n",
      "  warn_deprecated(\"2.2\", \"Passing one of 'on', 'true', 'off', 'false' as a \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "%matplotlib inline\n",
    "\n",
    "ind = np.arange(len(ranking_mean))\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(8,8))\n",
    "ax.set_title('Ranking of Movies (the lower the better)')\n",
    "ax.bar(ind+0.25, ranking_mean, width=0.5, yerr=ranking_std, color='#AF97B2')\n",
    "ax.set_xticklabels(('episode_1','episode_2','episode_3',\n",
    "           'episode_4', 'episode_5', 'episode_6'), rotation=45)\n",
    "ax.set_xticks(ind + 0.25)\n",
    "ax.tick_params(bottom='off', left='off', top='off')\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Computing numerical operations over ordinal scaled data is in general critical, as the computed means here won't reflect a standardized distance between the movies.\n",
    "\n",
    "If we only state which movie has been ranked better, than we are fine with using the mean for the moment. \n",
    "\n",
    "As we can see from the plot above, the last three movies have been ranked better, than the first three movies. This is interesting, as the cult status of Star Wars was generated in the 1980s, it might be worth looking at the age of the respondents. Also we'll at how many people have seen each of the movies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seen_sum = star_wars[star_wars.columns[3:9]].sum()\n",
    "\n",
    "ind = np.arange(len(seen_sum))\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(8,8))\n",
    "ax.set_title('How often was the movie seen')\n",
    "ax.bar(ind + 0.25, seen_sum, width=0.5, color='#CF97B2')\n",
    "ax.set_xticklabels(('episode_1','episode_2','episode_3',\n",
    "           'episode_4', 'episode_5', 'episode_6'), rotation=45)\n",
    "ax.set_xticks(ind + 0.25)\n",
    "ax.tick_params(bottom='off', left='off', top='off')\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18aae4cd278>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ind = np.arange(len(ranking_mean))\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(8,8))\n",
    "ax.set_title('Ranking vs. times seen')\n",
    "ax.bar(ind+0.5, ranking_mean*100, width=0.25, color='#AF97B2', label='Mean (x 100')\n",
    "ax.bar(ind + 0.25, seen_sum, width=0.25, color='#CF97B2', label='Times seen')\n",
    "ax.set_xticklabels(('episode_1','episode_2','episode_3',\n",
    "           'episode_4', 'episode_5', 'episode_6'), rotation=45)\n",
    "ax.set_xticks(ind + 0.25)\n",
    "ax.tick_params(bottom='off', left='off', top='off')\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When comparing the number of times a movie has been seen, with the average rating of these movies, one can see a tendency, that the more often a movie has been watched, the better it is rated.\n",
    "\n",
    "This is also stated by the correlation coefficient between *ranking_mean* and *seen_sum*.\n",
    "\n",
    "Next we will look at gender differences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between ranking and times seen: -0.88\n"
     ]
    }
   ],
   "source": [
    "print(\"Correlation between ranking and times seen: %1.2f\" %np.corrcoef(ranking_mean, seen_sum)[0,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18aae4fcd30>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "males = star_wars[star_wars[\"Gender\"] == \"Male\"]\n",
    "females = star_wars[star_wars[\"Gender\"] == \"Female\"]\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(7,5))\n",
    "ax.set_title('Mean: Male vs. Female')\n",
    "ax.bar(ind+0.5, males[males.columns[9:15]].mean(), width=0.25, color='#5898B2', label='male')\n",
    "ax.bar(ind + 0.25, females[males.columns[9:15]].mean(), width=0.25, color='#FF6680', label='female')\n",
    "ax.set_xticklabels(('episode_1','episode_2','episode_3',\n",
    "           'episode_4', 'episode_5', 'episode_6'), rotation=45)\n",
    "ax.set_xticks(ind + 0.25)\n",
    "ax.tick_params(bottom='off', left='off', top='off')\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18aae9f26d8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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i5syZw7qAt7zlLbz0UqOristPMVAMqt5+UAyWlfaPGzeuqSc16QgOGDVKYVAMFIOqtx8Ug7K1v1ytERERyZTgRESklJTgRESklJaFi0xEREqvKArmzp3LokWL6OcnfjriueeeY968eYOP2AFFUTBq1CjGjBkz5HgowYmIjABz585l+eWXp6ene5vlnp4elluu/heUumfBggXMnTuXsWObftb3YtRFKSIyAixatKiryW0k6unpYdGiAX+cYFBKcCIiI0C3uiVHulbiogQnIiIt+81vfsM+++zT7WosRsfDIiIj0BE33NfW+U3+yBZtnd+yQAlOREQAeOaZZ5g4cSJbbrkl999/PxtvvDHuzuTJk5k1axZnnnkmAMcddxxz585lzJgxnH766WywwQaLzWfOnDkce+yxPProoyxYsIAjjjiCXXbZpePtUReliIi8YerUqRxwwAHcdtttPP7441x77bVce+21fPOb3+SHP/whG2ywAVdffTW33HILRx55JKeccsoS8zjjjDPYZpttmDJlCldccQUnnngic+bM6XhbdAQn0qRWu4yq2EUky5511lmHjTbaCIANN9yQ973vfZgZ73rXu5g2bRqzZ8/m8MMP56mnnsLMeP3115eYx5133smtt97Kf/7nfwIwb948ZsyYwYQJEzraFiU4ERF5w+jRo994PWrUKFZYYYU3Xi9cuJDTTjuNrbfemnPPPZdp06bx8Y9/fIl5FEXBj370oyW6LjtNCU6aoqMXEQF45ZVXWHPNNQGIiH7H2W677Tj//PP59re/jZnx4IMPsummm3aymoDOwYmIyFI49NBDOfnkk9lzzz1ZuHBhv+McfvjhvP766+y000584AMf4NRTT+1wLRMriqLhCO5+HrA78HxEbJrLLgfemUdZFfhrRGzm7m8HHgEey8PujohD8jRbABcAY4EpwBcjovHCk2H/wdPe3l5mzZo1rMsY6QaLQRWO4KoeA30PuhuDOXPmsOKKK3Zl2X16enpYsGBBV+tQr7+4NPuDp810UV4AnAlc1FcQEZ/oe+3uk4G/1Yz/RERs1s98zgYOAu4mJbhdgZuaqaSIiMjSGrSLMiLuBPr9DXN3N8CBSxvNw93XAlaJiLvyUdtFwF5LX10REZHmtHqRyfuB5yLizzVl67n774HZwLER8UtgbWB6zTjTc1lTent7W6xmYz09PcO+jJFuuGPQ7fiu8PmTmxpvXKOBm2/eUh26HYPB6HvQ3Rg899xzI+JhyyOhDrVGjx495M+k1ZZMYvGjt2eBdSPixXzO7Vp33wTor7+0mfNvAMPeJ65zD8Mfg27Ht2Hi6pBux2Aw+h50Nwbz5s3r+k/VjMRzcPPmzVviMxk3rrlv9JATnLv3AB8D3jhzHhHzgHn59X3u/gSwIemIbXzN5OOB4b1yREREKq2V2wR2Ah6NiDe6Ht39be6+XH69PjABeDIingVecff35PN2+wDXtbBsERGRhgZNcO5+KXAX8E53n+7uB+RBE1ny4pJtgT+6+wPAlcAhEdF3gcqhwI+Bx4En0BWUIiIjyjnnnMN2223HYYcdNizznzx58huP7+qEQbsoI2LSAOX79lN2FXDVAOPfC3T+VnYRkWXQuBPOaev8Zh534KDjXHDBBVx88cWsu+66bV12t4ysy2VGqHb8LtNIv8lXRKrta1/7Gk8//TT77bcfe+yxB08//fQSP3dz+eWXc/PNN7Nw4UIee+wxDj74YObPn89VV13FCiuswMUXX8xqq63GJZdcwiWXXML8+fNZb731+MEPfsDYsWMXW97UqVM55phjePHFFxk7diynnXZa259dqUd1iYgIp5xyCmuuuSZXXHEFc+bMGfDnbh577DHOOussbrzxRk455RTGjh3LLbfcwhZbbMGVV14JwG677caUKVO47bbb2GCDDbj00iVvlf7qV7/KiSeeyM9+9jO+8Y1vcNRRR7W9TTqCExGRxQz0czcAW2+9NSuttBIrrbQSK6+8MjvvvDMAG220EQ8//DCQkuCpp57K7Nmzee2119huu+0Wm/9rr73Gfffdx8EHH/xG2fz589veDiU4ERFZzEA/d3P//fe/8fM5kH5Cp+/ndczsjYcvf+lLX+Lcc89lk0024fLLL+euu+5abD6LFi1ilVVW4dZbbx3WdqiLUkREFtP3czd9D+N/8MEHl2r6V199lTXWWIPXX3+da665ZonhK6+8Muussw433HADkBLqQw891HrF6yjBiYjIYlr9uZuvfOUr7L777kyaNGnAC0fOPPNMLrvsMnbaaSd22GEHbrnllnZUfTGD/lzOCND1n8upwlWUZf+pmHZccj2pxWdRdjsGg9GjuvRzOSPxUV2t/FyOjuBERKSUlOBERKSUlOBERKSUlOBEREaAZeB6iK5oJS5KcCIiI8CoUaNG3AUe3bZgwQJGjRp6mtKN3iIiI8CYMWOYO3cu8+bNw6ypiwTbbvTo0cybN68ry65XFAWjRo1izJgxQ56HEpyIyAhgZks8kLjTynariLooRUSklJTgRESklJTgRESklJTgRESklJTgRESklJTgRESklHSbQEU08zT9cY0GtvgkfRGRTtMRnIiIlJISnIiIlJISnIiIlJISnIiIlJISnIiIlJISnIiIlNKgtwm4+3nA7sDzEbFpLjseOBB4IY92dERMycOOAg4AFgJfiIibc/muwBnAcsCPI+I77W2KiIjIPzRzH9wFwJnARXXl34uI79YWuPvGwERgE9JtVbe5+4Z58FnAzsB04B53vz4iHm6h7iIiIgMatIsyIu4EXmpyfnsCl0XEvIh4Cngc2DL/PR4RT0bEfOCyPK6IiMiwaOVJJoe5+z7AvcAREfEysDZwd80403MZwLS68q2aXVBvb28L1RxcT0/PsC9juOc/0lW9/TDyY9CJ78FIV/UYlK39Q01wZwMnAkX+PxnYH+jvd9YL+j9SLJpd2HD/wmwnfsW227+S2/AxXB1Q9fZD92MwmLL9mvNQVD0Gy0r7x41r7hs9pAQXEc/1vXb3c4Cf5rfTgXVqRh0PzMyvByoXERFpuyElOHdfKyKezW8/CjyYX18P/MTdTyftNE8Afkc6spvg7usBM0gXonyylYqLiIg00sxtApcC2wO97j4dOA7Y3t03I3UzTgUOBoiIh9w9gIeBBcDnImJhns9hwM2k2wTOi4iH2t4aERGRbNAEFxGT+ik+t8H4JwEn9VM+BZiyVLUTEREZIj3JRERESkkJTkRESkkJTkRESkkJTkRESkkJTkRESkkJTkRESkkJTkRESkkJTkRESqmVXxMQkWXIuBPOGXycBsNmHndg+yoj0gE6ghMRkVJSghMRkVJSghMRkVJSghMRkVJSghMRkVJSghMRkVKqxG0CrV4ezeabt60uIiLSGTqCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUlKCExGRUhr0WZTufh6wO/B8RGyay04DPgLMB54A9ouIv7r724FHgMfy5HdHxCF5mi2AC4CxwBTgixFRtLU1IiIybI644b6Wpp/8kS3aVJPmNPOw5QuAM4GLaspuBY6KiAXufgpwFPC1POyJiNisn/mcDRwE3E1KcLsCNw2x3iLSYcvaxk1k0C7KiLgTeKmu7JaIWJDf3g2MbzQPd18LWCUi7spHbRcBew2tyiIiIoNrx8/l7A9cXvN+PXf/PTAbODYifgmsDUyvGWd6LmtKb29vG6rZXWVoQyuq3n5QDJaF9vf09CwT9Rwuw93+Tse2pQTn7scAC4BLctGzwLoR8WI+53atu28CWD+TN33+bdasWa1Us/FvvXVIq21oVbdjUPX2g2LQ7fY3o7e3d5mo53AZ7va3a97jxjW3Ng85wbn7Z0kXn+zYd7FIRMwD5uXX97n7E8CGpCO22m7M8cDMoS5bRERkMEO6TcDddyVdVLJHRMypKX+buy+XX68PTACejIhngVfc/T3ubsA+wHUt115ERGQAzdwmcCmwPdDr7tOB40hXTY4GbnV3+MftANsC33L3BcBC4JCI6LtA5VD+cZvATegKShGRjhp3wjmDj9No4Oabt60unTBogouISf0UnzvAuFcBVw0w7F5g06WqnYiIyBDpSSYiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKPd2ugIjIsuKIG+5rafrJH9miTTWRZugITkRESkkJTkRESqmpLkp3Pw/YHXg+IjbNZW8BLgfeDkwFPCJedncDzgA+BMwB9o2I+/M0nwWOzbP9dkRc2L6miIg0Nu6EcwYfp9HAzTdvW11k+DV7BHcBsGtd2deB2yNiAnB7fg+wGzAh/x0EnA1vJMTjgK2ALYHj3H21ViovIiIykKYSXETcCbxUV7wn0HcEdiGwV035RRFRRMTdwKruvhawC3BrRLwUES8Dt7Jk0hQREWmLVq6iXCMingWIiGfdffVcvjYwrWa86blsoPJB9fb2tlDNkaEMbWhF1dsPikHV2w+KQafbPxy3CVg/ZUWD8kHNmjWrpQo17FPvkFbb0Kpux6Dq7QfFoNvtB8WgLO0fN665lrRyFeVzueuR/P/5XD4dWKdmvPHAzAblIiIibddKgrse+Gx+/Vngupryfdzd3P09wN9yV+bNwAfdfbV8cckHc5mIiEjbNXubwKXA9kCvu08nXQ35HSDc/QDgGWDvPPoU0i0Cj5NuE9gPICJecvcTgXvyeN+KiPoLV0RERNqiqQQXEZMGGLRjP+MWwOcGmM95wHlN105ERGSI9CQTEREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREpJSU4EREppZ6hTuju7wQurylaH/gmsCpwIPBCLj86IqbkaY4CDgAWAl+IiJuHunwREZFGhpzgIuIxYDMAd18OmAFcA+wHfC8ivls7vrtvDEwENgHGAbe5+4YRsXCodRARERlIu7oodwSeiIinG4yzJ3BZRMyLiKeAx4Et27R8ERGRxQz5CK7ORODSmveHufs+wL3AERHxMrA2cHfNONNzmYiISNu1nODcfQVgD+CoXHQ2cCJQ5P+Tgf0B62fyopll9Pb2tlrNritDG1pR9faDYlD19oNi0On2t+MIbjfg/oh4DqDvP4C7nwP8NL+dDqxTM914YGYzC5g1a1ZLFRzX0tTt0WobWtXtGFS9/aAYdLv9oBiUpf3jxjXXknacg5tETfeku69VM+yjwIP59fXARHcf7e7rAROA37Vh+SIiIkto6QjO3VcEdgYOrik+1d03I3U/Tu0bFhEPuXsADwMLgM/pCkoRERkuLSW4iJgDvLWu7DMNxj8JOKmVZYqIiDRDTzIREZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFSUoITEZFS6ml1Bu4+FXgFWAgsiIh/dfe3AJcDbwemAh4RL7u7AWcAHwLmAPtGxP2t1kFERKReu47gdoiIzSLiX/P7rwO3R8QE4Pb8HmA3YEL+Owg4u03LFxERWcxwdVHuCVyYX18I7FVTflFEFBFxN7Cqu681THUQEZEKa0eCK4Bb3P0+dz8ol60REc8C5P+r5/K1gWk1007PZSIiIm3V8jk4YJuImOnuqwO3uvujDca1fsqKwRbQ29s75MqNFGVoQysSvFU7AAAN4UlEQVSq3n5QDKreflAMOt3+lhNcRMzM/59392uALYHn3H2tiHg2d0E+n0efDqxTM/l4YOZgy5g1a1ZLdRzX0tTt0WobWtXtGFS9/aAYdLv9oBiUpf3jxjXXkpa6KN39Te6+ct9r4IPAg8D1wGfzaJ8Frsuvrwf2cXdz9/cAf+vryhQREWmnVs/BrQH8yt0fAH4H3BgRPwO+A+zs7n8Gds7vAaYATwKPA+cA/9bi8kVERPrVUhdlRDwJ/O9+yl8EduynvAA+18oyRUREmqEnmYiISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCkpwYmISCn1DHVCd18HuAhYE1gE/CgiznD344EDgRfyqEdHxJQ8zVHAAcBC4AsRcXMLdRcRERnQkBMcsAA4IiLud/eVgfvc/dY87HsR8d3akd19Y2AisAkwDrjN3TeMiIUt1EFERKRfQ+6ijIhnI+L+/PoV4BFg7QaT7AlcFhHzIuIp4HFgy6EuX0REpJFWjuDe4O5vB/4F+C2wDXCYu+8D3Es6ynuZlPzurplsOo0TooiIyJC1nODcfSXgKuDwiJjt7mcDJwJF/j8Z2B+wfiYvmllGb29vq9XsujK0oRVVbz8oBlVvPygGnW5/SwnO3ZcnJbdLIuJqgIh4rmb4OcBP89vpwDo1k48HZjaznFmzZrVSTca1NHV7tNqGVnU7BlVvPygG3W4/KAZlaf+4cc21ZMjn4NzdgHOBRyLi9JrytWpG+yjwYH59PTDR3Ue7+3rABOB3Q12+iIhII60cwW0DfAb4k7v/IZcdDUxy981I3Y9TgYMBIuIhdw/gYdIVmJ/TFZQiIjJchpzgIuJX9H9ebUqDaU4CThrqMkVERJqlJ5mIiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgpKcGJiEgp9XR6ge6+K3AGsBzw44j4TqfrICIi5dfRIzh3Xw44C9gN2BiY5O4bd7IOIiJSDZ3uotwSeDwinoyI+cBlwJ4droOIiFSAFUXRsYW5+8eBXSPi/+b3nwG2iojDGkzWuQqKiMiywgYbodPn4Pqr0GAJbNBGiIiI1Ot0F+V0YJ2a9+OBmR2ug4iIVECnj+DuASa4+3rADGAi8MkO10FERCqgo0dwEbEAOAy4GXgkFcVDnayDiIhUQ0cvMhEREekUPclERERKSQlORERKSQlORERKSQlORFrm7rpftaLyIxhHJCW4Iej7Mo/kD3a4ufub3X1ct+vRLe7+Vndf391Hd7su3eLu67r7NgARUVQtybn7Ru6+R7fr0U35WcJfcffebtelP0pwSyl/oBe7++oRsbCKSc7dNwGuBy5199Pd/R3drlMnuftGwA2kB4d/393f2uUqdZS7m7uvRFoHznb33eCNJFeJbYq7bwhcCqzR7bp0i7tvAFwNvBIRs+qGjYidnUqsjO3i7uNJH+gEIKqY5HIy+wlp4/5x0hf8012tVAe5+ztJDwn/YUTsBmwCbFg3zoj4cg+XiCgi4lXgp8AU4KD8nFkiYlFXK9cB+TtwHfDvEXFOTvgr141T6nUgmwhcGRFnufsod98wbyNHzBG9EtzSWQk4H3gvcDdwVU2S6/hv63XJRsAVkbwAnARs7e5jRsIK3QHjgf+IiEvz+5WAw939BHffHdKXu2u164Cao7S5wOvAxcAn3X1/dz+0bpwyWpf0yMEH8/sLgfPd/Ux3/wiUfx3IXgSeyK+vByYDp7n7ZBgZMSjzSth2EfEocFbeSz0G+DUpya0VEQsq0lV1O/BfAO6+Amkj91ZgxbzXtmI3KzfcIuL2iOhr/2nA/wO+DLwK7Onub+tm/Tqh5ijtclL31NXAnaQfMt6kbpzSiYifA/sCN7r7/aTHDh5Fetbuh939LV2sXic9CRzj7qcDvwH2AE4D3ubuu3S1ZpkS3FLKXTNExELgWOAu0t7bx4FTRurJ1naJiL/nIzfyb/pNA16MiJfcfWvgWHdfpauV7JxjImJiRMwAfgCsT7XOySwPbOruWwL7kbrt3uHue3W3WsOnr5ciIq4EvgT8MiKOiog/A98H3gWs1cUqdkxE3AycAuwFPJ+7ru8HZgMjYkdXCa4FEbEgIr4KzAECuKn+ZGvZRcTrwCx3PwD4T+DuiJjd5WoNO3e3nOD7bAi8GZjXpSp1XEQ8DDxDuuDmooj4NKm7ckZXKzaMas8tRcS1wBE1gzckdVnP7UbduiRI5+S/4e7vcff3ANsAz3W3WomeRdkid//fwDXA4RFxfd7wVSKo+eKa0cD9wCrAZyLi9orFwIBdSOcfjoqI67tcpY7KR2sWEdfk9yvUJf5KyF1y3wO+XrV1AMDdPwnsRjpyuzgn/67TEVwTmrh4Yt++5NaRCnVBf22LiIURMQe4Ajg0Im7P5aVLbg0+21VIFxx8paLrwLU1yW1UmZPbQJ+tuy8PvI2KrgMAEfETUjf1xIi4dsTEoCgK/dX97b333pb/v7Xv9dJMV4a/pYnB3nvvPaZvmrLEYCnb31O29g8hBqVpdyvt1zowstYHdVEOID+hYD/gWeC3wPUR8XLdOD356snl87moUmkyBsvl2yRK1zVV9faDYlD19sOyHQN1UfbD3bcATgAOJV0Vtxd1Fw/kD3SBu68K/NzdS3Xl1FLEYGGOwR1likHV2w+KQdXbD8t+DJTgSI+ccff9a4rWB84BNgbWBr4cEXPc/Z/y+LUfaADHRsSzHa94G1U9BlVvPygGVW8/lC8GSnDJm4Afu/vB+f3jwCTSfS0fj4in8tVix7v7m/IHuhpwJXBiRPyiK7Vur6rHoOrtB8Wg6u2HksWg8gkunz97ANgT+J67fzoifg/8kfScvU3c/X3At4CrI+K1POmxwMkR8cuuVLyNqh6DqrcfFIOqtx/KGQNdZAJ4en7cLsBqpD7mg0lPZdgP+CDwCnBp7X1ufReYdK3SbVb1GFS9/aAYVL39UL4Y6AguPVrrW8C1EfEpYEfgTODDEfED0vPVDqq/v2WkfqBDUfUYVL39oBhUvf1QzhhU/gjO0wODzyU9gWBGLvsi6akEh0TEj7pZv06oegyq3n5QDKrefihnDCp3BNe35+Huq7v72HzPxt+AH9eM9gfSnsvTXajisKt6DKreflAMqt5+qEYMKnkE5+67kg7FHwWWj4hJ7n4FsCrpJ3AmAZ+IiD94SZ+rWPUYVL39oBhUvf1Q/hhULsG5+0akZyceBvwJ+C6wXkRs7+5Oeljo9Ii4rYvVHFZVj0HV2w+KQdXbD9WIQVV+hbrWXOCumvs19nP3K919v4g4v4v16qSqx6Dq7QfFoOrthwrEoPTn4Gr6mbfw9NM2C4D350PzPvcCY7pRv06oegyq3n5QDKrefqhmDCrRRenpzvujST9n8T+eHh56PnA88DLwFeBLEXFH92o5vKoeg6q3HxSDqrcfqheDUiY4d18FICJmu/s7gMuAj0XENHdfD1hI2ks5iPQLvNdFxE1dq/AwqHoMqt5+UAyq3n5QDEp3Di5/oEcCZwGzSYfhi4APuvsEYBNgZ9KVQUfWTLfMXSE0kKrHoOrtB8Wg6u0HxQDKewS3OjAa2J70hOtPkB41833gJuD/AGsB34+IRV2q5rCqegyq3n5QDKreflAMSpXg3H1U34fk7p8CHLg80s+p942zPfAfwBeW5ctfB1L1GFS9/aAYVL39oBj0KU2C8388+POfgGcjYr677wT8X+AG4A5SX/PVwDcj4oYuVndYVD0GVW8/KAZVbz8oBrVKkeBqPtAPAj8A7gOWBz5P+qG+/Ugf6nXA2IiYWaZ+ZlAMqt5+UAyq3n5QDOqVIsEBuPtWwN7ANcB0YCLpd40+BOwEfAw4MiJmdq2Sw6zqMah6+0ExqHr7QTGoVYobvfMNjAF8ICJ+DUyLiFNIey97RsSVpPs+SvuBVj0GVW8/KAZVbz8oBvWW2QRXc1f+VsBWwFeBd7n7l2uuBnoZWC+/Lt0HWvUYVL39oBhUvf2gGDSyTHdRuvuewDeBW0mXuk4HvkA6NL8UOAE4rkw3Ltaregyq3n5QDKreflAMBrIsH8GtSupb3gG4B9gsIo4BtgQ+TLrBcY+IuMndl+teTYdP1WNQ9faDYlD19oNi0Mgym+CA10l3538L+BLpxCmAAZ8CJpAuiyUiFnajgh1Q9RhUvf2gGFS9/aAYDGhZ76I8DPg34IsRcau7bwecB2wNrALcmF+/WNbLYKseg6q3HxSDqrcfFIOBLOsJbg3S/R1bAQ8Au5Muf/1pHr58RLzexSoOu6rHoOrtB8Wg6u0HxWAgy3SCA3D3NwH/CqwGzIiIe/quKgKowt5K1WNQ9faDYlD19oNi0J9lPsGJiIj0Z1m+yERERGRASnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJKSnAiIlJK/x+7kDC83lWBQwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig,ax = plt.subplots(figsize=(7,5))\n",
    "ax.set_title('Number of Times Movies watched: Male vs. Female')\n",
    "ax.bar(ind+0.5, males[males.columns[9:15]].sum(), width=0.25, color='#5898B2', label='male')\n",
    "ax.bar(ind + 0.25, females[males.columns[9:15]].sum(), width=0.25, color='#FF6680', label='female')\n",
    "ax.set_xticklabels(('episode_1','episode_2','episode_3',\n",
    "           'episode_4', 'episode_5', 'episode_6'), rotation=45)\n",
    "ax.set_xticks(ind + 0.25)\n",
    "ax.tick_params(bottom='off', left='off', top='off')\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More males looked episodes 1 to 3, but females rated these better than males. Maybe we find a more interesting difference when looking at ages or when looking at the columns related to the preference of the movie characters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['RespondentID',\n",
      "       'Have you seen any of the 6 films in the Star Wars franchise?',\n",
      "       'Do you consider yourself to be a fan of the Star Wars film franchise?',\n",
      "       'seen_1', 'seen_2', 'seen_3', 'seen_4', 'seen_5', 'seen_6', 'rank_1',\n",
      "       'rank_2', 'rank_3', 'rank_4', 'rank_5', 'rank_6',\n",
      "       'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.',\n",
      "       'Unnamed: 16', 'Unnamed: 17', 'Unnamed: 18', 'Unnamed: 19',\n",
      "       'Unnamed: 20', 'Unnamed: 21', 'Unnamed: 22', 'Unnamed: 23',\n",
      "       'Unnamed: 24', 'Unnamed: 25', 'Unnamed: 26', 'Unnamed: 27',\n",
      "       'Unnamed: 28', 'Which character shot first?',\n",
      "       'Are you familiar with the Expanded Universe?',\n",
      "       'Do you consider yourself to be a fan of the Expanded Universe?ÂÃ¦',\n",
      "       'Do you consider yourself to be a fan of the Star Trek franchise?',\n",
      "       'Gender', 'Age', 'Household Income', 'Education',\n",
      "       'Location (Census Region)'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(star_wars.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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