Star_wars_dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data source: https://github.com/fivethirtyeight/data/tree/master/star-wars-survey"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "star_wars = pd.read_csv('../data/star-wars-survey/StarWars.csv',encoding='ISO-8859-1')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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?æ</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",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 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",
       "\n",
       "  Do you consider yourself to be a fan of the Star Wars film franchise?  \\\n",
       "0                                           Response                      \n",
       "1                                                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",
       "\n",
       "                                    Unnamed: 4  \\\n",
       "0  Star Wars: Episode II  Attack of the Clones   \n",
       "1  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",
       "\n",
       "                          Unnamed: 6  \\\n",
       "0  Star Wars: Episode IV  A New Hope   \n",
       "1  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",
       "\n",
       "                                 Unnamed: 8  \\\n",
       "0  Star Wars: Episode VI Return of the Jedi   \n",
       "1  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",
       "\n",
       "            ...                Unnamed: 28       Which character shot first?  \\\n",
       "0           ...                       Yoda                          Response   \n",
       "1           ...             Very favorably  I don't understand this question   \n",
       "\n",
       "  Are you familiar with the Expanded Universe?  \\\n",
       "0                                     Response   \n",
       "1                                          Yes   \n",
       "\n",
       "  Do you consider yourself to be a fan of the Expanded Universe?æ  \\\n",
       "0                                           Response                 \n",
       "1                                                 No                 \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",
       "\n",
       "        Age Household Income           Education Location (Census Region)  \n",
       "0  Response         Response            Response                 Response  \n",
       "1     18-29              NaN  High school degree           South Atlantic  \n",
       "\n",
       "[2 rows x 38 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "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?æ',\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": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Cleaning up dataset\n",
    "\n",
    "#Dropping rows where RespondentID is null\n",
    "star_wars = star_wars[star_wars['RespondentID'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    552\n",
       "No     284\n",
       "Name: Do you consider yourself to be a fan of the Star Wars film franchise?, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars['Have you seen any of the 6 films in the Star Wars franchise?'].value_counts()\n",
    "\n",
    "star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Mapping Yes = True and No = False using dict\n",
    "TF = {'Yes':True,'No':False}\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(TF)\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(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "star_wars.rename(columns={'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",
    "                         },inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Star Wars: Episode I  The Phantom Menace\n"
     ]
    }
   ],
   "source": [
    "print(star_wars['seen_1'].loc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "TF={'Star Wars: Episode I  The Phantom Menace':True,'NaN':False}\n",
    "star_wars['seen_1'] = star_wars['seen_1'].map(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Star Wars: Episode II  Attack of the Clones\n"
     ]
    }
   ],
   "source": [
    "print(star_wars['seen_2'].loc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TF={'Star Wars: Episode II  Attack of the Clones':True,'NaN':False}\n",
    "star_wars['seen_2'] = star_wars['seen_2'].map(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Star Wars: Episode III  Revenge of the Sith\n"
     ]
    }
   ],
   "source": [
    "print(star_wars['seen_3'].loc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TF={'Star Wars: Episode III  Revenge of the Sith':True,'NaN':False}\n",
    "star_wars['seen_3'] = star_wars['seen_3'].map(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Star Wars: Episode IV  A New Hope\n"
     ]
    }
   ],
   "source": [
    "print(star_wars['seen_4'].loc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TF={'Star Wars: Episode IV  A New Hope':True,'NaN':False}\n",
    "star_wars['seen_4'] = star_wars['seen_4'].map(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Star Wars: Episode V The Empire Strikes Back\n"
     ]
    }
   ],
   "source": [
    "print(star_wars['seen_5'].loc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TF={'Star Wars: Episode V The Empire Strikes Back':True,'NaN':False}\n",
    "star_wars['seen_5'] = star_wars['seen_5'].map(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Star Wars: Episode VI Return of the Jedi\n"
     ]
    }
   ],
   "source": [
    "print(star_wars['seen_6'].loc[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TF={'Star Wars: Episode VI Return of the Jedi':True,'NaN':False}\n",
    "star_wars['seen_6'] = star_wars['seen_6'].map(TF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['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",
       "      dtype='object')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars.columns[9:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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.    3\n",
       "Unnamed: 10                                                                                                                                      2\n",
       "Unnamed: 11                                                                                                                                      1\n",
       "Unnamed: 12                                                                                                                                      4\n",
       "Unnamed: 13                                                                                                                                      5\n",
       "Unnamed: 14                                                                                                                                      6\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars[star_wars.columns[9:15]].loc[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Converting string object to floats\n",
    "star_wars[star_wars.columns[9:15]] = star_wars[star_wars.columns[9:15]].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "star_wars.rename(columns={'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.':'ranking_1'\n",
    "                          ,'Unnamed: 10':'ranking_2'\n",
    "                          ,'Unnamed: 11':'ranking_3'\n",
    "                          ,'Unnamed: 12':'ranking_4'\n",
    "                          ,'Unnamed: 13':'ranking_5'\n",
    "                          ,'Unnamed: 14':'ranking_6'\n",
    "                         },inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ranking_1', 'ranking_2', 'ranking_3', 'ranking_4', 'ranking_5',\n",
       "       'ranking_6'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars.columns[9:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lower ranking means better overall rating:\n",
      "\n",
      "1st movie mean ranking: 3.7329341317365268\n",
      "2nd movie mean ranking: 4.087320574162679\n",
      "3rd movie mean ranking: 4.341317365269461\n",
      "4th movie mean ranking: 3.272727272727273\n",
      "5th movie mean ranking: 2.513157894736842\n",
      "6th movie mean ranking: 3.047846889952153\n"
     ]
    }
   ],
   "source": [
    "print('Lower ranking means better overall rating:\\n')\n",
    "print('1st movie mean ranking: {0}'.format(star_wars['ranking_1'].mean()))\n",
    "print('2nd movie mean ranking: {0}'.format(star_wars['ranking_2'].mean()))\n",
    "print('3rd movie mean ranking: {0}'.format(star_wars['ranking_3'].mean()))\n",
    "print('4th movie mean ranking: {0}'.format(star_wars['ranking_4'].mean()))\n",
    "print('5th movie mean ranking: {0}'.format(star_wars['ranking_5'].mean()))\n",
    "print('6th movie mean ranking: {0}'.format(star_wars['ranking_6'].mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cleanup Summary:\n",
    "   - Dropped rows where RespondentID is null using .notnull()\n",
    "   - Mapped 'Yes' = True and 'No' = False using a dictionary. \n",
    "   - Renamed columns using .rename()\n",
    "   - Used dictionaries to create boolean variables for the first multiple choice question. If respondent watched the movie the boolean is True, if NaN it is False.\n",
    "   - Converted movie rankings into floats using .astype()\n",
    "   - Computed the mean rankings of each movie in the Star Wars series using .mean()\n",
    "   - Lower mean value indicates a ranking closer to the highest possible rank(rank 1).\n",
    "   - So lower mean values may be considered better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ranking_1</th>\n",
       "      <th>ranking_2</th>\n",
       "      <th>ranking_3</th>\n",
       "      <th>ranking_4</th>\n",
       "      <th>ranking_5</th>\n",
       "      <th>ranking_6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</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>3</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>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</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>6</th>\n",
       "      <td>1.0</td>\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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</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>8</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</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>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",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <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": [
       "      ranking_1  ranking_2  ranking_3  ranking_4  ranking_5  ranking_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": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_wars[['ranking_1','ranking_2','ranking_3','ranking_4','ranking_5','ranking_6']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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