6. Get variables.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done!\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "print('Done!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Movies with box office receipt data: 4,586\n",
      "Movies with budget/profit data: 2,754\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>imdb_id</th>\n",
       "      <th>107952</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bechdel_title</th>\n",
       "      <td>Return of Jafar, The</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_submitter_id</th>\n",
       "      <td>1111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_submitted_date</th>\n",
       "      <td>2010-07-04 04:40:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_dubious</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_rating</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_year</th>\n",
       "      <td>1994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_site_id</th>\n",
       "      <td>1066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bechdel_visible</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdbtitle</th>\n",
       "      <td>Aladdin: The Return of Jafar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdbyear</th>\n",
       "      <td>1994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>studio</th>\n",
       "      <td>Buena Vista Pictures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nVotes</th>\n",
       "      <td>20,897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userscore</th>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>metascore</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdb_release_date</th>\n",
       "      <td>1994-05-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mpaa_rating</th>\n",
       "      <td>G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdb_boxoffice</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdb_link</th>\n",
       "      <td>http://www.imdb.com/title/tt0107952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>english</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>usa</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdb_link.1</th>\n",
       "      <td>http://www.imdb.com/title/tt0107952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genres</th>\n",
       "      <td>Animation, Adventure, Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>runtime</th>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdb_plot</th>\n",
       "      <td>Jafar comes for revenge on Aladdin, using a fo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>awards</th>\n",
       "      <td>1 nomination.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>director</th>\n",
       "      <td>Toby Shelton, Tad Stones, Alan Zaslove</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>writers</th>\n",
       "      <td>Duane Capizzi (story), Douglas Langdale (story...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actors</th>\n",
       "      <td>Jason Alexander, Jonathan Freeman, Jeff Bennet...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>posterlink</th>\n",
       "      <td>https://images-na.ssl-images-amazon.com/images...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>website</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dvd_release_date</th>\n",
       "      <td>18 Jan 2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>languages</th>\n",
       "      <td>English</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>countries</th>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>all_ratings_list</th>\n",
       "      <td>[{'Value': '5.9/10', 'Source': 'Internet Movie...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>llave</th>\n",
       "      <td>aladdin94afar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title_boxofficemojo</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>studio_boxofficemojo</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totalgross</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totaltheaters</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>openinggross</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>openingtheaters</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>boxofficemojo_url</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>release_date</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>releasedate_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genre_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>budget_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revenue_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>has_trailer_thenumbers</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>the_numbers_url</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>boxoffice</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>budget</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>profit</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "imdb_id                                                            107952\n",
       "bechdel_title                                        Return of Jafar, The\n",
       "bechdel_submitter_id                                                 1111\n",
       "bechdel_submitted_date                                2010-07-04 04:40:17\n",
       "bechdel_dubious                                                         0\n",
       "bechdel_rating                                                          0\n",
       "bechdel_year                                                         1994\n",
       "bechdel_site_id                                                      1066\n",
       "bechdel_visible                                                         1\n",
       "imdbtitle                                    Aladdin: The Return of Jafar\n",
       "imdbyear                                                             1994\n",
       "studio                                               Buena Vista Pictures\n",
       "nVotes                                                             20,897\n",
       "userscore                                                             5.9\n",
       "metascore                                                             NaN\n",
       "imdb_release_date                                              1994-05-20\n",
       "mpaa_rating                                                             G\n",
       "imdb_boxoffice                                                        NaN\n",
       "imdb_link                             http://www.imdb.com/title/tt0107952\n",
       "english                                                                 1\n",
       "usa                                                                     1\n",
       "imdb_link.1                           http://www.imdb.com/title/tt0107952\n",
       "genres                                       Animation, Adventure, Comedy\n",
       "runtime                                                                69\n",
       "imdb_plot               Jafar comes for revenge on Aladdin, using a fo...\n",
       "awards                                                      1 nomination.\n",
       "director                           Toby Shelton, Tad Stones, Alan Zaslove\n",
       "writers                 Duane Capizzi (story), Douglas Langdale (story...\n",
       "actors                  Jason Alexander, Jonathan Freeman, Jeff Bennet...\n",
       "posterlink              https://images-na.ssl-images-amazon.com/images...\n",
       "website                                                               NaN\n",
       "dvd_release_date                                              18 Jan 2005\n",
       "languages                                                         English\n",
       "countries                                                             USA\n",
       "all_ratings_list        [{'Value': '5.9/10', 'Source': 'Internet Movie...\n",
       "llave                                                       aladdin94afar\n",
       "title_boxofficemojo                                                   NaN\n",
       "studio_boxofficemojo                                                  NaN\n",
       "totalgross                                                            NaN\n",
       "totaltheaters                                                         NaN\n",
       "openinggross                                                          NaN\n",
       "openingtheaters                                                       NaN\n",
       "boxofficemojo_url                                                     NaN\n",
       "release_date                                                          NaN\n",
       "releasedate_thenumbers                                                NaN\n",
       "title_thenumbers                                                      NaN\n",
       "genre_thenumbers                                                      NaN\n",
       "budget_thenumbers                                                     NaN\n",
       "revenue_thenumbers                                                    NaN\n",
       "year_thenumbers                                                       NaN\n",
       "has_trailer_thenumbers                                                NaN\n",
       "the_numbers_url                                                       NaN\n",
       "boxoffice                                                             NaN\n",
       "budget                                                                NaN\n",
       "profit                                                                NaN"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies = pd.read_csv('movies.csv',index_col='imdb_id')\n",
    "\n",
    "movies['imdb_boxoffice'] = movies['imdb_boxoffice'].str.replace('$','').str.replace(',','')\n",
    "movies['imdb_boxoffice'] = pd.to_numeric(movies['imdb_boxoffice'])\n",
    "\n",
    "#print('Movies with IMDb box office data: ',movies['imdb_boxoffice'][(~pd.isnull(movies['imdb_boxoffice']))].size)\n",
    "#print('Movies with boxofficemojo box office data: ',movies['totalgross'][(~pd.isnull(movies['totalgross']))].size)\n",
    "#print('Movies with the-numbers box office data: ',movies['revenue'][(~pd.isnull(movies['revenue']))].size)\n",
    "#print('\\n')\n",
    "#print('Movies with all three:',len(movies[['bechdel_title','date','imdb_boxoffice','totalgross','revenue']][(~pd.isnull(movies['imdb_boxoffice'])) & (~pd.isnull(movies['totalgross'])) & (~pd.isnull(movies['revenue']))]))\n",
    "#print('Movies with any one or more of the three:',len(movies[['bechdel_title','date','imdb_boxoffice','totalgross','revenue']][(~pd.isnull(movies['imdb_boxoffice'])) | (~pd.isnull(movies['totalgross'])) | (~pd.isnull(movies['revenue']))]))\n",
    "\n",
    "# Let's use the numbers where available, since that's what Keegan used.\n",
    "# Order of trustworthiness: the-numbers, boxofficemojo, IMDb\n",
    "movies['boxoffice'] = movies['revenue_thenumbers']\n",
    "movies['boxoffice'] = np.where(pd.isnull(movies['boxoffice']),movies['totalgross'],movies['boxoffice'])\n",
    "movies['boxoffice'] = np.where(pd.isnull(movies['boxoffice']),movies['imdb_boxoffice'],movies['boxoffice'])\n",
    "\n",
    "print('Movies with box office receipt data: {0:,.0f}'.format(len(movies[~pd.isnull(movies['boxoffice'])])))\n",
    "\n",
    "movies['budget'] = movies['budget_thenumbers']\n",
    "print('Movies with budget/profit data: {0:,.0f}'.format(len(movies[~pd.isnull(movies['budget'])])))\n",
    "\n",
    "\n",
    "movies['profit'] = movies['boxoffice'] - movies['budget']\n",
    "#movies[['bechdel_title','year','boxoffice','budget','profit']][~pd.isnull(movies['profit'])].style.format({'bechdel_title': '{:.40}', 'year': '{:.0f}', 'boxoffice': '${:,.0f}', 'budget': '${:,.0f}', 'profit': '${:,.0f}' })\n",
    "movies.sample(1).transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Movies with IMDb release dates:  7066\n",
      "Movies with boxofficemojo release dates:  2626\n",
      "Movies with the-numbers release dates:  4375\n",
      "Movies with all three: 2474\n",
      "Movies with all three: 7069\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bechdel_title</th>\n",
       "      <th>released</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>imdb_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1073105</th>\n",
       "      <td>Descent: Part 2, The</td>\n",
       "      <td>2009-12-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876154</th>\n",
       "      <td>To Have and to Hold</td>\n",
       "      <td>2006-11-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58700</th>\n",
       "      <td>Last Man on Earth, The</td>\n",
       "      <td>1964-03-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  bechdel_title    released\n",
       "imdb_id                                    \n",
       "1073105    Descent: Part 2, The  2009-12-02\n",
       "876154      To Have and to Hold  2006-11-06\n",
       "58700    Last Man on Earth, The  1964-03-08"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Movies with IMDb release dates: ',movies['imdb_release_date'][(~pd.isnull(movies['imdb_release_date']))].size)\n",
    "print('Movies with boxofficemojo release dates: ',movies['release_date'][(~pd.isnull(movies['release_date']))].size)\n",
    "print('Movies with the-numbers release dates: ',movies['releasedate_thenumbers'][(~pd.isnull(movies['releasedate_thenumbers']))].size)\n",
    "\n",
    "print('Movies with all three:',len(movies[['imdb_release_date','release_date','releasedate_thenumbers']][(~pd.isnull(movies['imdb_release_date'])) & (~pd.isnull(movies['release_date'])) & (~pd.isnull(movies['releasedate_thenumbers']))]))\n",
    "print('Movies with all three:',len(movies[['imdb_release_date','release_date','releasedate_thenumbers']][(~pd.isnull(movies['imdb_release_date'])) | (~pd.isnull(movies['release_date'])) | (~pd.isnull(movies['releasedate_thenumbers']))]))\n",
    "\n",
    "movies['released'] = movies['releasedate_thenumbers']\n",
    "movies['released'] = np.where(pd.isnull(movies['released']),movies['release_date'],movies['released'])\n",
    "movies['released'] = np.where(pd.isnull(movies['released']),movies['imdb_release_date'],movies['released'])\n",
    "\n",
    "movies[['bechdel_title','released']][~pd.isnull(movies['released'])].sample(3)\n",
    "#movies[['bechdel_title','imdb_release_date','release_date','releasedate']][(~pd.isnull(movies['imdb_release_date'])) & (~pd.isnull(movies['release_date'])) & (~pd.isnull(movies['releasedate']))].sample(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "old columns: 61\n",
      "new columns: 61\n",
      "Done\n"
     ]
    }
   ],
   "source": [
    "cpi = pd.read_csv('inflation/cpi-1913-2017.csv',index_col='Year')\n",
    "#inflator = dict(cpi.ix[2014,'Annual']/cpi['Annual'])\n",
    "cpi = cpi.drop(['HALF1','HALF2'],axis=1)\n",
    "#cpi.size\n",
    "dec2016 = cpi.get_value(2016,'Dec')\n",
    "\n",
    "inflator_array = np.empty((cpi.size,3),dtype=object)\n",
    "inflator_array.shape\n",
    "i = 0\n",
    "for j in cpi.index:\n",
    "    for k in cpi.columns:\n",
    "        inflator_array[i,0] = j\n",
    "        inflator_array[i,1] = str(k)\n",
    "        inflator_array[i,2] = cpi.loc[j][k] / dec2016\n",
    "        i = i + 1\n",
    "#for m in range(0,len(inflator)):\n",
    "#    for n in range(0,3):\n",
    "#        print(inflator[m,n])\n",
    "#dec2016 = cpi.get_value(2016,'Dec')\n",
    "#print(dec2016)\n",
    "#y\n",
    "inflator = pd.DataFrame(inflator_array,columns=[['year','month','factor']])\n",
    "inflator['year'] = pd.to_numeric(inflator['year'])\n",
    "inflator['month'] = inflator['month'].astype(str)\n",
    "inflator['factor'] = pd.to_numeric(inflator['factor'])\n",
    "inflator.dtypes\n",
    "\n",
    "movies['released'] = pd.to_datetime(movies['released'])\n",
    "movies['releaseyear'] = pd.to_datetime(movies['released'].dropna().apply(lambda x: x.year))\n",
    "movies['releasemonth'] = movies['released'].dropna().apply(lambda x: x.strftime('%b')).astype(str)\n",
    "movies.dtypes\n",
    "#print(movies.shape)\n",
    "\n",
    "# merge to preserve index from left table, cargo-culted from https://stackoverflow.com/questions/11976503/how-to-keep-index-when-using-pandas-merge\n",
    "#joined_df_con_llaves = joined_df.reset_index().merge(llaves_df, how='left', on=['imdbtitle','imdbyear']).set_index('imdb_id')\n",
    "movies_inflated = movies.reset_index().merge(inflator,how='left',left_on=['releaseyear','releasemonth'],right_on=['year','month']).set_index('imdb_id')\n",
    "\n",
    "#movies_inflated[['bechdel_title','released','factor']]\n",
    "#print(movies_inflated.columns)\n",
    "\n",
    "movies_inflated['boxoffice_adj'] = movies_inflated['boxoffice'] / movies_inflated['factor']\n",
    "movies_inflated['budget_adj'] = movies_inflated['budget'] / movies_inflated['factor']\n",
    "movies_inflated['openinggross_adj'] = movies_inflated['openinggross'] / movies_inflated['factor']\n",
    "movies_inflated['profit_adj'] = movies_inflated['boxoffice_adj'] - movies_inflated['budget_adj']\n",
    "movies_inflated['roi_adj'] = movies_inflated['profit_adj'] / movies_inflated['budget_adj']\n",
    "\n",
    "#movies_inflated[['bechdel_title','released','boxoffice','boxoffice_adj','budget','budget_adj','profit','profit_adj']].sample(3)#.style.format({'bechdel_title': '{:.40}', 'released': str, 'boxoffice': '${:,.0f}', 'boxoffice_adj': '${:,.0f}','budget': '${:,.0f}', 'budget_adj': '${:,.0f},})\n",
    "\n",
    "\n",
    "movies_inflated['title'] = movies_inflated['bechdel_title']\n",
    "\n",
    "movies_inflated = movies_inflated.drop('imdb_link.1', axis=1)\n",
    "movies_inflated = movies_inflated.drop('releaseyear', axis=1)\n",
    "movies_inflated = movies_inflated.drop('releasemonth', axis=1)\n",
    "movies_inflated = movies_inflated.drop('year', axis=1)\n",
    "movies_inflated = movies_inflated.drop('month', axis=1)\n",
    "\n",
    "#print(movies_inflated.shape)\n",
    "#movies_inflated.sample(3)\n",
    "\n",
    "print('old columns: {0:.0f}'.format(len(movies_inflated.columns)))\n",
    "#print(movies_inflated.columns)\n",
    "\n",
    "#print(movies_inflated.columns)\n",
    "\n",
    "new_column_order_list = list()\n",
    "# most important\n",
    "new_column_order_list += ['llave', 'title', 'released', 'bechdel_rating', 'bechdel_dubious']\n",
    "new_column_order_list += ['boxoffice_adj', 'budget_adj', 'profit_adj', 'roi_adj', 'openinggross_adj', 'totaltheaters', 'openingtheaters']\n",
    "new_column_order_list += ['boxoffice', 'budget', 'profit', 'openinggross']\n",
    "# less important\n",
    "new_column_order_list += ['mpaa_rating','studio', 'nVotes', 'userscore', 'metascore', 'genres', 'runtime', 'english', 'usa', 'imdb_plot']\n",
    "new_column_order_list += ['awards', 'director', 'writers', 'actors', 'posterlink', 'website', 'dvd_release_date', 'languages', 'countries', 'all_ratings_list']\n",
    "# Bechdel-specific\n",
    "new_column_order_list += ['bechdel_title', 'bechdel_submitter_id', 'bechdel_submitted_date', 'bechdel_year', 'bechdel_site_id', 'bechdel_visible']\n",
    "# IMDb-specific\n",
    "new_column_order_list += ['imdbtitle', 'imdbyear', 'imdb_release_date', 'imdb_boxoffice', 'imdb_link']\n",
    "# Boxofficemojo-specific\n",
    "new_column_order_list += ['title_boxofficemojo', 'studio_boxofficemojo', 'totalgross', 'boxofficemojo_url', 'release_date']\n",
    "# the-numbers-specific\n",
    "new_column_order_list += ['releasedate_thenumbers', 'title_thenumbers', 'genre_thenumbers', 'budget_thenumbers', 'revenue_thenumbers', 'year_thenumbers',  'has_trailer_thenumbers', 'the_numbers_url','factor']\n",
    "\n",
    "movies_inflated = movies_inflated[new_column_order_list]\n",
    "\n",
    "print('new columns: {0:.0f}'.format(len(movies_inflated.columns)))\n",
    "#print(movies_inflated.columns)\n",
    "movies_inflated.to_csv('movies_for_analysis.csv',encoding='utf-8')\n",
    "print('Done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}