{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "657d01e3",
   "metadata": {},
   "source": [
    "How do we read in our film scripts dataset? How would we sort the values in the dataset? How could we remove all the null values from the dataset? How we group our data by year?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "54a80dee",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ac4b0f67",
   "metadata": {},
   "outputs": [],
   "source": [
    "film_scripts = pd.read_csv('pudding_film_scripts.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2a583521",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>script_id</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>gross (inflation-adjusted)</th>\n",
       "      <th>link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tt0019777</td>\n",
       "      <td>4031</td>\n",
       "      <td>The Cocoanuts</td>\n",
       "      <td>1929</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.pages.drexel.edu/~ina22/splaylib/Sc...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     imdb_id  script_id          title  year  gross (inflation-adjusted)  \\\n",
       "0  tt0019777       4031  The Cocoanuts  1929                         NaN   \n",
       "\n",
       "                                                link  \n",
       "0  http://www.pages.drexel.edu/~ina22/splaylib/Sc...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts[0:1] #indexing rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ac658492",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>script_id</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>gross (inflation-adjusted)</th>\n",
       "      <th>link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1538</th>\n",
       "      <td>tt1022603</td>\n",
       "      <td>1534</td>\n",
       "      <td>(500) Days of Summer</td>\n",
       "      <td>2009</td>\n",
       "      <td>37.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/500 Days of...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>897</th>\n",
       "      <td>tt0147800</td>\n",
       "      <td>1512</td>\n",
       "      <td>10 Things I Hate About You</td>\n",
       "      <td>1999</td>\n",
       "      <td>65.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/10 Things I...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1864</th>\n",
       "      <td>tt2024544</td>\n",
       "      <td>1517</td>\n",
       "      <td>12 Years a Slave</td>\n",
       "      <td>2013</td>\n",
       "      <td>60.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/12 Years a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>tt0417385</td>\n",
       "      <td>1514</td>\n",
       "      <td>12 and Holding</td>\n",
       "      <td>2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/12 and Hold...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1753</th>\n",
       "      <td>tt1542344</td>\n",
       "      <td>1520</td>\n",
       "      <td>127 Hours</td>\n",
       "      <td>2010</td>\n",
       "      <td>20.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/127 Hours S...</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>831</th>\n",
       "      <td>tt0120906</td>\n",
       "      <td>8158</td>\n",
       "      <td>Zero Effect</td>\n",
       "      <td>1998</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Zero Effect (Jake Kasdan, 4.21.97).pdf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1292</th>\n",
       "      <td>tt0421090</td>\n",
       "      <td>3768</td>\n",
       "      <td>Zerophilia</td>\n",
       "      <td>2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/Zerophilia ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1326</th>\n",
       "      <td>tt0443706</td>\n",
       "      <td>6491</td>\n",
       "      <td>Zodiac</td>\n",
       "      <td>2007</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Zodiac (2007) (aka Chronicles) [Rev. 2006-7-5]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>tt0120907</td>\n",
       "      <td>6973</td>\n",
       "      <td>eXistenZ</td>\n",
       "      <td>1999</td>\n",
       "      <td>4.0</td>\n",
       "      <td>eXistenZ.pdf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1097</th>\n",
       "      <td>tt0295701</td>\n",
       "      <td>1497</td>\n",
       "      <td>xXx</td>\n",
       "      <td>2002</td>\n",
       "      <td>211.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/xXx.html</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        imdb_id  script_id                       title  year  \\\n",
       "1538  tt1022603       1534        (500) Days of Summer  2009   \n",
       "897   tt0147800       1512  10 Things I Hate About You  1999   \n",
       "1864  tt2024544       1517            12 Years a Slave  2013   \n",
       "1282  tt0417385       1514              12 and Holding  2005   \n",
       "1753  tt1542344       1520                   127 Hours  2010   \n",
       "...         ...        ...                         ...   ...   \n",
       "831   tt0120906       8158                 Zero Effect  1998   \n",
       "1292  tt0421090       3768                  Zerophilia  2005   \n",
       "1326  tt0443706       6491                      Zodiac  2007   \n",
       "832   tt0120907       6973                    eXistenZ  1999   \n",
       "1097  tt0295701       1497                         xXx  2002   \n",
       "\n",
       "      gross (inflation-adjusted)  \\\n",
       "1538                        37.0   \n",
       "897                         65.0   \n",
       "1864                        60.0   \n",
       "1282                         NaN   \n",
       "1753                        20.0   \n",
       "...                          ...   \n",
       "831                          3.0   \n",
       "1292                         NaN   \n",
       "1326                        41.0   \n",
       "832                          4.0   \n",
       "1097                       211.0   \n",
       "\n",
       "                                                   link  \n",
       "1538  http://www.imsdb.com/Movie Scripts/500 Days of...  \n",
       "897   http://www.imsdb.com/Movie Scripts/10 Things I...  \n",
       "1864  http://www.imsdb.com/Movie Scripts/12 Years a ...  \n",
       "1282  http://www.imsdb.com/Movie Scripts/12 and Hold...  \n",
       "1753  http://www.imsdb.com/Movie Scripts/127 Hours S...  \n",
       "...                                                 ...  \n",
       "831              Zero Effect (Jake Kasdan, 4.21.97).pdf  \n",
       "1292  http://www.imsdb.com/Movie Scripts/Zerophilia ...  \n",
       "1326  Zodiac (2007) (aka Chronicles) [Rev. 2006-7-5]...  \n",
       "832                                        eXistenZ.pdf  \n",
       "1097          film_20100519/all_imsdb_05_19_10/xXx.html  \n",
       "\n",
       "[2000 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts.sort_values(by=['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ae369d62",
   "metadata": {},
   "outputs": [],
   "source": [
    "film_scripts = film_scripts.rename(columns={'gross (inflation-adjusted)': 'gross_ia'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1f9baefa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for index, row in film_scripts[0:10].iterrows():\n",
    "#     print(row['gross_ia'])\n",
    "#     if row['gross_ia'] >= 0:\n",
    "#         print('is number')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "71ceef55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(film_scripts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cf8aedad",
   "metadata": {},
   "outputs": [],
   "source": [
    "subset_film_scripts = film_scripts[film_scripts.gross_ia.notna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c2592757",
   "metadata": {},
   "outputs": [],
   "source": [
    "films_year = subset_film_scripts.groupby('year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c1be0039",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>script_id</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tt0021884</td>\n",
       "      <td>8521</td>\n",
       "      <td>Frankenstein</td>\n",
       "      <td>1931</td>\n",
       "      <td>298.0</td>\n",
       "      <td>Frankenstein (Florey &amp; Fort) [1931-5-23] [Scan...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "     imdb_id  script_id         title  year  gross_ia  \\\n",
       "1  tt0021884       8521  Frankenstein  1931     298.0   \n",
       "\n",
       "                                                link  \n",
       "1  Frankenstein (Florey & Fort) [1931-5-23] [Scan...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
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    }
   ],
   "source": [
    "films_year.get_group(1931)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c0d4526d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
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       "      <th>title</th>\n",
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       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>tt0076759</td>\n",
       "      <td>1362</td>\n",
       "      <td>Star Wars: Episode IV - A New Hope</td>\n",
       "      <td>1977</td>\n",
       "      <td>1798.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/Star-Wars-A-N...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777</th>\n",
       "      <td>tt0120338</td>\n",
       "      <td>5136</td>\n",
       "      <td>Titanic</td>\n",
       "      <td>1997</td>\n",
       "      <td>1249.0</td>\n",
       "      <td>http://www.dailyscript.com/scripts/Titanic.txt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>tt0073195</td>\n",
       "      <td>2666</td>\n",
       "      <td>Jaws</td>\n",
       "      <td>1975</td>\n",
       "      <td>1103.0</td>\n",
       "      <td>http://www.dailyscript.com/scripts/Jaws.txt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>tt0061852</td>\n",
       "      <td>5534</td>\n",
       "      <td>The Jungle Book</td>\n",
       "      <td>1967</td>\n",
       "      <td>1029.0</td>\n",
       "      <td>http://www.cubbi.org/disney/scripts/tjb.txt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>tt0080684</td>\n",
       "      <td>3433</td>\n",
       "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
       "      <td>1980</td>\n",
       "      <td>937.0</td>\n",
       "      <td>http://www.scifiscripts.com/scripts/esb_final.txt</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       imdb_id  script_id                                           title  \\\n",
       "163  tt0076759       1362              Star Wars: Episode IV - A New Hope   \n",
       "777  tt0120338       5136                                         Titanic   \n",
       "137  tt0073195       2666                                            Jaws   \n",
       "81   tt0061852       5534                                 The Jungle Book   \n",
       "195  tt0080684       3433  Star Wars: Episode V - The Empire Strikes Back   \n",
       "\n",
       "     year  gross_ia                                               link  \n",
       "163  1977    1798.0  film_20100519/all_imsdb_05_19_10/Star-Wars-A-N...  \n",
       "777  1997    1249.0     http://www.dailyscript.com/scripts/Titanic.txt  \n",
       "137  1975    1103.0        http://www.dailyscript.com/scripts/Jaws.txt  \n",
       "81   1967    1029.0        http://www.cubbi.org/disney/scripts/tjb.txt  \n",
       "195  1980     937.0  http://www.scifiscripts.com/scripts/esb_final.txt  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset_film_scripts.nlargest(columns=['gross_ia'], n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "41515a88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "subset_film_scripts[['gross_ia']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "37a06af6",
   "metadata": {},
   "outputs": [],
   "source": [
    "film_scripts.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "11d86c17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year\n",
       "1929     1\n",
       "1931     2\n",
       "1932     4\n",
       "1933     3\n",
       "1934     2\n",
       "        ..\n",
       "2011    84\n",
       "2012    70\n",
       "2013    72\n",
       "2014    80\n",
       "2015    62\n",
       "Length: 81, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts.groupby('year').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d94214a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "films_year = film_scripts.groupby('year').size().reset_index(name='counts')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3f893474",
   "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>year</th>\n",
       "      <th>counts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1929</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1931</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1932</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1933</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1934</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2011</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2012</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2013</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2014</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2015</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  counts\n",
       "0   1929       1\n",
       "1   1931       2\n",
       "2   1932       4\n",
       "3   1933       3\n",
       "4   1934       2\n",
       "..   ...     ...\n",
       "76  2011      84\n",
       "77  2012      70\n",
       "78  2013      72\n",
       "79  2014      80\n",
       "80  2015      62\n",
       "\n",
       "[81 rows x 2 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "films_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5fa1d9cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "film_scripts_cleaned = film_scripts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "178d943c",
   "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>year</th>\n",
       "      <th>gross_ia</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1929</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1931</td>\n",
       "      <td>298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1932</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1933</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1934</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2011</td>\n",
       "      <td>209.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2012</td>\n",
       "      <td>680.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2013</td>\n",
       "      <td>429.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2014</td>\n",
       "      <td>372.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2015</td>\n",
       "      <td>927.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  gross_ia\n",
       "0   1929       0.0\n",
       "1   1931     298.0\n",
       "2   1932       0.0\n",
       "3   1933       0.0\n",
       "4   1934       0.0\n",
       "..   ...       ...\n",
       "76  2011     209.0\n",
       "77  2012     680.0\n",
       "78  2013     429.0\n",
       "79  2014     372.0\n",
       "80  2015     927.0\n",
       "\n",
       "[81 rows x 2 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts_cleaned.groupby('year')['gross_ia'].max().reset_index()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "68573d1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3508.0"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts[film_scripts.year == 2015]['gross_ia'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "2f53e6e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "38381195",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>script_id</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>gross_ia</th>\n",
       "      <th>link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tt0019777</td>\n",
       "      <td>4031</td>\n",
       "      <td>The Cocoanuts</td>\n",
       "      <td>1929</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.pages.drexel.edu/~ina22/splaylib/Sc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tt0021884</td>\n",
       "      <td>8521</td>\n",
       "      <td>Frankenstein</td>\n",
       "      <td>1931</td>\n",
       "      <td>298.0</td>\n",
       "      <td>Frankenstein (Florey &amp; Fort) [1931-5-23] [Scan...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tt0022054</td>\n",
       "      <td>1086</td>\n",
       "      <td>The Last Flight</td>\n",
       "      <td>1931</td>\n",
       "      <td>0.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/Last-Flight,-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tt0022626</td>\n",
       "      <td>1631</td>\n",
       "      <td>American Madness</td>\n",
       "      <td>1932</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/American Ma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tt0022958</td>\n",
       "      <td>2438</td>\n",
       "      <td>Grand Hotel</td>\n",
       "      <td>1932</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/Grand Hotel...</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>1995</th>\n",
       "      <td>tt3733778</td>\n",
       "      <td>8533</td>\n",
       "      <td>Pay the Ghost</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Pay The Ghost (Dan Kay, 9-1-09).pdf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>tt3808342</td>\n",
       "      <td>5499</td>\n",
       "      <td>Son of Saul</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://gointothestory.blcklst.com/wp-content/u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>tt3850214</td>\n",
       "      <td>8056</td>\n",
       "      <td>Dope</td>\n",
       "      <td>2015</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Dope (2013.10.31) [Digital].pdf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>tt3859076</td>\n",
       "      <td>5507</td>\n",
       "      <td>Truth</td>\n",
       "      <td>2015</td>\n",
       "      <td>2.0</td>\n",
       "      <td>http://gointothestory.blcklst.com/wp-content/u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>tt4270516</td>\n",
       "      <td>5410</td>\n",
       "      <td>Grandma</td>\n",
       "      <td>2015</td>\n",
       "      <td>7.0</td>\n",
       "      <td>http://gointothestory.blcklst.com/wp-content/u...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        imdb_id  script_id             title  year  gross_ia  \\\n",
       "0     tt0019777       4031     The Cocoanuts  1929       0.0   \n",
       "1     tt0021884       8521      Frankenstein  1931     298.0   \n",
       "2     tt0022054       1086   The Last Flight  1931       0.0   \n",
       "3     tt0022626       1631  American Madness  1932       0.0   \n",
       "4     tt0022958       2438       Grand Hotel  1932       0.0   \n",
       "...         ...        ...               ...   ...       ...   \n",
       "1995  tt3733778       8533     Pay the Ghost  2015       0.0   \n",
       "1996  tt3808342       5499       Son of Saul  2015       0.0   \n",
       "1997  tt3850214       8056              Dope  2015      18.0   \n",
       "1998  tt3859076       5507             Truth  2015       2.0   \n",
       "1999  tt4270516       5410           Grandma  2015       7.0   \n",
       "\n",
       "                                                   link  \n",
       "0     http://www.pages.drexel.edu/~ina22/splaylib/Sc...  \n",
       "1     Frankenstein (Florey & Fort) [1931-5-23] [Scan...  \n",
       "2     film_20100519/all_imsdb_05_19_10/Last-Flight,-...  \n",
       "3     http://www.imsdb.com/Movie Scripts/American Ma...  \n",
       "4     http://www.imsdb.com/Movie Scripts/Grand Hotel...  \n",
       "...                                                 ...  \n",
       "1995                Pay The Ghost (Dan Kay, 9-1-09).pdf  \n",
       "1996  http://gointothestory.blcklst.com/wp-content/u...  \n",
       "1997                    Dope (2013.10.31) [Digital].pdf  \n",
       "1998  http://gointothestory.blcklst.com/wp-content/u...  \n",
       "1999  http://gointothestory.blcklst.com/wp-content/u...  \n",
       "\n",
       "[2000 rows x 6 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "59a7fe1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df = pd.DataFrame({'gender': ['m','Male','fem.','FemalE','Femle']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3fc9a5a3",
   "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>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fem.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FemalE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Femle</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender\n",
       "0       m\n",
       "1    Male\n",
       "2    fem.\n",
       "3  FemalE\n",
       "4   Femle"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "51c27acb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      male\n",
       "1      male\n",
       "2    female\n",
       "3       NaN\n",
       "4       NaN\n",
       "Name: gender, dtype: object"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df['gender'].map({\n",
    "    'm':'male', 'Male':'male', 'fem.':'female'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "31090722",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c4bcdb36",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df.gender[test_df['gender'].str.match(r\"m\", flags=re.IGNORECASE)] = 'male'\n",
    "test_df.gender[test_df['gender'].str.match(r\"f\", flags=re.IGNORECASE)] = 'female'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ac91d6fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender\n",
       "0    male\n",
       "1    male\n",
       "2  female\n",
       "3  female\n",
       "4  female"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a06f05fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>script_id</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>gross_ia</th>\n",
       "      <th>link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tt0019777</td>\n",
       "      <td>4031</td>\n",
       "      <td>The Cocoanuts</td>\n",
       "      <td>1929</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.pages.drexel.edu/~ina22/splaylib/Sc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tt0021884</td>\n",
       "      <td>8521</td>\n",
       "      <td>Frankenstein</td>\n",
       "      <td>1931</td>\n",
       "      <td>298.0</td>\n",
       "      <td>Frankenstein (Florey &amp; Fort) [1931-5-23] [Scan...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tt0022054</td>\n",
       "      <td>1086</td>\n",
       "      <td>The Last Flight</td>\n",
       "      <td>1931</td>\n",
       "      <td>0.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/Last-Flight,-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tt0022626</td>\n",
       "      <td>1631</td>\n",
       "      <td>American Madness</td>\n",
       "      <td>1932</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/American Ma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tt0022958</td>\n",
       "      <td>2438</td>\n",
       "      <td>Grand Hotel</td>\n",
       "      <td>1932</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.imsdb.com/Movie Scripts/Grand Hotel...</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>1995</th>\n",
       "      <td>tt3733778</td>\n",
       "      <td>8533</td>\n",
       "      <td>Pay the Ghost</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Pay The Ghost (Dan Kay, 9-1-09).pdf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>tt3808342</td>\n",
       "      <td>5499</td>\n",
       "      <td>Son of Saul</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://gointothestory.blcklst.com/wp-content/u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>tt3850214</td>\n",
       "      <td>8056</td>\n",
       "      <td>Dope</td>\n",
       "      <td>2015</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Dope (2013.10.31) [Digital].pdf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>tt3859076</td>\n",
       "      <td>5507</td>\n",
       "      <td>Truth</td>\n",
       "      <td>2015</td>\n",
       "      <td>2.0</td>\n",
       "      <td>http://gointothestory.blcklst.com/wp-content/u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>tt4270516</td>\n",
       "      <td>5410</td>\n",
       "      <td>Grandma</td>\n",
       "      <td>2015</td>\n",
       "      <td>7.0</td>\n",
       "      <td>http://gointothestory.blcklst.com/wp-content/u...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        imdb_id  script_id             title  year  gross_ia  \\\n",
       "0     tt0019777       4031     The Cocoanuts  1929       0.0   \n",
       "1     tt0021884       8521      Frankenstein  1931     298.0   \n",
       "2     tt0022054       1086   The Last Flight  1931       0.0   \n",
       "3     tt0022626       1631  American Madness  1932       0.0   \n",
       "4     tt0022958       2438       Grand Hotel  1932       0.0   \n",
       "...         ...        ...               ...   ...       ...   \n",
       "1995  tt3733778       8533     Pay the Ghost  2015       0.0   \n",
       "1996  tt3808342       5499       Son of Saul  2015       0.0   \n",
       "1997  tt3850214       8056              Dope  2015      18.0   \n",
       "1998  tt3859076       5507             Truth  2015       2.0   \n",
       "1999  tt4270516       5410           Grandma  2015       7.0   \n",
       "\n",
       "                                                   link  \n",
       "0     http://www.pages.drexel.edu/~ina22/splaylib/Sc...  \n",
       "1     Frankenstein (Florey & Fort) [1931-5-23] [Scan...  \n",
       "2     film_20100519/all_imsdb_05_19_10/Last-Flight,-...  \n",
       "3     http://www.imsdb.com/Movie Scripts/American Ma...  \n",
       "4     http://www.imsdb.com/Movie Scripts/Grand Hotel...  \n",
       "...                                                 ...  \n",
       "1995                Pay The Ghost (Dan Kay, 9-1-09).pdf  \n",
       "1996  http://gointothestory.blcklst.com/wp-content/u...  \n",
       "1997                    Dope (2013.10.31) [Digital].pdf  \n",
       "1998  http://gointothestory.blcklst.com/wp-content/u...  \n",
       "1999  http://gointothestory.blcklst.com/wp-content/u...  \n",
       "\n",
       "[2000 rows x 6 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "film_scripts_cleaned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "2359f7fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "films_gross_sum = film_scripts_cleaned.groupby('year')['gross_ia'].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "205fe7d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>gross_ia</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1929</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1931</td>\n",
       "      <td>298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1932</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1933</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1934</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2011</td>\n",
       "      <td>4282.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2012</td>\n",
       "      <td>5288.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2013</td>\n",
       "      <td>4839.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2014</td>\n",
       "      <td>4159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2015</td>\n",
       "      <td>3508.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  gross_ia\n",
       "0   1929       0.0\n",
       "1   1931     298.0\n",
       "2   1932       0.0\n",
       "3   1933       0.0\n",
       "4   1934       0.0\n",
       "..   ...       ...\n",
       "76  2011    4282.0\n",
       "77  2012    5288.0\n",
       "78  2013    4839.0\n",
       "79  2014    4159.0\n",
       "80  2015    3508.0\n",
       "\n",
       "[81 rows x 2 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "films_gross_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "cb773ae7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((81, 2), (2000, 6))"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "films_gross_sum.shape, film_scripts_cleaned.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "e3464a00",
   "metadata": {},
   "outputs": [],
   "source": [
    "films_gross_sum = films_gross_sum.rename(columns={'gross_ia': 'gross_sum'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1455e7d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Index(['year', 'gross_sum'], dtype='object'),\n",
       " Index(['imdb_id', 'script_id', 'title', 'year', 'gross_ia', 'link'], dtype='object'))"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "films_gross_sum.columns, film_scripts_cleaned.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "438627cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_films = subset_film_scripts.merge(films_gross_sum, how='outer', on=['year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "f1affec0",
   "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>imdb_id</th>\n",
       "      <th>script_id</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>gross_ia</th>\n",
       "      <th>link</th>\n",
       "      <th>gross_sum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tt0021884</td>\n",
       "      <td>8521.0</td>\n",
       "      <td>Frankenstein</td>\n",
       "      <td>1931</td>\n",
       "      <td>298.0</td>\n",
       "      <td>Frankenstein (Florey &amp; Fort) [1931-5-23] [Scan...</td>\n",
       "      <td>298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tt0031725</td>\n",
       "      <td>3016.0</td>\n",
       "      <td>Ninotchka</td>\n",
       "      <td>1939</td>\n",
       "      <td>45.0</td>\n",
       "      <td>http://www.dailyscript.com/scripts/Ninotchka.txt</td>\n",
       "      <td>884.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tt0032138</td>\n",
       "      <td>1483.0</td>\n",
       "      <td>The Wizard of Oz</td>\n",
       "      <td>1939</td>\n",
       "      <td>839.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/Wizard-of-Oz,...</td>\n",
       "      <td>884.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tt0035423</td>\n",
       "      <td>1213.0</td>\n",
       "      <td>Kate &amp; Leopold</td>\n",
       "      <td>2001</td>\n",
       "      <td>72.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/Kate-&amp;-Leopol...</td>\n",
       "      <td>6293.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tt0120737</td>\n",
       "      <td>1115.0</td>\n",
       "      <td>The Lord of the Rings: The Fellowship of the Ring</td>\n",
       "      <td>2001</td>\n",
       "      <td>482.0</td>\n",
       "      <td>film_20100519/all_imsdb_05_19_10/Lord-of-the-R...</td>\n",
       "      <td>6293.0</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1682</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1683</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1684</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1686</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1969</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1687 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        imdb_id  script_id                                              title  \\\n",
       "0     tt0021884     8521.0                                       Frankenstein   \n",
       "1     tt0031725     3016.0                                          Ninotchka   \n",
       "2     tt0032138     1483.0                                   The Wizard of Oz   \n",
       "3     tt0035423     1213.0                                     Kate & Leopold   \n",
       "4     tt0120737     1115.0  The Lord of the Rings: The Fellowship of the Ring   \n",
       "...         ...        ...                                                ...   \n",
       "1682        NaN        NaN                                                NaN   \n",
       "1683        NaN        NaN                                                NaN   \n",
       "1684        NaN        NaN                                                NaN   \n",
       "1685        NaN        NaN                                                NaN   \n",
       "1686        NaN        NaN                                                NaN   \n",
       "\n",
       "      year  gross_ia                                               link  \\\n",
       "0     1931     298.0  Frankenstein (Florey & Fort) [1931-5-23] [Scan...   \n",
       "1     1939      45.0   http://www.dailyscript.com/scripts/Ninotchka.txt   \n",
       "2     1939     839.0  film_20100519/all_imsdb_05_19_10/Wizard-of-Oz,...   \n",
       "3     2001      72.0  film_20100519/all_imsdb_05_19_10/Kate-&-Leopol...   \n",
       "4     2001     482.0  film_20100519/all_imsdb_05_19_10/Lord-of-the-R...   \n",
       "...    ...       ...                                                ...   \n",
       "1682  1961       NaN                                                NaN   \n",
       "1683  1963       NaN                                                NaN   \n",
       "1684  1964       NaN                                                NaN   \n",
       "1685  1965       NaN                                                NaN   \n",
       "1686  1969       NaN                                                NaN   \n",
       "\n",
       "      gross_sum  \n",
       "0         298.0  \n",
       "1         884.0  \n",
       "2         884.0  \n",
       "3        6293.0  \n",
       "4        6293.0  \n",
       "...         ...  \n",
       "1682        0.0  \n",
       "1683        0.0  \n",
       "1684        0.0  \n",
       "1685        0.0  \n",
       "1686        0.0  \n",
       "\n",
       "[1687 rows x 7 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_films"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "3e02a9f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='gross_ia', ylabel='gross_sum'>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged_films.plot.scatter(x='gross_ia', y='gross_sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c3f98a5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "is310_env",
   "language": "python",
   "name": "is310_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}