analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyzing TIMDB (The Indian Movie Database)\n",
    "\n",
    "**The complete database can be found on [Github](https://github.com/pncnmnp/TIMDB).**\n",
    "\n",
    "**This notebook is created by the author of this dataset.**\n",
    "\n",
    "This database contains a list of Indian movies and it's meta-data, with release years ranging between 1950 and 2019.\n",
    "As the database is big, we will start by analyzing the primary dataset: `./1950-2019/bollywood_full.csv`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from nltk.corpus import stopwords\n",
    "from difflib import get_close_matches\n",
    "from surprise import Reader, Dataset, KNNBaseline\n",
    "\n",
    "file = \"./1950-2019/bollywood_full.csv\"\n",
    "df = pd.read_csv(open(file, \"r\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title_x</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>wiki_link</th>\n",
       "      <th>title_y</th>\n",
       "      <th>original_title</th>\n",
       "      <th>is_adult</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>story</th>\n",
       "      <th>summary</th>\n",
       "      <th>tagline</th>\n",
       "      <th>actors</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>tt8291224</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Uri:_The_Surgica...</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>138</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112.0</td>\n",
       "      <td>Divided over five chapters  the film chronicle...</td>\n",
       "      <td>Indian army special forces execute a covert op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...</td>\n",
       "      <td>4 wins</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>tt9472208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Battalion_609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>Battalion 609</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>131</td>\n",
       "      <td>War</td>\n",
       "      <td>4.1</td>\n",
       "      <td>73.0</td>\n",
       "      <td>The story revolves around a cricket match betw...</td>\n",
       "      <td>The story of Battalion 609 revolves around a c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Accidental Prime Minister (film)</td>\n",
       "      <td>tt6986710</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Accidental_P...</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>The Accidental Prime Minister</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>112</td>\n",
       "      <td>Biography|Drama</td>\n",
       "      <td>6.1</td>\n",
       "      <td>5549.0</td>\n",
       "      <td>Based on the memoir by Indian policy analyst S...</td>\n",
       "      <td>Explores Manmohan Singh's tenure as the Prime ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>tt8108208</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Why_Cheat_India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>Why Cheat India</td>\n",
       "      <td>0</td>\n",
       "      <td>2019</td>\n",
       "      <td>121</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1891.0</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>The movie focuses on existing malpractices in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 January 2019 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>tt6028796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Evening_Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>Evening Shadows</td>\n",
       "      <td>0</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.3</td>\n",
       "      <td>280.0</td>\n",
       "      <td>While gay rights and marriage equality has bee...</td>\n",
       "      <td>Under the 'Evening Shadows'  truth often plays...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...</td>\n",
       "      <td>17 wins &amp; 1 nomination</td>\n",
       "      <td>11 January 2019 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                title_x    imdb_id  \\\n",
       "0              Uri: The Surgical Strike  tt8291224   \n",
       "1                         Battalion 609  tt9472208   \n",
       "2  The Accidental Prime Minister (film)  tt6986710   \n",
       "3                       Why Cheat India  tt8108208   \n",
       "4                       Evening Shadows  tt6028796   \n",
       "\n",
       "                                         poster_path  \\\n",
       "0  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "1                                                NaN   \n",
       "2  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "3  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "4                                                NaN   \n",
       "\n",
       "                                           wiki_link  \\\n",
       "0  https://en.wikipedia.org/wiki/Uri:_The_Surgica...   \n",
       "1        https://en.wikipedia.org/wiki/Battalion_609   \n",
       "2  https://en.wikipedia.org/wiki/The_Accidental_P...   \n",
       "3      https://en.wikipedia.org/wiki/Why_Cheat_India   \n",
       "4      https://en.wikipedia.org/wiki/Evening_Shadows   \n",
       "\n",
       "                         title_y                 original_title  is_adult  \\\n",
       "0       Uri: The Surgical Strike       Uri: The Surgical Strike         0   \n",
       "1                  Battalion 609                  Battalion 609         0   \n",
       "2  The Accidental Prime Minister  The Accidental Prime Minister         0   \n",
       "3                Why Cheat India                Why Cheat India         0   \n",
       "4                Evening Shadows                Evening Shadows         0   \n",
       "\n",
       "  year_of_release runtime            genres  imdb_rating  imdb_votes  \\\n",
       "0            2019     138  Action|Drama|War          8.4     35112.0   \n",
       "1            2019     131               War          4.1        73.0   \n",
       "2            2019     112   Biography|Drama          6.1      5549.0   \n",
       "3            2019     121       Crime|Drama          6.0      1891.0   \n",
       "4            2018     102             Drama          7.3       280.0   \n",
       "\n",
       "                                               story  \\\n",
       "0  Divided over five chapters  the film chronicle...   \n",
       "1  The story revolves around a cricket match betw...   \n",
       "2  Based on the memoir by Indian policy analyst S...   \n",
       "3  The movie focuses on existing malpractices in ...   \n",
       "4  While gay rights and marriage equality has bee...   \n",
       "\n",
       "                                             summary tagline  \\\n",
       "0  Indian army special forces execute a covert op...     NaN   \n",
       "1  The story of Battalion 609 revolves around a c...     NaN   \n",
       "2  Explores Manmohan Singh's tenure as the Prime ...     NaN   \n",
       "3  The movie focuses on existing malpractices in ...     NaN   \n",
       "4  Under the 'Evening Shadows'  truth often plays...     NaN   \n",
       "\n",
       "                                              actors        wins_nominations  \\\n",
       "0  Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...                  4 wins   \n",
       "1  Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...                     NaN   \n",
       "2  Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...                     NaN   \n",
       "3  Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...                     NaN   \n",
       "4  Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...  17 wins & 1 nomination   \n",
       "\n",
       "              release_date  \n",
       "0    11 January 2019 (USA)  \n",
       "1  11 January 2019 (India)  \n",
       "2    11 January 2019 (USA)  \n",
       "3    18 January 2019 (USA)  \n",
       "4  11 January 2019 (India)  "
      ]
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    "df.head()"
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  {
   "cell_type": "code",
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       "      <td>4047</td>\n",
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       "      <td>71</td>\n",
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       "      <td>264</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>4020</td>\n",
       "      <td>4021</td>\n",
       "      <td>678</td>\n",
       "      <td>4271</td>\n",
       "      <td>250</td>\n",
       "      <td>2278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Aan</td>\n",
       "      <td>tt0347416</td>\n",
       "      <td>https://upload.wikimedia.org/wikipedia/en/thum...</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Aakraman</td>\n",
       "      <td>Anari</td>\n",
       "      <td>Dushman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014</td>\n",
       "      <td>\\N</td>\n",
       "      <td>Drama</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Royal Indian family consists of the Emperor ...</td>\n",
       "      <td>Add a Plot »</td>\n",
       "      <td>A million-dollar fake</td>\n",
       "      <td>Mala Sinha|Dharmendra|Kumkum|Sujit Kumar|Mehmo...</td>\n",
       "      <td>1 nomination</td>\n",
       "      <td>1977 (India)</td>\n",
       "    </tr>\n",
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       "      <th>freq</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110</td>\n",
       "      <td>919</td>\n",
       "      <td>513</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>264</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>229</td>\n",
       "      <td>8</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2387.874913</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>9404.126400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>75%</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       title_x    imdb_id                                        poster_path  \\\n",
       "count     4330       4330                                               3580   \n",
       "unique    4288       4284                                               3529   \n",
       "top        Aan  tt0347416  https://upload.wikimedia.org/wikipedia/en/thum...   \n",
       "freq         2          2                                                  7   \n",
       "mean       NaN        NaN                                                NaN   \n",
       "std        NaN        NaN                                                NaN   \n",
       "min        NaN        NaN                                                NaN   \n",
       "25%        NaN        NaN                                                NaN   \n",
       "50%        NaN        NaN                                                NaN   \n",
       "75%        NaN        NaN                                                NaN   \n",
       "max        NaN        NaN                                                NaN   \n",
       "\n",
       "                                     wiki_link title_y original_title  \\\n",
       "count                                     4330    4330           4330   \n",
       "unique                                    4330    4052           4047   \n",
       "top     https://en.wikipedia.org/wiki/Aakraman   Anari        Dushman   \n",
       "freq                                         1       4              4   \n",
       "mean                                       NaN     NaN            NaN   \n",
       "std                                        NaN     NaN            NaN   \n",
       "min                                        NaN     NaN            NaN   \n",
       "25%                                        NaN     NaN            NaN   \n",
       "50%                                        NaN     NaN            NaN   \n",
       "75%                                        NaN     NaN            NaN   \n",
       "max                                        NaN     NaN            NaN   \n",
       "\n",
       "        is_adult year_of_release runtime genres  imdb_rating     imdb_votes  \\\n",
       "count     4330.0            4330    4330   4330  4317.000000    4317.000000   \n",
       "unique       NaN              71     149    264          NaN            NaN   \n",
       "top          NaN            2014      \\N  Drama          NaN            NaN   \n",
       "freq         NaN             110     919    513          NaN            NaN   \n",
       "mean         0.0             NaN     NaN    NaN     5.911744    2387.874913   \n",
       "std          0.0             NaN     NaN    NaN     1.330077    9404.126400   \n",
       "min          0.0             NaN     NaN    NaN     0.000000       0.000000   \n",
       "25%          0.0             NaN     NaN    NaN     5.100000      32.000000   \n",
       "50%          0.0             NaN     NaN    NaN     6.100000     131.000000   \n",
       "75%          0.0             NaN     NaN    NaN     6.900000     966.000000   \n",
       "max          0.0             NaN     NaN    NaN     9.400000  310481.000000   \n",
       "\n",
       "                                                    story       summary  \\\n",
       "count                                                4065          4329   \n",
       "unique                                               4020          4021   \n",
       "top     A Royal Indian family consists of the Emperor ...  Add a Plot »   \n",
       "freq                                                    2           264   \n",
       "mean                                                  NaN           NaN   \n",
       "std                                                   NaN           NaN   \n",
       "min                                                   NaN           NaN   \n",
       "25%                                                   NaN           NaN   \n",
       "50%                                                   NaN           NaN   \n",
       "75%                                                   NaN           NaN   \n",
       "max                                                   NaN           NaN   \n",
       "\n",
       "                      tagline  \\\n",
       "count                     685   \n",
       "unique                    678   \n",
       "top     A million-dollar fake   \n",
       "freq                        2   \n",
       "mean                      NaN   \n",
       "std                       NaN   \n",
       "min                       NaN   \n",
       "25%                       NaN   \n",
       "50%                       NaN   \n",
       "75%                       NaN   \n",
       "max                       NaN   \n",
       "\n",
       "                                                   actors wins_nominations  \\\n",
       "count                                                4320             1344   \n",
       "unique                                               4271              250   \n",
       "top     Mala Sinha|Dharmendra|Kumkum|Sujit Kumar|Mehmo...     1 nomination   \n",
       "freq                                                    2              229   \n",
       "mean                                                  NaN              NaN   \n",
       "std                                                   NaN              NaN   \n",
       "min                                                   NaN              NaN   \n",
       "25%                                                   NaN              NaN   \n",
       "50%                                                   NaN              NaN   \n",
       "75%                                                   NaN              NaN   \n",
       "max                                                   NaN              NaN   \n",
       "\n",
       "        release_date  \n",
       "count           3049  \n",
       "unique          2278  \n",
       "top     1977 (India)  \n",
       "freq               8  \n",
       "mean             NaN  \n",
       "std              NaN  \n",
       "min              NaN  \n",
       "25%              NaN  \n",
       "50%              NaN  \n",
       "75%              NaN  \n",
       "max              NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4330, 18)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the above information, few elementary conclusions can be drawn:\n",
    "* There are 4330 movies in this dataset\n",
    "* As mean is `0.0` for `is_adult`, the value is same for all movies. Hence we can drop that attribute\n",
    "* `actors` and `genres` are separated by |\n",
    "* Many movies don't have information about `tagline` and `wins_nominations` (Less information pertaining to `wins_nominations` is obvious as not every film can win awards or get nominated 😄)\n",
    "* `runtime` is of dtype `object` as null values are entered in character form ('\\N'). We need to convert it to `float64` type\n",
    "* The mean IMDB rating is 5.91 and the maximum rating a film has been given is 9.4 \n",
    "\n",
    "**A note from documentation (for `./1950-2019/bollywood_full.csv`)**\n",
    "> (This dataset is merged ON \"imdb_id\", hence if you find a niche-movie missing, see the respective year's directory).\n",
    "\n",
    "**i.e** if a movie released in 1994 is missing from this dataset, check the directory `./1990-2009/`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(['is_adult'], axis=1)\n",
    "\n",
    "df[\"actors\"] = df[\"actors\"].apply(lambda actors: actors.strip().split(\"|\") if isinstance(actors, str) else [])\n",
    "df[\"genres\"] = df[\"genres\"].apply(lambda genres: genres.strip().split(\"|\") if isinstance(genres, str) else [])\n",
    "\n",
    "df[\"runtime\"] = pd.to_numeric(df[\"runtime\"].replace(\"\\\\N\", np.nan))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"runtime\"].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>actors</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[Vicky Kaushal, Paresh Rawal, Mohit Raina, Yam...</td>\n",
       "      <td>[Action, Drama, War]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[Vicky Ahuja, Shoaib Ibrahim, Shrikant Kamat, ...</td>\n",
       "      <td>[War]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[Anupam Kher, Akshaye Khanna, Aahana Kumra, At...</td>\n",
       "      <td>[Biography, Drama]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[Emraan Hashmi, Shreya Dhanwanthary, Snighdade...</td>\n",
       "      <td>[Crime, Drama]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[Mona Ambegaonkar, Ananth Narayan Mahadevan, D...</td>\n",
       "      <td>[Drama]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              actors                genres\n",
       "0  [Vicky Kaushal, Paresh Rawal, Mohit Raina, Yam...  [Action, Drama, War]\n",
       "1  [Vicky Ahuja, Shoaib Ibrahim, Shrikant Kamat, ...                 [War]\n",
       "2  [Anupam Kher, Akshaye Khanna, Aahana Kumra, At...    [Biography, Drama]\n",
       "3  [Emraan Hashmi, Shreya Dhanwanthary, Snighdade...        [Crime, Drama]\n",
       "4  [Mona Ambegaonkar, Ananth Narayan Mahadevan, D...               [Drama]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"actors\", \"genres\"]].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we continue, I have got to know *which film scored a 9.4 on IMDB* 😁"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>original_title</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>imdb_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Family of Thakurganj</td>\n",
       "      <td>2019</td>\n",
       "      <td>tt8897986</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          original_title year_of_release    imdb_id\n",
       "41  Family of Thakurganj            2019  tt8897986"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"imdb_rating\"] == 9.4][[\"original_title\", \"year_of_release\", \"imdb_id\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How ? What .... [Apparently this film does have a rating of 9.4](https://www.imdb.com/title/tt8897986/)! (as of December 27, 2019)\n",
    "\n",
    "Let's start playing with the dataset. First we will find statistics about `runtime` attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(count    3411.000000\n",
       " mean      140.250660\n",
       " std        23.763995\n",
       " min         7.000000\n",
       " 25%       126.000000\n",
       " 50%       140.000000\n",
       " 75%       155.000000\n",
       " max       321.000000\n",
       " Name: runtime, dtype: float64,\n",
       " 'Total hours of content created by Indian cinema: 7973.25')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df[\"runtime\"].describe(), \"Total hours of content created by Indian cinema: \" + str(sum(df[\"runtime\"].dropna().tolist())/60))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, **the average runtime of a Bollywood movie is around `140` minutes**.\n",
    "\n",
    "Also `7973` hours (approx.) of content has been produced by Indian Cinema. *That's impressive!*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "year_mapping = dict()\n",
    "for year in range(1950, 2020, 10):\n",
    "    year_mapping[year] = 0\n",
    "    for key in df[\"year_of_release\"].dropna().value_counts().keys():\n",
    "        if key != \"\\\\N\" and int(key) - year < 10:\n",
    "            year_mapping[year] += df[\"year_of_release\"].dropna().value_counts()[key]\n",
    "                \n",
    "plt.pie([val for val in year_mapping.values()], labels=[key for key in year_mapping.keys()], autopct=\"%.2f\")\n",
    "plt.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above pie chart shows the % of movies released (categorized by decade). Almost 75% of all movies were released in the last 3 decades. The film industry saw an approx. of 5% growth every decade!\n",
    "\n",
    "We will now look at the blockbusters produced by Indian cinema. For this, I will be using IMDB's rating algorithm: \n",
    "> weighted rating (WR) = (v ÷ (v+m)) × R + (m ÷ (v+m)) × C  \n",
    "Where:  \n",
    "R = average for the movie (mean) = (rating)  \n",
    "v = number of votes for the movie = (votes)  \n",
    "m = minimum votes required to be listed in the Top Rated list (currently 25,000)  \n",
    "C = the mean vote across the whole report\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the genres in the dataset are: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Action',\n",
       " 'Adventure',\n",
       " 'Animation',\n",
       " 'Biography',\n",
       " 'Comedy',\n",
       " 'Crime',\n",
       " 'Documentary',\n",
       " 'Drama',\n",
       " 'Family',\n",
       " 'Fantasy',\n",
       " 'History',\n",
       " 'Horror',\n",
       " 'Music',\n",
       " 'Musical',\n",
       " 'Mystery',\n",
       " 'Romance',\n",
       " 'Sci-Fi',\n",
       " 'Short',\n",
       " 'Sport',\n",
       " 'Thriller',\n",
       " 'War',\n",
       " 'Western'}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_genres = set([genre for genre in [genres for genres in df[\"genres\"].tolist()] for genre in genre])\n",
    "all_genres.remove(\"\\\\N\")\n",
    "all_genres"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def imdb_rating(film, C, m):\n",
    "    vote = film[\"imdb_votes\"]\n",
    "    rating = film[\"imdb_rating\"]\n",
    "\n",
    "    return ((vote / (vote + m)) * rating) + ((m / (vote + m)) * C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def top_movies(df, percentile=0.85, limit=10, offset=0, genre=None):\n",
    "    if genre != None:\n",
    "        top_df = df[df[\"genres\"].apply(lambda genres: genre in genres)]\n",
    "    else:\n",
    "        top_df = df\n",
    "\n",
    "    rating = df[df[\"imdb_rating\"].notnull()][\"imdb_rating\"]\n",
    "    votes = df[df[\"imdb_votes\"].notnull()][\"imdb_votes\"]\n",
    "    imdb_C = rating.mean()\n",
    "    # For the dataset, percentile = 0.85 roughly corresponds to 2500\n",
    "    # To match IMDB's parameter, percentile should be around 0.98026\n",
    "    imdb_m = votes.quantile(percentile)\n",
    "\n",
    "    top_df = top_df[top_df[\"imdb_votes\"] >= imdb_m]\n",
    "\n",
    "    pd.options.mode.chained_assignment = None\n",
    "    top_df[\"rating\"] = top_df.apply(imdb_rating, args=(imdb_C, imdb_m), axis=1)\n",
    "    top_df = top_df.sort_values(\"rating\", ascending=False)\n",
    "    \n",
    "    return top_df.iloc[offset: offset+limit]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>original_title</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>rating</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>imdb_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3615</th>\n",
       "      <td>Anand</td>\n",
       "      <td>8.8</td>\n",
       "      <td>23953.0</td>\n",
       "      <td>8.527217</td>\n",
       "      <td>1971</td>\n",
       "      <td>tt0066763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>916</th>\n",
       "      <td>3 Idiots</td>\n",
       "      <td>8.4</td>\n",
       "      <td>310481.0</td>\n",
       "      <td>8.380139</td>\n",
       "      <td>2009</td>\n",
       "      <td>tt1187043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1131</th>\n",
       "      <td>Taare Zameen Par</td>\n",
       "      <td>8.4</td>\n",
       "      <td>148498.0</td>\n",
       "      <td>8.358832</td>\n",
       "      <td>2007</td>\n",
       "      <td>tt0986264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>Dangal</td>\n",
       "      <td>8.4</td>\n",
       "      <td>131338.0</td>\n",
       "      <td>8.353554</td>\n",
       "      <td>2016</td>\n",
       "      <td>tt5074352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Andhadhun</td>\n",
       "      <td>8.4</td>\n",
       "      <td>51615.0</td>\n",
       "      <td>8.285127</td>\n",
       "      <td>2018</td>\n",
       "      <td>tt8108198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3119</th>\n",
       "      <td>Gol Maal</td>\n",
       "      <td>8.6</td>\n",
       "      <td>16086.0</td>\n",
       "      <td>8.238628</td>\n",
       "      <td>1979</td>\n",
       "      <td>tt0079221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Uri: The Surgical Strike</td>\n",
       "      <td>8.4</td>\n",
       "      <td>35112.0</td>\n",
       "      <td>8.234721</td>\n",
       "      <td>2019</td>\n",
       "      <td>tt8291224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1209</th>\n",
       "      <td>Bacheha-Ye aseman</td>\n",
       "      <td>8.3</td>\n",
       "      <td>56293.0</td>\n",
       "      <td>8.198516</td>\n",
       "      <td>1997</td>\n",
       "      <td>tt0118849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>Black Friday</td>\n",
       "      <td>8.5</td>\n",
       "      <td>16761.0</td>\n",
       "      <td>8.164265</td>\n",
       "      <td>2004</td>\n",
       "      <td>tt0400234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1201</th>\n",
       "      <td>Rang De Basanti</td>\n",
       "      <td>8.2</td>\n",
       "      <td>103071.0</td>\n",
       "      <td>8.145850</td>\n",
       "      <td>2006</td>\n",
       "      <td>tt0405508</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                original_title  imdb_rating  imdb_votes    rating  \\\n",
       "3615                     Anand          8.8     23953.0  8.527217   \n",
       "916                   3 Idiots          8.4    310481.0  8.380139   \n",
       "1131          Taare Zameen Par          8.4    148498.0  8.358832   \n",
       "354                     Dangal          8.4    131338.0  8.353554   \n",
       "146                  Andhadhun          8.4     51615.0  8.285127   \n",
       "3119                  Gol Maal          8.6     16086.0  8.238628   \n",
       "0     Uri: The Surgical Strike          8.4     35112.0  8.234721   \n",
       "1209         Bacheha-Ye aseman          8.3     56293.0  8.198516   \n",
       "1062              Black Friday          8.5     16761.0  8.164265   \n",
       "1201           Rang De Basanti          8.2    103071.0  8.145850   \n",
       "\n",
       "     year_of_release    imdb_id  \n",
       "3615            1971  tt0066763  \n",
       "916             2009  tt1187043  \n",
       "1131            2007  tt0986264  \n",
       "354             2016  tt5074352  \n",
       "146             2018  tt8108198  \n",
       "3119            1979  tt0079221  \n",
       "0               2019  tt8291224  \n",
       "1209            1997  tt0118849  \n",
       "1062            2004  tt0400234  \n",
       "1201            2006  tt0405508  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_movies(df)[[\"original_title\", \"imdb_rating\", \"imdb_votes\", \"rating\", \"year_of_release\", \"imdb_id\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To find top movies (by genre), simply fill the `genre` attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>original_title</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>rating</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>imdb_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>Drishyam</td>\n",
       "      <td>8.2</td>\n",
       "      <td>58340.0</td>\n",
       "      <td>8.106037</td>\n",
       "      <td>2015</td>\n",
       "      <td>tt4430212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>Talvar</td>\n",
       "      <td>8.2</td>\n",
       "      <td>26612.0</td>\n",
       "      <td>8.003625</td>\n",
       "      <td>2015</td>\n",
       "      <td>tt4934950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>673</th>\n",
       "      <td>Kahaani</td>\n",
       "      <td>8.1</td>\n",
       "      <td>53181.0</td>\n",
       "      <td>8.001818</td>\n",
       "      <td>2012</td>\n",
       "      <td>tt1821480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>Ugly</td>\n",
       "      <td>8.1</td>\n",
       "      <td>17483.0</td>\n",
       "      <td>7.826408</td>\n",
       "      <td>2013</td>\n",
       "      <td>tt2882328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Badla</td>\n",
       "      <td>7.9</td>\n",
       "      <td>15499.0</td>\n",
       "      <td>7.624009</td>\n",
       "      <td>2019</td>\n",
       "      <td>tt8130968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>Johnny Gaddaar</td>\n",
       "      <td>7.8</td>\n",
       "      <td>10612.0</td>\n",
       "      <td>7.440185</td>\n",
       "      <td>2007</td>\n",
       "      <td>tt1077248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>Detective Byomkesh Bakshy!</td>\n",
       "      <td>7.6</td>\n",
       "      <td>14674.0</td>\n",
       "      <td>7.354394</td>\n",
       "      <td>2015</td>\n",
       "      <td>tt3447364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>The Tashkent Files</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5524.0</td>\n",
       "      <td>7.349695</td>\n",
       "      <td>2019</td>\n",
       "      <td>tt8108268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>Ghajini</td>\n",
       "      <td>7.3</td>\n",
       "      <td>53086.0</td>\n",
       "      <td>7.237606</td>\n",
       "      <td>2008</td>\n",
       "      <td>tt1166100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1103</th>\n",
       "      <td>Manorama Six Feet Under</td>\n",
       "      <td>7.7</td>\n",
       "      <td>6013.0</td>\n",
       "      <td>7.175113</td>\n",
       "      <td>2007</td>\n",
       "      <td>tt0920464</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  original_title  imdb_rating  imdb_votes    rating  \\\n",
       "426                     Drishyam          8.2     58340.0  8.106037   \n",
       "436                       Talvar          8.2     26612.0  8.003625   \n",
       "673                      Kahaani          8.1     53181.0  8.001818   \n",
       "568                         Ugly          8.1     17483.0  7.826408   \n",
       "15                         Badla          7.9     15499.0  7.624009   \n",
       "1095              Johnny Gaddaar          7.8     10612.0  7.440185   \n",
       "393   Detective Byomkesh Bakshy!          7.6     14674.0  7.354394   \n",
       "27            The Tashkent Files          8.0      5524.0  7.349695   \n",
       "983                      Ghajini          7.3     53086.0  7.237606   \n",
       "1103     Manorama Six Feet Under          7.7      6013.0  7.175113   \n",
       "\n",
       "     year_of_release    imdb_id  \n",
       "426             2015  tt4430212  \n",
       "436             2015  tt4934950  \n",
       "673             2012  tt1821480  \n",
       "568             2013  tt2882328  \n",
       "15              2019  tt8130968  \n",
       "1095            2007  tt1077248  \n",
       "393             2015  tt3447364  \n",
       "27              2019  tt8108268  \n",
       "983             2008  tt1166100  \n",
       "1103            2007  tt0920464  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_movies(df, genre=\"Mystery\")[[\"original_title\", \"imdb_rating\", \"imdb_votes\", \"rating\", \"year_of_release\", \"imdb_id\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can get the *next 10 films* of the above list by simply changing the `offset` value!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\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>original_title</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>rating</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>imdb_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>731</th>\n",
       "      <td>Talaash</td>\n",
       "      <td>7.2</td>\n",
       "      <td>36801.0</td>\n",
       "      <td>7.118107</td>\n",
       "      <td>2012</td>\n",
       "      <td>tt1787988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1350</th>\n",
       "      <td>Ek Hasina Thi</td>\n",
       "      <td>7.6</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>7.103707</td>\n",
       "      <td>2004</td>\n",
       "      <td>tt0352314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1056</th>\n",
       "      <td>Bhool Bhulaiyaa</td>\n",
       "      <td>7.2</td>\n",
       "      <td>19469.0</td>\n",
       "      <td>7.053494</td>\n",
       "      <td>2007</td>\n",
       "      <td>tt0995031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1729</th>\n",
       "      <td>Kaun?</td>\n",
       "      <td>7.8</td>\n",
       "      <td>3071.0</td>\n",
       "      <td>6.952977</td>\n",
       "      <td>1999</td>\n",
       "      <td>tt0195002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>Te3n</td>\n",
       "      <td>7.2</td>\n",
       "      <td>10451.0</td>\n",
       "      <td>6.951466</td>\n",
       "      <td>2016</td>\n",
       "      <td>tt4814290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>Rahasya</td>\n",
       "      <td>7.6</td>\n",
       "      <td>3950.0</td>\n",
       "      <td>6.945926</td>\n",
       "      <td>2015</td>\n",
       "      <td>tt3337550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>691</th>\n",
       "      <td>Shanghai</td>\n",
       "      <td>7.2</td>\n",
       "      <td>9143.0</td>\n",
       "      <td>6.923540</td>\n",
       "      <td>2012</td>\n",
       "      <td>tt2072227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1114</th>\n",
       "      <td>No Smoking</td>\n",
       "      <td>7.2</td>\n",
       "      <td>5817.0</td>\n",
       "      <td>6.812959</td>\n",
       "      <td>2007</td>\n",
       "      <td>tt0995740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>Karthik Calling Karthik</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9451.0</td>\n",
       "      <td>6.772480</td>\n",
       "      <td>2010</td>\n",
       "      <td>tt1373156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1417</th>\n",
       "      <td>Bhoot</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3017.0</td>\n",
       "      <td>6.233540</td>\n",
       "      <td>2003</td>\n",
       "      <td>tt0341266</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               original_title  imdb_rating  imdb_votes    rating  \\\n",
       "731                   Talaash          7.2     36801.0  7.118107   \n",
       "1350            Ek Hasina Thi          7.6      6000.0  7.103707   \n",
       "1056          Bhool Bhulaiyaa          7.2     19469.0  7.053494   \n",
       "1729                    Kaun?          7.8      3071.0  6.952977   \n",
       "296                      Te3n          7.2     10451.0  6.951466   \n",
       "376                   Rahasya          7.6      3950.0  6.945926   \n",
       "691                  Shanghai          7.2      9143.0  6.923540   \n",
       "1114               No Smoking          7.2      5817.0  6.812959   \n",
       "835   Karthik Calling Karthik          7.0      9451.0  6.772480   \n",
       "1417                    Bhoot          6.5      3017.0  6.233540   \n",
       "\n",
       "     year_of_release    imdb_id  \n",
       "731             2012  tt1787988  \n",
       "1350            2004  tt0352314  \n",
       "1056            2007  tt0995031  \n",
       "1729            1999  tt0195002  \n",
       "296             2016  tt4814290  \n",
       "376             2015  tt3337550  \n",
       "691             2012  tt2072227  \n",
       "1114            2007  tt0995740  \n",
       "835             2010  tt1373156  \n",
       "1417            2003  tt0341266  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_movies(df, genre=\"Mystery\", offset=10)[[\"original_title\", \"imdb_rating\", \"imdb_votes\", \"rating\", \"year_of_release\", \"imdb_id\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now find the top writers and directors of all time. We will be needing 3 new datasets!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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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>imdb_id</th>\n",
       "      <th>directors</th>\n",
       "      <th>writers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tt0042184</td>\n",
       "      <td>nm0025608</td>\n",
       "      <td>nm0025608|nm0324690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tt0042207</td>\n",
       "      <td>nm0490178</td>\n",
       "      <td>nm0161032|nm1879927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tt0042225</td>\n",
       "      <td>nm0707533</td>\n",
       "      <td>\\N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tt0042233</td>\n",
       "      <td>nm0788880</td>\n",
       "      <td>nm0592578|nm0788880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tt0042380</td>\n",
       "      <td>nm0439074</td>\n",
       "      <td>nm1278450|nm0438022|nm1301772</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     imdb_id  directors                        writers\n",
       "0  tt0042184  nm0025608            nm0025608|nm0324690\n",
       "1  tt0042207  nm0490178            nm0161032|nm1879927\n",
       "2  tt0042225  nm0707533                             \\N\n",
       "3  tt0042233  nm0788880            nm0592578|nm0788880\n",
       "4  tt0042380  nm0439074  nm1278450|nm0438022|nm1301772"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crew_movie_path = \"./1950-2019/bollywood_crew.csv\"\n",
    "director_path = \"./1950-2019/bollywood_crew_data.csv\"\n",
    "writer_path = \"./1950-2019/bollywood_writers_data.csv\"\n",
    "\n",
    "crew_df = pd.read_csv(open(crew_movie_path))\n",
    "director_df = pd.read_csv(open(director_path))\n",
    "writer_df = pd.read_csv(open(writer_path))\n",
    "\n",
    "crew_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crew_id</th>\n",
       "      <th>name</th>\n",
       "      <th>born_year</th>\n",
       "      <th>death_year</th>\n",
       "      <th>profession</th>\n",
       "      <th>known_for</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nm0001408</td>\n",
       "      <td>Shekhar Kapur</td>\n",
       "      <td>1945</td>\n",
       "      <td>\\N</td>\n",
       "      <td>actor|director|producer</td>\n",
       "      <td>tt0240510|tt0414055|tt0109206|tt0127536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>nm0002172</td>\n",
       "      <td>Mukul Anand</td>\n",
       "      <td>1951</td>\n",
       "      <td>1997</td>\n",
       "      <td>director|writer|producer</td>\n",
       "      <td>tt0104607|tt0102201|tt0098999|tt0092026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>nm0002411</td>\n",
       "      <td>Mani Kaul</td>\n",
       "      <td>1944</td>\n",
       "      <td>2011</td>\n",
       "      <td>director|writer|actor</td>\n",
       "      <td>tt0207626|tt0066514|tt0070009|tt0102515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nm0003939</td>\n",
       "      <td>Vikramaditya Motwane</td>\n",
       "      <td>1976</td>\n",
       "      <td>\\N</td>\n",
       "      <td>producer|writer|director</td>\n",
       "      <td>tt0238936|tt3322420|tt1639426|tt1327035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>nm0004072</td>\n",
       "      <td>Kaizad Gustad</td>\n",
       "      <td>1968</td>\n",
       "      <td>\\N</td>\n",
       "      <td>director|writer|miscellaneous</td>\n",
       "      <td>tt0330082|tt3309662|tt0168529|tt0819646</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     crew_id                  name born_year death_year  \\\n",
       "0  nm0001408         Shekhar Kapur      1945         \\N   \n",
       "1  nm0002172           Mukul Anand      1951       1997   \n",
       "2  nm0002411             Mani Kaul      1944       2011   \n",
       "3  nm0003939  Vikramaditya Motwane      1976         \\N   \n",
       "4  nm0004072         Kaizad Gustad      1968         \\N   \n",
       "\n",
       "                      profession                                known_for  \n",
       "0        actor|director|producer  tt0240510|tt0414055|tt0109206|tt0127536  \n",
       "1       director|writer|producer  tt0104607|tt0102201|tt0098999|tt0092026  \n",
       "2          director|writer|actor  tt0207626|tt0066514|tt0070009|tt0102515  \n",
       "3       producer|writer|director  tt0238936|tt3322420|tt1639426|tt1327035  \n",
       "4  director|writer|miscellaneous  tt0330082|tt3309662|tt0168529|tt0819646  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "director_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>crew_id</th>\n",
       "      <th>name</th>\n",
       "      <th>born_year</th>\n",
       "      <th>death_year</th>\n",
       "      <th>profession</th>\n",
       "      <th>known_for</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nm0000636</td>\n",
       "      <td>William Shakespeare</td>\n",
       "      <td>1564</td>\n",
       "      <td>1616</td>\n",
       "      <td>writer|soundtrack|miscellaneous</td>\n",
       "      <td>tt3894536|tt5377528|tt5932378|tt8632012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>nm0002005</td>\n",
       "      <td>Agatha Christie</td>\n",
       "      <td>1890</td>\n",
       "      <td>1976</td>\n",
       "      <td>writer|camera_department</td>\n",
       "      <td>tt3402236|tt0029171|tt0051201|tt1349600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>nm0002042</td>\n",
       "      <td>Charles Dickens</td>\n",
       "      <td>1812</td>\n",
       "      <td>1870</td>\n",
       "      <td>writer|soundtrack|miscellaneous</td>\n",
       "      <td>tt0096061|tt0063385|tt0095776|tt0119223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nm0002172</td>\n",
       "      <td>Mukul Anand</td>\n",
       "      <td>1951</td>\n",
       "      <td>1997</td>\n",
       "      <td>director|writer|producer</td>\n",
       "      <td>tt0104607|tt0102201|tt0098999|tt0092026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>nm0002411</td>\n",
       "      <td>Mani Kaul</td>\n",
       "      <td>1944</td>\n",
       "      <td>2011</td>\n",
       "      <td>director|writer|actor</td>\n",
       "      <td>tt0207626|tt0066514|tt0070009|tt0102515</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     crew_id                 name born_year death_year  \\\n",
       "0  nm0000636  William Shakespeare      1564       1616   \n",
       "1  nm0002005      Agatha Christie      1890       1976   \n",
       "2  nm0002042      Charles Dickens      1812       1870   \n",
       "3  nm0002172          Mukul Anand      1951       1997   \n",
       "4  nm0002411            Mani Kaul      1944       2011   \n",
       "\n",
       "                        profession                                known_for  \n",
       "0  writer|soundtrack|miscellaneous  tt3894536|tt5377528|tt5932378|tt8632012  \n",
       "1         writer|camera_department  tt3402236|tt0029171|tt0051201|tt1349600  \n",
       "2  writer|soundtrack|miscellaneous  tt0096061|tt0063385|tt0095776|tt0119223  \n",
       "3         director|writer|producer  tt0104607|tt0102201|tt0098999|tt0092026  \n",
       "4            director|writer|actor  tt0207626|tt0066514|tt0070009|tt0102515  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "writer_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As in the main dataset, attributes such as `directors`, `writers`, `profession` and `known_for` are separated by |. As this is getting repetitive, we will create a method to deal with such situations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_attribute(df, attr, split_by=\"|\"):\n",
    "    return df[attr].apply(lambda row: row.split(split_by) if isinstance(row, str) else [])\n",
    "\n",
    "to_clean_attr = [(crew_df, \"directors\"), (crew_df, \"writers\"), (director_df, \"profession\"), (director_df, \"known_for\"), (writer_df, \"profession\"), (writer_df, \"known_for\")]\n",
    "\n",
    "for attr in to_clean_attr:\n",
    "    attr[0][attr[1]] = split_attribute(attr[0], attr[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_crew_freq(crew_type=\"directors\"):\n",
    "    # As we want list of top directors and writers\n",
    "    # We are only considering the top 250 movies generated by method top_movies()  \n",
    "    top_imdb_ids = top_movies(df, limit=250)[\"imdb_id\"].tolist()\n",
    "    freq = dict()\n",
    "\n",
    "    for imdb_id in top_imdb_ids:\n",
    "        info = crew_df[crew_df[\"imdb_id\"] == imdb_id][crew_type].all()\n",
    "        for crew_id in info:\n",
    "            if crew_type == \"directors\":\n",
    "                name = director_df[director_df[\"crew_id\"] == crew_id][\"name\"].all()\n",
    "            else:\n",
    "                name = writer_df[writer_df[\"crew_id\"] == crew_id][\"name\"].all()\n",
    "            try:\n",
    "                freq[name] += 1\n",
    "            except:\n",
    "                freq[name] = 1\n",
    "    \n",
    "    return freq\n",
    "\n",
    "LIMIT = 20\n",
    "director_freq = get_crew_freq(crew_type=\"directors\")\n",
    "director_freq = {k: v for k,v in sorted(director_freq.items(), key=lambda x: x[1], reverse=True)[:LIMIT]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.bar(director_freq.keys(), director_freq.values())\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like *Anurag Kashyap* is critically the most popular director (the views strongly correlate with that of IMDB audience). A similar histogram can be plotted for Writers and Actors. Here is a list of top writers: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xPwmsA+xI3Lx2B86ocYom18oOxPfxKUP+VuV9AxwF/AD4LvWvb4AfSfoo8H/M/m6fNUmw3PA+SFxnfwDuBvwMuO8YmdbX9zTo3Apc0iXAw2z/oTzfCDjV9pYVZA8dcthV7/LlHAcSqbKDF8q1E+QuAu7vhh+4pOW2H9xQ9mLgXsCviDnXWtFNOPdLbH+q7XlGnPt8YDvgx7YfJOm+wP/YHrrSGyJ/uu2HSDrb9jbl2Lm2V7jhTBNJP7G9IIXdJJ1ne+u+n+sBx9p+ZEX5RtfKFHan59h+UBPZIn/ykMOuuEM9B3gscLztbSQ9Fnim7Rc3nc980bkVOHGHvL7v+fXl2ERs7zWF8Z9Vfr68/9TAv0yQuwDYBLiyzmBlWwdwtKSXAV8Hbrx14Ak3jsLj64w5ZA6LgP8iqk72bzF3qqK8S+XKuzB7a/zrCkPfYPsGSUi6ve2LJU28Uffxm2JGsaTbESvci8YJSDqaIaaTvnk/tcK4p0m6v+2f1Jhr/xyeBrwHuDOhQOus6m4oP/8m6W7Ed+OuNYZvdK202Z0WjpH0JNvfbjj+jg3HBbjJ9tWSVpMk2yfU8Ze1uL5b00UF/nPgdElHEV+0XYHzJL0WwPYHRglKWgt4ISvaByuvwG1v0XDeGwM/kXQGsxXwJIWwnHifKs/f0D8dJt84sP0rAEl3pu991+CLxI5jF2Af4PnA1VUEJb0SeBvwe2abE6qs/i+XdAfgG8AJkv5IrAyrsg/wYeDuRJmH45l94x3GNBzdhxFK/HfE/7rujue9wFNsj73ZjODo8pm9DziL+Kw/XVW45bXyXUmvp+butLAv8CZJNwL/pKYpQtJdgP8B7mb7iYrS1g+1fXAF8evKTuWHwGGSrgL+XnHcNtd3a7poQnnbuL/bfvsY2a8AFwPPAd4BPBe4yPa+o2RGnGcrVlyNjrVlS9phxHy/X2fsJkh6KvB+wrZ3FeEIvcj2AyrKL7f94N62vBw70/Z2FWR/TlSprLRLGnOeHYANgeMc5YtXWsp7fi1wPjNf6luVYwX5H9l+eINxVwO2t31qeX57YC3b19U4R+NrRdIvhxy27YmLjLZIOhY4FHiz7QdKWgM4u4pDVtL6hMIW8B/EdfZ52xMXKdO6vpvSOQXehp4ttM8+eDvgB3UiU8oN5NGEAv820dDih7Z3n5NJzx679o2jyJ1LOP6+W97/jsCetl9Ycdwf295e0neA/wV+C3zV9j0ryJ4MPNb2TVXG6pNbHbjQ9khHUoVz3Af4BHAX21uVyJCn2v7vCrL3Bt7Nip/3RGUk6TTbD20w355tfwfC3PYNZu/WqkRz3Grvb0Lba6UNahdxdKbt7Qb8Ha3s6hXHbXR9T4vOmVCKPfaNrGgGqRKZ8M/y809FGf6OsDPWYXci6uJs23uVrdsXKsx7e+AjwP2ANYn6MX+tsUUceuOgWhTLP23/odj4VrN9sqQPVRm38N+SNgReV97DBkDVuNtLge9J+hazldFIU1f5+82Kdn2LW9gTP02YnD5VznmepC8BExU4sZp7GxGdsCOwF9XzJs4u4xxNPQXcH8XxN+Bxfc+rRnOcKOnpwNcaOsxbXSstFhltI47+WgIaXM63PVBp5yFpV+BAYtdR1+fQ6PqeFp1T4MzYY59MTXsssLTc5f8fEVq2HvCWmuP/vThsbpK0AbHNrJL88FGiYuNXgCXEVu0+NcZtdOMo/KnY+E4BvlhsfH+dINPPd23fQHwh6jqLfl0ea5ZHHe4IXFj8Bv021SqORIB1bJ8hqf9Y1ZXS2rZPLE6tXwEHSFpOhLBOlCW+zLUU8JSc7C8hzDc3S+qZBSrbkmlxrbRcZOzLTMTRjioRRxXnDPGevwncU9KPgEXEd6YK7wf+3fb5Ncbr0eb6bo/tTj2A5eXneX3Hzqwou0WVYxPO8XHgDsTN42fA2cChFeSWDZn32TXGPaP3/okVsICLK8quS6we1yBueK8C7lRj7J8DPyJWKbsAG87T/3qHYY8a8scSsfdnlee7EyF1VWRPLZ/Z14BXAP8OXDJP7/u95X98O+BEYoGy5zyN3fhaIWz+qwHnlud3AU6oKHtm+XkOcPvy+4U15q0y5wcAW5XP7vYVZX80H5/tXDy6uALvmUGuVATg/xa405jX93MksO3Asa8CleOrPZPF90lJxwEb2D6vgujfFHXTz5H0XiKcsE4pg2UluuDThBL/C7HFrMJbbf8X4VD7HICk9xChgROxfS9Ji4FHEgr8Y5L+5Ar2xTYmL9vfLzuNnrP0DNtXVZlz4eVEec/7SroC+CWwZ0XZfYmEmFcB7yS28s+vIjiFaKfH2X6jpH8HLgOeRqyIK+24ii39EcSq/we2v1FxXIBH2T6W2dfKPkQS2SSa7k6hfcTRweXzvbDMeV1iRb5zBdkzJX2RFX0OE/sbFD/L61kxg7Sq6acVXVTgte2xZTv2AGBDzU733YCaoVKSTgTeb/vbti8rx5ba3nu8JM8jFPYrynw3BZ5eddwWNw6IJIVBZf3EIceGIukewMMJBf5A4kvyw4pjNzZ5SXomEQ73PWaybt9g+6tV5G1fCjymfJlXs339JJk+2V4m4l8kvZBIx/9zRfHPE9FOj6cv2qnq2Mx8L3cBvmL7ugEz0EgkfZxIxDm8HNpH0mNtTwqf7PEWSTfaPqmc7w3EzauKAm+8yLD97+XXA4pjcEPguIpzBrhC0sdtv6yYSb9F9fDJjYgbVr9pzlRrUNPLkP4MzTJIW9G5KBRJG7lmyE5xUuxG/IP6/ynXA192CbuqeK5Lgd8AJ7mELEo6y/bgyn7qSLo7K9ZCGemll/RS4GVErHh/vZL1iW1jpdWopFuIDkz/Y/uomnNuE4J4LuHhv6o8X0TY48dmUkra0/YXVHIDBujVcPmm7T+OOceXiBvOzcR73wD4sO33VZh3q2gnRbbvbkRo278RJrtjbD+kguzFwP3csytEaOGFtu9XceyNgWMI5+8TiHTyPVwzdFPS5tRYZEj6X2p+F4eco2d6ejBwoO0jm56rxpiNM6SnQRdX4D9WpL4eStgzJ96BitI5StJDbVc1O4ziT8S27H8VWXtVleDDgQNYUQFXipEtJo9nAT9hdi2VcWFWXyLswO8G9us7fr2rJVf02IbYkj9H0n6E7f/7rpYk0cbktdqAyeQPVDM7rVt+rj/i71sALyUiHUZxf9t/lvRc4jPcj1hVTlTgtIx2sr1fUUbXOaJx/kokrFXh58BiZswPm5ZjVce+RhEL/l3i/e5e5TsG9Or9nELcrC6uOmZhOfD/FJm2XyeU+cR6NAM76tOJoIQziOzbp7la6OW9gI8BmzhiyLcGdrH97jEy08iQbk0XV+ACHgP8J2EbPQL4rO2fVpBtVfGsnKM/zvQFhCnnjrbvMUHuYsJ0spy+rVbV3YSiBszWtm+c+OLh8q3SfUtkwiMIM8qeRX6zCnJPJooUbcqMyevtFe2L7yMy2nrmgGcRTuCJpp/yfl9l+4Mj/v4O2yMjSiRdCDyIuAl+tNjjK9VRUYTEHVnmfigR7fRW21XMEJQV+0uBXuGt7wOftP3P0VK3yn6f+F70ClhtRxTmug5GR/BoxaJMaxIRO6Z68bEdievjkYTz+GzgFNsfniTbd447EabFZwOLbd97wuuH1Tfq4SrfbUnfA94EfKzsnARc4DHJS4qkpf4M6cFx5zx5CTqowPspF8wXiBXXucB+41bYkk4llMmgEq281dJA8SZJDwZePulCUSmsVHWcIfLHAs+w/ZcGsq8gVv+z0n1dvTzpMuD2RGTGD4gV1kQH0yQlWnHsnkOOMu7Xa8g2LjEq6VWEj+Bcwha9mCidW6koVBskfYaIovhcOfQ84GbbL6ogOzTjt4fnOPO3/M+3I8JN9yEcm5WTsST9G3Gj3pXIAB1W4XCqaIGSgKZB5xS4Ilh/T+Ki/j1wMGHXfhDh8BlZq6TNP6VvyzSUUVsmST3b+DOJ5J2vMXurNbbcpWbqUt+dcCCeOCA/sT61Wqb7SlrkCmnFI2RrK1FJHwO+ZPtHTcbsO88HCUVYu8ToiPOt4QoZd4oU9qez4k6vak3uFVb6VVf/5bVtIncaZ0QWB/+6hOPyB0SGcqWxi8no3wlfzf8BX7f9pwpyreu3l6CAlwJH2t5W0m7APrafUHHujZKXpkEXbeCnEV7+3Wxf3nd8maIW8jjaVDwbLCrVz7iiUu8feL5kQG5SuFHPDrical7xYfyGillp/fQ7AYdFQbhatlmTOs0/BQ6SdFfCRPYl2+dUnXcfvZt1v+Ks8pmPVMID5xrFUcTnvZy+m20NbpZ0T5dGGZL+hYoRDmoZuaN2GZHnEQ7ErYj3/ydFWYEqhaF+QRSfuqbKPPtoXb+diAw7mAg3/RUR4rtHFUG1S15qTRdX4KrqVOmT6dn3RKwQGlU8a4KkO4xaSUhaUsVRMyBzO+ILcsWk1U2fAn4AsCURWlU53VczhcO2JFZ0vRvIU4iV3UQHrtrVad6MsIU+m8huPBw4vIq/oy1lVdZTwv3mtsEb8jDZC2xv1WLsnQnb+aXENboZsJftYZ/loGyjyJ0++VY12Ms51gdeQMRHb2L79hXlmq78VwfeY/v1Vec44jwbEjpx4sq/T+Z8ZjKkH1h2P1+w/dg2c6lKF1fg91aUrNycioHztkdFI/ScopXRiI4uYy60EyQ9zgMha4qi8YcwIdGh7Co+YvvCcoGdRiiUO0l6ve3Dx4j33vewdN8q0Tu9MMlTgG1d4qglHUDcDCbiFnWai539PcB7JG1DfF5vJUxRE1G7EqP3qLqFHsKpkv7VzVKzcaTw35u4cUJkgFZdyTeN3OnRuAZ78bU8kliFX0b8v35QUbbxyt8RqVO7emPf2IcSvprryvN7AIfYftx4SaBd8lJruqjAGwfOD0YeKGJkP08kWlSlvx73WkSc7nJGX2hLgZMVyRRXl3GfA7yLcI5N4pG29ym/7wX81PZuir6gxzITobECfQp4C9uzSn1KmhiH3cddgP444H+UYyPR+FjsSuYXRUnQJxIr8J0Js8AB1aYMwGcpJUbL858SppwqCryNEn4E8IISqVC5HrhG9JQE7qWok/0LTw7PO05RNbI/cqeOybBNRuRawAeIchd1q/O1rYVyjpq3S1wGnCFpX8LX9CYie7gKbTKkW9NFBX6T7U80lN1U0v62311snEcQoU6VGfSKK7p4j6zWZvvTkm4ATpL0OOILtQ+wo0sm5wT6FedjiQsU27+rsXn4qqSn2r6izPlRRNxr1ea1hxEXeC8CZDdCOY5jUiz2SMruZA/gSUQ43JeBvW3XKcAFsLHtIyTtD2D7JklVb/qNlHDhiTXn2WNcxMUawP0knTrOMWf7DYpqhL0V6dI6kTtukBEpaQNHlmqvL+0G/dfmKAf/AG27L61F7Db6F1KVKjja/lgxPZ1MtEvc1nalzllulyHdHq8EBVmqPIjkjzsRK7CXEW2ieseqFtsREde7P9Gd5dVTmJeAn1R43TOIhI4zCMVS9fwnE2no2xBJRJuU42tQvZjVdkQ24SaEUjwX2LTm+9yWWCXtC2wzx//rk4AXEfH1bc7zPSJNulfMansiAamK7GbDHhVlP1/lWIP308uqnLPPvoyzOlFadXHvMeH1x5SfvyTs9r/se1xaccyvExmnBxDJQEcB357r91rG3oPYnT2PcACfCWxV4frYsO/5jkT3p9cCa87HvG13x4mpFoHzmgnlgwgr+xRRXe/gIlw5rGwgXGk1QrH+0iMcesXJ0Zv3ZkQdkDrNYu9DNFHYBPiQ7c+W448nih69ruK8H0q87xuILLOq9UgaNVZQpEaPxBXCu9pS/u8fIZy+F1BKjLrGCkkDrcVcIflJA6UVymd4vqfQ6FjSXT1mdah2/TTRiBZh465TSZu5YrehinPYgZrdl9SigJikY4AX9z7X8l35pMc4fiWdTpSg/a2kBxGZq+8mkrf+6Qox+9OgMwq8DSMiIXrYNSqHSepVpDORqXaZx9RvKJEU4waf2oU/ZOzBBr33J0Kk/ljGrlRXW9F/9JVVlFefTH/lvrcTSuFWbH+OeaDY0bckFNklrpDNWORqtxYrppo3EREzf+sdJsxgS23v3/R9VEUR89+0n2ajnIHBG1ZT1CJbWE/g6EoAACAASURBVFNql9h3vrUcNfBH/b2/ts9BwC2OCpKrAedMWphNi84pcEnPIO7M10v6f8TW/p22a9my+853F9u/r/C6XYnIhI+V52cQKzoDb3TFONv5RFPKyitRKNsQ5p/ajRXUss1XGxRd6TdntlKY0zZ0kt7dRlkXG/CNk46NkG3UT7NP/mRqtgibxv+3ycp/2BzUoIBY8Ye9gBVX7yMrjEo636XfpqSzgP1tf6c8P2++FHgXnZhvsf0VSY8gaqK8j4hKqZymXrzGTyfu1vcjVlmTeCMRDdFjTSJcaj0i0mGlU+CjFHT57PYgamxUoW7XohWm0lK+EYriSvckwtL6C4DNaRs62/urRX9HIophcEU77Nit9EWwLJP0f9Tsp9kXLdSkRdjdx5nMKprL9gW2rLPyH6BNAbHDiPf9ZCI67DmUuuJjOEnSEcSO9o6E3wZF8tm8Nd3uogLvfRF3Ibal35JUpUnt2kR9hecQq8n1iWiKql+qNW3/pu/5Dx3e9WsV9aZXahRx1M8hnKm/JIotVaLqSn1aSPqh7UdoxQJLPf4AvM/2xyecaglRVbDJDaRNa7FGMc2K0NC7A2uX/1fP37MB0VxiHG37aY7LGZjE34kQujY0yhbuo9cu8S3Ub5d4H9vPkrSL7YMlHcbk+PVXExFldwUe0Wea24SZsNU5p4smlGOAK4iQum2Ji+eMCQ6HLxEJBscTIWknAT/3mLopQ87xc9v3GvG3X7hCh/Y2qEF9jeIA3aM8riFioF/vClUEB85TuyHzgPJdh9k24cpOtRHn3gg41fbYMLNiF33VOKffGNl1CYevCHvqhsAXq6wQ1TCbsfgNXkDcePozdK8nKm5WiWmed9rYwNUyW3gaqNTrKabClxBmnGXjAiNWFrq4An8mUWj+INt/KluWN0yQuT/huLuIcGzcLKnunet0SS+2PavLh6SXMFO6cySKsqrvZKYeeF1F1qS+xsXESuLJtn9e5lG1m3w/tRsye0z2a12GRYJIenQF0Y2BnxR/Rb9SmGi79+yY87oO10YxzcWx+zlJT3fNZgSK0rs/d1+lzHL8JcAWtvcbLnnr6wYd3oNzG/eZtTEZtFn534qkXwA/ZqZa5iQTSD8Hl9X724DvEAuOKs2rF5zOrcB71A3vKqugPYhtzzXE3X6rKg7MvvF6dsVe2OGDiTKru006T/HuP40IJ6v9oatBfQ1FVbVnE0kdxxG7j8/U2XmU8yyzvWTA8z7njskmkSAD8kOduFVMQmoRjqdIeNqL2GbvRCwebmf7SVXmXc6xCys61cbttpYDSwavrRIVcd6ka6fvs3oaYQbo9d/cA/i97SY3/nmj7FAfQuy0H058v8/zTGLSbZLOKfAhX+rFREJLpS91OceDiQvzmcDlth9WQ3Yn4osFER99UkW5k4Gdbd8y8cXD5ZcSNVFqp3YXc8CuxHveiXDafN328RXlTyEcxp8hnENXAi8YZ7aaBm0iQaYwdqtwvL7z9GKaj3X1EMZPEqvAHYnPfHfCTDjyfY+7wUu6sMZNb5ntJZOOTZsRO4DrCFPSpzwmpK/Ir0GYrXYgsmg3IhT4S8bIPIlo3PDr8vxNhJnyV8BrXDHEV9Gs/L5l/pe4Zvu5VnieMoam9SCyCDciqn9BXOQHNzyXiC7c8zHv7YhV8P5EttZrgddWkDufKNP5E8LTfkl5fj5xgdadxx2BvYETa8hsRqwENyC2mR8A7jUPn9myvv/5ar3fa8hvT2TV/YXY5t8M/Lmi7I+m+D7uALy5xuvPG/i5HmEWGCdzJnDvIcfv3fscK459EfAvfc+3IHY9c/2//jCRJf2U8vgC8HGi5MPELFbCx3I6scPeqOKY5wLrlt93IVrPPYQodXFcxXPsQjhgv0dEdf0aeOJcf169Rxdt4I3DuwZx/AeqRqG05V2EIlmLeja+J09zEo6qiEvLo6pMbyVyA5GUUwlFYsZ33bwiYeNIkEJt232bcDxFXZy3ELvDbxAFpd5BpGiPqxo5SK9+9t8k3Y2IurnrBJm3AseWiKxeRMgSYsHw6hpjv4YII+wvZTtyFTuImifjPMyzG10frZlOOVXs2XsQK++XAS9SdN86xfaJY2TsGV/H0wjz4umEv6vqe34/Udeo52O6J+GIPbaifCu6qMDbfqkXiru5QY3onvIsF8bltm8sDrytma+i8Q0bMjucxbdI2tClVGdNdiWU2WuYiQSp1NWmbw4/l7S67ZuBQyWdTSi1UbQJxzuMWIUdSTjalxFhhFvb/l2NaR+jyFV4H+FvMWFKGYntY4vP4w3AK8vhC4Cnu4bZzfZxilK2vdIJF7tiKVuNSMYhrtVJrCdpsWfMGYuJnQdUcJJ6pnH5fYliYq8mcjfWHiO2mqR1iGtsZ6LURI9KNcyJBuH9TaMvJaKG5oUu2sDXJT7w1Zj5Un/J9Tt5zCuKllHfdUW78xD5c4gV1eZEedCjgAe4hmOsKWrRkFmRhr8NcAKzszjHJndMYfU+77Z7DbQ9k3Q5UQiqkd+jnOP2wFoNb4BNxvuPYcddLXu1ceu+Yo/+JNGZR4Tp5mWEaeLFtsfusiUdSTRW+AUlEgU43ePT4V9MNJ24DrjOpQmDpAcCH3S1piOfIBY2RxA3q2cQZpTvQuVyto3pjAKX9HwPqZ+hSJk9zPbIFkgaUZO6h+cn1vR6WnQD6sXaSnojUUT+I/MRCVLGbtyQWbNrotzKsP/lENkTgac1VV6KOjS/J0xWryFu9h8fWDENyqxF2FH/CBxNrGgfRSiGd45bKBSn66OZScA5uf+5J5RVlbST7ZM0vC64gWuJBLJadfDroCjW1mMtYmV6lu3dK8jWTsMfkL89Myv/S8Yp3yGySwi/WN0eAYsJk89ZPVlJdyeihi6rIH/omD/bFYpptaFLCvwsokLY0r5j6xJb2ss93kPfK6TUuDXYQqOofvYhIsvrKbZ/WTW0sGlInFo2ZG5L09V7yzGPIG6w6xIO3wsIRf4I4EG2R/okJF1GmA5qV8ws8m+3/bYxSmEjYG3PU7uuMqc7AF/2mO5EmlIyjlo0By4LuZcSN1sIU9YnXTHyp6t0SYHfiYji+ILt/1X0+vs2EU0xNkmh7xynEKVUe63B1ge+ZXtom7Qpzfu+jkSOoZlqVZWgoh3YPsBptg+XtAXwTNvvqSDbKCROU6jiWOyp72bFL+bELLemq/cy5puJFesHiG4pjyRW0S+yfeYY2Qtsb1XC0i63vUnf3yp3hp8rJB08brEyB+Pdjgi1G5mI1LdAGopLZ6gJ47yNIc2Bq6z8i/xniFLRvWvjecDNnuOyrops508AdynXzdbAU21PLO8xlfG7osABFD3njiXsW7sSd9gP15C/hHAo3Vie354I1arT+aMWkj5t+8UjlGElJdh3rrUJm+olNefQqkJdGyT9kHBsfZDY8exFhARWynRr8p7LmIcRYY+vIRxaRxNK/L/HmYPUlxauFet6T6Vs6pixG7eh0+w69cNkK+1aNDsee3WifMIRVRdJfedZDVjP0amnyutbNQcednOdjxuupO8TZrZP9cyZVXfG06AzUSh9dsGlxKrqROA3veMVnQXDWoPNaV1q2y8uPxs74wAkPQU4iLDnbqEoIv8OVyvp2qhCXRl3B+CPts+T9Exii/pz4BMVoxPWdjTplSOi5gBF1uBEBd7iPa/XM7VJ2sf2V8rxExQp5+O4h6Kynvp+pzy/+6Q5t6RxGzpmaqc8nFjF/l95/gwih6AqB/X9fhPwK9uXVxFU1Bzah3B0n0m0Vvuw7UmfObRvDnyzpHva/kWZy79Qs2duQ9axfYZmtzds5ANoQmcUOLPDu745cKxKtTVsv0vSscRKDGAvN6wjXpURDqn+OVX1Uh9ANFD+XpE7p1ykVdiABhXqJH2MCAFbq+xe1iPMWA8n+h9WaQZ9Y1mN/UzRtfwKZsLDJnEAzd5zf9TH4ApwUkRIf12dZQN/G3w+VVzqmFQxOQyR/RyApJcS1fFuKs8/ScXO8OU83y9yGxE36xuASgqcqPz4Z0nPJXbK+xGRS1UUeNvmwG8gmof3x6/vVUN+FpK+YXu3Ci+9RhHi6yK3OxHtNC90RoHbbvzPGGAdIhvvUEmLNKRj+5QZ16i20o2n8E/b1w3c6SuFp7X47Ha0ff8SmXEFcGdHbPeniGzQKuxLfOavIop57QQMtW0Poel7vq+k84gv8j3L75Tnk2LXG+/IVJr7Fn/NsHNXae5L8e+8mBUrT1aJaLgjccPujbVeOTZpzGOA/WxfoCgQdxZxw7qnpKWeEMZXuF2xme8GfNT2P1WxaJxbNgcuu7x7E05UiCiWqkXfhvGKiq97OWEVuK+kK4hSzfMWFNEZBT4NiqNkCfFPPpRwenyBmQ7eU2eKN54LJT0HWL1cqK8CRrZy60fN+wXeUF53g6Rf9cKsbFtSJe9+n8PwL9RfETV9z/erOc60+BKRObucFfu3mgk3jz6OIlbN36W+GeBA4OzicxGxij6ggtwWti8ov+8FnGD7P4qj/0dEBNQkPgVcRqSon6II46xkA+/H9mWS7tPzH417bTG33MX2zxxJblsSyTsPkvQdTy4y9yDgXkRdo1ud/FXNRrYvBR6jiIhbrRcgMV90yonZFkUyzDZEzGfP4TBv7Y9Us8LcgOw6RGRFzwzyHSIuuUqbrUb9AhWJKB8gFMFryu+U56+2PdFGqYjPfTMrZnFO/MxHvOf/do344C4i6RzbD2ohvwlR08NEmOzELND+MRXx95+2/eW285G0hsfEhZeojYOYKT/wMaIEwkOA99v+4ITzLyVqw3+2PP8ZYb5ZB7jJ9j5jZN9KrJaXl/He7YFy0ZMoztb/ITKtn6iIFnuo7YPrnKcpq5oC7xVu7yXFrEuE5c25AleDCnMD8s/oc8aNPDZCtlG/QE0nPOwSwj55Pn3mD9do5ixpHdt/m/zKlQdFMsjgTatS3R1FPZNTbX+74dhPpS8e2vbRFWSOJhqeXE74N7Zw1NtfmyiGNbGaYRNlpshv+ARh734C0RT6c8Bbq9yoFaURtnVRZOpLblPp7DRG9kJgO9t/Kzb/4zy7HstEik/tUKJY2QMV4adnu/TLnHM8T1WzpvUgis4MPnYm7LOTZF9PbPMuJWyMpxHd1udj3rUrzA3In1Xl2AjZM8rPU4CtiEYHl87T+/5hC9mHEREUvy7PH0hkUs7HvNci7JsfJxTaIcAhFWXfQ5gSvk2ELx4NfLOC3PWEyeF64mZ3Q/n9eqpXUTyQiND6z/I4gegGNEnuzkQq+1HA4/qO70h0caoy9rFE0te55fkaRP37cTLnDDyvdV0Onp+o8d/7/YIJsmcNPF/e4Do5s/w8e9R7mstHF23gLwQeSqQpQwT/LyfCzN5h+/OjBG0fJOmxxJdkS+Iuf8Icz7dHkwpzSHoi8CRWbBy7AdXDlYb1C5yvjiNvUyRZnEjNEEYidvzxlKgj2+dKmrOkqwE+T5idHk+f2ami7G5Eg95aTjRPp4vRk4iM0VsAJH0OOJtY2Y4b+yoiBHDw+MnMfNcmsbHtIyTtX2RvkjTJhr+WZvf/vLH/uScnut0iaRMXM5GLHb/sgCY5vP9FUi+irefw7j3H1UJ0/1pW770dwPa06+1Ziy4q8DWA+7k4J8q27TDChnUK8cUbiiJB4v/mUWn3M6zCXBV722+JaICnMrtx7PWEXXoitnuV7L5PdUfatNiLqG9xO2ZXqKsUfWP7NwNRKK1ieyUdYPuACi+9l+1nSNrV9ucUMc5Vw/EuJd5v4ygIRfjpI4jP6ge2v1FD/A7MRKFs2HQODWiizK5kxrcCUXSs99xMaARNfJ+OlvQ64kYF0Sv3ICaHL+468Pygoa8az2uJBcY9Jf0IWESYR+eFLirwTT3bs3xVOXZthciI9YHjJV1LJDp8xRVbqrXF9jvLr0eWkK1KFeZsnwucK+mLblckqFZD5CmynZtnuv5G0sMAF7v9vlRfBY+iavf03rX0J0WNjt8RZoYq/A04pzgD+3cdVbMhP05ERvRqiO8j6bG2X15B/N2sGIVSK4uyBcOU2TPGCbhlgpsjc/Ua4L+JAAEDFxK767E1uV2htV6F8c9SJLttSXzel3ge6690zolZLu7FRJF+CMV0OeEoO6bKBVE838/qydp+zBxNF0nbAb/pbfEU5Tp7bZsO8OQKdUfYfqYi1XiFf5arRXMcx0xD5P5ysO+fINe6iqOiMNP7bNfJBuzJbkx0ankM8eU4HtjXDcqVNhj7RURd760JJ9V6hFL4ZAXZxhUYi/zFxC6zt5JdjQhzqxQeqYjj7jnjKkWhTIOyULiZPmVGhNa1icdeECbt1DS9BL1WdFGBi1CAvdjtHwFHusYbKWFWzyC6taxfRQk2RVFF8TFlh/AoorHwK4EHEV/SsdstSXe1fWWJqV0BV4jmUMPaDFOKQrkIuCeR4HAj3FoJcS4/86nUBVkoyg7t5Z5p5rEZkRgzLimsX752BIykN9p+76jPrspnpiG1YoYd6wKSnuIx0TuaqRh5Z8LZ3uuNuyMRQTTVTlqj6JwJpSjqr5ZHLSS9jPCSLyJW8C9usjKsyep9q+xnAUttH0mYUs6ZJGz7yvJzlqIuq7I9iJX8JE6V9K+u2RC5ioKuwMgypKMo8bmjcJ85ahT9Ke9vJ4ppVR17GruORhUYNVNIan3gIklnlOcPAc6YOPk4x3uI6+xCZvscJoUw9kxTtcsFlAXR3YG1BxySGxChsyslkja1/ZsRfx67IHRJ0JN0PFFC4Mry/K7AZ6c5z3F0ToEXx8hHiGy7NYmKaX91tcYImxIJKBMV5xRZXTPJDDsTDYV7TPz8FZlmLye+IN8kwsJeAbyOyHj74hjZntllDWAvRZ2I2qtgNc/khAlfhBEMa5G3bpnDRkRK/ugB+0wVkl5d1XRRmEYkyKHMVGDckVKBsYLcOCda1c+xaQTM0YouSP9q+/V1ZIlInRcA92C2Q/J6JkS/9FNMm5sze+cwl6aIEyQ9wQONGyT9J5FAdkyFc2zaU96F3xMm3nmhcwqcBo1qe9jeH0DSnZmtiKo0XW3K4cD3i6Pl75RIBkn3olq40eeJ7jCnAS8ivhACdqtwI5rWNq5NSN23mEkrXwvYgrCNjkwM6bfNK1K59yWU4JeJJrJ1qHUDmdKuo1EFxlFONUmPIHZbVRKBGkfAOOrc1C4rUW6Qn5P09LK7rI2kQwh/w+DOoZICb+iofy0R1LCL7Z+V8+xPZCzvUHHqJ0r6DjMO52dR2qnNB11U4Lh+o1og7FrECuFuRPTKZoQimphl1mKu7yrRCHcFju+z1a/GTPPZcfyLS1ZXiae+kqiPPTFLzfavyqrqQtv3nfT6MTQOqfNARpqiscXLRry8/3V3Ir5gzyUy87a1/cf6U2+G2hXqb1OBsTf+NoQieQbhP6iqGFtFwBTZbxILpP4uSCMVqUodc2DzYSaoKmYnYHvb9684x2EcxYyjvtLNy/a3Jd0I9BpCv4iofvmoqtea7VcUh2avwulS218fJzNNuqjA/yZpTeJCey+h0KpsTyFCjbYnmuVuI2lH5qFymO0fDzn204rit4YklRXS5VWU94DMJerr+N2ANiF1g/M5S9LY/pqKmt1PI6q8/avtv9QZQ9F/tHejXEdSr6BSnT6kn6YU6i/zPq/cuKoo8EYVGMtNY4/yuIYIdVXNULtvMlNuuQlrEUlm/fHXk1bCvTrmtW5SA5wm6f4tfFL38Ji2b6MoO6W9iJLFpwI71fl+lXN8jepVRadKF6NQajeq7ZNdZnuJovnsNo4C8gveJmsciky23kpIRKW1v1FDGSlayW1DOML6V1VVMs3ahtT1r8hWI5IsNrL9+DEytxCrqJuYbQKp1Qi6DZLOtL2dZtfWaFVkqsKYtxA7mxf2rmdJl05yft4WUMRSf5NYHDTx0ywFPlLHUd93oxdwe2KhcjMVrjOVOisDiwWqyE6TTq3Aizngf2w/l6gTUdde+SdJ6xFfki9KuorhDrOVBturT+E0b2k5hzaZnP1OwZsIm/hYc4DtqjuquaR2oX71pWEPo8IN82mEf+dkRez+l2FWSdpxY7fOFyjnqV2LfApRQwAHE30sZxU9m0QbR71blC5wKZLV5hzToIsr8B8S25x/NJBdh1D8IkwnGwBfdMVC+6sqDR1EPdkVGmZI2s5jGguvDCg6/ywlYnz/SCnUPxixMCBzNfAbwqF1OgPKd5STcsh51iXSvPcgTBmHAV+3ffwYmdb5AuU8pxILnMGkr5E3XUUa+yC3Rg3ZnmhakXSa7YdWmeOA3ND326Pq+27LPAdGzIzbQQV+GBFC+E1mmwPGNXwd3ObAzJfrBqJb+Zttnzjd2a4ctAy9bJzJWWSXE86/K8rzHYiklPkpt9kS1SjUX3aIjyUU79bEbuNw2xe2GP+OhCPzWbZ3HvO6jwFfsv2jpmOV87StRd6LGnohcARR0/uqCnIfJ2q4HE39omeU3dLljqYOjyY+/8Ns/6n2m6iBonTv+xkIjHCF8rvToFMmlMIvymM1KsbsjtvmlC/dVkQ89bx0kl4AGodeFho5iAr7AN8oEUDbEgkuT2p4rnlDDWpbl6io44Djyq5lD+B7kt5u+6NN5lGiIZaWxzh+ChykSCQ5grhxNOn3eoykJ7lmLfIpRA2tTSjuWn1b+zgSWFLCc5cSUSlfYu6vtXeyAIERt+J5qlu7sj+Alyz0HObwvS0rP8/rO3Z2DfleNEjT8R9K9NA8A1i00J9HxTnXrm1dXnd7wpb9FaIz+1uAu8/jvDcD/ouozHcxkVB0nwpyg7XI/973fGwtcqLq3y/KuOst0P/rrPLzjZQa/3Wu8Rbj9r5b5xI7NXrXzHw8umhCOZnhTppJZSdXWUoUymOITkC/I5xxL/CE6JsBB9G9iSSRSg4izaSF97h/GfePUD0CZqFoEoVSzHtbEY0cvuyZHpMLQoklPwTY2tNxho8ap3XUkNpl+6Lo7PMhIoPyKbZ/qYY1gOog6btE9uuBRJbwVUQFzofN5bg9umhC6U/zXYtwrjUqs7oK8TzC5PQKIvRyU+Jzm0SbTM4mtZVXJprUtt6T8MvsC7xKM3XM5zP8cQ3giYTJbGcivvmAGvIPJzrK/FXSnoTZ60Me45TzdKKG2mT7QmTq7gO8qyjvLRjTG2CKPJXwo+3LTGDENLJ5K9G5FfgwVHpdLvQ8VjZaJu/0n2dBHEQLiSJj9CPEivoCSqF+2+ct6MRGoOg0tQdh8z2DCEE8ynatMFlJ5xGt67YmijJ9Bnim7aqp5Y1Qw76tA+dYkxnfzpzW5V5ZAiNWhnjbWki6U99jY0mPZ367jnSJW7u4SGpUo6JwJHBzn4NoU8JBNJIS7omk6yX9eeBxnaRfKqpDrpQ4WnntQIQRvoTY2q+9oJMaz/5EJuH9bD/V9pfqKu/CTY5V3a5EtNDHmE6Br0kMZvtuSI1s37Kw+BnR1f7jwE81h+33bK9ve4OBx/qOgIlNiGvmw3M1fo8umlCWM5M9dRMRn1ups/sqSH8ccptsvlsc/Q2fRmS7fURRf2YknpDoUMwTpxJftpUSRwXJW0MAJX2Feaw0V4cp+oCuVxR02hN4lKKmy+2mdO5x9Pq2/j9m+rbWSUB7P9GM+RK4tSzB4cCDpz3RSTiikc5V1FafUzqnwG1vsdBz6BAe8Xtd/ilpDyL8sNdUoNaXeliiQ1k1dYlKWZEd51lEEa0X2v6dpMVM7i3ZinKT+LMj7PAUmi02btdT3hC1hooZZsGw/am5HqOTNnBFn8TNmZ0VeNiCTWglRTN1VPprqEBNp1qJgd4HOM324cVB9Ezb76kgu6CJDtNE0q9tr5Qr8K6jUqeohfwhRPjjF8qh5xLNVCpFsXSVzilwSZ8nWnSdw0xWoL2St8laVVEUDtuJgUQH2yul2WtI+OOtfyJKOKw75G+dR6OLM1GeX0v0Np0Tk5ekA5mpwNifYV2pzEVJnHo58Ihy6AfAx9yg5EaX6KICv4hoYdStiXcQTaehcqcqQJZU/5F4Cp3M55IBBbwmYeqqXDZhzHk3Ino9btlyiqPO/8shh+2KlRgl7Wv7w5OO3dbonA2cCOnahAmV4ZKpsG/52SYevFcB8hQ6UAFyZVfQk+h3GisC0XclUr1rMd8+iyn4tp7PilEfLxhy7DZFF1fgJxMd3c9gdtGblTqzr4tMo0BSKQb1dyJk9blEeNgXbf9hOrNMJtGfTVrhtfPqs5C0k+2TSoTTCnhCMaviXH8OYTrp7xK1PhE9NbIA2G2BLq7AD1joCaxCtC6Q1BeLfAvRN3E1IuFkZDPmpDkDinA1onhZnQ4z812caQfgJGaim/qpUszqVGI3vjGz+6VeT9TfuU3TuRX4ICoNX22/fKHncltFUXP52eWxNhFfe7jHtIWTtAHhVLo7Edd7Qnn+eqLYz65zPe82SPpX1+jusrIg6dC+pzcBlwGfdoWSrkV+3n0W5aa+u+0j5mqM2yqdVOAa0vDVDct1JvWoWiBJ0lFE4arTiJocdyYiOfa1fc58zLUNkn5AVBb8LGHymVQH5TZBX3GmdxOr2nkpzjSFMMI5cd6u7HRGgWt4w9fX2x7bkSNpz4gCSYfbPmqMzPkuTRsUNdevBBa7ZsPYhUTSvYH/JBYKZwCH2j5hYWc1HjVoiTYgvyA+i7ZhhAPnutV5a3u/qU1yJaRLCnyVbfi6ULQpkCTpLNvbjnreFcrNZzfgf4n62ALeNMm5tlCoQUu0CedbjTBRzqnPom0Y4YhzVnbedpUuOTEbN3xNGrM/UbTqda7XXQXggZL+XH4XsHZ5Pq9du5siaWuiROkuhP3+KbbPknQ3wiy0UipwYB3b/1VXaJLPgjl2OrcNI5yC87aTdGYF3kMNGr4mSV0kfZ8opfpV238f+NvzbM9HrenaSPpvIuGmbku0BfFZSNoO+I3t35Xn/0HUqv8VcECNTMxWztuu0jkF3o8qNnxN79u8eAAABA5JREFUkts6fU48ER3hbyRKtFba8SyUz0LSWcBjbF9byr9+GXglketxP9u7z+X4XafTCjxJ5oriwHw30QquPyPxNulzWSifRX+IYkkcu9r2AeX52BZ2A+dp5bztKl2ygSfJfHIo0RD4g8COhD18pW2AouggNBJHg4pxLJTPYnVJazhqr+8M7N33tzr66SjCeftd+py3t3VSgSfJcNa2faIk2f4VcICk5cBbF3piI+hlIa5FOPDOJZTv1sAy4KHjhMfF9M8xhwPfl3QNEb74AwBF96c6sfeNnLddJxV4kgznxhJC9zNJrwCuILrErJTY3hFA0teAbXtZpIr2ZAcs4NTGYvtdkk4E7goc31dldDXCFl6VYyQ9qa7ztuukDTxJhlCiIy4C7kDUB9kQeK/tHy/oxCYg6cLBwlPDjt1WaOu87TqpwJPkNoSkw4lMxv7ONOvZ3mPhZpXMFanAk6QPSR+y/eoRnXl6nWk+tbKuxCWtBbwU6HVkPwX4RJdKGDRB0sOBc2z/VdKewLbAh2z/eoGnNqekAk+SPiQ92PbyMZ15Ngbeafv+8zmvZDySzgMeSDhtP0skYT3T9tgOS10nnZhJ0oft5eXnyM48kla6PovTaH/XcW6ybUm7Ah+1fbCklbLv6jTJFXiSDKFsyQ8gOtKswYxTbKVM5JF0V9tXltrtK1BCIW+zlNIHxxHx+o8iyuCe28suva2SCjxJhiDpYuA1rFjVb6VsBTeN9nddRtImRI+AM23/QNJi4NG2D1vgqc0paUJJkuFcZ/vYhZ5EDVq3v+sypRjWB/oObQY8hCh2d5slV+BJMoTSYGB1omxsf/PsSSnpC0qT9ne3FVbFTl2pwJNkCJJOHnLYtnea98k0pGr7uy6zqnfqSgWeJLchmrS/6zKreqeutIEnyQgk7QI8gNnlZN+xcDMazYj2d3tXaX/XcVbpTl25Ak+SIUj6JLAOUUr2M8DuwBm2V8rYYkknEe3vjmzQ/q7zrKqdulKBJ8kQJJ1ne+u+n+sBx9p+5ELPLRnPqtSpa6UtUJ8kC0yvD+bfSiPjfxIlT5OVHNt/tL30tq68IW3gSTKKYyTdAXgfcBaRnv7phZ1SkswmTShJMgFJtwfWsl2nQ0ySzDlpQkmSPiRtV9Kye8//g8hsfKekOy3czJJkRVKBJ8lsPgX8A0DSo4ADiYiG64ClCzivJFmBtIEnyWxWt31t+f1ZwFLbRwJHSjpnAeeVJCuQK/Akmc3qJZsRIpPxpL6/5YInWanICzJJZnM48H1J1xChhD8AkHQvwoySJCsNGYWSJANI2p6I+T6+l4peiiatt7JXI0xWLVKBJ0mSdJS0gSdJknSUVOBJkiQdJRV4kiRJR0kFniRJ0lFSgSdJknSU/w8twD9BFVYqOAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "writer_freq = {k: v for k,v in sorted(get_crew_freq(crew_type=\"writers\").items(), key=lambda x: x[1], reverse=True)[:LIMIT]}\n",
    "plt.bar(writer_freq.keys(), writer_freq.values())\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is suprising that *Anurag Kashyap* has topped this list as well! Let's experiment something else, we will try showing a correlation between top directors and top writers, the perfect recipe for success!\n",
    "\n",
    "i.e we are finding which top directors and writers have collaborated with each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_directors = list(director_freq.keys())\n",
    "top_writers = list(writer_freq.keys())\n",
    "\n",
    "crew_corr = np.zeros(shape=(len(top_directors), len(top_writers)))\n",
    "\n",
    "def fill_crew_corr(crew_corr, top_directors, top_writers):\n",
    "    top_imdb_ids = top_movies(df, limit=250)[\"imdb_id\"].tolist()\n",
    "\n",
    "    for imdb_id in top_imdb_ids:\n",
    "        d_ids = crew_df[crew_df[\"imdb_id\"] == imdb_id][\"directors\"].all()\n",
    "        w_ids = crew_df[crew_df[\"imdb_id\"] == imdb_id][\"writers\"].all()        \n",
    "\n",
    "        directors = [director_df[director_df[\"crew_id\"] == d_id][\"name\"].all() for d_id in d_ids]\n",
    "        writers = [writer_df[writer_df[\"crew_id\"] == w_id][\"name\"].all() for w_id in w_ids]\n",
    " \n",
    "        for director in directors:\n",
    "            for writer in writers:\n",
    "                if writer in top_writers and director in top_directors:\n",
    "                    crew_corr[top_writers.index(writer)][top_directors.index(director)] += 1\n",
    "    \n",
    "    return crew_corr\n",
    "\n",
    "crew_corr = fill_crew_corr(crew_corr, top_directors, top_writers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0e8bb38240>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = sns.light_palette(\"Blue\", as_cmap=True)\n",
    "\n",
    "sns.heatmap(crew_corr, xticklabels=top_directors, yticklabels=top_writers, linewidth=0.5, cmap=cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The heatmap is mostly empty, but as we can observe some popular directors and writers frequently collaborate with each other! Let's further this analysis by creating a 4D model to compare relationship between top actors, writers and directors. To create a 4D model, we will need frequency of a (director, actor, writer) relationship (for each movie)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "relation_dwa = dict() # This dictionary will hold the frequency count of {(director, writer, actor): freq, ..}\n",
    "\n",
    "def find_dwa_reln(relation_dwa, top_directors, top_writers):\n",
    "    top_imdb_ids = top_movies(df, limit=250)[\"imdb_id\"].tolist()\n",
    "\n",
    "    for imdb_id in top_imdb_ids:\n",
    "        d_ids = crew_df[crew_df[\"imdb_id\"] == imdb_id][\"directors\"].all()\n",
    "        w_ids = crew_df[crew_df[\"imdb_id\"] == imdb_id][\"writers\"].all()\n",
    "\n",
    "        all_actors = df[df[\"imdb_id\"] == imdb_id][\"actors\"].all()\n",
    "        \n",
    "        directors = [director_df[director_df[\"crew_id\"] == d_id][\"name\"].all() for d_id in d_ids]\n",
    "        writers = [writer_df[writer_df[\"crew_id\"] == w_id][\"name\"].all() for w_id in w_ids]\n",
    "\n",
    "        for director in directors:\n",
    "            for writer in writers:\n",
    "                for actor in [actor for actor in all_actors if actor != \"\"]:\n",
    "                        try:\n",
    "                            relation_dwa[(director, writer, actor)] += 1\n",
    "                        except:\n",
    "                            relation_dwa[(director, writer, actor)] = 1\n",
    "         \n",
    "    return relation_dwa\n",
    "\n",
    "relation_dwa = {k: v for k,v in sorted(find_dwa_reln(relation_dwa, top_directors, top_writers).items(), key=lambda x: x[1], reverse=True)[:40]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Xuniques, X = np.unique([rel[0] for rel in relation_dwa], return_inverse=True)\n",
    "Yuniques, Y = np.unique([rel[1] for rel in relation_dwa], return_inverse=True)\n",
    "Zuniques, Z = np.unique([rel[2] for rel in relation_dwa], return_inverse=True)\n",
    "\n",
    "fig = plt.figure(figsize=(20, 15))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "img = ax.scatter(X, Y, Z, c=[relation_dwa[rel] for rel in relation_dwa], cmap=cmap)\n",
    "ax.set(xticks=range(len(Xuniques)), xticklabels=Xuniques,\n",
    "       yticks=range(len(Yuniques)), yticklabels=Yuniques,\n",
    "       zticks=range(len(Zuniques)), zticklabels=Zuniques)\n",
    "\n",
    "ax.set_xlabel(\"directors\"); ax.set_ylabel(\"writers\"); ax.set_zlabel(\"actors\");\n",
    "ax.zaxis.labelpad = ax.xaxis.labelpad = ax.yaxis.labelpad = 50\n",
    "plt.rcParams[\"axes.labelweight\"] = \"bold\"\n",
    "\n",
    "fig.colorbar(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like the heatmap, this model appears sparse!\n",
    "In the model above, the color scheme (`c`) acts as the fourth dimension (showing frequency)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Content based filtering\n",
    "We will now perform content based filtering using actors, director, writer, title, genres, story, summary and tagline (if any). For content based filtering the strategy we will follow is a trivial one. We will perform cosine similarity on the attributes mentioned above (after removing the stopwords and other minor cleaning). Getting director and writer info is being repeated frequently, so we will write a method for it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_director_writer(df, person=\"director\"):\n",
    "    if person == \"director\":\n",
    "        d_ids = crew_df[crew_df[\"imdb_id\"] == df[\"imdb_id\"]][\"directors\"].all()\n",
    "        directors = [director_df[director_df[\"crew_id\"] == d_id][\"name\"].all() for d_id in d_ids]\n",
    "        return directors\n",
    "    elif person == \"writer\":\n",
    "        w_ids = crew_df[crew_df[\"imdb_id\"] == df[\"imdb_id\"]][\"writers\"].all()\n",
    "        writers = [writer_df[writer_df[\"crew_id\"] == w_id][\"name\"].all() for w_id in w_ids]\n",
    "        return writers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>original_title</th>\n",
       "      <th>genres</th>\n",
       "      <th>runtime</th>\n",
       "      <th>imdb_rating</th>\n",
       "      <th>imdb_votes</th>\n",
       "      <th>year_of_release</th>\n",
       "      <th>wins_nominations</th>\n",
       "      <th>release_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1070</th>\n",
       "      <td>Chak De! India</td>\n",
       "      <td>Drama, Family, Sport</td>\n",
       "      <td>153.0</td>\n",
       "      <td>8.2</td>\n",
       "      <td>68421.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>28 wins &amp; 13 nominations</td>\n",
       "      <td>10 August 2007 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>Iqbal</td>\n",
       "      <td>Drama, Sport</td>\n",
       "      <td>132.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>14864.0</td>\n",
       "      <td>2005</td>\n",
       "      <td>9 wins &amp; 13 nominations</td>\n",
       "      <td>20 January 2006 (USA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>Ferrari Ki Sawaari</td>\n",
       "      <td>Comedy, Drama, Family</td>\n",
       "      <td>140.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>4693.0</td>\n",
       "      <td>2012</td>\n",
       "      <td>4 nominations</td>\n",
       "      <td>15 June 2012 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1126</th>\n",
       "      <td>Say Salaam India: 'Let's Bring the Cup Home'</td>\n",
       "      <td>Drama, Sport</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.4</td>\n",
       "      <td>84.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749</th>\n",
       "      <td>Patiala House</td>\n",
       "      <td>Drama, Sport</td>\n",
       "      <td>140.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>8301.0</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11 February 2011 (India)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1044</th>\n",
       "      <td>Meerabai Not Out</td>\n",
       "      <td>Comedy, Drama, Romance</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>960</th>\n",
       "      <td>Dil Bole Hadippa!</td>\n",
       "      <td>Comedy, Drama, Sport</td>\n",
       "      <td>148.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3528.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18 September 2009 (India)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    original_title                  genres  \\\n",
       "1070                                Chak De! India    Drama, Family, Sport   \n",
       "1259                                         Iqbal            Drama, Sport   \n",
       "692                             Ferrari Ki Sawaari   Comedy, Drama, Family   \n",
       "1126  Say Salaam India: 'Let's Bring the Cup Home'            Drama, Sport   \n",
       "749                                  Patiala House            Drama, Sport   \n",
       "1044                              Meerabai Not Out  Comedy, Drama, Romance   \n",
       "960                              Dil Bole Hadippa!    Comedy, Drama, Sport   \n",
       "\n",
       "      runtime  imdb_rating  imdb_votes year_of_release  \\\n",
       "1070    153.0          8.2     68421.0            2007   \n",
       "1259    132.0          8.1     14864.0            2005   \n",
       "692     140.0          6.4      4693.0            2012   \n",
       "1126      NaN          6.4        84.0            2007   \n",
       "749     140.0          5.6      8301.0            2011   \n",
       "1044      NaN          4.0        86.0            2008   \n",
       "960     148.0          4.5      3528.0            2009   \n",
       "\n",
       "              wins_nominations               release_date  \n",
       "1070  28 wins & 13 nominations     10 August 2007 (India)  \n",
       "1259   9 wins & 13 nominations      20 January 2006 (USA)  \n",
       "692              4 nominations       15 June 2012 (India)  \n",
       "1126                       NaN                        NaN  \n",
       "749                        NaN   11 February 2011 (India)  \n",
       "1044                       NaN                        NaN  \n",
       "960                        NaN  18 September 2009 (India)  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def content_based(title, df, limit, offset):\n",
    "    df[\"desc\"] = df[\"original_title\"].fillna(\"\").apply(lambda x: x.lower()) + df[\"story\"].fillna(\"\").apply(lambda x: x.lower()) + df[\"summary\"].fillna(\"\").apply(lambda x: x.lower()) + df[\"tagline\"].fillna(\"\").apply(lambda x: x.lower()) + df[\"genres\"].apply(lambda x: (\" \".join(x)).lower())\n",
    "\n",
    "    df[\"crew\"] = df[\"actors\"].fillna(\"\").apply(lambda actors: (\" \".join([actor.replace(\" \", \"\") for actor in actors[:5]])).lower())\n",
    "\n",
    "    #Let's try guessing the title index!\n",
    "    try:\n",
    "        index = df.index[df[\"original_title\"] == title][0]\n",
    "    except:\n",
    "        try:\n",
    "            title = get_close_matches(title, [movie for movie in df[\"original_title\"].tolist()])[0]\n",
    "            index = df.index[df[\"original_title\"] == title][0]\n",
    "        except:\n",
    "            return None\n",
    "\n",
    "    df[\"directors\"] = df.apply(get_director_writer, args=(\"director\",), axis=1)\n",
    "    df[\"writers\"] = df.apply(get_director_writer, args=(\"writer\",), axis=1)\n",
    "\n",
    "    df[\"crew\"] += \" \"+df[\"directors\"].fillna(\"\").apply(lambda direcs: (\" \".join([direc.replace(\" \", \"\") for direc in DIRECTOR_WT*direcs if isinstance(direc, bool) == False])).lower())\n",
    "    df[\"crew\"] += \" \"+df[\"writers\"].fillna(\"\").apply(lambda writers: (\" \".join([writer.replace(\" \", \"\") for writer in WRITER_WT*writers if isinstance(writer, bool) == False])).lower())\n",
    "    tfidf = CountVectorizer(analyzer=\"word\", stop_words=stopwords.words(\"english\"), ngram_range=(1, 2))\n",
    "    tfidf_mat = tfidf.fit_transform(df[\"desc\"] + df[\"crew\"])\n",
    "    cosine_sim = cosine_similarity(tfidf_mat, tfidf_mat)\n",
    "        \n",
    "    rec_movie = cosine_sim[index]\n",
    "    ids = rec_movie.argsort()[::-1][1 : limit]\n",
    "    return top_movies(df.iloc[ids], percentile=0.2)[[\"original_title\", \"genres\", \"runtime\", \"imdb_rating\", \"imdb_votes\", \"year_of_release\", \"wins_nominations\", \"release_date\"]]\n",
    "\n",
    "# You can include director and writer's significance by increasing their weight\n",
    "DIRECTOR_WT = 1\n",
    "WRITER_WT = 1\n",
    "content_df = content_based(\"MS Dhoni An untold story\", df, 10, 0)\n",
    "content_df[\"genres\"] = content_df[\"genres\"].apply(lambda x: \", \".join(x))\n",
    "content_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, our approach is able to predict cricket based films for *MS Dhoni: An Untold Story*. We are passing our results to the `top_movies` method we wrote earlier with a 0.2 percentile to remove the worst reviewed films. Also I have added `difflib`'s `get_close_matches` method to predict the movie which is closest to the film entered by the user. This is helpful in situations where one doesn't know the exact movie title!\n",
    "\n",
    "Again, this is a very basic approach and many sophisticated approaches exist! You can also use `tags.csv`, `genome_tags.csv` and `genome_scores.csv`. From [TIMDB's documentation](https://github.com/pncnmnp/TIMDB): \n",
    "> The genome-scores were available for very few movies (64 in total) from \"Full\" MovieLens dataset.\n",
    "\n",
    "*Based on my observation, `tags.csv` has tags for 504 movies!* Therefore, if the movie is not very popular, your best bet would be to generate tags from summary, story and tagline."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Collaborative Filtering\n",
    "Let us conclude this exploration by performing basic collaborative filtering using `./collaborative/ratings.csv`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimating biases using als...\n",
      "Computing the pearson_baseline similarity matrix...\n",
      "Done computing similarity matrix.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['3 Idiots (2009)',\n",
       " 'Chak De India! (2007)',\n",
       " 'Like Stars on Earth (Taare Zameen Par) (2007)',\n",
       " 'Paint It Yellow (Rang De Basanti) (2006)',\n",
       " 'Children of Heaven  The (Bacheha-Ye Aseman) (1997)',\n",
       " 'Munna bhai M.B.B.S. (2003)',\n",
       " 'Queen (2014)',\n",
       " 'Andaz Apna Apna (1994)',\n",
       " 'Swades: We  the People (Our Country) (2004)',\n",
       " 'Sholay (1975)']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def collaborative(m_id):\n",
    "    df_coll = pd.read_csv(open(\"./collaborative/ratings.csv\"))\n",
    "    df_titles = pd.read_csv(open(\"./collaborative/titles.csv\"))\n",
    "\n",
    "    reader = Reader(rating_scale=(1, 5))\n",
    "    sim_options = {\"name\": \"pearson_baseline\", \"user_based\": False}\n",
    "    data = Dataset.load_from_df(df_coll[[\"user_id\", \"movie_id\", \"rating\"]], reader)\n",
    "\n",
    "    trainset = data.build_full_trainset()\n",
    "    model = KNNBaseline(sim_options=sim_options)\n",
    "    model.fit(trainset)\n",
    "\n",
    "    inn_id = model.trainset.to_inner_iid(m_id)\n",
    "    inn_id_neigh = model.get_neighbors(inn_id, k=10)\n",
    "\n",
    "    titles = list()\n",
    "    for movielens_id in inn_id_neigh:\n",
    "        titles += [df_titles[df_titles[\"movie_id\"] == model.trainset.to_raw_iid(movielens_id)][\"title\"].all()]\n",
    "    \n",
    "    return titles\n",
    "\n",
    "# Here 157392 is the movie_id for the movie: Dangal (2016)\n",
    "collaborative(167392)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From above you can see, we are being recommended movies with *Aamir Khan* in them. Also *sports* based movies and movies with the theme - *struggle* are popular. You can use `./collaborative/links.csv` to convert a `movie_id` to it's equivalent `imdb_id` and get the statistics for the same from `./1950-2019/bollywood_full.csv`. From the documentation: \n",
    "> The leading zeros are removed for imdb_id, which are not removed for the rest of the database(i.e for \"1950-1989\", \"1990-2009\", \"2010-2019\" and \"1950-2019\").  \n",
    "**Example:** in links.csv if imdb_id is 123456, it can be tt0123456 in imdb_id col in the datasets in \"1950-1989\", \"1990-2009\" and \"2010-2019\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So this is it! Hopefully I have given you a good overview of how this dataset looks like and what basic operations you can perform with it. **Try caching the models and dataframes to perform quick recommendations.** You can try and create a hybrid approach which combines results from content-based and collaborative filtering approaches. If you have any questions, you can [contact](https://pncnmnp.github.io/#contact) me.\n",
    "\n",
    "Keep exploring! 😄"
   ]
  }
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