├── .ipynb_checkpoints
    ├── preprocessing 2.ipynb
    ├── preprocessing 3.ipynb
    ├── preprocessing 4.ipynb
    └── sentiment.ipynb
├── Procfile
├── README.md
├── datasets
    ├── final_data.csv
    ├── main_data.csv
    ├── movie.csv
    ├── movie_metadata.csv
    └── reviews.txt
├── main.py
├── main_data.csv
├── nlp_model.pkl
├── requirements.txt
├── static
    ├── autocomplete.js
    ├── default.jpg
    ├── image.jpg
    ├── loader.gif
    ├── recommend.js
    └── style.css
├── templates
    ├── home.html
    └── recommend.html
└── tranform.pkl


/.ipynb_checkpoints/preprocessing 2.ipynb:
--------------------------------------------------------------------------------
1 | {"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np\nimport pandas as pd","execution_count":86,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"credits = pd.read_csv('credits.csv')","execution_count":87,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"credits","execution_count":88,"outputs":[{"output_type":"execute_result","execution_count":88,"data":{"text/plain":"                                                                             cast  \\\n0      [{'cast_id': 14, 'character': 'Woody (voice)', 'credit_id': '52fe4284c3...   \n1      [{'cast_id': 1, 'character': 'Alan Parrish', 'credit_id': '52fe44bfc3a3...   \n2      [{'cast_id': 2, 'character': 'Max Goldman', 'credit_id': '52fe466a92514...   \n3      [{'cast_id': 1, 'character': \"Savannah 'Vannah' Jackson\", 'credit_id': ...   \n4      [{'cast_id': 1, 'character': 'George Banks', 'credit_id': '52fe44959251...   \n...                                                                           ...   \n45471  [{'cast_id': 0, 'character': '', 'credit_id': '5894a909925141427e0079a5...   \n45472  [{'cast_id': 1002, 'character': 'Sister Angela', 'credit_id': '52fe4af1...   \n45473  [{'cast_id': 6, 'character': 'Emily Shaw', 'credit_id': '52fe4776c3a368...   \n45474  [{'cast_id': 2, 'character': '', 'credit_id': '52fe4ea59251416c7515d7d5...   \n45475                                                                          []   \n\n                                                                             crew  \\\n0      [{'credit_id': '52fe4284c3a36847f8024f49', 'department': 'Directing', '...   \n1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'department': 'Production', ...   \n2      [{'credit_id': '52fe466a9251416c75077a89', 'department': 'Directing', '...   \n3      [{'credit_id': '52fe44779251416c91011acb', 'department': 'Directing', '...   \n4      [{'credit_id': '52fe44959251416c75039ed7', 'department': 'Sound', 'gend...   \n...                                                                           ...   \n45471  [{'credit_id': '5894a97d925141426c00818c', 'department': 'Directing', '...   \n45472  [{'credit_id': '52fe4af1c3a36847f81e9b15', 'department': 'Directing', '...   \n45473  [{'credit_id': '52fe4776c3a368484e0c8387', 'department': 'Directing', '...   \n45474  [{'credit_id': '533bccebc3a36844cf0011a7', 'department': 'Directing', '...   \n45475  [{'credit_id': '593e676c92514105b702e68e', 'department': 'Directing', '...   \n\n           id  \n0         862  \n1        8844  \n2       15602  \n3       31357  \n4       11862  \n...       ...  \n45471  439050  \n45472  111109  \n45473   67758  \n45474  227506  \n45475  461257  \n\n[45476 rows x 3 columns]","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>cast</th>\n      <th>crew</th>\n      <th>id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>[{'cast_id': 14, 'character': 'Woody (voice)', 'credit_id': '52fe4284c3...</td>\n      <td>[{'credit_id': '52fe4284c3a36847f8024f49', 'department': 'Directing', '...</td>\n      <td>862</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>[{'cast_id': 1, 'character': 'Alan Parrish', 'credit_id': '52fe44bfc3a3...</td>\n      <td>[{'credit_id': '52fe44bfc3a36847f80a7cd1', 'department': 'Production', ...</td>\n      <td>8844</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>[{'cast_id': 2, 'character': 'Max Goldman', 'credit_id': '52fe466a92514...</td>\n      <td>[{'credit_id': '52fe466a9251416c75077a89', 'department': 'Directing', '...</td>\n      <td>15602</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>[{'cast_id': 1, 'character': \"Savannah 'Vannah' Jackson\", 'credit_id': ...</td>\n      <td>[{'credit_id': '52fe44779251416c91011acb', 'department': 'Directing', '...</td>\n      <td>31357</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>[{'cast_id': 1, 'character': 'George Banks', 'credit_id': '52fe44959251...</td>\n      <td>[{'credit_id': '52fe44959251416c75039ed7', 'department': 'Sound', 'gend...</td>\n      <td>11862</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45471</th>\n      <td>[{'cast_id': 0, 'character': '', 'credit_id': '5894a909925141427e0079a5...</td>\n      <td>[{'credit_id': '5894a97d925141426c00818c', 'department': 'Directing', '...</td>\n      <td>439050</td>\n    </tr>\n    <tr>\n      <th>45472</th>\n      <td>[{'cast_id': 1002, 'character': 'Sister Angela', 'credit_id': '52fe4af1...</td>\n      <td>[{'credit_id': '52fe4af1c3a36847f81e9b15', 'department': 'Directing', '...</td>\n      <td>111109</td>\n    </tr>\n    <tr>\n      <th>45473</th>\n      <td>[{'cast_id': 6, 'character': 'Emily Shaw', 'credit_id': '52fe4776c3a368...</td>\n      <td>[{'credit_id': '52fe4776c3a368484e0c8387', 'department': 'Directing', '...</td>\n      <td>67758</td>\n    </tr>\n    <tr>\n      <th>45474</th>\n      <td>[{'cast_id': 2, 'character': '', 'credit_id': '52fe4ea59251416c7515d7d5...</td>\n      <td>[{'credit_id': '533bccebc3a36844cf0011a7', 'department': 'Directing', '...</td>\n      <td>227506</td>\n    </tr>\n    <tr>\n      <th>45475</th>\n      <td>[]</td>\n      <td>[{'credit_id': '593e676c92514105b702e68e', 'department': 'Directing', '...</td>\n      <td>461257</td>\n    </tr>\n  </tbody>\n</table>\n<p>45476 rows × 3 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"meta = pd.read_csv('movies_metadata.csv')","execution_count":89,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3063: DtypeWarning: Columns (10) have mixed types.Specify dtype option on import or set low_memory=False.\n  interactivity=interactivity, compiler=compiler, result=result)\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"meta['release_date'] = pd.to_datetime(meta['release_date'], errors='coerce')","execution_count":90,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\nmeta['year'] = meta['release_date'].dt.year","execution_count":91,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"meta['year'].value_counts().sort_index()","execution_count":92,"outputs":[{"output_type":"execute_result","execution_count":92,"data":{"text/plain":"1874.0       1\n1878.0       1\n1883.0       1\n1887.0       1\n1888.0       2\n          ... \n2015.0    1905\n2016.0    1604\n2017.0     532\n2018.0       5\n2020.0       1\nName: year, Length: 135, dtype: int64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Getting only movies upto 2017 movies as we don't have enough data for the movies from 2018, 2019 and 2020. \n# We'll deal with it in the upcoming preprocessing files\nnew_meta = meta.loc[meta.year <= 2017,['genres','id','title','year']]","execution_count":93,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\nnew_meta","execution_count":94,"outputs":[{"output_type":"execute_result","execution_count":94,"data":{"text/plain":"                                                                           genres  \\\n0      [{'id': 16, 'name': 'Animation'}, {'id': 35, 'name': 'Comedy'}, {'id': ...   \n1      [{'id': 12, 'name': 'Adventure'}, {'id': 14, 'name': 'Fantasy'}, {'id':...   \n2                [{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]   \n3      [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}, {'id': 1074...   \n4                                                  [{'id': 35, 'name': 'Comedy'}]   \n...                                                                           ...   \n45460  [{'id': 18, 'name': 'Drama'}, {'id': 28, 'name': 'Action'}, {'id': 1074...   \n45462                                               [{'id': 18, 'name': 'Drama'}]   \n45463  [{'id': 28, 'name': 'Action'}, {'id': 18, 'name': 'Drama'}, {'id': 53, ...   \n45464                                                                          []   \n45465                                                                          []   \n\n           id                        title    year  \n0         862                    Toy Story  1995.0  \n1        8844                      Jumanji  1995.0  \n2       15602             Grumpier Old Men  1995.0  \n3       31357            Waiting to Exhale  1995.0  \n4       11862  Father of the Bride Part II  1995.0  \n...       ...                          ...     ...  \n45460   30840                   Robin Hood  1991.0  \n45462  111109          Century of Birthing  2011.0  \n45463   67758                     Betrayal  2003.0  \n45464  227506             Satan Triumphant  1917.0  \n45465  461257                     Queerama  2017.0  \n\n[45370 rows x 4 columns]","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>genres</th>\n      <th>id</th>\n      <th>title</th>\n      <th>year</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>[{'id': 16, 'name': 'Animation'}, {'id': 35, 'name': 'Comedy'}, {'id': ...</td>\n      <td>862</td>\n      <td>Toy Story</td>\n      <td>1995.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>[{'id': 12, 'name': 'Adventure'}, {'id': 14, 'name': 'Fantasy'}, {'id':...</td>\n      <td>8844</td>\n      <td>Jumanji</td>\n      <td>1995.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>[{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]</td>\n      <td>15602</td>\n      <td>Grumpier Old Men</td>\n      <td>1995.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}, {'id': 1074...</td>\n      <td>31357</td>\n      <td>Waiting to Exhale</td>\n      <td>1995.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>[{'id': 35, 'name': 'Comedy'}]</td>\n      <td>11862</td>\n      <td>Father of the Bride Part II</td>\n      <td>1995.0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45460</th>\n      <td>[{'id': 18, 'name': 'Drama'}, {'id': 28, 'name': 'Action'}, {'id': 1074...</td>\n      <td>30840</td>\n      <td>Robin Hood</td>\n      <td>1991.0</td>\n    </tr>\n    <tr>\n      <th>45462</th>\n      <td>[{'id': 18, 'name': 'Drama'}]</td>\n      <td>111109</td>\n      <td>Century of Birthing</td>\n      <td>2011.0</td>\n    </tr>\n    <tr>\n      <th>45463</th>\n      <td>[{'id': 28, 'name': 'Action'}, {'id': 18, 'name': 'Drama'}, {'id': 53, ...</td>\n      <td>67758</td>\n      <td>Betrayal</td>\n      <td>2003.0</td>\n    </tr>\n    <tr>\n      <th>45464</th>\n      <td>[]</td>\n      <td>227506</td>\n      <td>Satan Triumphant</td>\n      <td>1917.0</td>\n    </tr>\n    <tr>\n      <th>45465</th>\n      <td>[]</td>\n      <td>461257</td>\n      <td>Queerama</td>\n      <td>2017.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>45370 rows × 4 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_meta['id'] = new_meta['id'].astype(int)","execution_count":95,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data = pd.merge(new_meta, credits, on='id')","execution_count":96,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"pd.set_option('display.max_colwidth', 75)\ndata","execution_count":97,"outputs":[{"output_type":"execute_result","execution_count":97,"data":{"text/plain":"                                                                           genres  \\\n0      [{'id': 16, 'name': 'Animation'}, {'id': 35, 'name': 'Comedy'}, {'id': ...   \n1      [{'id': 12, 'name': 'Adventure'}, {'id': 14, 'name': 'Fantasy'}, {'id':...   \n2                [{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]   \n3      [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}, {'id': 1074...   \n4                                                  [{'id': 35, 'name': 'Comedy'}]   \n...                                                                           ...   \n45440  [{'id': 18, 'name': 'Drama'}, {'id': 28, 'name': 'Action'}, {'id': 1074...   \n45441                                               [{'id': 18, 'name': 'Drama'}]   \n45442  [{'id': 28, 'name': 'Action'}, {'id': 18, 'name': 'Drama'}, {'id': 53, ...   \n45443                                                                          []   \n45444                                                                          []   \n\n           id                        title    year  \\\n0         862                    Toy Story  1995.0   \n1        8844                      Jumanji  1995.0   \n2       15602             Grumpier Old Men  1995.0   \n3       31357            Waiting to Exhale  1995.0   \n4       11862  Father of the Bride Part II  1995.0   \n...       ...                          ...     ...   \n45440   30840                   Robin Hood  1991.0   \n45441  111109          Century of Birthing  2011.0   \n45442   67758                     Betrayal  2003.0   \n45443  227506             Satan Triumphant  1917.0   \n45444  461257                     Queerama  2017.0   \n\n                                                                             cast  \\\n0      [{'cast_id': 14, 'character': 'Woody (voice)', 'credit_id': '52fe4284c3...   \n1      [{'cast_id': 1, 'character': 'Alan Parrish', 'credit_id': '52fe44bfc3a3...   \n2      [{'cast_id': 2, 'character': 'Max Goldman', 'credit_id': '52fe466a92514...   \n3      [{'cast_id': 1, 'character': \"Savannah 'Vannah' Jackson\", 'credit_id': ...   \n4      [{'cast_id': 1, 'character': 'George Banks', 'credit_id': '52fe44959251...   \n...                                                                           ...   \n45440  [{'cast_id': 1, 'character': 'Sir Robert Hode', 'credit_id': '52fe44439...   \n45441  [{'cast_id': 1002, 'character': 'Sister Angela', 'credit_id': '52fe4af1...   \n45442  [{'cast_id': 6, 'character': 'Emily Shaw', 'credit_id': '52fe4776c3a368...   \n45443  [{'cast_id': 2, 'character': '', 'credit_id': '52fe4ea59251416c7515d7d5...   \n45444                                                                          []   \n\n                                                                             crew  \n0      [{'credit_id': '52fe4284c3a36847f8024f49', 'department': 'Directing', '...  \n1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'department': 'Production', ...  \n2      [{'credit_id': '52fe466a9251416c75077a89', 'department': 'Directing', '...  \n3      [{'credit_id': '52fe44779251416c91011acb', 'department': 'Directing', '...  \n4      [{'credit_id': '52fe44959251416c75039ed7', 'department': 'Sound', 'gend...  \n...                                                                           ...  \n45440  [{'credit_id': '52fe44439251416c9100a899', 'department': 'Directing', '...  \n45441  [{'credit_id': '52fe4af1c3a36847f81e9b15', 'department': 'Directing', '...  \n45442  [{'credit_id': '52fe4776c3a368484e0c8387', 'department': 'Directing', '...  \n45443  [{'credit_id': '533bccebc3a36844cf0011a7', 'department': 'Directing', '...  \n45444  [{'credit_id': '593e676c92514105b702e68e', 'department': 'Directing', '...  \n\n[45445 rows x 6 columns]","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>genres</th>\n      <th>id</th>\n      <th>title</th>\n      <th>year</th>\n      <th>cast</th>\n      <th>crew</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>[{'id': 16, 'name': 'Animation'}, {'id': 35, 'name': 'Comedy'}, {'id': ...</td>\n      <td>862</td>\n      <td>Toy Story</td>\n      <td>1995.0</td>\n      <td>[{'cast_id': 14, 'character': 'Woody (voice)', 'credit_id': '52fe4284c3...</td>\n      <td>[{'credit_id': '52fe4284c3a36847f8024f49', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>[{'id': 12, 'name': 'Adventure'}, {'id': 14, 'name': 'Fantasy'}, {'id':...</td>\n      <td>8844</td>\n      <td>Jumanji</td>\n      <td>1995.0</td>\n      <td>[{'cast_id': 1, 'character': 'Alan Parrish', 'credit_id': '52fe44bfc3a3...</td>\n      <td>[{'credit_id': '52fe44bfc3a36847f80a7cd1', 'department': 'Production', ...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>[{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]</td>\n      <td>15602</td>\n      <td>Grumpier Old Men</td>\n      <td>1995.0</td>\n      <td>[{'cast_id': 2, 'character': 'Max Goldman', 'credit_id': '52fe466a92514...</td>\n      <td>[{'credit_id': '52fe466a9251416c75077a89', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}, {'id': 1074...</td>\n      <td>31357</td>\n      <td>Waiting to Exhale</td>\n      <td>1995.0</td>\n      <td>[{'cast_id': 1, 'character': \"Savannah 'Vannah' Jackson\", 'credit_id': ...</td>\n      <td>[{'credit_id': '52fe44779251416c91011acb', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>[{'id': 35, 'name': 'Comedy'}]</td>\n      <td>11862</td>\n      <td>Father of the Bride Part II</td>\n      <td>1995.0</td>\n      <td>[{'cast_id': 1, 'character': 'George Banks', 'credit_id': '52fe44959251...</td>\n      <td>[{'credit_id': '52fe44959251416c75039ed7', 'department': 'Sound', 'gend...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45440</th>\n      <td>[{'id': 18, 'name': 'Drama'}, {'id': 28, 'name': 'Action'}, {'id': 1074...</td>\n      <td>30840</td>\n      <td>Robin Hood</td>\n      <td>1991.0</td>\n      <td>[{'cast_id': 1, 'character': 'Sir Robert Hode', 'credit_id': '52fe44439...</td>\n      <td>[{'credit_id': '52fe44439251416c9100a899', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>45441</th>\n      <td>[{'id': 18, 'name': 'Drama'}]</td>\n      <td>111109</td>\n      <td>Century of Birthing</td>\n      <td>2011.0</td>\n      <td>[{'cast_id': 1002, 'character': 'Sister Angela', 'credit_id': '52fe4af1...</td>\n      <td>[{'credit_id': '52fe4af1c3a36847f81e9b15', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>45442</th>\n      <td>[{'id': 28, 'name': 'Action'}, {'id': 18, 'name': 'Drama'}, {'id': 53, ...</td>\n      <td>67758</td>\n      <td>Betrayal</td>\n      <td>2003.0</td>\n      <td>[{'cast_id': 6, 'character': 'Emily Shaw', 'credit_id': '52fe4776c3a368...</td>\n      <td>[{'credit_id': '52fe4776c3a368484e0c8387', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>45443</th>\n      <td>[]</td>\n      <td>227506</td>\n      <td>Satan Triumphant</td>\n      <td>1917.0</td>\n      <td>[{'cast_id': 2, 'character': '', 'credit_id': '52fe4ea59251416c7515d7d5...</td>\n      <td>[{'credit_id': '533bccebc3a36844cf0011a7', 'department': 'Directing', '...</td>\n    </tr>\n    <tr>\n      <th>45444</th>\n      <td>[]</td>\n      <td>461257</td>\n      <td>Queerama</td>\n      <td>2017.0</td>\n      <td>[]</td>\n      <td>[{'credit_id': '593e676c92514105b702e68e', 'department': 'Directing', '...</td>\n    </tr>\n  </tbody>\n</table>\n<p>45445 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# evaluates an expression node or a string containing a Python literal or container display\nimport ast\ndata['genres'] = data['genres'].map(lambda x: ast.literal_eval(x))\ndata['cast'] = data['cast'].map(lambda x: ast.literal_eval(x))\ndata['crew'] = data['crew'].map(lambda x: ast.literal_eval(x))","execution_count":98,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def make_genresList(x):\n    gen = []\n    st = \" \"\n    for i in x:\n        if i.get('name') == 'Science Fiction':\n            scifi = 'Sci-Fi'\n            gen.append(scifi)\n        else:\n            gen.append(i.get('name'))\n    if gen == []:\n        return np.NaN\n    else:\n        return (st.join(gen))","execution_count":99,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['genres_list'] = data['genres'].map(lambda x: make_genresList(x))","execution_count":100,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['genres_list']","execution_count":101,"outputs":[{"output_type":"execute_result","execution_count":101,"data":{"text/plain":"0         Animation Comedy Family\n1        Adventure Fantasy Family\n2                  Romance Comedy\n3            Comedy Drama Romance\n4                          Comedy\n                   ...           \n45440        Drama Action Romance\n45441                       Drama\n45442       Action Drama Thriller\n45443                         NaN\n45444                         NaN\nName: genres_list, Length: 45445, dtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor1(x):\n    casts = []\n    for i in x:\n        casts.append(i.get('name'))\n    if casts == []:\n        return np.NaN\n    else:\n        return (casts[0])","execution_count":102,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['actor_1_name'] = data['cast'].map(lambda x: get_actor1(x))","execution_count":103,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor2(x):\n    casts = []\n    for i in x:\n        casts.append(i.get('name'))\n    if casts == [] or len(casts)<=1:\n        return np.NaN\n    else:\n        return (casts[1])","execution_count":104,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['actor_2_name'] = data['cast'].map(lambda x: get_actor2(x))","execution_count":105,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['actor_2_name']","execution_count":106,"outputs":[{"output_type":"execute_result","execution_count":106,"data":{"text/plain":"0                Tim Allen\n1            Jonathan Hyde\n2              Jack Lemmon\n3           Angela Bassett\n4             Diane Keaton\n               ...        \n45440          Uma Thurman\n45441          Perry Dizon\n45442         Adam Baldwin\n45443    Nathalie Lissenko\n45444                  NaN\nName: actor_2_name, Length: 45445, dtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor3(x):\n    casts = []\n    for i in x:\n        casts.append(i.get('name'))\n    if casts == [] or len(casts)<=2:\n        return np.NaN\n    else:\n        return (casts[2])","execution_count":107,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['actor_3_name'] = data['cast'].map(lambda x: get_actor3(x))","execution_count":108,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['actor_3_name']","execution_count":109,"outputs":[{"output_type":"execute_result","execution_count":109,"data":{"text/plain":"0            Don Rickles\n1          Kirsten Dunst\n2            Ann-Margret\n3         Loretta Devine\n4           Martin Short\n              ...       \n45440    David Morrissey\n45441      Hazel Orencio\n45442      Julie du Page\n45443       Pavel Pavlov\n45444                NaN\nName: actor_3_name, Length: 45445, dtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_directors(x):\n    dt = []\n    st = \" \"\n    for i in x:\n        if i.get('job') == 'Director':\n            dt.append(i.get('name'))\n    if dt == []:\n        return np.NaN\n    else:\n        return (st.join(dt))","execution_count":110,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['director_name'] = data['crew'].map(lambda x: get_directors(x))","execution_count":111,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['director_name']","execution_count":112,"outputs":[{"output_type":"execute_result","execution_count":112,"data":{"text/plain":"0           John Lasseter\n1            Joe Johnston\n2           Howard Deutch\n3         Forest Whitaker\n4           Charles Shyer\n               ...       \n45440          John Irvin\n45441            Lav Diaz\n45442      Mark L. Lester\n45443    Yakov Protazanov\n45444       Daisy Asquith\nName: director_name, Length: 45445, dtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie = data.loc[:,['director_name','actor_1_name','actor_2_name','actor_3_name','genres_list','title']]","execution_count":113,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie","execution_count":114,"outputs":[{"output_type":"execute_result","execution_count":114,"data":{"text/plain":"          director_name      actor_1_name       actor_2_name     actor_3_name  \\\n0         John Lasseter         Tom Hanks          Tim Allen      Don Rickles   \n1          Joe Johnston    Robin Williams      Jonathan Hyde    Kirsten Dunst   \n2         Howard Deutch    Walter Matthau        Jack Lemmon      Ann-Margret   \n3       Forest Whitaker   Whitney Houston     Angela Bassett   Loretta Devine   \n4         Charles Shyer      Steve Martin       Diane Keaton     Martin Short   \n...                 ...               ...                ...              ...   \n45440        John Irvin    Patrick Bergin        Uma Thurman  David Morrissey   \n45441          Lav Diaz      Angel Aquino        Perry Dizon    Hazel Orencio   \n45442    Mark L. Lester     Erika Eleniak       Adam Baldwin    Julie du Page   \n45443  Yakov Protazanov  Iwan Mosschuchin  Nathalie Lissenko     Pavel Pavlov   \n45444     Daisy Asquith               NaN                NaN              NaN   \n\n                    genres_list                        title  \n0       Animation Comedy Family                    Toy Story  \n1      Adventure Fantasy Family                      Jumanji  \n2                Romance Comedy             Grumpier Old Men  \n3          Comedy Drama Romance            Waiting to Exhale  \n4                        Comedy  Father of the Bride Part II  \n...                         ...                          ...  \n45440      Drama Action Romance                   Robin Hood  \n45441                     Drama          Century of Birthing  \n45442     Action Drama Thriller                     Betrayal  \n45443                       NaN             Satan Triumphant  \n45444                       NaN                     Queerama  \n\n[45445 rows x 6 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres_list</th>\n      <th>title</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>Toy Story</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>Jumanji</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>Grumpier Old Men</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>Waiting to Exhale</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>Father of the Bride Part II</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45440</th>\n      <td>John Irvin</td>\n      <td>Patrick Bergin</td>\n      <td>Uma Thurman</td>\n      <td>David Morrissey</td>\n      <td>Drama Action Romance</td>\n      <td>Robin Hood</td>\n    </tr>\n    <tr>\n      <th>45441</th>\n      <td>Lav Diaz</td>\n      <td>Angel Aquino</td>\n      <td>Perry Dizon</td>\n      <td>Hazel Orencio</td>\n      <td>Drama</td>\n      <td>Century of Birthing</td>\n    </tr>\n    <tr>\n      <th>45442</th>\n      <td>Mark L. Lester</td>\n      <td>Erika Eleniak</td>\n      <td>Adam Baldwin</td>\n      <td>Julie du Page</td>\n      <td>Action Drama Thriller</td>\n      <td>Betrayal</td>\n    </tr>\n    <tr>\n      <th>45443</th>\n      <td>Yakov Protazanov</td>\n      <td>Iwan Mosschuchin</td>\n      <td>Nathalie Lissenko</td>\n      <td>Pavel Pavlov</td>\n      <td>NaN</td>\n      <td>Satan Triumphant</td>\n    </tr>\n    <tr>\n      <th>45444</th>\n      <td>Daisy Asquith</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Queerama</td>\n    </tr>\n  </tbody>\n</table>\n<p>45445 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie.isna().sum()","execution_count":115,"outputs":[{"output_type":"execute_result","execution_count":115,"data":{"text/plain":"director_name     835\nactor_1_name     2354\nactor_2_name     3683\nactor_3_name     4593\ngenres_list      2384\ntitle               0\ndtype: int64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie = movie.dropna(how='any')","execution_count":116,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie.isna().sum()","execution_count":117,"outputs":[{"output_type":"execute_result","execution_count":117,"data":{"text/plain":"director_name    0\nactor_1_name     0\nactor_2_name     0\nactor_3_name     0\ngenres_list      0\ntitle            0\ndtype: int64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie = movie.rename(columns={'genres_list':'genres'})\nmovie = movie.rename(columns={'title':'movie_title'})","execution_count":118,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie['movie_title'] = movie['movie_title'].str.lower()","execution_count":119,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie['comb'] = movie['actor_1_name'] + ' ' + movie['actor_2_name'] + ' '+ movie['actor_3_name'] + ' '+ movie['director_name'] +' ' + movie['genres']","execution_count":120,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie","execution_count":121,"outputs":[{"output_type":"execute_result","execution_count":121,"data":{"text/plain":"         director_name     actor_1_name    actor_2_name     actor_3_name  \\\n0        John Lasseter        Tom Hanks       Tim Allen      Don Rickles   \n1         Joe Johnston   Robin Williams   Jonathan Hyde    Kirsten Dunst   \n2        Howard Deutch   Walter Matthau     Jack Lemmon      Ann-Margret   \n3      Forest Whitaker  Whitney Houston  Angela Bassett   Loretta Devine   \n4        Charles Shyer     Steve Martin    Diane Keaton     Martin Short   \n...                ...              ...             ...              ...   \n45438         Ben Rock       Monty Bane     Lucy Butler    David Grammer   \n45439    Aaron Osborne       Lisa Boyle       Kena Land    Zaneta Polard   \n45440       John Irvin   Patrick Bergin     Uma Thurman  David Morrissey   \n45441         Lav Diaz     Angel Aquino     Perry Dizon    Hazel Orencio   \n45442   Mark L. Lester    Erika Eleniak    Adam Baldwin    Julie du Page   \n\n                         genres                  movie_title  \\\n0       Animation Comedy Family                    toy story   \n1      Adventure Fantasy Family                      jumanji   \n2                Romance Comedy             grumpier old men   \n3          Comedy Drama Romance            waiting to exhale   \n4                        Comedy  father of the bride part ii   \n...                         ...                          ...   \n45438                    Horror          the burkittsville 7   \n45439                    Sci-Fi              caged heat 3000   \n45440      Drama Action Romance                   robin hood   \n45441                     Drama          century of birthing   \n45442     Action Drama Thriller                     betrayal   \n\n                                                                             comb  \n0           Tom Hanks Tim Allen Don Rickles John Lasseter Animation Comedy Family  \n1      Robin Williams Jonathan Hyde Kirsten Dunst Joe Johnston Adventure Fanta...  \n2             Walter Matthau Jack Lemmon Ann-Margret Howard Deutch Romance Comedy  \n3      Whitney Houston Angela Bassett Loretta Devine Forest Whitaker Comedy Dr...  \n4                     Steve Martin Diane Keaton Martin Short Charles Shyer Comedy  \n...                                                                           ...  \n45438                        Monty Bane Lucy Butler David Grammer Ben Rock Horror  \n45439                     Lisa Boyle Kena Land Zaneta Polard Aaron Osborne Sci-Fi  \n45440  Patrick Bergin Uma Thurman David Morrissey John Irvin Drama Action Romance  \n45441                       Angel Aquino Perry Dizon Hazel Orencio Lav Diaz Drama  \n45442  Erika Eleniak Adam Baldwin Julie du Page Mark L. Lester Action Drama Th...  \n\n[39201 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>toy story</td>\n      <td>Tom Hanks Tim Allen Don Rickles John Lasseter Animation Comedy Family</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>jumanji</td>\n      <td>Robin Williams Jonathan Hyde Kirsten Dunst Joe Johnston Adventure Fanta...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>grumpier old men</td>\n      <td>Walter Matthau Jack Lemmon Ann-Margret Howard Deutch Romance Comedy</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>waiting to exhale</td>\n      <td>Whitney Houston Angela Bassett Loretta Devine Forest Whitaker Comedy Dr...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>father of the bride part ii</td>\n      <td>Steve Martin Diane Keaton Martin Short Charles Shyer Comedy</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45438</th>\n      <td>Ben Rock</td>\n      <td>Monty Bane</td>\n      <td>Lucy Butler</td>\n      <td>David Grammer</td>\n      <td>Horror</td>\n      <td>the burkittsville 7</td>\n      <td>Monty Bane Lucy Butler David Grammer Ben Rock Horror</td>\n    </tr>\n    <tr>\n      <th>45439</th>\n      <td>Aaron Osborne</td>\n      <td>Lisa Boyle</td>\n      <td>Kena Land</td>\n      <td>Zaneta Polard</td>\n      <td>Sci-Fi</td>\n      <td>caged heat 3000</td>\n      <td>Lisa Boyle Kena Land Zaneta Polard Aaron Osborne Sci-Fi</td>\n    </tr>\n    <tr>\n      <th>45440</th>\n      <td>John Irvin</td>\n      <td>Patrick Bergin</td>\n      <td>Uma Thurman</td>\n      <td>David Morrissey</td>\n      <td>Drama Action Romance</td>\n      <td>robin hood</td>\n      <td>Patrick Bergin Uma Thurman David Morrissey John Irvin Drama Action Romance</td>\n    </tr>\n    <tr>\n      <th>45441</th>\n      <td>Lav Diaz</td>\n      <td>Angel Aquino</td>\n      <td>Perry Dizon</td>\n      <td>Hazel Orencio</td>\n      <td>Drama</td>\n      <td>century of birthing</td>\n      <td>Angel Aquino Perry Dizon Hazel Orencio Lav Diaz Drama</td>\n    </tr>\n    <tr>\n      <th>45442</th>\n      <td>Mark L. Lester</td>\n      <td>Erika Eleniak</td>\n      <td>Adam Baldwin</td>\n      <td>Julie du Page</td>\n      <td>Action Drama Thriller</td>\n      <td>betrayal</td>\n      <td>Erika Eleniak Adam Baldwin Julie du Page Mark L. Lester Action Drama Th...</td>\n    </tr>\n  </tbody>\n</table>\n<p>39201 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie.drop_duplicates(subset =\"movie_title\", keep = 'last', inplace = True)","execution_count":122,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie","execution_count":123,"outputs":[{"output_type":"execute_result","execution_count":123,"data":{"text/plain":"         director_name     actor_1_name    actor_2_name     actor_3_name  \\\n0        John Lasseter        Tom Hanks       Tim Allen      Don Rickles   \n1         Joe Johnston   Robin Williams   Jonathan Hyde    Kirsten Dunst   \n2        Howard Deutch   Walter Matthau     Jack Lemmon      Ann-Margret   \n3      Forest Whitaker  Whitney Houston  Angela Bassett   Loretta Devine   \n4        Charles Shyer     Steve Martin    Diane Keaton     Martin Short   \n...                ...              ...             ...              ...   \n45438         Ben Rock       Monty Bane     Lucy Butler    David Grammer   \n45439    Aaron Osborne       Lisa Boyle       Kena Land    Zaneta Polard   \n45440       John Irvin   Patrick Bergin     Uma Thurman  David Morrissey   \n45441         Lav Diaz     Angel Aquino     Perry Dizon    Hazel Orencio   \n45442   Mark L. Lester    Erika Eleniak    Adam Baldwin    Julie du Page   \n\n                         genres                  movie_title  \\\n0       Animation Comedy Family                    toy story   \n1      Adventure Fantasy Family                      jumanji   \n2                Romance Comedy             grumpier old men   \n3          Comedy Drama Romance            waiting to exhale   \n4                        Comedy  father of the bride part ii   \n...                         ...                          ...   \n45438                    Horror          the burkittsville 7   \n45439                    Sci-Fi              caged heat 3000   \n45440      Drama Action Romance                   robin hood   \n45441                     Drama          century of birthing   \n45442     Action Drama Thriller                     betrayal   \n\n                                                                             comb  \n0           Tom Hanks Tim Allen Don Rickles John Lasseter Animation Comedy Family  \n1      Robin Williams Jonathan Hyde Kirsten Dunst Joe Johnston Adventure Fanta...  \n2             Walter Matthau Jack Lemmon Ann-Margret Howard Deutch Romance Comedy  \n3      Whitney Houston Angela Bassett Loretta Devine Forest Whitaker Comedy Dr...  \n4                     Steve Martin Diane Keaton Martin Short Charles Shyer Comedy  \n...                                                                           ...  \n45438                        Monty Bane Lucy Butler David Grammer Ben Rock Horror  \n45439                     Lisa Boyle Kena Land Zaneta Polard Aaron Osborne Sci-Fi  \n45440  Patrick Bergin Uma Thurman David Morrissey John Irvin Drama Action Romance  \n45441                       Angel Aquino Perry Dizon Hazel Orencio Lav Diaz Drama  \n45442  Erika Eleniak Adam Baldwin Julie du Page Mark L. Lester Action Drama Th...  \n\n[36341 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>toy story</td>\n      <td>Tom Hanks Tim Allen Don Rickles John Lasseter Animation Comedy Family</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>jumanji</td>\n      <td>Robin Williams Jonathan Hyde Kirsten Dunst Joe Johnston Adventure Fanta...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>grumpier old men</td>\n      <td>Walter Matthau Jack Lemmon Ann-Margret Howard Deutch Romance Comedy</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>waiting to exhale</td>\n      <td>Whitney Houston Angela Bassett Loretta Devine Forest Whitaker Comedy Dr...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>father of the bride part ii</td>\n      <td>Steve Martin Diane Keaton Martin Short Charles Shyer Comedy</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45438</th>\n      <td>Ben Rock</td>\n      <td>Monty Bane</td>\n      <td>Lucy Butler</td>\n      <td>David Grammer</td>\n      <td>Horror</td>\n      <td>the burkittsville 7</td>\n      <td>Monty Bane Lucy Butler David Grammer Ben Rock Horror</td>\n    </tr>\n    <tr>\n      <th>45439</th>\n      <td>Aaron Osborne</td>\n      <td>Lisa Boyle</td>\n      <td>Kena Land</td>\n      <td>Zaneta Polard</td>\n      <td>Sci-Fi</td>\n      <td>caged heat 3000</td>\n      <td>Lisa Boyle Kena Land Zaneta Polard Aaron Osborne Sci-Fi</td>\n    </tr>\n    <tr>\n      <th>45440</th>\n      <td>John Irvin</td>\n      <td>Patrick Bergin</td>\n      <td>Uma Thurman</td>\n      <td>David Morrissey</td>\n      <td>Drama Action Romance</td>\n      <td>robin hood</td>\n      <td>Patrick Bergin Uma Thurman David Morrissey John Irvin Drama Action Romance</td>\n    </tr>\n    <tr>\n      <th>45441</th>\n      <td>Lav Diaz</td>\n      <td>Angel Aquino</td>\n      <td>Perry Dizon</td>\n      <td>Hazel Orencio</td>\n      <td>Drama</td>\n      <td>century of birthing</td>\n      <td>Angel Aquino Perry Dizon Hazel Orencio Lav Diaz Drama</td>\n    </tr>\n    <tr>\n      <th>45442</th>\n      <td>Mark L. Lester</td>\n      <td>Erika Eleniak</td>\n      <td>Adam Baldwin</td>\n      <td>Julie du Page</td>\n      <td>Action Drama Thriller</td>\n      <td>betrayal</td>\n      <td>Erika Eleniak Adam Baldwin Julie du Page Mark L. Lester Action Drama Th...</td>\n    </tr>\n  </tbody>\n</table>\n<p>36341 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"movie.to_csv('movie.csv',index=False)","execution_count":124,"outputs":[]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}


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/.ipynb_checkpoints/preprocessing 3.ipynb:
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1 | {"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np","execution_count":2,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Extracting features of 2018 movies from Wikipedia"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"link = \"https://en.wikipedia.org/wiki/List_of_American_films_of_2018\"\ndf1 = pd.read_html(link, header=0)[2]\ndf2 = pd.read_html(link, header=0)[3]\ndf3 = pd.read_html(link, header=0)[4]\ndf4 = pd.read_html(link, header=0)[5]","execution_count":3,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df = df1.append(df2.append(df3.append(df4,ignore_index=True),ignore_index=True),ignore_index=True)","execution_count":4,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df","execution_count":5,"outputs":[{"output_type":"execute_result","execution_count":5,"data":{"text/plain":"      Opening  Opening.1                       Title  \\\n0     JANUARY          5     Insidious: The Last Key   \n1     JANUARY          5            The Strange Ones   \n2     JANUARY          5                    Stratton   \n3     JANUARY         10               Sweet Country   \n4     JANUARY         12                The Commuter   \n..        ...        ...                         ...   \n263  DECEMBER         25             Holmes & Watson   \n264  DECEMBER         25                        Vice   \n265  DECEMBER         25         On the Basis of Sex   \n266  DECEMBER         25                   Destroyer   \n267  DECEMBER         28  Black Mirror: Bandersnatch   \n\n                                    Production company  \\\n0    Universal Pictures / Blumhouse Productions / S...   \n1                               Vertical Entertainment   \n2                                    Momentum Pictures   \n3                                 Samuel Goldwyn Films   \n4        Lionsgate / StudioCanal / The Picture Company   \n..                                                 ...   \n263       Columbia Pictures / Gary Sanchez Productions   \n264          Annapurna Pictures / Plan B Entertainment   \n265                                     Focus Features   \n266                                 Annapurna Pictures   \n267                                            Netflix   \n\n                                         Cast and crew   Ref.  \n0    Adam Robitel (director); Leigh Whannell (scree...    [2]  \n1    Lauren Wolkstein (director); Christopher Radcl...    [3]  \n2    Simon West (director); Duncan Falconer, Warren...    [4]  \n3    Warwick Thornton (director); David Tranter, St...    [5]  \n4    Jaume Collet-Serra (director); Byron Willinger...    [6]  \n..                                                 ...    ...  \n263  Etan Cohen (director/screenplay); Will Ferrell...  [162]  \n264  Adam McKay (director/screenplay); Christian Ba...  [136]  \n265  Mimi Leder (director); Daniel Stiepleman (scre...  [223]  \n266  Karyn Kusama (director); Phil Hay, Matt Manfre...  [256]  \n267  David Slade (director); Charlie Brooker (scree...  [257]  \n\n[268 rows x 6 columns]","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>Opening</th>\n      <th>Opening.1</th>\n      <th>Title</th>\n      <th>Production company</th>\n      <th>Cast and crew</th>\n      <th>Ref.</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JANUARY</td>\n      <td>5</td>\n      <td>Insidious: The Last Key</td>\n      <td>Universal Pictures / Blumhouse Productions / S...</td>\n      <td>Adam Robitel (director); Leigh Whannell (scree...</td>\n      <td>[2]</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JANUARY</td>\n      <td>5</td>\n      <td>The Strange Ones</td>\n      <td>Vertical Entertainment</td>\n      <td>Lauren Wolkstein (director); Christopher Radcl...</td>\n      <td>[3]</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>JANUARY</td>\n      <td>5</td>\n      <td>Stratton</td>\n      <td>Momentum Pictures</td>\n      <td>Simon West (director); Duncan Falconer, Warren...</td>\n      <td>[4]</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JANUARY</td>\n      <td>10</td>\n      <td>Sweet Country</td>\n      <td>Samuel Goldwyn Films</td>\n      <td>Warwick Thornton (director); David Tranter, St...</td>\n      <td>[5]</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>JANUARY</td>\n      <td>12</td>\n      <td>The Commuter</td>\n      <td>Lionsgate / StudioCanal / The Picture Company</td>\n      <td>Jaume Collet-Serra (director); Byron Willinger...</td>\n      <td>[6]</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>263</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Holmes &amp; Watson</td>\n      <td>Columbia Pictures / Gary Sanchez Productions</td>\n      <td>Etan Cohen (director/screenplay); Will Ferrell...</td>\n      <td>[162]</td>\n    </tr>\n    <tr>\n      <th>264</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Vice</td>\n      <td>Annapurna Pictures / Plan B Entertainment</td>\n      <td>Adam McKay (director/screenplay); Christian Ba...</td>\n      <td>[136]</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>On the Basis of Sex</td>\n      <td>Focus Features</td>\n      <td>Mimi Leder (director); Daniel Stiepleman (scre...</td>\n      <td>[223]</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Destroyer</td>\n      <td>Annapurna Pictures</td>\n      <td>Karyn Kusama (director); Phil Hay, Matt Manfre...</td>\n      <td>[256]</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>DECEMBER</td>\n      <td>28</td>\n      <td>Black Mirror: Bandersnatch</td>\n      <td>Netflix</td>\n      <td>David Slade (director); Charlie Brooker (scree...</td>\n      <td>[257]</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"!pip install tmdbv3api","execution_count":6,"outputs":[{"output_type":"stream","text":"Collecting tmdbv3api\n  Downloading tmdbv3api-1.6.1-py2.py3-none-any.whl (13 kB)\nRequirement already satisfied: requests in /opt/conda/lib/python3.7/site-packages (from tmdbv3api) (2.23.0)\nRequirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (2.9)\nRequirement already satisfied: chardet<4,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (3.0.4)\nRequirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (1.24.3)\nRequirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (2020.6.20)\nInstalling collected packages: tmdbv3api\nSuccessfully installed tmdbv3api-1.6.1\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tmdbv3api import TMDb\nimport json\nimport requests\ntmdb = TMDb()\ntmdb.api_key = 'YOUR_API_KEY'","execution_count":7,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tmdbv3api import Movie\ntmdb_movie = Movie()\ndef get_genre(x):\n    genres = []\n    result = tmdb_movie.search(x)\n    movie_id = result[0].id\n    response = requests.get('https://api.themoviedb.org/3/movie/{}?api_key={}'.format(movie_id,tmdb.api_key))\n    data_json = response.json()\n    if data_json['genres']:\n        genre_str = \" \" \n        for i in range(0,len(data_json['genres'])):\n            genres.append(data_json['genres'][i]['name'])\n        return genre_str.join(genres)\n    else:\n        np.NaN","execution_count":8,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df['genres'] = df['Title'].map(lambda x: get_genre(str(x)))","execution_count":9,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df","execution_count":10,"outputs":[{"output_type":"execute_result","execution_count":10,"data":{"text/plain":"      Opening  Opening.1                       Title  \\\n0     JANUARY          5     Insidious: The Last Key   \n1     JANUARY          5            The Strange Ones   \n2     JANUARY          5                    Stratton   \n3     JANUARY         10               Sweet Country   \n4     JANUARY         12                The Commuter   \n..        ...        ...                         ...   \n263  DECEMBER         25             Holmes & Watson   \n264  DECEMBER         25                        Vice   \n265  DECEMBER         25         On the Basis of Sex   \n266  DECEMBER         25                   Destroyer   \n267  DECEMBER         28  Black Mirror: Bandersnatch   \n\n                                    Production company  \\\n0    Universal Pictures / Blumhouse Productions / S...   \n1                               Vertical Entertainment   \n2                                    Momentum Pictures   \n3                                 Samuel Goldwyn Films   \n4        Lionsgate / StudioCanal / The Picture Company   \n..                                                 ...   \n263       Columbia Pictures / Gary Sanchez Productions   \n264          Annapurna Pictures / Plan B Entertainment   \n265                                     Focus Features   \n266                                 Annapurna Pictures   \n267                                            Netflix   \n\n                                         Cast and crew   Ref.  \\\n0    Adam Robitel (director); Leigh Whannell (scree...    [2]   \n1    Lauren Wolkstein (director); Christopher Radcl...    [3]   \n2    Simon West (director); Duncan Falconer, Warren...    [4]   \n3    Warwick Thornton (director); David Tranter, St...    [5]   \n4    Jaume Collet-Serra (director); Byron Willinger...    [6]   \n..                                                 ...    ...   \n263  Etan Cohen (director/screenplay); Will Ferrell...  [162]   \n264  Adam McKay (director/screenplay); Christian Ba...  [136]   \n265  Mimi Leder (director); Daniel Stiepleman (scre...  [223]   \n266  Karyn Kusama (director); Phil Hay, Matt Manfre...  [256]   \n267  David Slade (director); Charlie Brooker (scree...  [257]   \n\n                                              genres  \n0                            Mystery Horror Thriller  \n1                                     Thriller Drama  \n2                                    Action Thriller  \n3                              Drama History Western  \n4                                    Action Thriller  \n..                                               ...  \n263                   Mystery Adventure Comedy Crime  \n264        Thriller Science Fiction Action Adventure  \n265                                    Drama History  \n266                      Thriller Crime Drama Action  \n267  Science Fiction Mystery Drama Thriller TV Movie  \n\n[268 rows x 7 columns]","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>Opening</th>\n      <th>Opening.1</th>\n      <th>Title</th>\n      <th>Production company</th>\n      <th>Cast and crew</th>\n      <th>Ref.</th>\n      <th>genres</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JANUARY</td>\n      <td>5</td>\n      <td>Insidious: The Last Key</td>\n      <td>Universal Pictures / Blumhouse Productions / S...</td>\n      <td>Adam Robitel (director); Leigh Whannell (scree...</td>\n      <td>[2]</td>\n      <td>Mystery Horror Thriller</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JANUARY</td>\n      <td>5</td>\n      <td>The Strange Ones</td>\n      <td>Vertical Entertainment</td>\n      <td>Lauren Wolkstein (director); Christopher Radcl...</td>\n      <td>[3]</td>\n      <td>Thriller Drama</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>JANUARY</td>\n      <td>5</td>\n      <td>Stratton</td>\n      <td>Momentum Pictures</td>\n      <td>Simon West (director); Duncan Falconer, Warren...</td>\n      <td>[4]</td>\n      <td>Action Thriller</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JANUARY</td>\n      <td>10</td>\n      <td>Sweet Country</td>\n      <td>Samuel Goldwyn Films</td>\n      <td>Warwick Thornton (director); David Tranter, St...</td>\n      <td>[5]</td>\n      <td>Drama History Western</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>JANUARY</td>\n      <td>12</td>\n      <td>The Commuter</td>\n      <td>Lionsgate / StudioCanal / The Picture Company</td>\n      <td>Jaume Collet-Serra (director); Byron Willinger...</td>\n      <td>[6]</td>\n      <td>Action Thriller</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>263</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Holmes &amp; Watson</td>\n      <td>Columbia Pictures / Gary Sanchez Productions</td>\n      <td>Etan Cohen (director/screenplay); Will Ferrell...</td>\n      <td>[162]</td>\n      <td>Mystery Adventure Comedy Crime</td>\n    </tr>\n    <tr>\n      <th>264</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Vice</td>\n      <td>Annapurna Pictures / Plan B Entertainment</td>\n      <td>Adam McKay (director/screenplay); Christian Ba...</td>\n      <td>[136]</td>\n      <td>Thriller Science Fiction Action Adventure</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>On the Basis of Sex</td>\n      <td>Focus Features</td>\n      <td>Mimi Leder (director); Daniel Stiepleman (scre...</td>\n      <td>[223]</td>\n      <td>Drama History</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Destroyer</td>\n      <td>Annapurna Pictures</td>\n      <td>Karyn Kusama (director); Phil Hay, Matt Manfre...</td>\n      <td>[256]</td>\n      <td>Thriller Crime Drama Action</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>DECEMBER</td>\n      <td>28</td>\n      <td>Black Mirror: Bandersnatch</td>\n      <td>Netflix</td>\n      <td>David Slade (director); Charlie Brooker (scree...</td>\n      <td>[257]</td>\n      <td>Science Fiction Mystery Drama Thriller TV Movie</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018 = df[['Title','Cast and crew','genres']]","execution_count":11,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018","execution_count":12,"outputs":[{"output_type":"execute_result","execution_count":12,"data":{"text/plain":"                          Title  \\\n0       Insidious: The Last Key   \n1              The Strange Ones   \n2                      Stratton   \n3                 Sweet Country   \n4                  The Commuter   \n..                          ...   \n263             Holmes & Watson   \n264                        Vice   \n265         On the Basis of Sex   \n266                   Destroyer   \n267  Black Mirror: Bandersnatch   \n\n                                         Cast and crew  \\\n0    Adam Robitel (director); Leigh Whannell (scree...   \n1    Lauren Wolkstein (director); Christopher Radcl...   \n2    Simon West (director); Duncan Falconer, Warren...   \n3    Warwick Thornton (director); David Tranter, St...   \n4    Jaume Collet-Serra (director); Byron Willinger...   \n..                                                 ...   \n263  Etan Cohen (director/screenplay); Will Ferrell...   \n264  Adam McKay (director/screenplay); Christian Ba...   \n265  Mimi Leder (director); Daniel Stiepleman (scre...   \n266  Karyn Kusama (director); Phil Hay, Matt Manfre...   \n267  David Slade (director); Charlie Brooker (scree...   \n\n                                              genres  \n0                            Mystery Horror Thriller  \n1                                     Thriller Drama  \n2                                    Action Thriller  \n3                              Drama History Western  \n4                                    Action Thriller  \n..                                               ...  \n263                   Mystery Adventure Comedy Crime  \n264        Thriller Science Fiction Action Adventure  \n265                                    Drama History  \n266                      Thriller Crime Drama Action  \n267  Science Fiction Mystery Drama Thriller TV Movie  \n\n[268 rows x 3 columns]","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>Title</th>\n      <th>Cast and crew</th>\n      <th>genres</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Insidious: The Last Key</td>\n      <td>Adam Robitel (director); Leigh Whannell (scree...</td>\n      <td>Mystery Horror Thriller</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>The Strange Ones</td>\n      <td>Lauren Wolkstein (director); Christopher Radcl...</td>\n      <td>Thriller Drama</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Stratton</td>\n      <td>Simon West (director); Duncan Falconer, Warren...</td>\n      <td>Action Thriller</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Sweet Country</td>\n      <td>Warwick Thornton (director); David Tranter, St...</td>\n      <td>Drama History Western</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>The Commuter</td>\n      <td>Jaume Collet-Serra (director); Byron Willinger...</td>\n      <td>Action Thriller</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>263</th>\n      <td>Holmes &amp; Watson</td>\n      <td>Etan Cohen (director/screenplay); Will Ferrell...</td>\n      <td>Mystery Adventure Comedy Crime</td>\n    </tr>\n    <tr>\n      <th>264</th>\n      <td>Vice</td>\n      <td>Adam McKay (director/screenplay); Christian Ba...</td>\n      <td>Thriller Science Fiction Action Adventure</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>On the Basis of Sex</td>\n      <td>Mimi Leder (director); Daniel Stiepleman (scre...</td>\n      <td>Drama History</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>Destroyer</td>\n      <td>Karyn Kusama (director); Phil Hay, Matt Manfre...</td>\n      <td>Thriller Crime Drama Action</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>Black Mirror: Bandersnatch</td>\n      <td>David Slade (director); Charlie Brooker (scree...</td>\n      <td>Science Fiction Mystery Drama Thriller TV Movie</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 3 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_director(x):\n    if \" (director)\" in x:\n        return x.split(\" (director)\")[0]\n    elif \" (directors)\" in x:\n        return x.split(\" (directors)\")[0]\n    else:\n        return x.split(\" (director/screenplay)\")[0]","execution_count":13,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018['director_name'] = df_2018['Cast and crew'].map(lambda x: get_director(x))","execution_count":14,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor1(x):\n    return ((x.split(\"screenplay); \")[-1]).split(\", \")[0])","execution_count":15,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018['actor_1_name'] = df_2018['Cast and crew'].map(lambda x: get_actor1(x))","execution_count":16,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor2(x):\n    if len((x.split(\"screenplay); \")[-1]).split(\", \")) < 2:\n        return np.NaN\n    else:\n        return ((x.split(\"screenplay); \")[-1]).split(\", \")[1])","execution_count":17,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018['actor_2_name'] = df_2018['Cast and crew'].map(lambda x: get_actor2(x))","execution_count":18,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor3(x):\n    if len((x.split(\"screenplay); \")[-1]).split(\", \")) < 3:\n        return np.NaN\n    else:\n        return ((x.split(\"screenplay); \")[-1]).split(\", \")[2])","execution_count":19,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018['actor_3_name'] = df_2018['Cast and crew'].map(lambda x: get_actor3(x))","execution_count":20,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2018","execution_count":21,"outputs":[{"output_type":"execute_result","execution_count":21,"data":{"text/plain":"                          Title  \\\n0       Insidious: The Last Key   \n1              The Strange Ones   \n2                      Stratton   \n3                 Sweet Country   \n4                  The Commuter   \n..                          ...   \n263             Holmes & Watson   \n264                        Vice   \n265         On the Basis of Sex   \n266                   Destroyer   \n267  Black Mirror: Bandersnatch   \n\n                                         Cast and crew  \\\n0    Adam Robitel (director); Leigh Whannell (scree...   \n1    Lauren Wolkstein (director); Christopher Radcl...   \n2    Simon West (director); Duncan Falconer, Warren...   \n3    Warwick Thornton (director); David Tranter, St...   \n4    Jaume Collet-Serra (director); Byron Willinger...   \n..                                                 ...   \n263  Etan Cohen (director/screenplay); Will Ferrell...   \n264  Adam McKay (director/screenplay); Christian Ba...   \n265  Mimi Leder (director); Daniel Stiepleman (scre...   \n266  Karyn Kusama (director); Phil Hay, Matt Manfre...   \n267  David Slade (director); Charlie Brooker (scree...   \n\n                                              genres       director_name  \\\n0                            Mystery Horror Thriller        Adam Robitel   \n1                                     Thriller Drama    Lauren Wolkstein   \n2                                    Action Thriller          Simon West   \n3                              Drama History Western    Warwick Thornton   \n4                                    Action Thriller  Jaume Collet-Serra   \n..                                               ...                 ...   \n263                   Mystery Adventure Comedy Crime          Etan Cohen   \n264        Thriller Science Fiction Action Adventure          Adam McKay   \n265                                    Drama History          Mimi Leder   \n266                      Thriller Crime Drama Action        Karyn Kusama   \n267  Science Fiction Mystery Drama Thriller TV Movie         David Slade   \n\n        actor_1_name            actor_2_name    actor_3_name  \n0          Lin Shaye           Angus Sampson  Leigh Whannell  \n1      Alex Pettyfer  James Freedson-Jackson   Emily Althaus  \n2     Dominic Cooper          Austin Stowell      Gemma Chan  \n3        Bryan Brown               Sam Neill             NaN  \n4        Liam Neeson            Vera Farmiga  Patrick Wilson  \n..               ...                     ...             ...  \n263     Will Ferrell          John C. Reilly    Rebecca Hall  \n264   Christian Bale               Amy Adams    Steve Carell  \n265   Felicity Jones            Armie Hammer  Justin Theroux  \n266    Nicole Kidman          Sebastian Stan    Toby Kebbell  \n267  Fionn Whitehead            Will Poulter   Asim Chaudhry  \n\n[268 rows x 7 columns]","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>Title</th>\n      <th>Cast and crew</th>\n      <th>genres</th>\n      <th>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Insidious: The Last Key</td>\n      <td>Adam Robitel (director); Leigh Whannell (scree...</td>\n      <td>Mystery Horror Thriller</td>\n      <td>Adam Robitel</td>\n      <td>Lin Shaye</td>\n      <td>Angus Sampson</td>\n      <td>Leigh Whannell</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>The Strange Ones</td>\n      <td>Lauren Wolkstein (director); Christopher Radcl...</td>\n      <td>Thriller Drama</td>\n      <td>Lauren Wolkstein</td>\n      <td>Alex Pettyfer</td>\n      <td>James Freedson-Jackson</td>\n      <td>Emily Althaus</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Stratton</td>\n      <td>Simon West (director); Duncan Falconer, Warren...</td>\n      <td>Action Thriller</td>\n      <td>Simon West</td>\n      <td>Dominic Cooper</td>\n      <td>Austin Stowell</td>\n      <td>Gemma Chan</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Sweet Country</td>\n      <td>Warwick Thornton (director); David Tranter, St...</td>\n      <td>Drama History Western</td>\n      <td>Warwick Thornton</td>\n      <td>Bryan Brown</td>\n      <td>Sam Neill</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>The Commuter</td>\n      <td>Jaume Collet-Serra (director); Byron Willinger...</td>\n      <td>Action Thriller</td>\n      <td>Jaume Collet-Serra</td>\n      <td>Liam Neeson</td>\n      <td>Vera Farmiga</td>\n      <td>Patrick Wilson</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>263</th>\n      <td>Holmes &amp; Watson</td>\n      <td>Etan Cohen (director/screenplay); Will Ferrell...</td>\n      <td>Mystery Adventure Comedy Crime</td>\n      <td>Etan Cohen</td>\n      <td>Will Ferrell</td>\n      <td>John C. Reilly</td>\n      <td>Rebecca Hall</td>\n    </tr>\n    <tr>\n      <th>264</th>\n      <td>Vice</td>\n      <td>Adam McKay (director/screenplay); Christian Ba...</td>\n      <td>Thriller Science Fiction Action Adventure</td>\n      <td>Adam McKay</td>\n      <td>Christian Bale</td>\n      <td>Amy Adams</td>\n      <td>Steve Carell</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>On the Basis of Sex</td>\n      <td>Mimi Leder (director); Daniel Stiepleman (scre...</td>\n      <td>Drama History</td>\n      <td>Mimi Leder</td>\n      <td>Felicity Jones</td>\n      <td>Armie Hammer</td>\n      <td>Justin Theroux</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>Destroyer</td>\n      <td>Karyn Kusama (director); Phil Hay, Matt Manfre...</td>\n      <td>Thriller Crime Drama Action</td>\n      <td>Karyn Kusama</td>\n      <td>Nicole Kidman</td>\n      <td>Sebastian Stan</td>\n      <td>Toby Kebbell</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>Black Mirror: Bandersnatch</td>\n      <td>David Slade (director); Charlie Brooker (scree...</td>\n      <td>Science Fiction Mystery Drama Thriller TV Movie</td>\n      <td>David Slade</td>\n      <td>Fionn Whitehead</td>\n      <td>Will Poulter</td>\n      <td>Asim Chaudhry</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"\ndf_2018 = df_2018.rename(columns={'Title':'movie_title'})","execution_count":22,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df18 = df_2018.loc[:,['director_name','actor_1_name','actor_2_name','actor_3_name','genres','movie_title']]","execution_count":23,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df18","execution_count":24,"outputs":[{"output_type":"execute_result","execution_count":24,"data":{"text/plain":"          director_name     actor_1_name            actor_2_name  \\\n0          Adam Robitel        Lin Shaye           Angus Sampson   \n1      Lauren Wolkstein    Alex Pettyfer  James Freedson-Jackson   \n2            Simon West   Dominic Cooper          Austin Stowell   \n3      Warwick Thornton      Bryan Brown               Sam Neill   \n4    Jaume Collet-Serra      Liam Neeson            Vera Farmiga   \n..                  ...              ...                     ...   \n263          Etan Cohen     Will Ferrell          John C. Reilly   \n264          Adam McKay   Christian Bale               Amy Adams   \n265          Mimi Leder   Felicity Jones            Armie Hammer   \n266        Karyn Kusama    Nicole Kidman          Sebastian Stan   \n267         David Slade  Fionn Whitehead            Will Poulter   \n\n       actor_3_name                                           genres  \\\n0    Leigh Whannell                          Mystery Horror Thriller   \n1     Emily Althaus                                   Thriller Drama   \n2        Gemma Chan                                  Action Thriller   \n3               NaN                            Drama History Western   \n4    Patrick Wilson                                  Action Thriller   \n..              ...                                              ...   \n263    Rebecca Hall                   Mystery Adventure Comedy Crime   \n264    Steve Carell        Thriller Science Fiction Action Adventure   \n265  Justin Theroux                                    Drama History   \n266    Toby Kebbell                      Thriller Crime Drama Action   \n267   Asim Chaudhry  Science Fiction Mystery Drama Thriller TV Movie   \n\n                    movie_title  \n0       Insidious: The Last Key  \n1              The Strange Ones  \n2                      Stratton  \n3                 Sweet Country  \n4                  The Commuter  \n..                          ...  \n263             Holmes & Watson  \n264                        Vice  \n265         On the Basis of Sex  \n266                   Destroyer  \n267  Black Mirror: Bandersnatch  \n\n[268 rows x 6 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Adam Robitel</td>\n      <td>Lin Shaye</td>\n      <td>Angus Sampson</td>\n      <td>Leigh Whannell</td>\n      <td>Mystery Horror Thriller</td>\n      <td>Insidious: The Last Key</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Lauren Wolkstein</td>\n      <td>Alex Pettyfer</td>\n      <td>James Freedson-Jackson</td>\n      <td>Emily Althaus</td>\n      <td>Thriller Drama</td>\n      <td>The Strange Ones</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Simon West</td>\n      <td>Dominic Cooper</td>\n      <td>Austin Stowell</td>\n      <td>Gemma Chan</td>\n      <td>Action Thriller</td>\n      <td>Stratton</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Warwick Thornton</td>\n      <td>Bryan Brown</td>\n      <td>Sam Neill</td>\n      <td>NaN</td>\n      <td>Drama History Western</td>\n      <td>Sweet Country</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Jaume Collet-Serra</td>\n      <td>Liam Neeson</td>\n      <td>Vera Farmiga</td>\n      <td>Patrick Wilson</td>\n      <td>Action Thriller</td>\n      <td>The Commuter</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>263</th>\n      <td>Etan Cohen</td>\n      <td>Will Ferrell</td>\n      <td>John C. Reilly</td>\n      <td>Rebecca Hall</td>\n      <td>Mystery Adventure Comedy Crime</td>\n      <td>Holmes &amp; Watson</td>\n    </tr>\n    <tr>\n      <th>264</th>\n      <td>Adam McKay</td>\n      <td>Christian Bale</td>\n      <td>Amy Adams</td>\n      <td>Steve Carell</td>\n      <td>Thriller Science Fiction Action Adventure</td>\n      <td>Vice</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>Mimi Leder</td>\n      <td>Felicity Jones</td>\n      <td>Armie Hammer</td>\n      <td>Justin Theroux</td>\n      <td>Drama History</td>\n      <td>On the Basis of Sex</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>Karyn Kusama</td>\n      <td>Nicole Kidman</td>\n      <td>Sebastian Stan</td>\n      <td>Toby Kebbell</td>\n      <td>Thriller Crime Drama Action</td>\n      <td>Destroyer</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>David Slade</td>\n      <td>Fionn Whitehead</td>\n      <td>Will Poulter</td>\n      <td>Asim Chaudhry</td>\n      <td>Science Fiction Mystery Drama Thriller TV Movie</td>\n      <td>Black Mirror: Bandersnatch</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df18['actor_2_name'] = new_df18['actor_2_name'].replace(np.nan, 'unknown')\nnew_df18['actor_3_name'] = new_df18['actor_3_name'].replace(np.nan, 'unknown')","execution_count":25,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df18['movie_title'] = new_df18['movie_title'].str.lower()","execution_count":26,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df18['comb'] = new_df18['actor_1_name'] + ' ' + new_df18['actor_2_name'] + ' '+ new_df18['actor_3_name'] + ' '+ new_df18['director_name'] +' ' + new_df18['genres']","execution_count":27,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df18","execution_count":28,"outputs":[{"output_type":"execute_result","execution_count":28,"data":{"text/plain":"          director_name     actor_1_name            actor_2_name  \\\n0          Adam Robitel        Lin Shaye           Angus Sampson   \n1      Lauren Wolkstein    Alex Pettyfer  James Freedson-Jackson   \n2            Simon West   Dominic Cooper          Austin Stowell   \n3      Warwick Thornton      Bryan Brown               Sam Neill   \n4    Jaume Collet-Serra      Liam Neeson            Vera Farmiga   \n..                  ...              ...                     ...   \n263          Etan Cohen     Will Ferrell          John C. Reilly   \n264          Adam McKay   Christian Bale               Amy Adams   \n265          Mimi Leder   Felicity Jones            Armie Hammer   \n266        Karyn Kusama    Nicole Kidman          Sebastian Stan   \n267         David Slade  Fionn Whitehead            Will Poulter   \n\n       actor_3_name                                           genres  \\\n0    Leigh Whannell                          Mystery Horror Thriller   \n1     Emily Althaus                                   Thriller Drama   \n2        Gemma Chan                                  Action Thriller   \n3           unknown                            Drama History Western   \n4    Patrick Wilson                                  Action Thriller   \n..              ...                                              ...   \n263    Rebecca Hall                   Mystery Adventure Comedy Crime   \n264    Steve Carell        Thriller Science Fiction Action Adventure   \n265  Justin Theroux                                    Drama History   \n266    Toby Kebbell                      Thriller Crime Drama Action   \n267   Asim Chaudhry  Science Fiction Mystery Drama Thriller TV Movie   \n\n                    movie_title  \\\n0       insidious: the last key   \n1              the strange ones   \n2                      stratton   \n3                 sweet country   \n4                  the commuter   \n..                          ...   \n263             holmes & watson   \n264                        vice   \n265         on the basis of sex   \n266                   destroyer   \n267  black mirror: bandersnatch   \n\n                                                  comb  \n0    Lin Shaye Angus Sampson Leigh Whannell Adam Ro...  \n1    Alex Pettyfer James Freedson-Jackson Emily Alt...  \n2    Dominic Cooper Austin Stowell Gemma Chan Simon...  \n3    Bryan Brown Sam Neill unknown Warwick Thornton...  \n4    Liam Neeson Vera Farmiga Patrick Wilson Jaume ...  \n..                                                 ...  \n263  Will Ferrell John C. Reilly Rebecca Hall Etan ...  \n264  Christian Bale Amy Adams Steve Carell Adam McK...  \n265  Felicity Jones Armie Hammer Justin Theroux Mim...  \n266  Nicole Kidman Sebastian Stan Toby Kebbell Kary...  \n267  Fionn Whitehead Will Poulter Asim Chaudhry Dav...  \n\n[268 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Adam Robitel</td>\n      <td>Lin Shaye</td>\n      <td>Angus Sampson</td>\n      <td>Leigh Whannell</td>\n      <td>Mystery Horror Thriller</td>\n      <td>insidious: the last key</td>\n      <td>Lin Shaye Angus Sampson Leigh Whannell Adam Ro...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Lauren Wolkstein</td>\n      <td>Alex Pettyfer</td>\n      <td>James Freedson-Jackson</td>\n      <td>Emily Althaus</td>\n      <td>Thriller Drama</td>\n      <td>the strange ones</td>\n      <td>Alex Pettyfer James Freedson-Jackson Emily Alt...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Simon West</td>\n      <td>Dominic Cooper</td>\n      <td>Austin Stowell</td>\n      <td>Gemma Chan</td>\n      <td>Action Thriller</td>\n      <td>stratton</td>\n      <td>Dominic Cooper Austin Stowell Gemma Chan Simon...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Warwick Thornton</td>\n      <td>Bryan Brown</td>\n      <td>Sam Neill</td>\n      <td>unknown</td>\n      <td>Drama History Western</td>\n      <td>sweet country</td>\n      <td>Bryan Brown Sam Neill unknown Warwick Thornton...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Jaume Collet-Serra</td>\n      <td>Liam Neeson</td>\n      <td>Vera Farmiga</td>\n      <td>Patrick Wilson</td>\n      <td>Action Thriller</td>\n      <td>the commuter</td>\n      <td>Liam Neeson Vera Farmiga Patrick Wilson Jaume ...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>263</th>\n      <td>Etan Cohen</td>\n      <td>Will Ferrell</td>\n      <td>John C. Reilly</td>\n      <td>Rebecca Hall</td>\n      <td>Mystery Adventure Comedy Crime</td>\n      <td>holmes &amp; watson</td>\n      <td>Will Ferrell John C. Reilly Rebecca Hall Etan ...</td>\n    </tr>\n    <tr>\n      <th>264</th>\n      <td>Adam McKay</td>\n      <td>Christian Bale</td>\n      <td>Amy Adams</td>\n      <td>Steve Carell</td>\n      <td>Thriller Science Fiction Action Adventure</td>\n      <td>vice</td>\n      <td>Christian Bale Amy Adams Steve Carell Adam McK...</td>\n    </tr>\n    <tr>\n      <th>265</th>\n      <td>Mimi Leder</td>\n      <td>Felicity Jones</td>\n      <td>Armie Hammer</td>\n      <td>Justin Theroux</td>\n      <td>Drama History</td>\n      <td>on the basis of sex</td>\n      <td>Felicity Jones Armie Hammer Justin Theroux Mim...</td>\n    </tr>\n    <tr>\n      <th>266</th>\n      <td>Karyn Kusama</td>\n      <td>Nicole Kidman</td>\n      <td>Sebastian Stan</td>\n      <td>Toby Kebbell</td>\n      <td>Thriller Crime Drama Action</td>\n      <td>destroyer</td>\n      <td>Nicole Kidman Sebastian Stan Toby Kebbell Kary...</td>\n    </tr>\n    <tr>\n      <th>267</th>\n      <td>David Slade</td>\n      <td>Fionn Whitehead</td>\n      <td>Will Poulter</td>\n      <td>Asim Chaudhry</td>\n      <td>Science Fiction Mystery Drama Thriller TV Movie</td>\n      <td>black mirror: bandersnatch</td>\n      <td>Fionn Whitehead Will Poulter Asim Chaudhry Dav...</td>\n    </tr>\n  </tbody>\n</table>\n<p>268 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Extracting features of 2019 movies from Wikipedia"},{"metadata":{"trusted":true},"cell_type":"code","source":"link = \"https://en.wikipedia.org/wiki/List_of_American_films_of_2019\"\ndf1 = pd.read_html(link, header=0)[3]\ndf2 = pd.read_html(link, header=0)[4]\ndf3 = pd.read_html(link, header=0)[5]\ndf4 = pd.read_html(link, header=0)[6]","execution_count":29,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df = df1.append(df2.append(df3.append(df4,ignore_index=True),ignore_index=True),ignore_index=True)","execution_count":30,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df","execution_count":31,"outputs":[{"output_type":"execute_result","execution_count":31,"data":{"text/plain":"      Opening  Opening.1             Title  \\\n0     JANUARY          4       Escape Room   \n1     JANUARY          4        Rust Creek   \n2     JANUARY          4  American Hangman   \n3     JANUARY         11  A Dog's Way Home   \n4     JANUARY         11        The Upside   \n..        ...        ...               ...   \n236  DECEMBER         25      Little Women   \n237  DECEMBER         25              1917   \n238  DECEMBER         25        Just Mercy   \n239  DECEMBER         27          Clemency   \n240  DECEMBER         27        Apparition   \n\n                                    Production company  \\\n0                                    Columbia Pictures   \n1                                            IFC Films   \n2                          Hangman Justice Productions   \n3                                    Columbia Pictures   \n4                                    STX Entertainment   \n..                                                 ...   \n236            Columbia Pictures / Regency Enterprises   \n237  Universal Pictures / DreamWorks Pictures / Ent...   \n238          Warner Bros. Pictures / Participant Media   \n239                                               Neon   \n240                                  Vertical Pictures   \n\n                                         Cast and crew   Ref.  \n0    Adam Robitel (director); Bragi F. Schut, Maria...    [2]  \n1    Jen McGowan (director); Julie Lipson (screenpl...    [3]  \n2    Wilson Coneybeare (director/screenplay); Donal...    [4]  \n3    Charles Martin Smith (director); W. Bruce Came...    [5]  \n4    Neil Burger (director); Jon Hartmere (screenpl...    [6]  \n..                                                 ...    ...  \n236  Greta Gerwig (director/screenplay); Saoirse Ro...  [222]  \n237  Sam Mendes (director/screenplay); Krysty Wilso...  [223]  \n238  Destin Daniel Cretton (director/screenplay), A...  [224]  \n239  Chinonye Chukwu (director/screenplay); Alfre W...  [225]  \n240  Waymon Boone (director/screenplay); Mena Suvar...  [226]  \n\n[241 rows x 6 columns]","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>Opening</th>\n      <th>Opening.1</th>\n      <th>Title</th>\n      <th>Production company</th>\n      <th>Cast and crew</th>\n      <th>Ref.</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JANUARY</td>\n      <td>4</td>\n      <td>Escape Room</td>\n      <td>Columbia Pictures</td>\n      <td>Adam Robitel (director); Bragi F. Schut, Maria...</td>\n      <td>[2]</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JANUARY</td>\n      <td>4</td>\n      <td>Rust Creek</td>\n      <td>IFC Films</td>\n      <td>Jen McGowan (director); Julie Lipson (screenpl...</td>\n      <td>[3]</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>JANUARY</td>\n      <td>4</td>\n      <td>American Hangman</td>\n      <td>Hangman Justice Productions</td>\n      <td>Wilson Coneybeare (director/screenplay); Donal...</td>\n      <td>[4]</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JANUARY</td>\n      <td>11</td>\n      <td>A Dog's Way Home</td>\n      <td>Columbia Pictures</td>\n      <td>Charles Martin Smith (director); W. Bruce Came...</td>\n      <td>[5]</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>JANUARY</td>\n      <td>11</td>\n      <td>The Upside</td>\n      <td>STX Entertainment</td>\n      <td>Neil Burger (director); Jon Hartmere (screenpl...</td>\n      <td>[6]</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>236</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Little Women</td>\n      <td>Columbia Pictures / Regency Enterprises</td>\n      <td>Greta Gerwig (director/screenplay); Saoirse Ro...</td>\n      <td>[222]</td>\n    </tr>\n    <tr>\n      <th>237</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>1917</td>\n      <td>Universal Pictures / DreamWorks Pictures / Ent...</td>\n      <td>Sam Mendes (director/screenplay); Krysty Wilso...</td>\n      <td>[223]</td>\n    </tr>\n    <tr>\n      <th>238</th>\n      <td>DECEMBER</td>\n      <td>25</td>\n      <td>Just Mercy</td>\n      <td>Warner Bros. Pictures / Participant Media</td>\n      <td>Destin Daniel Cretton (director/screenplay), A...</td>\n      <td>[224]</td>\n    </tr>\n    <tr>\n      <th>239</th>\n      <td>DECEMBER</td>\n      <td>27</td>\n      <td>Clemency</td>\n      <td>Neon</td>\n      <td>Chinonye Chukwu (director/screenplay); Alfre W...</td>\n      <td>[225]</td>\n    </tr>\n    <tr>\n      <th>240</th>\n      <td>DECEMBER</td>\n      <td>27</td>\n      <td>Apparition</td>\n      <td>Vertical Pictures</td>\n      <td>Waymon Boone (director/screenplay); Mena Suvar...</td>\n      <td>[226]</td>\n    </tr>\n  </tbody>\n</table>\n<p>241 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df['genres'] = df['Title'].map(lambda x: get_genre(str(x)))","execution_count":32,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019 = df[['Title','Cast and crew','genres']]","execution_count":33,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019","execution_count":34,"outputs":[{"output_type":"execute_result","execution_count":34,"data":{"text/plain":"                Title                                      Cast and crew  \\\n0         Escape Room  Adam Robitel (director); Bragi F. Schut, Maria...   \n1          Rust Creek  Jen McGowan (director); Julie Lipson (screenpl...   \n2    American Hangman  Wilson Coneybeare (director/screenplay); Donal...   \n3    A Dog's Way Home  Charles Martin Smith (director); W. Bruce Came...   \n4          The Upside  Neil Burger (director); Jon Hartmere (screenpl...   \n..                ...                                                ...   \n236      Little Women  Greta Gerwig (director/screenplay); Saoirse Ro...   \n237              1917  Sam Mendes (director/screenplay); Krysty Wilso...   \n238        Just Mercy  Destin Daniel Cretton (director/screenplay), A...   \n239          Clemency  Chinonye Chukwu (director/screenplay); Alfre W...   \n240        Apparition  Waymon Boone (director/screenplay); Mena Suvar...   \n\n                             genres  \n0    Thriller Action Mystery Horror  \n1                    Thriller Drama  \n2                          Thriller  \n3            Drama Adventure Family  \n4                      Comedy Drama  \n..                              ...  \n236                   Drama Romance  \n237        War Drama Action History  \n238                     Drama Crime  \n239                           Drama  \n240                 Horror Thriller  \n\n[241 rows x 3 columns]","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>Title</th>\n      <th>Cast and crew</th>\n      <th>genres</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Escape Room</td>\n      <td>Adam Robitel (director); Bragi F. Schut, Maria...</td>\n      <td>Thriller Action Mystery Horror</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Rust Creek</td>\n      <td>Jen McGowan (director); Julie Lipson (screenpl...</td>\n      <td>Thriller Drama</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>American Hangman</td>\n      <td>Wilson Coneybeare (director/screenplay); Donal...</td>\n      <td>Thriller</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>A Dog's Way Home</td>\n      <td>Charles Martin Smith (director); W. Bruce Came...</td>\n      <td>Drama Adventure Family</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>The Upside</td>\n      <td>Neil Burger (director); Jon Hartmere (screenpl...</td>\n      <td>Comedy Drama</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>236</th>\n      <td>Little Women</td>\n      <td>Greta Gerwig (director/screenplay); Saoirse Ro...</td>\n      <td>Drama Romance</td>\n    </tr>\n    <tr>\n      <th>237</th>\n      <td>1917</td>\n      <td>Sam Mendes (director/screenplay); Krysty Wilso...</td>\n      <td>War Drama Action History</td>\n    </tr>\n    <tr>\n      <th>238</th>\n      <td>Just Mercy</td>\n      <td>Destin Daniel Cretton (director/screenplay), A...</td>\n      <td>Drama Crime</td>\n    </tr>\n    <tr>\n      <th>239</th>\n      <td>Clemency</td>\n      <td>Chinonye Chukwu (director/screenplay); Alfre W...</td>\n      <td>Drama</td>\n    </tr>\n    <tr>\n      <th>240</th>\n      <td>Apparition</td>\n      <td>Waymon Boone (director/screenplay); Mena Suvar...</td>\n      <td>Horror Thriller</td>\n    </tr>\n  </tbody>\n</table>\n<p>241 rows × 3 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019['director_name'] = df_2019['Cast and crew'].map(lambda x: get_director(str(x)))","execution_count":35,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019['actor_1_name'] = df_2019['Cast and crew'].map(lambda x: get_actor1(x))","execution_count":36,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019['actor_2_name'] = df_2019['Cast and crew'].map(lambda x: get_actor2(x))","execution_count":37,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019['actor_3_name'] = df_2019['Cast and crew'].map(lambda x: get_actor3(x))","execution_count":38,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2019 = df_2019.rename(columns={'Title':'movie_title'})","execution_count":39,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df19 = df_2019.loc[:,['director_name','actor_1_name','actor_2_name','actor_3_name','genres','movie_title']]","execution_count":40,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\nnew_df19['actor_2_name'] = new_df19['actor_2_name'].replace(np.nan, 'unknown')\nnew_df19['actor_3_name'] = new_df19['actor_3_name'].replace(np.nan, 'unknown')","execution_count":41,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df19['movie_title'] = new_df19['movie_title'].str.lower()","execution_count":42,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df19['comb'] = new_df19['actor_1_name'] + ' ' + new_df19['actor_2_name'] + ' '+ new_df19['actor_3_name'] + ' '+ new_df19['director_name'] +' ' + new_df19['genres']","execution_count":43,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df19","execution_count":44,"outputs":[{"output_type":"execute_result","execution_count":44,"data":{"text/plain":"             director_name         actor_1_name          actor_2_name  \\\n0             Adam Robitel       Taylor Russell          Logan Miller   \n1              Jen McGowan    Hermione Corfield           Jay Paulson   \n2        Wilson Coneybeare    Donald Sutherland    Vincent Kartheiser   \n3     Charles Martin Smith  Bryce Dallas Howard    Edward James Olmos   \n4              Neil Burger       Bryan Cranston            Kevin Hart   \n..                     ...                  ...                   ...   \n236           Greta Gerwig        Saoirse Ronan           Emma Watson   \n237             Sam Mendes        George MacKay  Dean-Charles Chapman   \n238  Destin Daniel Cretton    Michael B. Jordan            Jamie Foxx   \n239        Chinonye Chukwu        Alfre Woodard        Wendell Pierce   \n240           Waymon Boone          Mena Suvari          Kevin Pollak   \n\n         actor_3_name                          genres       movie_title  \\\n0    Deborah Ann Woll  Thriller Action Mystery Horror       escape room   \n1        Sean O'Bryan                  Thriller Drama        rust creek   \n2       Oliver Dennis                        Thriller  american hangman   \n3     Alexandra Shipp          Drama Adventure Family  a dog's way home   \n4       Nicole Kidman                    Comedy Drama        the upside   \n..                ...                             ...               ...   \n236     Florence Pugh                   Drama Romance      little women   \n237       Mark Strong        War Drama Action History              1917   \n238       Brie Larson                     Drama Crime        just mercy   \n239       Aldis Hodge                           Drama          clemency   \n240           unknown                 Horror Thriller        apparition   \n\n                                                  comb  \n0    Taylor Russell Logan Miller Deborah Ann Woll A...  \n1    Hermione Corfield Jay Paulson Sean O'Bryan Jen...  \n2    Donald Sutherland Vincent Kartheiser Oliver De...  \n3    Bryce Dallas Howard Edward James Olmos Alexand...  \n4    Bryan Cranston Kevin Hart Nicole Kidman Neil B...  \n..                                                 ...  \n236  Saoirse Ronan Emma Watson Florence Pugh Greta ...  \n237  George MacKay Dean-Charles Chapman Mark Strong...  \n238  Michael B. Jordan Jamie Foxx Brie Larson Desti...  \n239  Alfre Woodard Wendell Pierce Aldis Hodge Chino...  \n240  Mena Suvari Kevin Pollak unknown Waymon Boone ...  \n\n[241 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Adam Robitel</td>\n      <td>Taylor Russell</td>\n      <td>Logan Miller</td>\n      <td>Deborah Ann Woll</td>\n      <td>Thriller Action Mystery Horror</td>\n      <td>escape room</td>\n      <td>Taylor Russell Logan Miller Deborah Ann Woll A...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Jen McGowan</td>\n      <td>Hermione Corfield</td>\n      <td>Jay Paulson</td>\n      <td>Sean O'Bryan</td>\n      <td>Thriller Drama</td>\n      <td>rust creek</td>\n      <td>Hermione Corfield Jay Paulson Sean O'Bryan Jen...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Wilson Coneybeare</td>\n      <td>Donald Sutherland</td>\n      <td>Vincent Kartheiser</td>\n      <td>Oliver Dennis</td>\n      <td>Thriller</td>\n      <td>american hangman</td>\n      <td>Donald Sutherland Vincent Kartheiser Oliver De...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Charles Martin Smith</td>\n      <td>Bryce Dallas Howard</td>\n      <td>Edward James Olmos</td>\n      <td>Alexandra Shipp</td>\n      <td>Drama Adventure Family</td>\n      <td>a dog's way home</td>\n      <td>Bryce Dallas Howard Edward James Olmos Alexand...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Neil Burger</td>\n      <td>Bryan Cranston</td>\n      <td>Kevin Hart</td>\n      <td>Nicole Kidman</td>\n      <td>Comedy Drama</td>\n      <td>the upside</td>\n      <td>Bryan Cranston Kevin Hart Nicole Kidman Neil B...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>236</th>\n      <td>Greta Gerwig</td>\n      <td>Saoirse Ronan</td>\n      <td>Emma Watson</td>\n      <td>Florence Pugh</td>\n      <td>Drama Romance</td>\n      <td>little women</td>\n      <td>Saoirse Ronan Emma Watson Florence Pugh Greta ...</td>\n    </tr>\n    <tr>\n      <th>237</th>\n      <td>Sam Mendes</td>\n      <td>George MacKay</td>\n      <td>Dean-Charles Chapman</td>\n      <td>Mark Strong</td>\n      <td>War Drama Action History</td>\n      <td>1917</td>\n      <td>George MacKay Dean-Charles Chapman Mark Strong...</td>\n    </tr>\n    <tr>\n      <th>238</th>\n      <td>Destin Daniel Cretton</td>\n      <td>Michael B. Jordan</td>\n      <td>Jamie Foxx</td>\n      <td>Brie Larson</td>\n      <td>Drama Crime</td>\n      <td>just mercy</td>\n      <td>Michael B. Jordan Jamie Foxx Brie Larson Desti...</td>\n    </tr>\n    <tr>\n      <th>239</th>\n      <td>Chinonye Chukwu</td>\n      <td>Alfre Woodard</td>\n      <td>Wendell Pierce</td>\n      <td>Aldis Hodge</td>\n      <td>Drama</td>\n      <td>clemency</td>\n      <td>Alfre Woodard Wendell Pierce Aldis Hodge Chino...</td>\n    </tr>\n    <tr>\n      <th>240</th>\n      <td>Waymon Boone</td>\n      <td>Mena Suvari</td>\n      <td>Kevin Pollak</td>\n      <td>unknown</td>\n      <td>Horror Thriller</td>\n      <td>apparition</td>\n      <td>Mena Suvari Kevin Pollak unknown Waymon Boone ...</td>\n    </tr>\n  </tbody>\n</table>\n<p>241 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"my_df = new_df18.append(new_df19,ignore_index=True)","execution_count":45,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"my_df","execution_count":46,"outputs":[{"output_type":"execute_result","execution_count":46,"data":{"text/plain":"             director_name       actor_1_name            actor_2_name  \\\n0             Adam Robitel          Lin Shaye           Angus Sampson   \n1         Lauren Wolkstein      Alex Pettyfer  James Freedson-Jackson   \n2               Simon West     Dominic Cooper          Austin Stowell   \n3         Warwick Thornton        Bryan Brown               Sam Neill   \n4       Jaume Collet-Serra        Liam Neeson            Vera Farmiga   \n..                     ...                ...                     ...   \n504           Greta Gerwig      Saoirse Ronan             Emma Watson   \n505             Sam Mendes      George MacKay    Dean-Charles Chapman   \n506  Destin Daniel Cretton  Michael B. Jordan              Jamie Foxx   \n507        Chinonye Chukwu      Alfre Woodard          Wendell Pierce   \n508           Waymon Boone        Mena Suvari            Kevin Pollak   \n\n       actor_3_name                    genres              movie_title  \\\n0    Leigh Whannell   Mystery Horror Thriller  insidious: the last key   \n1     Emily Althaus            Thriller Drama         the strange ones   \n2        Gemma Chan           Action Thriller                 stratton   \n3           unknown     Drama History Western            sweet country   \n4    Patrick Wilson           Action Thriller             the commuter   \n..              ...                       ...                      ...   \n504   Florence Pugh             Drama Romance             little women   \n505     Mark Strong  War Drama Action History                     1917   \n506     Brie Larson               Drama Crime               just mercy   \n507     Aldis Hodge                     Drama                 clemency   \n508         unknown           Horror Thriller               apparition   \n\n                                                  comb  \n0    Lin Shaye Angus Sampson Leigh Whannell Adam Ro...  \n1    Alex Pettyfer James Freedson-Jackson Emily Alt...  \n2    Dominic Cooper Austin Stowell Gemma Chan Simon...  \n3    Bryan Brown Sam Neill unknown Warwick Thornton...  \n4    Liam Neeson Vera Farmiga Patrick Wilson Jaume ...  \n..                                                 ...  \n504  Saoirse Ronan Emma Watson Florence Pugh Greta ...  \n505  George MacKay Dean-Charles Chapman Mark Strong...  \n506  Michael B. Jordan Jamie Foxx Brie Larson Desti...  \n507  Alfre Woodard Wendell Pierce Aldis Hodge Chino...  \n508  Mena Suvari Kevin Pollak unknown Waymon Boone ...  \n\n[509 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Adam Robitel</td>\n      <td>Lin Shaye</td>\n      <td>Angus Sampson</td>\n      <td>Leigh Whannell</td>\n      <td>Mystery Horror Thriller</td>\n      <td>insidious: the last key</td>\n      <td>Lin Shaye Angus Sampson Leigh Whannell Adam Ro...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Lauren Wolkstein</td>\n      <td>Alex Pettyfer</td>\n      <td>James Freedson-Jackson</td>\n      <td>Emily Althaus</td>\n      <td>Thriller Drama</td>\n      <td>the strange ones</td>\n      <td>Alex Pettyfer James Freedson-Jackson Emily Alt...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Simon West</td>\n      <td>Dominic Cooper</td>\n      <td>Austin Stowell</td>\n      <td>Gemma Chan</td>\n      <td>Action Thriller</td>\n      <td>stratton</td>\n      <td>Dominic Cooper Austin Stowell Gemma Chan Simon...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Warwick Thornton</td>\n      <td>Bryan Brown</td>\n      <td>Sam Neill</td>\n      <td>unknown</td>\n      <td>Drama History Western</td>\n      <td>sweet country</td>\n      <td>Bryan Brown Sam Neill unknown Warwick Thornton...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Jaume Collet-Serra</td>\n      <td>Liam Neeson</td>\n      <td>Vera Farmiga</td>\n      <td>Patrick Wilson</td>\n      <td>Action Thriller</td>\n      <td>the commuter</td>\n      <td>Liam Neeson Vera Farmiga Patrick Wilson Jaume ...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>504</th>\n      <td>Greta Gerwig</td>\n      <td>Saoirse Ronan</td>\n      <td>Emma Watson</td>\n      <td>Florence Pugh</td>\n      <td>Drama Romance</td>\n      <td>little women</td>\n      <td>Saoirse Ronan Emma Watson Florence Pugh Greta ...</td>\n    </tr>\n    <tr>\n      <th>505</th>\n      <td>Sam Mendes</td>\n      <td>George MacKay</td>\n      <td>Dean-Charles Chapman</td>\n      <td>Mark Strong</td>\n      <td>War Drama Action History</td>\n      <td>1917</td>\n      <td>George MacKay Dean-Charles Chapman Mark Strong...</td>\n    </tr>\n    <tr>\n      <th>506</th>\n      <td>Destin Daniel Cretton</td>\n      <td>Michael B. Jordan</td>\n      <td>Jamie Foxx</td>\n      <td>Brie Larson</td>\n      <td>Drama Crime</td>\n      <td>just mercy</td>\n      <td>Michael B. Jordan Jamie Foxx Brie Larson Desti...</td>\n    </tr>\n    <tr>\n      <th>507</th>\n      <td>Chinonye Chukwu</td>\n      <td>Alfre Woodard</td>\n      <td>Wendell Pierce</td>\n      <td>Aldis Hodge</td>\n      <td>Drama</td>\n      <td>clemency</td>\n      <td>Alfre Woodard Wendell Pierce Aldis Hodge Chino...</td>\n    </tr>\n    <tr>\n      <th>508</th>\n      <td>Waymon Boone</td>\n      <td>Mena Suvari</td>\n      <td>Kevin Pollak</td>\n      <td>unknown</td>\n      <td>Horror Thriller</td>\n      <td>apparition</td>\n      <td>Mena Suvari Kevin Pollak unknown Waymon Boone ...</td>\n    </tr>\n  </tbody>\n</table>\n<p>509 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"old_df = pd.read_csv('../input/movie.csv')","execution_count":51,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"old_df","execution_count":52,"outputs":[{"output_type":"execute_result","execution_count":52,"data":{"text/plain":"         director_name     actor_1_name    actor_2_name     actor_3_name  \\\n0        John Lasseter        Tom Hanks       Tim Allen      Don Rickles   \n1         Joe Johnston   Robin Williams   Jonathan Hyde    Kirsten Dunst   \n2        Howard Deutch   Walter Matthau     Jack Lemmon      Ann-Margret   \n3      Forest Whitaker  Whitney Houston  Angela Bassett   Loretta Devine   \n4        Charles Shyer     Steve Martin    Diane Keaton     Martin Short   \n...                ...              ...             ...              ...   \n36336         Ben Rock       Monty Bane     Lucy Butler    David Grammer   \n36337    Aaron Osborne       Lisa Boyle       Kena Land    Zaneta Polard   \n36338       John Irvin   Patrick Bergin     Uma Thurman  David Morrissey   \n36339         Lav Diaz     Angel Aquino     Perry Dizon    Hazel Orencio   \n36340   Mark L. Lester    Erika Eleniak    Adam Baldwin    Julie du Page   \n\n                         genres                  movie_title  \\\n0       Animation Comedy Family                    toy story   \n1      Adventure Fantasy Family                      jumanji   \n2                Romance Comedy             grumpier old men   \n3          Comedy Drama Romance            waiting to exhale   \n4                        Comedy  father of the bride part ii   \n...                         ...                          ...   \n36336                    Horror          the burkittsville 7   \n36337                    Sci-Fi              caged heat 3000   \n36338      Drama Action Romance                   robin hood   \n36339                     Drama          century of birthing   \n36340     Action Drama Thriller                     betrayal   \n\n                                                    comb  \n0      Tom Hanks Tim Allen Don Rickles John Lasseter ...  \n1      Robin Williams Jonathan Hyde Kirsten Dunst Joe...  \n2      Walter Matthau Jack Lemmon Ann-Margret Howard ...  \n3      Whitney Houston Angela Bassett Loretta Devine ...  \n4      Steve Martin Diane Keaton Martin Short Charles...  \n...                                                  ...  \n36336  Monty Bane Lucy Butler David Grammer Ben Rock ...  \n36337  Lisa Boyle Kena Land Zaneta Polard Aaron Osbor...  \n36338  Patrick Bergin Uma Thurman David Morrissey Joh...  \n36339  Angel Aquino Perry Dizon Hazel Orencio Lav Dia...  \n36340  Erika Eleniak Adam Baldwin Julie du Page Mark ...  \n\n[36341 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>toy story</td>\n      <td>Tom Hanks Tim Allen Don Rickles John Lasseter ...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>jumanji</td>\n      <td>Robin Williams Jonathan Hyde Kirsten Dunst Joe...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>grumpier old men</td>\n      <td>Walter Matthau Jack Lemmon Ann-Margret Howard ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>waiting to exhale</td>\n      <td>Whitney Houston Angela Bassett Loretta Devine ...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>father of the bride part ii</td>\n      <td>Steve Martin Diane Keaton Martin Short Charles...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>36336</th>\n      <td>Ben Rock</td>\n      <td>Monty Bane</td>\n      <td>Lucy Butler</td>\n      <td>David Grammer</td>\n      <td>Horror</td>\n      <td>the burkittsville 7</td>\n      <td>Monty Bane Lucy Butler David Grammer Ben Rock ...</td>\n    </tr>\n    <tr>\n      <th>36337</th>\n      <td>Aaron Osborne</td>\n      <td>Lisa Boyle</td>\n      <td>Kena Land</td>\n      <td>Zaneta Polard</td>\n      <td>Sci-Fi</td>\n      <td>caged heat 3000</td>\n      <td>Lisa Boyle Kena Land Zaneta Polard Aaron Osbor...</td>\n    </tr>\n    <tr>\n      <th>36338</th>\n      <td>John Irvin</td>\n      <td>Patrick Bergin</td>\n      <td>Uma Thurman</td>\n      <td>David Morrissey</td>\n      <td>Drama Action Romance</td>\n      <td>robin hood</td>\n      <td>Patrick Bergin Uma Thurman David Morrissey Joh...</td>\n    </tr>\n    <tr>\n      <th>36339</th>\n      <td>Lav Diaz</td>\n      <td>Angel Aquino</td>\n      <td>Perry Dizon</td>\n      <td>Hazel Orencio</td>\n      <td>Drama</td>\n      <td>century of birthing</td>\n      <td>Angel Aquino Perry Dizon Hazel Orencio Lav Dia...</td>\n    </tr>\n    <tr>\n      <th>36340</th>\n      <td>Mark L. Lester</td>\n      <td>Erika Eleniak</td>\n      <td>Adam Baldwin</td>\n      <td>Julie du Page</td>\n      <td>Action Drama Thriller</td>\n      <td>betrayal</td>\n      <td>Erika Eleniak Adam Baldwin Julie du Page Mark ...</td>\n    </tr>\n  </tbody>\n</table>\n<p>36341 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df = old_df.append(my_df,ignore_index=True)","execution_count":53,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df","execution_count":54,"outputs":[{"output_type":"execute_result","execution_count":54,"data":{"text/plain":"               director_name       actor_1_name          actor_2_name  \\\n0              John Lasseter          Tom Hanks             Tim Allen   \n1               Joe Johnston     Robin Williams         Jonathan Hyde   \n2              Howard Deutch     Walter Matthau           Jack Lemmon   \n3            Forest Whitaker    Whitney Houston        Angela Bassett   \n4              Charles Shyer       Steve Martin          Diane Keaton   \n...                      ...                ...                   ...   \n36845           Greta Gerwig      Saoirse Ronan           Emma Watson   \n36846             Sam Mendes      George MacKay  Dean-Charles Chapman   \n36847  Destin Daniel Cretton  Michael B. Jordan            Jamie Foxx   \n36848        Chinonye Chukwu      Alfre Woodard        Wendell Pierce   \n36849           Waymon Boone        Mena Suvari          Kevin Pollak   \n\n         actor_3_name                    genres                  movie_title  \\\n0         Don Rickles   Animation Comedy Family                    toy story   \n1       Kirsten Dunst  Adventure Fantasy Family                      jumanji   \n2         Ann-Margret            Romance Comedy             grumpier old men   \n3      Loretta Devine      Comedy Drama Romance            waiting to exhale   \n4        Martin Short                    Comedy  father of the bride part ii   \n...               ...                       ...                          ...   \n36845   Florence Pugh             Drama Romance                 little women   \n36846     Mark Strong  War Drama Action History                         1917   \n36847     Brie Larson               Drama Crime                   just mercy   \n36848     Aldis Hodge                     Drama                     clemency   \n36849         unknown           Horror Thriller                   apparition   \n\n                                                    comb  \n0      Tom Hanks Tim Allen Don Rickles John Lasseter ...  \n1      Robin Williams Jonathan Hyde Kirsten Dunst Joe...  \n2      Walter Matthau Jack Lemmon Ann-Margret Howard ...  \n3      Whitney Houston Angela Bassett Loretta Devine ...  \n4      Steve Martin Diane Keaton Martin Short Charles...  \n...                                                  ...  \n36845  Saoirse Ronan Emma Watson Florence Pugh Greta ...  \n36846  George MacKay Dean-Charles Chapman Mark Strong...  \n36847  Michael B. Jordan Jamie Foxx Brie Larson Desti...  \n36848  Alfre Woodard Wendell Pierce Aldis Hodge Chino...  \n36849  Mena Suvari Kevin Pollak unknown Waymon Boone ...  \n\n[36850 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>toy story</td>\n      <td>Tom Hanks Tim Allen Don Rickles John Lasseter ...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>jumanji</td>\n      <td>Robin Williams Jonathan Hyde Kirsten Dunst Joe...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>grumpier old men</td>\n      <td>Walter Matthau Jack Lemmon Ann-Margret Howard ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>waiting to exhale</td>\n      <td>Whitney Houston Angela Bassett Loretta Devine ...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>father of the bride part ii</td>\n      <td>Steve Martin Diane Keaton Martin Short Charles...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>36845</th>\n      <td>Greta Gerwig</td>\n      <td>Saoirse Ronan</td>\n      <td>Emma Watson</td>\n      <td>Florence Pugh</td>\n      <td>Drama Romance</td>\n      <td>little women</td>\n      <td>Saoirse Ronan Emma Watson Florence Pugh Greta ...</td>\n    </tr>\n    <tr>\n      <th>36846</th>\n      <td>Sam Mendes</td>\n      <td>George MacKay</td>\n      <td>Dean-Charles Chapman</td>\n      <td>Mark Strong</td>\n      <td>War Drama Action History</td>\n      <td>1917</td>\n      <td>George MacKay Dean-Charles Chapman Mark Strong...</td>\n    </tr>\n    <tr>\n      <th>36847</th>\n      <td>Destin Daniel Cretton</td>\n      <td>Michael B. Jordan</td>\n      <td>Jamie Foxx</td>\n      <td>Brie Larson</td>\n      <td>Drama Crime</td>\n      <td>just mercy</td>\n      <td>Michael B. Jordan Jamie Foxx Brie Larson Desti...</td>\n    </tr>\n    <tr>\n      <th>36848</th>\n      <td>Chinonye Chukwu</td>\n      <td>Alfre Woodard</td>\n      <td>Wendell Pierce</td>\n      <td>Aldis Hodge</td>\n      <td>Drama</td>\n      <td>clemency</td>\n      <td>Alfre Woodard Wendell Pierce Aldis Hodge Chino...</td>\n    </tr>\n    <tr>\n      <th>36849</th>\n      <td>Waymon Boone</td>\n      <td>Mena Suvari</td>\n      <td>Kevin Pollak</td>\n      <td>unknown</td>\n      <td>Horror Thriller</td>\n      <td>apparition</td>\n      <td>Mena Suvari Kevin Pollak unknown Waymon Boone ...</td>\n    </tr>\n  </tbody>\n</table>\n<p>36850 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df.isna().sum()","execution_count":55,"outputs":[{"output_type":"execute_result","execution_count":55,"data":{"text/plain":"director_name    0\nactor_1_name     0\nactor_2_name     0\nactor_3_name     0\ngenres           4\nmovie_title      0\ncomb             4\ndtype: int64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df = final_df.dropna(how='any')","execution_count":56,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df.to_csv('final_data.csv',index=False)","execution_count":57,"outputs":[]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}


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/.ipynb_checkpoints/preprocessing 4.ipynb:
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1 | {"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport requests\nimport bs4 as bs\nimport urllib.request","execution_count":1,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Extracting features of 2020 movies from Wikipedia"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"link = \"https://en.wikipedia.org/wiki/List_of_American_films_of_2020\"","execution_count":2,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"source = urllib.request.urlopen(link).read()\nsoup = bs.BeautifulSoup(source,'lxml')","execution_count":3,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"tables = soup.find_all('table',class_='wikitable sortable')","execution_count":4,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df1 = pd.read_html(str(tables[0]))[0]\ndf2 = pd.read_html(str(tables[1]))[0]\ndf3 = pd.read_html(str(tables[2]))[0]\ndf4 = pd.read_html(str(tables[3]).replace(\"'1\\\"\\'\",'\"1\"'))[0] # avoided \"ValueError: invalid literal for int() with base 10: '1\"'","execution_count":5,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df = df1.append(df2.append(df3.append(df4,ignore_index=True),ignore_index=True),ignore_index=True)","execution_count":6,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df","execution_count":7,"outputs":[{"output_type":"execute_result","execution_count":7,"data":{"text/plain":"      Opening  Opening.1              Title  \\\n0     JANUARY        3.0         The Grudge   \n1     JANUARY       10.0         Underwater   \n2     JANUARY       10.0        Like a Boss   \n3     JANUARY       10.0  Inherit the Viper   \n4     JANUARY       10.0         The Sonata   \n..        ...        ...                ...   \n150  DECEMBER       23.0  Top Gun: Maverick   \n151  DECEMBER       23.0       The Croods 2   \n152  DECEMBER       25.0            Respect   \n153  DECEMBER       25.0      The Last Duel   \n154  DECEMBER       25.0  News of the World   \n\n                                    Production company  \\\n0    Screen Gems / Stage 6 Films / Ghost House Pict...   \n1    20th Century Fox / TSG Entertainment / Chernin...   \n2                                   Paramount Pictures   \n3       Barry Films / Tycor International Film Company   \n4                                   Screen Media Films   \n..                                                 ...   \n150  Paramount Pictures / Skydance Media / Don Simp...   \n151          Universal Pictures / DreamWorks Animation   \n152  Metro-Goldwyn-Mayer / Universal Pictures / Bro...   \n153  20th Century Studios / Scott Free Productions ...   \n154                      Universal Pictures / Playtone   \n\n                                         Cast and crew   Ref.  \n0    Nicolas Pesce (director/screenplay); Andrea Ri...    [2]  \n1    William Eubank (director); Brian Duffield, Ada...    [3]  \n2    Miguel Arteta (director); Sam Pitman, Adam Col...    [4]  \n3    Anthony Jerjen (director); Andrew Crabtree (sc...    [5]  \n4    Andrew Desmond (director/screenplay); Arthur M...    [6]  \n..                                                 ...    ...  \n150  Joseph Kosinski (director); Ehren Kruger, Eric...  [149]  \n151  Joel Crawford (director); Kevin Hageman, Dan H...  [150]  \n152  Liesl Tommy (director); Tracey Scott Wilson (s...  [151]  \n153  Ridley Scott (director); Ben Affleck, Matt Dam...  [152]  \n154  Paul Greengrass (director/screenplay); Luke Da...  [153]  \n\n[155 rows x 6 columns]","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>Opening</th>\n      <th>Opening.1</th>\n      <th>Title</th>\n      <th>Production company</th>\n      <th>Cast and crew</th>\n      <th>Ref.</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>JANUARY</td>\n      <td>3.0</td>\n      <td>The Grudge</td>\n      <td>Screen Gems / Stage 6 Films / Ghost House Pict...</td>\n      <td>Nicolas Pesce (director/screenplay); Andrea Ri...</td>\n      <td>[2]</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>JANUARY</td>\n      <td>10.0</td>\n      <td>Underwater</td>\n      <td>20th Century Fox / TSG Entertainment / Chernin...</td>\n      <td>William Eubank (director); Brian Duffield, Ada...</td>\n      <td>[3]</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>JANUARY</td>\n      <td>10.0</td>\n      <td>Like a Boss</td>\n      <td>Paramount Pictures</td>\n      <td>Miguel Arteta (director); Sam Pitman, Adam Col...</td>\n      <td>[4]</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>JANUARY</td>\n      <td>10.0</td>\n      <td>Inherit the Viper</td>\n      <td>Barry Films / Tycor International Film Company</td>\n      <td>Anthony Jerjen (director); Andrew Crabtree (sc...</td>\n      <td>[5]</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>JANUARY</td>\n      <td>10.0</td>\n      <td>The Sonata</td>\n      <td>Screen Media Films</td>\n      <td>Andrew Desmond (director/screenplay); Arthur M...</td>\n      <td>[6]</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>DECEMBER</td>\n      <td>23.0</td>\n      <td>Top Gun: Maverick</td>\n      <td>Paramount Pictures / Skydance Media / Don Simp...</td>\n      <td>Joseph Kosinski (director); Ehren Kruger, Eric...</td>\n      <td>[149]</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>DECEMBER</td>\n      <td>23.0</td>\n      <td>The Croods 2</td>\n      <td>Universal Pictures / DreamWorks Animation</td>\n      <td>Joel Crawford (director); Kevin Hageman, Dan H...</td>\n      <td>[150]</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>DECEMBER</td>\n      <td>25.0</td>\n      <td>Respect</td>\n      <td>Metro-Goldwyn-Mayer / Universal Pictures / Bro...</td>\n      <td>Liesl Tommy (director); Tracey Scott Wilson (s...</td>\n      <td>[151]</td>\n    </tr>\n    <tr>\n      <th>153</th>\n      <td>DECEMBER</td>\n      <td>25.0</td>\n      <td>The Last Duel</td>\n      <td>20th Century Studios / Scott Free Productions ...</td>\n      <td>Ridley Scott (director); Ben Affleck, Matt Dam...</td>\n      <td>[152]</td>\n    </tr>\n    <tr>\n      <th>154</th>\n      <td>DECEMBER</td>\n      <td>25.0</td>\n      <td>News of the World</td>\n      <td>Universal Pictures / Playtone</td>\n      <td>Paul Greengrass (director/screenplay); Luke Da...</td>\n      <td>[153]</td>\n    </tr>\n  </tbody>\n</table>\n<p>155 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020 = df[['Title','Cast and crew']]","execution_count":8,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020","execution_count":9,"outputs":[{"output_type":"execute_result","execution_count":9,"data":{"text/plain":"                 Title                                      Cast and crew\n0           The Grudge  Nicolas Pesce (director/screenplay); Andrea Ri...\n1           Underwater  William Eubank (director); Brian Duffield, Ada...\n2          Like a Boss  Miguel Arteta (director); Sam Pitman, Adam Col...\n3    Inherit the Viper  Anthony Jerjen (director); Andrew Crabtree (sc...\n4           The Sonata  Andrew Desmond (director/screenplay); Arthur M...\n..                 ...                                                ...\n150  Top Gun: Maverick  Joseph Kosinski (director); Ehren Kruger, Eric...\n151       The Croods 2  Joel Crawford (director); Kevin Hageman, Dan H...\n152            Respect  Liesl Tommy (director); Tracey Scott Wilson (s...\n153      The Last Duel  Ridley Scott (director); Ben Affleck, Matt Dam...\n154  News of the World  Paul Greengrass (director/screenplay); Luke Da...\n\n[155 rows x 2 columns]","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>Title</th>\n      <th>Cast and crew</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>The Grudge</td>\n      <td>Nicolas Pesce (director/screenplay); Andrea Ri...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Underwater</td>\n      <td>William Eubank (director); Brian Duffield, Ada...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Like a Boss</td>\n      <td>Miguel Arteta (director); Sam Pitman, Adam Col...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Inherit the Viper</td>\n      <td>Anthony Jerjen (director); Andrew Crabtree (sc...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>The Sonata</td>\n      <td>Andrew Desmond (director/screenplay); Arthur M...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>Top Gun: Maverick</td>\n      <td>Joseph Kosinski (director); Ehren Kruger, Eric...</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>The Croods 2</td>\n      <td>Joel Crawford (director); Kevin Hageman, Dan H...</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>Respect</td>\n      <td>Liesl Tommy (director); Tracey Scott Wilson (s...</td>\n    </tr>\n    <tr>\n      <th>153</th>\n      <td>The Last Duel</td>\n      <td>Ridley Scott (director); Ben Affleck, Matt Dam...</td>\n    </tr>\n    <tr>\n      <th>154</th>\n      <td>News of the World</td>\n      <td>Paul Greengrass (director/screenplay); Luke Da...</td>\n    </tr>\n  </tbody>\n</table>\n<p>155 rows × 2 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"!pip install tmdbv3api","execution_count":12,"outputs":[{"output_type":"stream","text":"Collecting tmdbv3api\n  Downloading tmdbv3api-1.6.1-py2.py3-none-any.whl (13 kB)\nRequirement already satisfied: requests in /opt/conda/lib/python3.7/site-packages (from tmdbv3api) (2.23.0)\nRequirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (2020.6.20)\nRequirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (2.9)\nRequirement already satisfied: chardet<4,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (3.0.4)\nRequirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->tmdbv3api) (1.24.3)\nInstalling collected packages: tmdbv3api\nSuccessfully installed tmdbv3api-1.6.1\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tmdbv3api import TMDb\nimport json\nimport requests\ntmdb = TMDb()\ntmdb.api_key = 'YOUR_API_KEY'","execution_count":13,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tmdbv3api import Movie\ntmdb_movie = Movie()\ndef get_genre(x):\n    genres = []\n    result = tmdb_movie.search(x)\n    movie_id = result[0].id\n    response = requests.get('https://api.themoviedb.org/3/movie/{}?api_key={}'.format(movie_id,tmdb.api_key))\n    data_json = response.json()\n    if data_json['genres']:\n        genre_str = \" \" \n        for i in range(0,len(data_json['genres'])):\n            genres.append(data_json['genres'][i]['name'])\n        return genre_str.join(genres)\n    else:\n        np.NaN","execution_count":14,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020['genres'] = df_2020['Title'].map(lambda x: get_genre(str(x)))","execution_count":15,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020","execution_count":16,"outputs":[{"output_type":"execute_result","execution_count":16,"data":{"text/plain":"                 Title                                      Cast and crew  \\\n0           The Grudge  Nicolas Pesce (director/screenplay); Andrea Ri...   \n1           Underwater  William Eubank (director); Brian Duffield, Ada...   \n2          Like a Boss  Miguel Arteta (director); Sam Pitman, Adam Col...   \n3    Inherit the Viper  Anthony Jerjen (director); Andrew Crabtree (sc...   \n4           The Sonata  Andrew Desmond (director/screenplay); Arthur M...   \n..                 ...                                                ...   \n150  Top Gun: Maverick  Joseph Kosinski (director); Ehren Kruger, Eric...   \n151       The Croods 2  Joel Crawford (director); Kevin Hageman, Dan H...   \n152            Respect  Liesl Tommy (director); Tracey Scott Wilson (s...   \n153      The Last Duel  Ridley Scott (director); Ben Affleck, Matt Dam...   \n154  News of the World  Paul Greengrass (director/screenplay); Luke Da...   \n\n                                     genres  \n0                            Horror Mystery  \n1    Action Horror Science Fiction Thriller  \n2                                    Comedy  \n3                      Drama Thriller Crime  \n4                   Horror Thriller Mystery  \n..                                      ...  \n150                            Action Drama  \n151              Animation Adventure Family  \n152                             Music Drama  \n153                                   Drama  \n154                           Drama Western  \n\n[155 rows x 3 columns]","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>Title</th>\n      <th>Cast and crew</th>\n      <th>genres</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>The Grudge</td>\n      <td>Nicolas Pesce (director/screenplay); Andrea Ri...</td>\n      <td>Horror Mystery</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Underwater</td>\n      <td>William Eubank (director); Brian Duffield, Ada...</td>\n      <td>Action Horror Science Fiction Thriller</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Like a Boss</td>\n      <td>Miguel Arteta (director); Sam Pitman, Adam Col...</td>\n      <td>Comedy</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Inherit the Viper</td>\n      <td>Anthony Jerjen (director); Andrew Crabtree (sc...</td>\n      <td>Drama Thriller Crime</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>The Sonata</td>\n      <td>Andrew Desmond (director/screenplay); Arthur M...</td>\n      <td>Horror Thriller Mystery</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>Top Gun: Maverick</td>\n      <td>Joseph Kosinski (director); Ehren Kruger, Eric...</td>\n      <td>Action Drama</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>The Croods 2</td>\n      <td>Joel Crawford (director); Kevin Hageman, Dan H...</td>\n      <td>Animation Adventure Family</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>Respect</td>\n      <td>Liesl Tommy (director); Tracey Scott Wilson (s...</td>\n      <td>Music Drama</td>\n    </tr>\n    <tr>\n      <th>153</th>\n      <td>The Last Duel</td>\n      <td>Ridley Scott (director); Ben Affleck, Matt Dam...</td>\n      <td>Drama</td>\n    </tr>\n    <tr>\n      <th>154</th>\n      <td>News of the World</td>\n      <td>Paul Greengrass (director/screenplay); Luke Da...</td>\n      <td>Drama Western</td>\n    </tr>\n  </tbody>\n</table>\n<p>155 rows × 3 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_director(x):\n    if \" (director)\" in x:\n        return x.split(\" (director)\")[0]\n    elif \" (directors)\" in x:\n        return x.split(\" (directors)\")[0]\n    else:\n        return x.split(\" (director/screenplay)\")[0]","execution_count":17,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020['director_name'] = df_2020['Cast and crew'].map(lambda x: get_director(str(x)))","execution_count":18,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor1(x):\n    return ((x.split(\"screenplay); \")[-1]).split(\", \")[0])","execution_count":19,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020['actor_1_name'] = df_2020['Cast and crew'].map(lambda x: get_actor1(str(x)))","execution_count":20,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor2(x):\n    if len((x.split(\"screenplay); \")[-1]).split(\", \")) < 2:\n        return np.NaN\n    else:\n        return ((x.split(\"screenplay); \")[-1]).split(\", \")[1])","execution_count":21,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020['actor_2_name'] = df_2020['Cast and crew'].map(lambda x: get_actor2(str(x)))","execution_count":22,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_actor3(x):\n    if len((x.split(\"screenplay); \")[-1]).split(\", \")) < 3:\n        return np.NaN\n    else:\n        return ((x.split(\"screenplay); \")[-1]).split(\", \")[2])","execution_count":23,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\ndf_2020['actor_3_name'] = df_2020['Cast and crew'].map(lambda x: get_actor3(str(x)))","execution_count":24,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020","execution_count":25,"outputs":[{"output_type":"execute_result","execution_count":25,"data":{"text/plain":"                 Title                                      Cast and crew  \\\n0           The Grudge  Nicolas Pesce (director/screenplay); Andrea Ri...   \n1           Underwater  William Eubank (director); Brian Duffield, Ada...   \n2          Like a Boss  Miguel Arteta (director); Sam Pitman, Adam Col...   \n3    Inherit the Viper  Anthony Jerjen (director); Andrew Crabtree (sc...   \n4           The Sonata  Andrew Desmond (director/screenplay); Arthur M...   \n..                 ...                                                ...   \n150  Top Gun: Maverick  Joseph Kosinski (director); Ehren Kruger, Eric...   \n151       The Croods 2  Joel Crawford (director); Kevin Hageman, Dan H...   \n152            Respect  Liesl Tommy (director); Tracey Scott Wilson (s...   \n153      The Last Duel  Ridley Scott (director); Ben Affleck, Matt Dam...   \n154  News of the World  Paul Greengrass (director/screenplay); Luke Da...   \n\n                                     genres    director_name  \\\n0                            Horror Mystery    Nicolas Pesce   \n1    Action Horror Science Fiction Thriller   William Eubank   \n2                                    Comedy    Miguel Arteta   \n3                      Drama Thriller Crime   Anthony Jerjen   \n4                   Horror Thriller Mystery   Andrew Desmond   \n..                                      ...              ...   \n150                            Action Drama  Joseph Kosinski   \n151              Animation Adventure Family    Joel Crawford   \n152                             Music Drama      Liesl Tommy   \n153                                   Drama     Ridley Scott   \n154                           Drama Western  Paul Greengrass   \n\n           actor_1_name       actor_2_name       actor_3_name  \n0    Andrea Riseborough      Demián Bichir           John Cho  \n1       Kristen Stewart     Vincent Cassel    Jessica Henwick  \n2       Tiffany Haddish         Rose Byrne        Salma Hayek  \n3         Josh Hartnett  Margarita Levieva     Chandler Riggs  \n4         Freya Tingley     Simon Abkarian       Rutger Hauer  \n..                  ...                ...                ...  \n150          Tom Cruise       Miles Teller  Jennifer Connelly  \n151        Nicolas Cage         Emma Stone      Ryan Reynolds  \n152     Jennifer Hudson    Forest Whitaker      Marlon Wayans  \n153          Matt Damon        Adam Driver        Jodie Comer  \n154           Tom Hanks      Helena Zengel    Neil Sandilands  \n\n[155 rows x 7 columns]","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>Title</th>\n      <th>Cast and crew</th>\n      <th>genres</th>\n      <th>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>The Grudge</td>\n      <td>Nicolas Pesce (director/screenplay); Andrea Ri...</td>\n      <td>Horror Mystery</td>\n      <td>Nicolas Pesce</td>\n      <td>Andrea Riseborough</td>\n      <td>Demián Bichir</td>\n      <td>John Cho</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Underwater</td>\n      <td>William Eubank (director); Brian Duffield, Ada...</td>\n      <td>Action Horror Science Fiction Thriller</td>\n      <td>William Eubank</td>\n      <td>Kristen Stewart</td>\n      <td>Vincent Cassel</td>\n      <td>Jessica Henwick</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Like a Boss</td>\n      <td>Miguel Arteta (director); Sam Pitman, Adam Col...</td>\n      <td>Comedy</td>\n      <td>Miguel Arteta</td>\n      <td>Tiffany Haddish</td>\n      <td>Rose Byrne</td>\n      <td>Salma Hayek</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Inherit the Viper</td>\n      <td>Anthony Jerjen (director); Andrew Crabtree (sc...</td>\n      <td>Drama Thriller Crime</td>\n      <td>Anthony Jerjen</td>\n      <td>Josh Hartnett</td>\n      <td>Margarita Levieva</td>\n      <td>Chandler Riggs</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>The Sonata</td>\n      <td>Andrew Desmond (director/screenplay); Arthur M...</td>\n      <td>Horror Thriller Mystery</td>\n      <td>Andrew Desmond</td>\n      <td>Freya Tingley</td>\n      <td>Simon Abkarian</td>\n      <td>Rutger Hauer</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>Top Gun: Maverick</td>\n      <td>Joseph Kosinski (director); Ehren Kruger, Eric...</td>\n      <td>Action Drama</td>\n      <td>Joseph Kosinski</td>\n      <td>Tom Cruise</td>\n      <td>Miles Teller</td>\n      <td>Jennifer Connelly</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>The Croods 2</td>\n      <td>Joel Crawford (director); Kevin Hageman, Dan H...</td>\n      <td>Animation Adventure Family</td>\n      <td>Joel Crawford</td>\n      <td>Nicolas Cage</td>\n      <td>Emma Stone</td>\n      <td>Ryan Reynolds</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>Respect</td>\n      <td>Liesl Tommy (director); Tracey Scott Wilson (s...</td>\n      <td>Music Drama</td>\n      <td>Liesl Tommy</td>\n      <td>Jennifer Hudson</td>\n      <td>Forest Whitaker</td>\n      <td>Marlon Wayans</td>\n    </tr>\n    <tr>\n      <th>153</th>\n      <td>The Last Duel</td>\n      <td>Ridley Scott (director); Ben Affleck, Matt Dam...</td>\n      <td>Drama</td>\n      <td>Ridley Scott</td>\n      <td>Matt Damon</td>\n      <td>Adam Driver</td>\n      <td>Jodie Comer</td>\n    </tr>\n    <tr>\n      <th>154</th>\n      <td>News of the World</td>\n      <td>Paul Greengrass (director/screenplay); Luke Da...</td>\n      <td>Drama Western</td>\n      <td>Paul Greengrass</td>\n      <td>Tom Hanks</td>\n      <td>Helena Zengel</td>\n      <td>Neil Sandilands</td>\n    </tr>\n  </tbody>\n</table>\n<p>155 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_2020 = df_2020.rename(columns={'Title':'movie_title'})","execution_count":26,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df20 = df_2020.loc[:,['director_name','actor_1_name','actor_2_name','actor_3_name','genres','movie_title']]","execution_count":27,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df20","execution_count":28,"outputs":[{"output_type":"execute_result","execution_count":28,"data":{"text/plain":"       director_name        actor_1_name       actor_2_name  \\\n0      Nicolas Pesce  Andrea Riseborough      Demián Bichir   \n1     William Eubank     Kristen Stewart     Vincent Cassel   \n2      Miguel Arteta     Tiffany Haddish         Rose Byrne   \n3     Anthony Jerjen       Josh Hartnett  Margarita Levieva   \n4     Andrew Desmond       Freya Tingley     Simon Abkarian   \n..               ...                 ...                ...   \n150  Joseph Kosinski          Tom Cruise       Miles Teller   \n151    Joel Crawford        Nicolas Cage         Emma Stone   \n152      Liesl Tommy     Jennifer Hudson    Forest Whitaker   \n153     Ridley Scott          Matt Damon        Adam Driver   \n154  Paul Greengrass           Tom Hanks      Helena Zengel   \n\n          actor_3_name                                  genres  \\\n0             John Cho                          Horror Mystery   \n1      Jessica Henwick  Action Horror Science Fiction Thriller   \n2          Salma Hayek                                  Comedy   \n3       Chandler Riggs                    Drama Thriller Crime   \n4         Rutger Hauer                 Horror Thriller Mystery   \n..                 ...                                     ...   \n150  Jennifer Connelly                            Action Drama   \n151      Ryan Reynolds              Animation Adventure Family   \n152      Marlon Wayans                             Music Drama   \n153        Jodie Comer                                   Drama   \n154    Neil Sandilands                           Drama Western   \n\n           movie_title  \n0           The Grudge  \n1           Underwater  \n2          Like a Boss  \n3    Inherit the Viper  \n4           The Sonata  \n..                 ...  \n150  Top Gun: Maverick  \n151       The Croods 2  \n152            Respect  \n153      The Last Duel  \n154  News of the World  \n\n[155 rows x 6 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Nicolas Pesce</td>\n      <td>Andrea Riseborough</td>\n      <td>Demián Bichir</td>\n      <td>John Cho</td>\n      <td>Horror Mystery</td>\n      <td>The Grudge</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>William Eubank</td>\n      <td>Kristen Stewart</td>\n      <td>Vincent Cassel</td>\n      <td>Jessica Henwick</td>\n      <td>Action Horror Science Fiction Thriller</td>\n      <td>Underwater</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Miguel Arteta</td>\n      <td>Tiffany Haddish</td>\n      <td>Rose Byrne</td>\n      <td>Salma Hayek</td>\n      <td>Comedy</td>\n      <td>Like a Boss</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Anthony Jerjen</td>\n      <td>Josh Hartnett</td>\n      <td>Margarita Levieva</td>\n      <td>Chandler Riggs</td>\n      <td>Drama Thriller Crime</td>\n      <td>Inherit the Viper</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Andrew Desmond</td>\n      <td>Freya Tingley</td>\n      <td>Simon Abkarian</td>\n      <td>Rutger Hauer</td>\n      <td>Horror Thriller Mystery</td>\n      <td>The Sonata</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>Joseph Kosinski</td>\n      <td>Tom Cruise</td>\n      <td>Miles Teller</td>\n      <td>Jennifer Connelly</td>\n      <td>Action Drama</td>\n      <td>Top Gun: Maverick</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>Joel Crawford</td>\n      <td>Nicolas Cage</td>\n      <td>Emma Stone</td>\n      <td>Ryan Reynolds</td>\n      <td>Animation Adventure Family</td>\n      <td>The Croods 2</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>Liesl Tommy</td>\n      <td>Jennifer Hudson</td>\n      <td>Forest Whitaker</td>\n      <td>Marlon Wayans</td>\n      <td>Music Drama</td>\n      <td>Respect</td>\n    </tr>\n    <tr>\n      <th>153</th>\n      <td>Ridley Scott</td>\n      <td>Matt Damon</td>\n      <td>Adam Driver</td>\n      <td>Jodie Comer</td>\n      <td>Drama</td>\n      <td>The Last Duel</td>\n    </tr>\n    <tr>\n      <th>154</th>\n      <td>Paul Greengrass</td>\n      <td>Tom Hanks</td>\n      <td>Helena Zengel</td>\n      <td>Neil Sandilands</td>\n      <td>Drama Western</td>\n      <td>News of the World</td>\n    </tr>\n  </tbody>\n</table>\n<p>155 rows × 6 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df20['comb'] = new_df20['actor_1_name'] + ' ' + new_df20['actor_2_name'] + ' '+ new_df20['actor_3_name'] + ' '+ new_df20['director_name'] +' ' + new_df20['genres']","execution_count":29,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df20 = new_df20.dropna(how='any')","execution_count":30,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df20['movie_title'] = new_df20['movie_title'].str.lower()","execution_count":31,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"Entry point for launching an IPython kernel.\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_df20","execution_count":32,"outputs":[{"output_type":"execute_result","execution_count":32,"data":{"text/plain":"       director_name        actor_1_name       actor_2_name  \\\n0      Nicolas Pesce  Andrea Riseborough      Demián Bichir   \n1     William Eubank     Kristen Stewart     Vincent Cassel   \n2      Miguel Arteta     Tiffany Haddish         Rose Byrne   \n3     Anthony Jerjen       Josh Hartnett  Margarita Levieva   \n4     Andrew Desmond       Freya Tingley     Simon Abkarian   \n..               ...                 ...                ...   \n150  Joseph Kosinski          Tom Cruise       Miles Teller   \n151    Joel Crawford        Nicolas Cage         Emma Stone   \n152      Liesl Tommy     Jennifer Hudson    Forest Whitaker   \n153     Ridley Scott          Matt Damon        Adam Driver   \n154  Paul Greengrass           Tom Hanks      Helena Zengel   \n\n          actor_3_name                                  genres  \\\n0             John Cho                          Horror Mystery   \n1      Jessica Henwick  Action Horror Science Fiction Thriller   \n2          Salma Hayek                                  Comedy   \n3       Chandler Riggs                    Drama Thriller Crime   \n4         Rutger Hauer                 Horror Thriller Mystery   \n..                 ...                                     ...   \n150  Jennifer Connelly                            Action Drama   \n151      Ryan Reynolds              Animation Adventure Family   \n152      Marlon Wayans                             Music Drama   \n153        Jodie Comer                                   Drama   \n154    Neil Sandilands                           Drama Western   \n\n           movie_title                                               comb  \n0           the grudge  Andrea Riseborough Demián Bichir John Cho Nico...  \n1           underwater  Kristen Stewart Vincent Cassel Jessica Henwick...  \n2          like a boss  Tiffany Haddish Rose Byrne Salma Hayek Miguel ...  \n3    inherit the viper  Josh Hartnett Margarita Levieva Chandler Riggs...  \n4           the sonata  Freya Tingley Simon Abkarian Rutger Hauer Andr...  \n..                 ...                                                ...  \n150  top gun: maverick  Tom Cruise Miles Teller Jennifer Connelly Jose...  \n151       the croods 2  Nicolas Cage Emma Stone Ryan Reynolds Joel Cra...  \n152            respect  Jennifer Hudson Forest Whitaker Marlon Wayans ...  \n153      the last duel  Matt Damon Adam Driver Jodie Comer Ridley Scot...  \n154  news of the world  Tom Hanks Helena Zengel Neil Sandilands Paul G...  \n\n[141 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Nicolas Pesce</td>\n      <td>Andrea Riseborough</td>\n      <td>Demián Bichir</td>\n      <td>John Cho</td>\n      <td>Horror Mystery</td>\n      <td>the grudge</td>\n      <td>Andrea Riseborough Demián Bichir John Cho Nico...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>William Eubank</td>\n      <td>Kristen Stewart</td>\n      <td>Vincent Cassel</td>\n      <td>Jessica Henwick</td>\n      <td>Action Horror Science Fiction Thriller</td>\n      <td>underwater</td>\n      <td>Kristen Stewart Vincent Cassel Jessica Henwick...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Miguel Arteta</td>\n      <td>Tiffany Haddish</td>\n      <td>Rose Byrne</td>\n      <td>Salma Hayek</td>\n      <td>Comedy</td>\n      <td>like a boss</td>\n      <td>Tiffany Haddish Rose Byrne Salma Hayek Miguel ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Anthony Jerjen</td>\n      <td>Josh Hartnett</td>\n      <td>Margarita Levieva</td>\n      <td>Chandler Riggs</td>\n      <td>Drama Thriller Crime</td>\n      <td>inherit the viper</td>\n      <td>Josh Hartnett Margarita Levieva Chandler Riggs...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Andrew Desmond</td>\n      <td>Freya Tingley</td>\n      <td>Simon Abkarian</td>\n      <td>Rutger Hauer</td>\n      <td>Horror Thriller Mystery</td>\n      <td>the sonata</td>\n      <td>Freya Tingley Simon Abkarian Rutger Hauer Andr...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>150</th>\n      <td>Joseph Kosinski</td>\n      <td>Tom Cruise</td>\n      <td>Miles Teller</td>\n      <td>Jennifer Connelly</td>\n      <td>Action Drama</td>\n      <td>top gun: maverick</td>\n      <td>Tom Cruise Miles Teller Jennifer Connelly Jose...</td>\n    </tr>\n    <tr>\n      <th>151</th>\n      <td>Joel Crawford</td>\n      <td>Nicolas Cage</td>\n      <td>Emma Stone</td>\n      <td>Ryan Reynolds</td>\n      <td>Animation Adventure Family</td>\n      <td>the croods 2</td>\n      <td>Nicolas Cage Emma Stone Ryan Reynolds Joel Cra...</td>\n    </tr>\n    <tr>\n      <th>152</th>\n      <td>Liesl Tommy</td>\n      <td>Jennifer Hudson</td>\n      <td>Forest Whitaker</td>\n      <td>Marlon Wayans</td>\n      <td>Music Drama</td>\n      <td>respect</td>\n      <td>Jennifer Hudson Forest Whitaker Marlon Wayans ...</td>\n    </tr>\n    <tr>\n      <th>153</th>\n      <td>Ridley Scott</td>\n      <td>Matt Damon</td>\n      <td>Adam Driver</td>\n      <td>Jodie Comer</td>\n      <td>Drama</td>\n      <td>the last duel</td>\n      <td>Matt Damon Adam Driver Jodie Comer Ridley Scot...</td>\n    </tr>\n    <tr>\n      <th>154</th>\n      <td>Paul Greengrass</td>\n      <td>Tom Hanks</td>\n      <td>Helena Zengel</td>\n      <td>Neil Sandilands</td>\n      <td>Drama Western</td>\n      <td>news of the world</td>\n      <td>Tom Hanks Helena Zengel Neil Sandilands Paul G...</td>\n    </tr>\n  </tbody>\n</table>\n<p>141 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"old_df = pd.read_csv('../input/final_data.csv')","execution_count":34,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"old_df","execution_count":35,"outputs":[{"output_type":"execute_result","execution_count":35,"data":{"text/plain":"               director_name       actor_1_name          actor_2_name  \\\n0              John Lasseter          Tom Hanks             Tim Allen   \n1               Joe Johnston     Robin Williams         Jonathan Hyde   \n2              Howard Deutch     Walter Matthau           Jack Lemmon   \n3            Forest Whitaker    Whitney Houston        Angela Bassett   \n4              Charles Shyer       Steve Martin          Diane Keaton   \n...                      ...                ...                   ...   \n36841           Greta Gerwig      Saoirse Ronan           Emma Watson   \n36842             Sam Mendes      George MacKay  Dean-Charles Chapman   \n36843  Destin Daniel Cretton  Michael B. Jordan            Jamie Foxx   \n36844        Chinonye Chukwu      Alfre Woodard        Wendell Pierce   \n36845           Waymon Boone        Mena Suvari          Kevin Pollak   \n\n         actor_3_name                    genres                  movie_title  \\\n0         Don Rickles   Animation Comedy Family                    toy story   \n1       Kirsten Dunst  Adventure Fantasy Family                      jumanji   \n2         Ann-Margret            Romance Comedy             grumpier old men   \n3      Loretta Devine      Comedy Drama Romance            waiting to exhale   \n4        Martin Short                    Comedy  father of the bride part ii   \n...               ...                       ...                          ...   \n36841   Florence Pugh             Drama Romance                 little women   \n36842     Mark Strong  War Drama Action History                         1917   \n36843     Brie Larson               Drama Crime                   just mercy   \n36844     Aldis Hodge                     Drama                     clemency   \n36845         unknown           Horror Thriller                   apparition   \n\n                                                    comb  \n0      Tom Hanks Tim Allen Don Rickles John Lasseter ...  \n1      Robin Williams Jonathan Hyde Kirsten Dunst Joe...  \n2      Walter Matthau Jack Lemmon Ann-Margret Howard ...  \n3      Whitney Houston Angela Bassett Loretta Devine ...  \n4      Steve Martin Diane Keaton Martin Short Charles...  \n...                                                  ...  \n36841  Saoirse Ronan Emma Watson Florence Pugh Greta ...  \n36842  George MacKay Dean-Charles Chapman Mark Strong...  \n36843  Michael B. Jordan Jamie Foxx Brie Larson Desti...  \n36844  Alfre Woodard Wendell Pierce Aldis Hodge Chino...  \n36845  Mena Suvari Kevin Pollak unknown Waymon Boone ...  \n\n[36846 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>toy story</td>\n      <td>Tom Hanks Tim Allen Don Rickles John Lasseter ...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>jumanji</td>\n      <td>Robin Williams Jonathan Hyde Kirsten Dunst Joe...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>grumpier old men</td>\n      <td>Walter Matthau Jack Lemmon Ann-Margret Howard ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>waiting to exhale</td>\n      <td>Whitney Houston Angela Bassett Loretta Devine ...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>father of the bride part ii</td>\n      <td>Steve Martin Diane Keaton Martin Short Charles...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>36841</th>\n      <td>Greta Gerwig</td>\n      <td>Saoirse Ronan</td>\n      <td>Emma Watson</td>\n      <td>Florence Pugh</td>\n      <td>Drama Romance</td>\n      <td>little women</td>\n      <td>Saoirse Ronan Emma Watson Florence Pugh Greta ...</td>\n    </tr>\n    <tr>\n      <th>36842</th>\n      <td>Sam Mendes</td>\n      <td>George MacKay</td>\n      <td>Dean-Charles Chapman</td>\n      <td>Mark Strong</td>\n      <td>War Drama Action History</td>\n      <td>1917</td>\n      <td>George MacKay Dean-Charles Chapman Mark Strong...</td>\n    </tr>\n    <tr>\n      <th>36843</th>\n      <td>Destin Daniel Cretton</td>\n      <td>Michael B. Jordan</td>\n      <td>Jamie Foxx</td>\n      <td>Brie Larson</td>\n      <td>Drama Crime</td>\n      <td>just mercy</td>\n      <td>Michael B. Jordan Jamie Foxx Brie Larson Desti...</td>\n    </tr>\n    <tr>\n      <th>36844</th>\n      <td>Chinonye Chukwu</td>\n      <td>Alfre Woodard</td>\n      <td>Wendell Pierce</td>\n      <td>Aldis Hodge</td>\n      <td>Drama</td>\n      <td>clemency</td>\n      <td>Alfre Woodard Wendell Pierce Aldis Hodge Chino...</td>\n    </tr>\n    <tr>\n      <th>36845</th>\n      <td>Waymon Boone</td>\n      <td>Mena Suvari</td>\n      <td>Kevin Pollak</td>\n      <td>unknown</td>\n      <td>Horror Thriller</td>\n      <td>apparition</td>\n      <td>Mena Suvari Kevin Pollak unknown Waymon Boone ...</td>\n    </tr>\n  </tbody>\n</table>\n<p>36846 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df = old_df.append(new_df20,ignore_index=True)","execution_count":36,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df","execution_count":37,"outputs":[{"output_type":"execute_result","execution_count":37,"data":{"text/plain":"         director_name     actor_1_name     actor_2_name       actor_3_name  \\\n0        John Lasseter        Tom Hanks        Tim Allen        Don Rickles   \n1         Joe Johnston   Robin Williams    Jonathan Hyde      Kirsten Dunst   \n2        Howard Deutch   Walter Matthau      Jack Lemmon        Ann-Margret   \n3      Forest Whitaker  Whitney Houston   Angela Bassett     Loretta Devine   \n4        Charles Shyer     Steve Martin     Diane Keaton       Martin Short   \n...                ...              ...              ...                ...   \n36982  Joseph Kosinski       Tom Cruise     Miles Teller  Jennifer Connelly   \n36983    Joel Crawford     Nicolas Cage       Emma Stone      Ryan Reynolds   \n36984      Liesl Tommy  Jennifer Hudson  Forest Whitaker      Marlon Wayans   \n36985     Ridley Scott       Matt Damon      Adam Driver        Jodie Comer   \n36986  Paul Greengrass        Tom Hanks    Helena Zengel    Neil Sandilands   \n\n                           genres                  movie_title  \\\n0         Animation Comedy Family                    toy story   \n1        Adventure Fantasy Family                      jumanji   \n2                  Romance Comedy             grumpier old men   \n3            Comedy Drama Romance            waiting to exhale   \n4                          Comedy  father of the bride part ii   \n...                           ...                          ...   \n36982                Action Drama            top gun: maverick   \n36983  Animation Adventure Family                 the croods 2   \n36984                 Music Drama                      respect   \n36985                       Drama                the last duel   \n36986               Drama Western            news of the world   \n\n                                                    comb  \n0      Tom Hanks Tim Allen Don Rickles John Lasseter ...  \n1      Robin Williams Jonathan Hyde Kirsten Dunst Joe...  \n2      Walter Matthau Jack Lemmon Ann-Margret Howard ...  \n3      Whitney Houston Angela Bassett Loretta Devine ...  \n4      Steve Martin Diane Keaton Martin Short Charles...  \n...                                                  ...  \n36982  Tom Cruise Miles Teller Jennifer Connelly Jose...  \n36983  Nicolas Cage Emma Stone Ryan Reynolds Joel Cra...  \n36984  Jennifer Hudson Forest Whitaker Marlon Wayans ...  \n36985  Matt Damon Adam Driver Jodie Comer Ridley Scot...  \n36986  Tom Hanks Helena Zengel Neil Sandilands Paul G...  \n\n[36987 rows x 7 columns]","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>director_name</th>\n      <th>actor_1_name</th>\n      <th>actor_2_name</th>\n      <th>actor_3_name</th>\n      <th>genres</th>\n      <th>movie_title</th>\n      <th>comb</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>John Lasseter</td>\n      <td>Tom Hanks</td>\n      <td>Tim Allen</td>\n      <td>Don Rickles</td>\n      <td>Animation Comedy Family</td>\n      <td>toy story</td>\n      <td>Tom Hanks Tim Allen Don Rickles John Lasseter ...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Joe Johnston</td>\n      <td>Robin Williams</td>\n      <td>Jonathan Hyde</td>\n      <td>Kirsten Dunst</td>\n      <td>Adventure Fantasy Family</td>\n      <td>jumanji</td>\n      <td>Robin Williams Jonathan Hyde Kirsten Dunst Joe...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Howard Deutch</td>\n      <td>Walter Matthau</td>\n      <td>Jack Lemmon</td>\n      <td>Ann-Margret</td>\n      <td>Romance Comedy</td>\n      <td>grumpier old men</td>\n      <td>Walter Matthau Jack Lemmon Ann-Margret Howard ...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Forest Whitaker</td>\n      <td>Whitney Houston</td>\n      <td>Angela Bassett</td>\n      <td>Loretta Devine</td>\n      <td>Comedy Drama Romance</td>\n      <td>waiting to exhale</td>\n      <td>Whitney Houston Angela Bassett Loretta Devine ...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Charles Shyer</td>\n      <td>Steve Martin</td>\n      <td>Diane Keaton</td>\n      <td>Martin Short</td>\n      <td>Comedy</td>\n      <td>father of the bride part ii</td>\n      <td>Steve Martin Diane Keaton Martin Short Charles...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>36982</th>\n      <td>Joseph Kosinski</td>\n      <td>Tom Cruise</td>\n      <td>Miles Teller</td>\n      <td>Jennifer Connelly</td>\n      <td>Action Drama</td>\n      <td>top gun: maverick</td>\n      <td>Tom Cruise Miles Teller Jennifer Connelly Jose...</td>\n    </tr>\n    <tr>\n      <th>36983</th>\n      <td>Joel Crawford</td>\n      <td>Nicolas Cage</td>\n      <td>Emma Stone</td>\n      <td>Ryan Reynolds</td>\n      <td>Animation Adventure Family</td>\n      <td>the croods 2</td>\n      <td>Nicolas Cage Emma Stone Ryan Reynolds Joel Cra...</td>\n    </tr>\n    <tr>\n      <th>36984</th>\n      <td>Liesl Tommy</td>\n      <td>Jennifer Hudson</td>\n      <td>Forest Whitaker</td>\n      <td>Marlon Wayans</td>\n      <td>Music Drama</td>\n      <td>respect</td>\n      <td>Jennifer Hudson Forest Whitaker Marlon Wayans ...</td>\n    </tr>\n    <tr>\n      <th>36985</th>\n      <td>Ridley Scott</td>\n      <td>Matt Damon</td>\n      <td>Adam Driver</td>\n      <td>Jodie Comer</td>\n      <td>Drama</td>\n      <td>the last duel</td>\n      <td>Matt Damon Adam Driver Jodie Comer Ridley Scot...</td>\n    </tr>\n    <tr>\n      <th>36986</th>\n      <td>Paul Greengrass</td>\n      <td>Tom Hanks</td>\n      <td>Helena Zengel</td>\n      <td>Neil Sandilands</td>\n      <td>Drama Western</td>\n      <td>news of the world</td>\n      <td>Tom Hanks Helena Zengel Neil Sandilands Paul G...</td>\n    </tr>\n  </tbody>\n</table>\n<p>36987 rows × 7 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"final_df.to_csv('main_data.csv',index=False)","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}


--------------------------------------------------------------------------------
/.ipynb_checkpoints/sentiment.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "code",
  5 |    "execution_count": 15,
  6 |    "metadata": {},
  7 |    "outputs": [],
  8 |    "source": [
  9 |     "import pandas as pd\n",
 10 |     "import numpy as np\n",
 11 |     "import nltk\n",
 12 |     "from nltk.corpus import stopwords\n",
 13 |     "from sklearn.feature_extraction.text import TfidfVectorizer\n",
 14 |     "from sklearn.model_selection import train_test_split\n",
 15 |     "from sklearn import naive_bayes\n",
 16 |     "from sklearn.metrics import roc_auc_score,accuracy_score\n",
 17 |     "import pickle"
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "code",
 22 |    "execution_count": 2,
 23 |    "metadata": {},
 24 |    "outputs": [
 25 |     {
 26 |      "name": "stderr",
 27 |      "output_type": "stream",
 28 |      "text": [
 29 |       "[nltk_data] Downloading package stopwords to\n",
 30 |       "[nltk_data]     C:\\Users\\tharun\\AppData\\Roaming\\nltk_data...\n",
 31 |       "[nltk_data]   Unzipping corpora\\stopwords.zip.\n"
 32 |      ]
 33 |     },
 34 |     {
 35 |      "data": {
 36 |       "text/plain": [
 37 |        "True"
 38 |       ]
 39 |      },
 40 |      "execution_count": 2,
 41 |      "metadata": {},
 42 |      "output_type": "execute_result"
 43 |     }
 44 |    ],
 45 |    "source": [
 46 |     "nltk.download(\"stopwords\")"
 47 |    ]
 48 |   },
 49 |   {
 50 |    "cell_type": "code",
 51 |    "execution_count": 3,
 52 |    "metadata": {},
 53 |    "outputs": [],
 54 |    "source": [
 55 |     "dataset = pd.read_csv('reviews.txt',sep = '\\t', names =['Reviews','Comments'])"
 56 |    ]
 57 |   },
 58 |   {
 59 |    "cell_type": "code",
 60 |    "execution_count": 4,
 61 |    "metadata": {},
 62 |    "outputs": [
 63 |     {
 64 |      "data": {
 65 |       "text/html": [
 66 |        "<div>\n",
 67 |        "<style scoped>\n",
 68 |        "    .dataframe tbody tr th:only-of-type {\n",
 69 |        "        vertical-align: middle;\n",
 70 |        "    }\n",
 71 |        "\n",
 72 |        "    .dataframe tbody tr th {\n",
 73 |        "        vertical-align: top;\n",
 74 |        "    }\n",
 75 |        "\n",
 76 |        "    .dataframe thead th {\n",
 77 |        "        text-align: right;\n",
 78 |        "    }\n",
 79 |        "</style>\n",
 80 |        "<table border=\"1\" class=\"dataframe\">\n",
 81 |        "  <thead>\n",
 82 |        "    <tr style=\"text-align: right;\">\n",
 83 |        "      <th></th>\n",
 84 |        "      <th>Reviews</th>\n",
 85 |        "      <th>Comments</th>\n",
 86 |        "    </tr>\n",
 87 |        "  </thead>\n",
 88 |        "  <tbody>\n",
 89 |        "    <tr>\n",
 90 |        "      <th>0</th>\n",
 91 |        "      <td>1</td>\n",
 92 |        "      <td>The Da Vinci Code book is just awesome.</td>\n",
 93 |        "    </tr>\n",
 94 |        "    <tr>\n",
 95 |        "      <th>1</th>\n",
 96 |        "      <td>1</td>\n",
 97 |        "      <td>this was the first clive cussler i've ever rea...</td>\n",
 98 |        "    </tr>\n",
 99 |        "    <tr>\n",
100 |        "      <th>2</th>\n",
101 |        "      <td>1</td>\n",
102 |        "      <td>i liked the Da Vinci Code a lot.</td>\n",
103 |        "    </tr>\n",
104 |        "    <tr>\n",
105 |        "      <th>3</th>\n",
106 |        "      <td>1</td>\n",
107 |        "      <td>i liked the Da Vinci Code a lot.</td>\n",
108 |        "    </tr>\n",
109 |        "    <tr>\n",
110 |        "      <th>4</th>\n",
111 |        "      <td>1</td>\n",
112 |        "      <td>I liked the Da Vinci Code but it ultimatly did...</td>\n",
113 |        "    </tr>\n",
114 |        "    <tr>\n",
115 |        "      <th>...</th>\n",
116 |        "      <td>...</td>\n",
117 |        "      <td>...</td>\n",
118 |        "    </tr>\n",
119 |        "    <tr>\n",
120 |        "      <th>6913</th>\n",
121 |        "      <td>0</td>\n",
122 |        "      <td>Brokeback Mountain was boring.</td>\n",
123 |        "    </tr>\n",
124 |        "    <tr>\n",
125 |        "      <th>6914</th>\n",
126 |        "      <td>0</td>\n",
127 |        "      <td>So Brokeback Mountain was really depressing.</td>\n",
128 |        "    </tr>\n",
129 |        "    <tr>\n",
130 |        "      <th>6915</th>\n",
131 |        "      <td>0</td>\n",
132 |        "      <td>As I sit here, watching the MTV Movie Awards, ...</td>\n",
133 |        "    </tr>\n",
134 |        "    <tr>\n",
135 |        "      <th>6916</th>\n",
136 |        "      <td>0</td>\n",
137 |        "      <td>Ok brokeback mountain is such a horrible movie.</td>\n",
138 |        "    </tr>\n",
139 |        "    <tr>\n",
140 |        "      <th>6917</th>\n",
141 |        "      <td>0</td>\n",
142 |        "      <td>Oh, and Brokeback Mountain was a terrible movie.</td>\n",
143 |        "    </tr>\n",
144 |        "  </tbody>\n",
145 |        "</table>\n",
146 |        "<p>6918 rows × 2 columns</p>\n",
147 |        "</div>"
148 |       ],
149 |       "text/plain": [
150 |        "      Reviews                                           Comments\n",
151 |        "0           1            The Da Vinci Code book is just awesome.\n",
152 |        "1           1  this was the first clive cussler i've ever rea...\n",
153 |        "2           1                   i liked the Da Vinci Code a lot.\n",
154 |        "3           1                   i liked the Da Vinci Code a lot.\n",
155 |        "4           1  I liked the Da Vinci Code but it ultimatly did...\n",
156 |        "...       ...                                                ...\n",
157 |        "6913        0                     Brokeback Mountain was boring.\n",
158 |        "6914        0       So Brokeback Mountain was really depressing.\n",
159 |        "6915        0  As I sit here, watching the MTV Movie Awards, ...\n",
160 |        "6916        0    Ok brokeback mountain is such a horrible movie.\n",
161 |        "6917        0   Oh, and Brokeback Mountain was a terrible movie.\n",
162 |        "\n",
163 |        "[6918 rows x 2 columns]"
164 |       ]
165 |      },
166 |      "execution_count": 4,
167 |      "metadata": {},
168 |      "output_type": "execute_result"
169 |     }
170 |    ],
171 |    "source": [
172 |     "dataset"
173 |    ]
174 |   },
175 |   {
176 |    "cell_type": "code",
177 |    "execution_count": 5,
178 |    "metadata": {},
179 |    "outputs": [],
180 |    "source": [
181 |     "stopset = set(stopwords.words('english'))"
182 |    ]
183 |   },
184 |   {
185 |    "cell_type": "code",
186 |    "execution_count": 6,
187 |    "metadata": {},
188 |    "outputs": [],
189 |    "source": [
190 |     "vectorizer = TfidfVectorizer(use_idf = True,lowercase = True, strip_accents='ascii',stop_words=stopset)"
191 |    ]
192 |   },
193 |   {
194 |    "cell_type": "code",
195 |    "execution_count": 16,
196 |    "metadata": {},
197 |    "outputs": [],
198 |    "source": [
199 |     "X = vectorizer.fit_transform(dataset.Comments)\n",
200 |     "y = dataset.Reviews\n",
201 |     "pickle.dump(vectorizer, open('tranform.pkl', 'wb'))"
202 |    ]
203 |   },
204 |   {
205 |    "cell_type": "code",
206 |    "execution_count": 17,
207 |    "metadata": {},
208 |    "outputs": [],
209 |    "source": [
210 |     "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)"
211 |    ]
212 |   },
213 |   {
214 |    "cell_type": "code",
215 |    "execution_count": 18,
216 |    "metadata": {},
217 |    "outputs": [
218 |     {
219 |      "data": {
220 |       "text/plain": [
221 |        "MultinomialNB()"
222 |       ]
223 |      },
224 |      "execution_count": 18,
225 |      "metadata": {},
226 |      "output_type": "execute_result"
227 |     }
228 |    ],
229 |    "source": [
230 |     "clf = naive_bayes.MultinomialNB()\n",
231 |     "clf.fit(X_train,y_train)"
232 |    ]
233 |   },
234 |   {
235 |    "cell_type": "code",
236 |    "execution_count": 19,
237 |    "metadata": {},
238 |    "outputs": [
239 |     {
240 |      "data": {
241 |       "text/plain": [
242 |        "97.47109826589595"
243 |       ]
244 |      },
245 |      "execution_count": 19,
246 |      "metadata": {},
247 |      "output_type": "execute_result"
248 |     }
249 |    ],
250 |    "source": [
251 |     "accuracy_score(y_test,clf.predict(X_test))*100"
252 |    ]
253 |   },
254 |   {
255 |    "cell_type": "code",
256 |    "execution_count": 20,
257 |    "metadata": {},
258 |    "outputs": [
259 |     {
260 |      "data": {
261 |       "text/plain": [
262 |        "MultinomialNB()"
263 |       ]
264 |      },
265 |      "execution_count": 20,
266 |      "metadata": {},
267 |      "output_type": "execute_result"
268 |     }
269 |    ],
270 |    "source": [
271 |     "clf = naive_bayes.MultinomialNB()\n",
272 |     "clf.fit(X,y)"
273 |    ]
274 |   },
275 |   {
276 |    "cell_type": "code",
277 |    "execution_count": 21,
278 |    "metadata": {},
279 |    "outputs": [
280 |     {
281 |      "data": {
282 |       "text/plain": [
283 |        "98.77167630057804"
284 |       ]
285 |      },
286 |      "execution_count": 21,
287 |      "metadata": {},
288 |      "output_type": "execute_result"
289 |     }
290 |    ],
291 |    "source": [
292 |     "accuracy_score(y_test,clf.predict(X_test))*100"
293 |    ]
294 |   },
295 |   {
296 |    "cell_type": "code",
297 |    "execution_count": 22,
298 |    "metadata": {},
299 |    "outputs": [],
300 |    "source": [
301 |     "filename = 'nlp_model.pkl'\n",
302 |     "pickle.dump(clf, open(filename, 'wb'))"
303 |    ]
304 |   }
305 |  ],
306 |  "metadata": {
307 |   "kernelspec": {
308 |    "display_name": "Python 3",
309 |    "language": "python",
310 |    "name": "python3"
311 |   },
312 |   "language_info": {
313 |    "codemirror_mode": {
314 |     "name": "ipython",
315 |     "version": 3
316 |    },
317 |    "file_extension": ".py",
318 |    "mimetype": "text/x-python",
319 |    "name": "python",
320 |    "nbconvert_exporter": "python",
321 |    "pygments_lexer": "ipython3",
322 |    "version": "3.8.3"
323 |   }
324 |  },
325 |  "nbformat": 4,
326 |  "nbformat_minor": 4
327 | }
328 | 


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/Procfile:
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1 | web: gunicorn main:app


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/README.md:
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 1 | # Movie-Recommendation-System
 2 | 
 3 | This application provides all the details of the requested movie such as overview, genre, release date, rating, runtime, top cast, reviews, recommended movies, etc.
 4 | 
 5 | The details of the movies(title, genre, runtime, ratings, posters, etc) are fetched using an API by TMDB, https://www.themoviedb.org, and using the IMDB id of the movie in the API, I did web scraping to get the reviews given by the user in the IMDB site using `beautifulsoup4` and performed sentiment analysis on those reviews.
 6 | 
 7 | ## Link to the application
 8 | 
 9 | Check out the live demo: https://lookupforcinema.herokuapp.com
10 | 
11 | # Medium Article About My Project
12 | 
13 | https://medium.com/analytics-vidhya/build-a-movie-recommendation-flask-based-deployment-8e2970f1f5f1
14 | 
15 | ## Finding similar movies
16 | ### Without taking content into account (Just based on ratings)
17 | 
18 | Here just based on the ratings of the users for different movies, we use K nearest neighbours algorithm to find the movies which are similar.
19 | 
20 | ### With taking Content into account
21 | 
22 | Here we just information about the movies, in this case the information of genres to predict the most similar movies.
23 | 
24 | ## Matrix Factorisation(Collabarative Filtering)
25 | 
26 | Two approaches were tried to do matrix factorisation, the low rank method is very slow, so used scipy's SVD for sparse matrix.
27 | 
28 | ## Architecture
29 | 
30 | ![110212434-597bb700-7ec1-11eb-9ffa-7ac319e33123](https://user-images.githubusercontent.com/41158838/140876791-13716f4e-7e62-4f1e-8f06-155ce8360f16.jpg)
31 | 
32 | ## Deep Learning Methods
33 | 
34 | One popular recommender systems approach is called Matrix Factorisation. It works on the principle that we can learn a low-dimensional representation (embedding) of user and movie. For example, for each movie, we can have how much action it has, how long it is, and so on. For each user, we can encode how much they like action, or how much they like long movies, etc. Thus, we can combine the user and the movie embeddings to estimate the ratings on unseen movies. This approach can also be viewed as: given a matrix (A [M X N]) containing users and movies, we want to estimate low dimensional matrices (W [M X k] and H [M X k]), such that: A≈W.H<sup>T</sub>
35 | ### 1.Matrix Factorisation based on Deep learning
36 | ### 2. Matrix Factorisation based on Deep learning with non negative embeddings.
37 | ### 3. Advanced neural network with different number of embeddings for both and movies.
38 | 
39 | ## Required Tools
40 | 
41 | 1. Keras
42 | 2. Scipy
43 | 3. Numpy
44 | 4. Pandas
45 | 5. python 3
46 | 
47 | ### Sources of the datasets 
48 | 
49 | 1. [IMDB 5000 Movie Dataset](https://www.kaggle.com/carolzhangdc/imdb-5000-movie-dataset)
50 | 2. [The Movies Dataset](https://www.kaggle.com/rounakbanik/the-movies-dataset)
51 | 3. [List of movies in 2018](https://en.wikipedia.org/wiki/List_of_American_films_of_2018)
52 | 4. [List of movies in 2019](https://en.wikipedia.org/wiki/List_of_American_films_of_2019)
53 | 5. [List of movies in 2020](https://en.wikipedia.org/wiki/List_of_American_films_of_2020)
54 | 
55 | ### Please do ⭐ the repository, if it helped you in anyways
56 | 


--------------------------------------------------------------------------------
/main.py:
--------------------------------------------------------------------------------
  1 | import numpy as np
  2 | import pandas as pd
  3 | from flask import Flask, render_template, request
  4 | from sklearn.feature_extraction.text import CountVectorizer
  5 | from sklearn.metrics.pairwise import cosine_similarity
  6 | import json
  7 | import bs4 as bs
  8 | import urllib.request
  9 | import pickle
 10 | import requests
 11 | from datetime import date, datetime
 12 | 
 13 | # load the nlp model and tfidf vectorizer from disk
 14 | filename = 'nlp_model.pkl'
 15 | clf = pickle.load(open(filename, 'rb'))
 16 | vectorizer = pickle.load(open('tranform.pkl','rb'))
 17 |     
 18 | # converting list of string to list (eg. "["abc","def"]" to ["abc","def"])
 19 | def convert_to_list(my_list):
 20 |     my_list = my_list.split('","')
 21 |     my_list[0] = my_list[0].replace('["','')
 22 |     my_list[-1] = my_list[-1].replace('"]','')
 23 |     return my_list
 24 | 
 25 | # convert list of numbers to list (eg. "[1,2,3]" to [1,2,3])
 26 | def convert_to_list_num(my_list):
 27 |     my_list = my_list.split(',')
 28 |     my_list[0] = my_list[0].replace("[","")
 29 |     my_list[-1] = my_list[-1].replace("]","")
 30 |     return my_list
 31 | 
 32 | def get_suggestions():
 33 |     data = pd.read_csv('main_data.csv')
 34 |     return list(data['movie_title'].str.capitalize())
 35 | 
 36 | app = Flask(__name__)
 37 | 
 38 | @app.route("/")
 39 | @app.route("/home")
 40 | def home():
 41 |     suggestions = get_suggestions()
 42 |     return render_template('home.html',suggestions=suggestions)
 43 | 
 44 | 
 45 | @app.route("/recommend",methods=["POST"])
 46 | def recommend():
 47 |     # getting data from AJAX request
 48 |     title = request.form['title']
 49 |     cast_ids = request.form['cast_ids']
 50 |     cast_names = request.form['cast_names']
 51 |     cast_chars = request.form['cast_chars']
 52 |     cast_bdays = request.form['cast_bdays']
 53 |     cast_bios = request.form['cast_bios']
 54 |     cast_places = request.form['cast_places']
 55 |     cast_profiles = request.form['cast_profiles']
 56 |     imdb_id = request.form['imdb_id']
 57 |     poster = request.form['poster']
 58 |     genres = request.form['genres']
 59 |     overview = request.form['overview']
 60 |     vote_average = request.form['rating']
 61 |     vote_count = request.form['vote_count']
 62 |     rel_date = request.form['rel_date']
 63 |     release_date = request.form['release_date']
 64 |     runtime = request.form['runtime']
 65 |     status = request.form['status']
 66 |     rec_movies = request.form['rec_movies']
 67 |     rec_posters = request.form['rec_posters']
 68 |     rec_movies_org = request.form['rec_movies_org']
 69 |     rec_year = request.form['rec_year']
 70 |     rec_vote = request.form['rec_vote']
 71 | 
 72 |     # get movie suggestions for auto complete
 73 |     suggestions = get_suggestions()
 74 | 
 75 |     # call the convert_to_list function for every string that needs to be converted to list
 76 |     rec_movies_org = convert_to_list(rec_movies_org)
 77 |     rec_movies = convert_to_list(rec_movies)
 78 |     rec_posters = convert_to_list(rec_posters)
 79 |     cast_names = convert_to_list(cast_names)
 80 |     cast_chars = convert_to_list(cast_chars)
 81 |     cast_profiles = convert_to_list(cast_profiles)
 82 |     cast_bdays = convert_to_list(cast_bdays)
 83 |     cast_bios = convert_to_list(cast_bios)
 84 |     cast_places = convert_to_list(cast_places)
 85 |     
 86 |     # convert string to list (eg. "[1,2,3]" to [1,2,3])
 87 |     cast_ids = convert_to_list_num(cast_ids)
 88 |     rec_vote = convert_to_list_num(rec_vote)
 89 |     rec_year = convert_to_list_num(rec_year)
 90 |     
 91 |     # rendering the string to python string
 92 |     for i in range(len(cast_bios)):
 93 |         cast_bios[i] = cast_bios[i].replace(r'\n', '\n').replace(r'\"','\"')
 94 | 
 95 |     for i in range(len(cast_chars)):
 96 |         cast_chars[i] = cast_chars[i].replace(r'\n', '\n').replace(r'\"','\"') 
 97 |     
 98 |     # combining multiple lists as a dictionary which can be passed to the html file so that it can be processed easily and the order of information will be preserved
 99 |     movie_cards = {rec_posters[i]: [rec_movies[i],rec_movies_org[i],rec_vote[i],rec_year[i]] for i in range(len(rec_posters))}
100 | 
101 |     casts = {cast_names[i]:[cast_ids[i], cast_chars[i], cast_profiles[i]] for i in range(len(cast_profiles))}
102 | 
103 |     cast_details = {cast_names[i]:[cast_ids[i], cast_profiles[i], cast_bdays[i], cast_places[i], cast_bios[i]] for i in range(len(cast_places))}
104 | 
105 |     # web scraping to get user reviews from IMDB site
106 |     sauce = urllib.request.urlopen('https://www.imdb.com/title/{}/reviews?ref_=tt_ov_rt'.format(imdb_id)).read()
107 |     soup = bs.BeautifulSoup(sauce,'lxml')
108 |     soup_result = soup.find_all("div",{"class":"text show-more__control"})
109 | 
110 |     reviews_list = [] # list of reviews
111 |     reviews_status = [] # list of comments (good or bad)
112 |     for reviews in soup_result:
113 |         if reviews.string:
114 |             reviews_list.append(reviews.string)
115 |             # passing the review to our model
116 |             movie_review_list = np.array([reviews.string])
117 |             movie_vector = vectorizer.transform(movie_review_list)
118 |             pred = clf.predict(movie_vector)
119 |             reviews_status.append('Positive' if pred else 'Negative')
120 | 
121 |     # getting current date
122 |     movie_rel_date = ""
123 |     curr_date = ""
124 |     if(rel_date):
125 |         today = str(date.today())
126 |         curr_date = datetime.strptime(today,'%Y-%m-%d')
127 |         movie_rel_date = datetime.strptime(rel_date, '%Y-%m-%d')
128 | 
129 |     # combining reviews and comments into a dictionary
130 |     movie_reviews = {reviews_list[i]: reviews_status[i] for i in range(len(reviews_list))}     
131 | 
132 |     # passing all the data to the html file
133 |     return render_template('recommend.html',title=title,poster=poster,overview=overview,vote_average=vote_average,
134 |         vote_count=vote_count,release_date=release_date,movie_rel_date=movie_rel_date,curr_date=curr_date,runtime=runtime,status=status,genres=genres,movie_cards=movie_cards,reviews=movie_reviews,casts=casts,cast_details=cast_details)
135 | 
136 | if __name__ == '__main__':
137 |     app.run(debug=True)
138 | 


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/nlp_model.pkl:
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https://raw.githubusercontent.com/Tharun-tharun/Movie-Recommendation-System-with-Sentiment-Analysis/fc73e55a6dd98283c45aadcdd3fd43c8fc4f24d3/nlp_model.pkl


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/requirements.txt:
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 1 | Flask==1.1.1
 2 | gunicorn==19.9.0
 3 | Jinja2==2.11.3
 4 | MarkupSafe==1.1.1
 5 | Werkzeug==0.15.5
 6 | numpy>=1.9.2
 7 | scipy>=0.15.1
 8 | nltk>=3.6.4
 9 | scikit-learn>=0.18
10 | pandas>=0.19
11 | beautifulsoup4==4.9.1
12 | jsonschema==3.2.0
13 | tmdbv3api==1.6.1
14 | lxml==4.9.1
15 | urllib3
16 | requests
17 | pickleshare==0.7.5
18 | 


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/static/autocomplete.js:
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 1 | new autoComplete({
 2 |     data: {                              // Data src [Array, Function, Async] | (REQUIRED)
 3 |       src: films,
 4 |     },
 5 |     selector: "#autoComplete",           // Input field selector              | (Optional)
 6 |     threshold: 2,                        // Min. Chars length to start Engine | (Optional)
 7 |     debounce: 100,                       // Post duration for engine to start | (Optional)
 8 |     searchEngine: "strict",              // Search Engine type/mode           | (Optional)
 9 |     resultsList: {                       // Rendered results list object      | (Optional)
10 |         render: true,
11 |         container: source => {
12 |             source.setAttribute("id", "food_list");
13 |         },
14 |         destination: document.querySelector("#autoComplete"),
15 |         position: "afterend",
16 |         element: "ul"
17 |     },
18 |     maxResults: 5,                         // Max. number of rendered results | (Optional)
19 |     highlight: true,                       // Highlight matching results      | (Optional)
20 |     resultItem: {                          // Rendered result item            | (Optional)
21 |         content: (data, source) => {
22 |             source.innerHTML = data.match;
23 |         },
24 |         element: "li"
25 |     },
26 |     noResults: () => {                     // Action script on noResults      | (Optional)
27 |         const result = document.createElement("li");
28 |         result.setAttribute("class", "no_result");
29 |         result.setAttribute("tabindex", "1");
30 |         result.innerHTML = "No Results";
31 |         document.querySelector("#autoComplete_list").appendChild(result);
32 |     },
33 |     onSelection: feedback => {             // Action script onSelection event | (Optional)
34 |         document.getElementById('autoComplete').value = feedback.selection.value;
35 |     }
36 | });


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/static/default.jpg:
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https://raw.githubusercontent.com/Tharun-tharun/Movie-Recommendation-System-with-Sentiment-Analysis/fc73e55a6dd98283c45aadcdd3fd43c8fc4f24d3/static/default.jpg


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/static/image.jpg:
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https://raw.githubusercontent.com/Tharun-tharun/Movie-Recommendation-System-with-Sentiment-Analysis/fc73e55a6dd98283c45aadcdd3fd43c8fc4f24d3/static/image.jpg


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/static/loader.gif:
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https://raw.githubusercontent.com/Tharun-tharun/Movie-Recommendation-System-with-Sentiment-Analysis/fc73e55a6dd98283c45aadcdd3fd43c8fc4f24d3/static/loader.gif


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/static/recommend.js:
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  1 | $(function() {
  2 |   // Button will be disabled until we type something inside the input field
  3 |   const source = document.getElementById('autoComplete');
  4 |   const inputHandler = function(e) {
  5 |     if(e.target.value==""){
  6 |       $('.movie-button').attr('disabled', true);
  7 |     }
  8 |     else{
  9 |       $('.movie-button').attr('disabled', false);
 10 |     }
 11 |   }
 12 |   source.addEventListener('input', inputHandler);
 13 | 
 14 |   $('.fa-arrow-up').click(function(){
 15 |     $('html, body').animate({scrollTop:0}, 'slow');
 16 |   });
 17 | 
 18 |   $('.app-title').click(function(){
 19 |     window.location.href = '/';
 20 |   })
 21 | 
 22 |   $('.movie-button').on('click',function(){
 23 |     var my_api_key = '55a6a5ca3cdfe2fea08ca6f270dde6a2';
 24 |     var title = $('.movie').val();
 25 |     if (title=="") {
 26 |       $('.results').css('display','none');
 27 |       $('.fail').css('display','block');
 28 |     }
 29 | 
 30 |     if (($('.fail').text() && ($('.footer').css('position') == 'absolute'))) {
 31 |       $('.footer').css('position', 'fixed');
 32 |     }
 33 | 
 34 |     else{
 35 |       load_details(my_api_key,title);
 36 |     }
 37 |   });
 38 | });
 39 | 
 40 | // will be invoked when clicking on the recommended movie cards
 41 | function recommendcard(e){
 42 |   $("#loader").fadeIn();
 43 |   var my_api_key = '55a6a5ca3cdfe2fea08ca6f270dde6a2';
 44 |   var title = e.getAttribute('title'); 
 45 |   load_details(my_api_key,title);
 46 | }
 47 | 
 48 | 
 49 | // get the details of the movie from the API (based on the name of the movie)
 50 | function load_details(my_api_key,title){
 51 |   $.ajax({
 52 |     type: 'GET',
 53 |     url:'https://api.themoviedb.org/3/search/movie?api_key='+my_api_key+'&query='+title,
 54 |     async: false,
 55 |     success: function(movie){
 56 |       if(movie.results.length<1){
 57 |         $('.fail').css('display','block');
 58 |         $('.results').css('display','none');
 59 |         $("#loader").delay(500).fadeOut();
 60 |       }
 61 |       else if(movie.results.length==1) {
 62 |         $("#loader").fadeIn();
 63 |         $('.fail').css('display','none');
 64 |         $('.results').delay(1000).css('display','block');
 65 |         var movie_id = movie.results[0].id;
 66 |         var movie_title = movie.results[0].title;
 67 |         var movie_title_org = movie.results[0].original_title;
 68 |         get_movie_details(movie_id,my_api_key,movie_title,movie_title_org);
 69 |       }
 70 |       else{
 71 |         var close_match = {};
 72 |         var flag=0;
 73 |         var movie_id="";
 74 |         var movie_title="";
 75 |         var movie_title_org="";
 76 |         $("#loader").fadeIn();
 77 |         $('.fail').css('display','none');
 78 |         $('.results').delay(1000).css('display','block');
 79 |         for(var count in movie.results){
 80 |           if(title==movie.results[count].original_title){
 81 |             flag = 1;
 82 |             movie_id = movie.results[count].id;
 83 |             movie_title = movie.results[count].title;
 84 |             movie_title_org = movie.results[count].original_title;
 85 |             break;
 86 |           }
 87 |           else{
 88 |             close_match[movie.results[count].title] = similarity(title,  movie.results[count].title);
 89 |           }
 90 |         }
 91 |         if(flag==0){
 92 |           movie_title = Object.keys(close_match).reduce(function(a, b){ return close_match[a] > close_match[b] ? a : b });
 93 |           var index = Object.keys(close_match).indexOf(movie_title)
 94 |           movie_id = movie.results[index].id;
 95 |           movie_title_org = movie.results[index].original_title;
 96 |         }
 97 |         get_movie_details(movie_id,my_api_key,movie_title,movie_title_org);
 98 |       }
 99 |     },
100 |     error: function(error){
101 |       alert('Invalid Request - '+error);
102 |       $("#loader").delay(500).fadeOut();
103 |     },
104 |   });
105 | }
106 | 
107 | // getting closest match to the requested movie name using Levenshtein distance
108 | function similarity(s1, s2) {
109 |   var longer = s1;
110 |   var shorter = s2;
111 |   if (s1.length < s2.length) {
112 |     longer = s2;
113 |     shorter = s1;
114 |   }
115 |   var longerLength = longer.length;
116 |   if (longerLength == 0) {
117 |     return 1.0;
118 |   }
119 |   return (longerLength - editDistance(longer, shorter)) / parseFloat(longerLength);
120 | }
121 | 
122 | function editDistance(s1, s2) {
123 |   s1 = s1.toLowerCase();
124 |   s2 = s2.toLowerCase();
125 | 
126 |   var costs = new Array();
127 |   for (var i = 0; i <= s1.length; i++) {
128 |     var lastValue = i;
129 |     for (var j = 0; j <= s2.length; j++) {
130 |       if (i == 0)
131 |         costs[j] = j;
132 |       else {
133 |         if (j > 0) {
134 |           var newValue = costs[j - 1];
135 |           if (s1.charAt(i - 1) != s2.charAt(j - 1))
136 |             newValue = Math.min(Math.min(newValue, lastValue),
137 |               costs[j]) + 1;
138 |           costs[j - 1] = lastValue;
139 |           lastValue = newValue;
140 |         }
141 |       }
142 |     }
143 |     if (i > 0)
144 |       costs[s2.length] = lastValue;
145 |   }
146 |   return costs[s2.length];
147 | }
148 | 
149 | // get all the details of the movie using the movie id.
150 | function get_movie_details(movie_id,my_api_key,movie_title,movie_title_org) {
151 |   $.ajax({
152 |     type:'GET',
153 |     url:'https://api.themoviedb.org/3/movie/'+movie_id+'?api_key='+my_api_key,
154 |     success: function(movie_details){
155 |       show_details(movie_details,movie_title,my_api_key,movie_id,movie_title_org);
156 |     },
157 |     error: function(error){
158 |       alert("API Error! - "+error);
159 |       $("#loader").delay(500).fadeOut();
160 |     },
161 |   });
162 | }
163 | 
164 | // passing all the details to python's flask for displaying and scraping the movie reviews using imdb id
165 | function show_details(movie_details,movie_title,my_api_key,movie_id,movie_title_org){
166 |   var imdb_id = movie_details.imdb_id;
167 |   var poster;
168 |   if(movie_details.poster_path){
169 |     poster = 'https://image.tmdb.org/t/p/original'+movie_details.poster_path;
170 |   }
171 |   else {
172 |     poster = 'static/default.jpg';
173 |   }
174 |   var overview = movie_details.overview;
175 |   var genres = movie_details.genres;
176 |   var rating = movie_details.vote_average;
177 |   var vote_count = movie_details.vote_count;
178 |   var release_date = movie_details.release_date;
179 |   var runtime = parseInt(movie_details.runtime);
180 |   var status = movie_details.status;
181 |   var genre_list = []
182 |   for (var genre in genres){
183 |     genre_list.push(genres[genre].name);
184 |   }
185 |   var my_genre = genre_list.join(", ");
186 |   if(runtime%60==0){
187 |     runtime = Math.floor(runtime/60)+" hour(s)"
188 |   }
189 |   else {
190 |     runtime = Math.floor(runtime/60)+" hour(s) "+(runtime%60)+" min(s)"
191 |   }
192 | 
193 |   // calling `get_movie_cast` to get the top cast for the queried movie
194 |   movie_cast = get_movie_cast(movie_id,my_api_key);
195 |   
196 |   // calling `get_individual_cast` to get the individual cast details
197 |   ind_cast = get_individual_cast(movie_cast,my_api_key);
198 | 
199 |   // calling `get_recommendations` to get the recommended movies for the given movie id from the TMDB API
200 |   recommendations = get_recommendations(movie_id, my_api_key);
201 |   
202 |   details = {
203 |       'title':movie_title,
204 |       'cast_ids':JSON.stringify(movie_cast.cast_ids),
205 |       'cast_names':JSON.stringify(movie_cast.cast_names),
206 |       'cast_chars':JSON.stringify(movie_cast.cast_chars),
207 |       'cast_profiles':JSON.stringify(movie_cast.cast_profiles),
208 |       'cast_bdays':JSON.stringify(ind_cast.cast_bdays),
209 |       'cast_bios':JSON.stringify(ind_cast.cast_bios),
210 |       'cast_places':JSON.stringify(ind_cast.cast_places),
211 |       'imdb_id':imdb_id,
212 |       'poster':poster,
213 |       'genres':my_genre,
214 |       'overview':overview,
215 |       'rating':rating,
216 |       'vote_count':vote_count.toLocaleString(),
217 |       'rel_date':release_date,  
218 |       'release_date':new Date(release_date).toDateString().split(' ').slice(1).join(' '),
219 |       'runtime':runtime,
220 |       'status':status,
221 |       'rec_movies':JSON.stringify(recommendations.rec_movies),
222 |       'rec_posters':JSON.stringify(recommendations.rec_posters),
223 |       'rec_movies_org':JSON.stringify(recommendations.rec_movies_org),
224 |       'rec_year':JSON.stringify(recommendations.rec_year),
225 |       'rec_vote':JSON.stringify(recommendations.rec_vote)
226 |   }
227 | 
228 |   $.ajax({
229 |     type:'POST',
230 |     data:details,
231 |     url:"/recommend",
232 |     dataType: 'html',
233 |     complete: function(){
234 |       $("#loader").delay(500).fadeOut();
235 |     },
236 |     success: function(response) {
237 |       $('.results').html(response);
238 |       $('#autoComplete').val('');
239 |       $('.footer').css('position','absolute');
240 |       if ($('.movie-content')) {
241 |         $('.movie-content').after('<div class="gototop"><i title="Go to Top" class="fa fa-arrow-up"></i></div>');
242 |       }
243 |       $(window).scrollTop(0);
244 |     }
245 |   });
246 | }
247 | 
248 | // getting the details of individual cast
249 | function get_individual_cast(movie_cast,my_api_key) {
250 |     cast_bdays = [];
251 |     cast_bios = [];
252 |     cast_places = [];
253 |     for(var cast_id in movie_cast.cast_ids){
254 |       $.ajax({
255 |         type:'GET',
256 |         url:'https://api.themoviedb.org/3/person/'+movie_cast.cast_ids[cast_id]+'?api_key='+my_api_key,
257 |         async:false,
258 |         success: function(cast_details){
259 |           cast_bdays.push((new Date(cast_details.birthday)).toDateString().split(' ').slice(1).join(' '));
260 |           if(cast_details.biography){
261 |             cast_bios.push(cast_details.biography);
262 |           }
263 |           else {
264 |             cast_bios.push("Not Available");
265 |           }
266 |           if(cast_details.place_of_birth){
267 |             cast_places.push(cast_details.place_of_birth);
268 |           }
269 |           else {
270 |             cast_places.push("Not Available");
271 |           }
272 |         }
273 |       });
274 |     }
275 |     return {cast_bdays:cast_bdays,cast_bios:cast_bios,cast_places:cast_places};
276 |   }
277 | 
278 | // getting the details of the cast for the requested movie
279 | function get_movie_cast(movie_id,my_api_key){
280 |     cast_ids= [];
281 |     cast_names = [];
282 |     cast_chars = [];
283 |     cast_profiles = [];
284 |     top_10 = [0,1,2,3,4,5,6,7,8,9];
285 |     $.ajax({
286 |       type:'GET',
287 |       url:"https://api.themoviedb.org/3/movie/"+movie_id+"/credits?api_key="+my_api_key,
288 |       async:false,
289 |       success: function(my_movie){
290 |         if(my_movie.cast.length>0){
291 |           if(my_movie.cast.length>=10){
292 |             top_cast = [0,1,2,3,4,5,6,7,8,9];
293 |           }
294 |           else {
295 |             top_cast = [0,1,2,3,4];
296 |           }
297 |           for(var my_cast in top_cast){
298 |             cast_ids.push(my_movie.cast[my_cast].id)
299 |             cast_names.push(my_movie.cast[my_cast].name);
300 |             cast_chars.push(my_movie.cast[my_cast].character);
301 |             if(my_movie.cast[my_cast].profile_path){
302 |               cast_profiles.push("https://image.tmdb.org/t/p/original"+my_movie.cast[my_cast].profile_path);
303 |             }
304 |             else {
305 |               cast_profiles.push("static/default.jpg");
306 |             }
307 |           }
308 |         }
309 |       },
310 |       error: function(error){
311 |         alert("Invalid Request! - "+error);
312 |         $("#loader").delay(500).fadeOut();
313 |       }
314 |     });
315 | 
316 |     return {cast_ids:cast_ids,cast_names:cast_names,cast_chars:cast_chars,cast_profiles:cast_profiles};
317 |   }
318 | 
319 |   // getting recommendations
320 |   function get_recommendations(movie_id, my_api_key) {
321 |     rec_movies = [];
322 |     rec_posters = [];
323 |     rec_movies_org = [];
324 |     rec_year = [];
325 |     rec_vote = [];
326 |     
327 |     $.ajax({
328 |       type: 'GET',
329 |       url: "https://api.themoviedb.org/3/movie/"+movie_id+"/recommendations?api_key="+my_api_key,
330 |       async: false,
331 |       success: function(recommend) {
332 |         for(var recs in recommend.results) {
333 |           rec_movies.push(recommend.results[recs].title);
334 |           rec_movies_org.push(recommend.results[recs].original_title);
335 |           rec_year.push(new Date(recommend.results[recs].release_date).getFullYear());
336 |           rec_vote.push(recommend.results[recs].vote_average);
337 |           if(recommend.results[recs].poster_path){
338 |             rec_posters.push("https://image.tmdb.org/t/p/original"+recommend.results[recs].poster_path);
339 |           }
340 |           else {
341 |             rec_posters.push("static/default.jpg");
342 |           }
343 |         }
344 |       },
345 |       error: function(error) {
346 |         alert("Invalid Request! - "+error);
347 |         $("#loader").delay(500).fadeOut();
348 |       }
349 |     });
350 |     return {rec_movies:rec_movies,rec_movies_org:rec_movies_org,rec_posters:rec_posters,rec_year:rec_year,rec_vote:rec_vote};
351 |   }
352 | 


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/static/style.css:
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  1 | /* width */
  2 | ::-webkit-scrollbar {
  3 |   width: 15px;
  4 | }
  5 | 
  6 | /* Track */
  7 | ::-webkit-scrollbar-track {
  8 |   border-radius: 10px;
  9 | }
 10 |  
 11 | /* Handle */
 12 | ::-webkit-scrollbar-thumb {
 13 |   background: #e50914; 
 14 |   border-radius: 10px;
 15 | }
 16 | 
 17 | /* Handle on hover */
 18 | ::-webkit-scrollbar-thumb:hover {
 19 |   background: #b30000; 
 20 | }
 21 | 
 22 | .movie {
 23 | 	color: #fff;
 24 | 	margin-left: auto;
 25 | 	margin-right: auto;
 26 | 	resize: none;
 27 | }
 28 | 
 29 | .movie-content {
 30 | 	display: flex;
 31 | 	flex-wrap: wrap;
 32 | 	justify-content:center;
 33 | }
 34 | 
 35 | .movie-content > div {
 36 |     margin:20px;
 37 | }
 38 | 
 39 | .btn-block{
 40 | 	width: 15%;
 41 | 	text-align: center;
 42 | 	margin-left: auto;
 43 | 	margin-right: auto;
 44 | 	color: #e4e0e0;
 45 | }
 46 | 
 47 | #content {
 48 | 	background-image: url("../static/image.jpg");
 49 | 	background-color: #181818;
 50 | 	font-family: 'Noto Sans JP', sans-serif;
 51 | }
 52 | 
 53 | #details {
 54 | 	margin-left: 50px;
 55 | }
 56 | 
 57 | .body-content {
 58 | 	position: relative;
 59 |   	min-height: 100%;
 60 | }
 61 | 
 62 | .footer {
 63 | 	color: #e4e0e0;
 64 | 	background-color: #e50914d1;
 65 | 	text-align:center;
 66 | 	position: fixed;
 67 | 	bottom: 0;
 68 |  	width: 100%;
 69 | }
 70 | 
 71 | .social-icons {
 72 | 	margin-left: 15px;
 73 | }
 74 | 
 75 | h1 {
 76 |     font-family: 'Netflix Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;
 77 |     color: #e50914;
 78 |     font-weight: bold;
 79 |     margin-top: 30px;
 80 |     text-shadow: #000000 0px 0px 13px;
 81 |  }
 82 | 
 83 | .github-corner:hover .octo-arm {
 84 |   	animation: octocat-wave 560ms ease-in-out;
 85 | }
 86 | 
 87 | .fa-arrow-up {
 88 | 	font-size: 1.5em;
 89 | 	color: #ffffff;
 90 |     background: #e50914;
 91 |     padding: 10px;
 92 | 	border-radius: 50%;
 93 | 	float: right;
 94 |     bottom: 25px;
 95 |     position: relative;
 96 | }
 97 | 
 98 | .fa-arrow-up:hover {
 99 | 	cursor: pointer;
100 | }
101 | 
102 | .app-title:hover {
103 | 	cursor: pointer;
104 | }
105 | 
106 | @keyframes octocat-wave {
107 |   0%,
108 |   100% {
109 |     transform: rotate(0)
110 |   }
111 | 
112 |   20%,
113 |   60% {
114 |     transform: rotate(-25deg)
115 |   }
116 | 
117 |   40%,
118 |   80% {
119 |     transform: rotate(10deg)
120 |   }
121 | }
122 | 
123 | #autoComplete {
124 |   background-position: 98% ;
125 | }
126 | 
127 | #name {
128 | 	color: white;
129 | 	padding: 1px;
130 | }
131 | 
132 | h6 {
133 |     margin-bottom: 20px;  
134 | }
135 | 
136 | @media only screen and (max-width: 650px) {
137 |     #mcontent {
138 |       display: block;
139 |     }
140 |     .poster-lg {
141 |       display: none;
142 |     }
143 |     #details {
144 | 		margin-left: 30px;
145 | 	}
146 |     #loader {
147 | 		display: none;
148 | 		position: fixed;
149 | 		z-index: 100;
150 | 		left: 0;
151 | 		top:0;
152 | 		width: 100%;
153 | 		height: 100%;
154 | 		background-image: url("../static/loader.gif");
155 | 		background-size: 40%;
156 | 		background-position: 50% 50%;
157 | 		background-color: rgba(255, 255, 255, 1);
158 | 		background-repeat: no-repeat;
159 | 		-webkit-transition: background-image 0.2s ease-in-out;
160 | 		transition: background-image 0.2s ease-in-out;
161 | 	}
162 | 
163 | 	#loader-text {
164 | 		vertical-align: middle;
165 | 		color:white;
166 | 	}
167 | 
168 | 	#autoComplete {
169 | 	  background-position: 97% ;
170 | 	}
171 | 	
172 | 	svg[data-toggle=tooltip] {
173 | 		width: 50px;
174 | 		height: 50px;
175 | 	}
176 | 
177 | 	.fa-arrow-up{
178 | 		font-size: 1em;
179 | 		color: #ffffff;
180 | 		background: #e50914;
181 | 		padding: 10px;
182 | 		border-radius: 50%;
183 | 		float: right;
184 | 		bottom: 10px;
185 | 		position: relative;
186 | 	}
187 | }
188 | 
189 | @media only screen and (max-width: 991px) {
190 | 	.modal-body{
191 | 		display: block;
192 | 	}
193 | 	.profile-pic {
194 | 		margin-left: auto;
195 | 		margin-right: auto;
196 | 		display: block;
197 | 		margin-bottom: 20px;
198 | 	}
199 | }
200 | @media only screen and (min-width: 992px) {
201 | 	.modal-body {
202 | 		display: flex;
203 | 	}
204 | }
205 | 
206 | @media only screen and (min-width: 651px) {
207 |   .poster-sm {
208 |     display: none;
209 |    }
210 | 
211 | 	#mcontent {
212 | 		display: flex;
213 | 		flex-wrap: nowrap;
214 | 	}
215 | 
216 | 	#loader {
217 | 		display: none;
218 | 		position: fixed;
219 | 		z-index: 100;
220 | 		left: 0;
221 | 		top:0;
222 | 		width: 100%;
223 | 		height: 100%;
224 | 		background-image: url("../static/loader.gif");
225 | 		background-size: 20%;
226 | 		background-position: 50% 50%;
227 | 		background-color: rgba(255, 255, 255, 1);
228 | 		background-repeat: no-repeat;
229 | 		-webkit-transition: background-image 0.2s ease-in-out;
230 | 		transition: background-image 0.2s ease-in-out;
231 | 	}
232 | 
233 | 	#loader-text {
234 | 		vertical-align: middle;
235 | 		color:white;
236 | 	}
237 | 
238 | }
239 | 
240 | .poster{
241 |     -webkit-box-shadow: 0px 1px 15px 4px rgba(250,250,250,1);
242 |     -moz-box-shadow: 0px 1px 15px 4px rgba(250,250,250,1);
243 |     box-shadow: 0px 1px 15px 4px rgba(250,250,250,1);
244 | }
245 | 
246 | .card:hover {
247 | 	cursor: pointer;
248 | }
249 | 
250 | .castcard:hover {
251 |     cursor: pointer;
252 | }
253 | 
254 | .cast-img {
255 | 	filter: brightness(100%);
256 | 	-moz-transition: all 0.75s ease;
257 |     -webkit-transition: all 0.75s ease;
258 | 	transition: all 0.75s ease;
259 | }
260 | 
261 | 
262 | .cast-img:hover {
263 | 	filter: brightness(50%);
264 | 	-moz-transition: all 0.75s ease;
265 |     -webkit-transition: all 0.75s ease;
266 |     transition: all 0.75s ease;
267 | }
268 | 
269 | .fig {
270 | 	display: flex;
271 | 	align-items: center;
272 | 	justify-content: center;
273 | 	backdrop-filter: brightness(50%);
274 | 	position: absolute;
275 | 	bottom: 0px;
276 | 	top: 0px;
277 | 	right: 0px;
278 | 	left: 0px;
279 | 	opacity: 0;
280 | 	-moz-transition: all 0.75s ease;
281 |     -webkit-transition: all 0.75s ease;
282 |     transition: all 0.75s ease;
283 | }
284 | 
285 | .fig:hover {
286 | 	opacity: 1;
287 | 	backdrop-filter:br;
288 | 	-moz-transition: all 0.75s ease;
289 |     -webkit-transition: all 0.75s ease;
290 |     transition: all 0.75s ease;
291 | }
292 | 
293 | .card-btn {
294 | 	border-radius: 20px;
295 | }
296 | 
297 | .imghvr {
298 | 	position: relative;
299 | }
300 | 
301 | .table td {
302 |     border-color: white;
303 |     border-style:solid; 
304 |     border-width:1px;
305 | }
306 | 
307 | .fail {
308 | 	display: none;
309 | 	color: white;
310 | }
311 | 


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/templates/home.html:
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  1 | <!DOCTYPE html>
  2 | <html>
  3 | <head>
  4 |   <title>The Movie Cinema</title>
  5 |   <meta charset="UTF-8">
  6 |   <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
  7 | 
  8 |   <!-- Google Fonts -->
  9 |   <link href="https://fonts.googleapis.com/css?family=IBM+Plex+Sans&display=swap" rel="stylesheet">
 10 |   <link href="https://fonts.googleapis.com/css2?family=Noto+Sans+JP&display=swap" rel="stylesheet">
 11 | 
 12 |   <!-- Font Awesome -->
 13 |   <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
 14 | 
 15 |   <!-- Bootstrap -->
 16 |   <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
 17 | 
 18 |   <!-- jQuery -->
 19 |   <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
 20 | 
 21 |   <!-- Auto Complete -->
 22 |   <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@tarekraafat/autocomplete.js@7.2.0/dist/css/autoComplete.min.css">
 23 | 
 24 |   <!-- External CSS -->
 25 |   <link rel= "stylesheet" type= "text/css" href= "{{ url_for('static',filename='style.css') }}">
 26 | 
 27 |   <script type="text/javascript">
 28 |     var films = {{suggestions|tojson}};
 29 |     $(document).ready(function(){
 30 |       $("#myModal").modal('show');
 31 |     });
 32 |   </script>
 33 | 
 34 | </head>
 35 | 
 36 | <body id="content" style="font-family: 'Noto Sans JP', sans-serif;">
 37 | <div class="body-content">
 38 | 	<div class="ml-container" style="display: block;">
 39 | 		<a href="https://github.com/Tharun-tharun/Movie-Recommendation-System-with-Sentiment-Analysis" target="_blank" class="github-corner" title="View source on GitHub">
 40 | 		      <svg data-toggle="tooltip"
 41 | 		      data-placement="left" width="80" height="80" viewBox="0 0 250 250"
 42 | 			style="fill:#e50914; color:#fff; position: fixed;z-index:100; top: 0; border: 0; right: 0;" aria-hidden="true">
 43 | 			<path d="M0,0 L115,115 L130,115 L142,142 L250,250 L250,0 Z"></path>
 44 | 			<path
 45 | 			  d="M128.3,109.0 C113.8,99.7 119.0,89.6 119.0,89.6 C122.0,82.7 120.5,78.6 120.5,78.6 C119.2,72.0 123.4,76.3 123.4,76.3 C127.3,80.9 125.5,87.3 125.5,87.3 C122.9,97.6 130.6,101.9 134.4,103.2"
 46 | 			  fill="currentColor" style="transform-origin: 130px 106px;" class="octo-arm"></path>
 47 | 			<path
 48 | 			  d="M115.0,115.0 C114.9,115.1 118.7,116.5 119.8,115.4 L133.7,101.6 C136.9,99.2 139.9,98.4 142.2,98.6 C133.8,88.0 127.5,74.4 143.8,58.0 C148.5,53.4 154.0,51.2 159.7,51.0 C160.3,49.4 163.2,43.6 171.4,40.1 C171.4,40.1 176.1,42.5 178.8,56.2 C183.1,58.6 187.2,61.8 190.9,65.4 C194.5,69.0 197.7,73.2 200.1,77.6 C213.8,80.2 216.3,84.9 216.3,84.9 C212.7,93.1 206.9,96.0 205.4,96.6 C205.1,102.4 203.0,107.8 198.3,112.5 C181.9,128.9 168.3,122.5 157.7,114.1 C157.9,116.9 156.7,120.9 152.7,124.9 L141.0,136.5 C139.8,137.7 141.6,141.9 141.8,141.8 Z"
 49 | 			  fill="currentColor" class="octo-body"></path>
 50 | 		      </svg>
 51 | 		    </a>
 52 |     <center><h1 class="app-title">The Movie Cinema</h1></center>
 53 |     <div class="form-group shadow-textarea" style="margin-top: 30px;text-align: center;color: white;">
 54 |         <input type="text" name="movie" class="movie form-control" id="autoComplete" autocomplete="off" placeholder="Enter the Movie Name" style="background-color: #ffffff;border-color:#ffffff;width: 60%;color: #181818" required="required" />
 55 |         <br>
 56 |     </div>
 57 | 
 58 |     <div class="form-group" style="text-align: center;">
 59 |       <button class="btn btn-primary btn-block movie-button" style="background-color: #e50914;text-align: center;border-color: #e50914;width:120px;" disabled="true" >Enter</button><br><br>
 60 |     </div>
 61 | 	</div>
 62 | 
 63 |   <div id="loader" class="text-center">
 64 |   </div>
 65 |   
 66 |   <div class="fail">
 67 |     <center><h3>Sorry! The movie you requested is not in our database. 
 68 |     Please check the spelling or try with other movies!</h3></center>
 69 |   </div>
 70 | 
 71 | 	<div class="results">
 72 |     <center>
 73 |       <h2 id="name" class="text-uppercase"></h2>
 74 |     </center>
 75 | 	</div>
 76 | 	
 77 | 	<div class="modal fade" id="myModal" tabindex="-1" role="dialog" aria-labelledby="exampleModalLabel3" aria-hidden="true">
 78 |     <div class="modal-dialog modal-md" role="document">
 79 |       <div class="modal-content">
 80 |         <div class="modal-header" style="background-color: #e50914;color: white;">
 81 |           <h5 class="modal-title" id="exampleModalLabel3">Hey there!</h5>
 82 |           <button type="button" class="close" data-dismiss="modal" aria-label="Close">
 83 |             <span aria-hidden="true" style="color: white">&times;</span>
 84 |           </button>
 85 |         </div>
 86 |         <div class="modal-body">
 87 |           <p>Don't worry if the movie that you are looking for is not auto-suggested while typing. Just type the movie name and click on "enter". You will be good to go even though if you made some typo errors.</p>
 88 |         </div>
 89 |         <div class="modal-footer" style="text-align: center;">
 90 |           <button type="button" class="btn btn-secondary" data-dismiss="modal">Let's go!</button>
 91 |         </div>
 92 |       </div>
 93 |     </div>
 94 |   </div>
 95 | 	
 96 | 	<footer class="footer">
 97 |     <br/> 
 98 |     <div class="social" style="margin-bottom: 8px">
 99 |     <a class="social-icons" href="https://github.com/Tharun-tharun" target="_blank"><i class="fa fa-github-alt" style="font-size:24px;color: #e4e0e0"></i></a>
100 |     <a class="social-icons" href="https://www.linkedin.com/in/tharun-p-827813177" target="_blank"><i class="fa fa-linkedin-square" style="font-size:24px;color: #e4e0e0"></i></a>
101 |     <a class="social-icons" href="https://twitter.com/tharunp_33" target="_blank"><i class="fa fa-twitter" style="font-size:24px;color: #e4e0e0"></i></a>
102 |   </div>
103 |   </footer>
104 | 	</div>
105 | 	
106 | 	<script src="https://cdn.jsdelivr.net/npm/@tarekraafat/autocomplete.js@7.2.0/dist/js/autoComplete.min.js"></script>
107 |   <script type="text/javascript" src="{{url_for('static', filename='autocomplete.js')}}"></script>
108 | 
109 |   <script type="text/javascript" src="{{url_for('static', filename='recommend.js')}}"></script>
110 |   <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js" integrity="sha384-ApNbgh9B+Y1QKtv3Rn7W3mgPxhU9K/ScQsAP7hUibX39j7fakFPskvXusvfa0b4Q" crossorigin="anonymous"></script>
111 |   <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js" integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous"></script>
112 | 
113 | </body>
114 | </html>
115 | 


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/templates/recommend.html:
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  1 | <!DOCTYPE html>
  2 | <html>
  3 | <head>
  4 | 	<title>NEW</title>
  5 | 
  6 | 	<meta charset="UTF-8">
  7 | 	<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
  8 | 
  9 | 	<!-- Google Fonts -->
 10 | 	<link href="https://fonts.googleapis.com/css?family=IBM+Plex+Sans&display=swap" rel="stylesheet">
 11 | 	<link href="https://fonts.googleapis.com/css2?family=Noto+Sans+JP&display=swap" rel="stylesheet">
 12 |   <link href="https://fonts.googleapis.com/css2?family=Rowdies:wght@300&display=swap" rel="stylesheet">
 13 | 
 14 | 	<!-- Font Awesome -->
 15 | 	<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
 16 | 
 17 | 	<!-- Bootstrap -->
 18 | 	<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
 19 | 
 20 | 	<link rel= "stylesheet" type= "text/css" href= "{{ url_for('static',filename='style.css') }}">
 21 | 
 22 | </head>
 23 | 
 24 | <body id="content">
 25 | 
 26 | 	<div class="results">
 27 | 	    <center>
 28 | 	      <h2 id="name" class="text-uppercase" style="font-family: 'Rowdies', cursive;">{{title}}</h2>
 29 | 	    </center>
 30 | 	</div>
 31 | 	<br/>
 32 | 
 33 |   <div id="mycontent">
 34 |     <div id="mcontent">
 35 |       <div class="poster-lg">
 36 |         <img class="poster" style="border-radius: 40px;margin-left: 90px;" height="400" width="250" src={{poster}}>
 37 |       </div>
 38 |       <div class="poster-sm text-center">
 39 |         <img class="poster" style="border-radius: 40px;margin-bottom: 5%;" height="400" width="250" src={{poster}}>
 40 |       </div>
 41 |       <div id="details">
 42 |         <br/>
 43 |         <h6 id="title" style="color:white;">TITLE: &nbsp;{{title}}</h6>
 44 |         <h6 id="overview" style="color:white;max-width: 85%">OVERVIEW: <br/><br/>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;{{overview}}</h6>
 45 |         <h6 id="vote_average" style="color:white;">RATING: &nbsp;{{vote_average}}/10 ({{vote_count}} votes)</h6>
 46 |         <h6 id="genres" style="color:white;">GENRE: &nbsp;{{genres}}</h6>
 47 |         <h6 id="date" style="color:white;">RELEASE DATE: &nbsp;{{release_date}}</h6>
 48 |         <h6 id="runtime" style="color:white;">RUNTIME: &nbsp;{{runtime}}</h6>
 49 |         <h6 id="status" style="color:white;">STATUS: &nbsp;{{status}}</h6>
 50 |       </div>
 51 |     </div>
 52 |   </div>  
 53 |   <br/>
 54 | 	
 55 | {% for name, details in cast_details.items() if not cast_details.hidden %}
 56 |   <div class="modal fade" id="{{details[0]}}" tabindex="-1" role="dialog" aria-labelledby="exampleModalLabel3" aria-hidden="true">
 57 |     <div class="modal-dialog modal-lg" role="document">
 58 |       <div class="modal-content">
 59 |         <div class="modal-header" style="background-color: #e50914;color: white;">
 60 |           <h5 class="modal-title" id="exampleModalLabel3">{{name}}</h5>
 61 |           <button type="button" class="close" data-dismiss="modal" aria-label="Close">
 62 |             <span aria-hidden="true" style="color: white">&times;</span>
 63 |           </button>
 64 |         </div>
 65 | 
 66 |         <div class="modal-body">
 67 |           <img class="profile-pic" src="{{details[1]}}" alt="{{name}} - profile" style="width: 250px;height:400px;border-radius: 10px;" />
 68 |           <div style="margin-left: 20px">
 69 |             <p><strong>Birthday:</strong> {{details[2]}} </p>
 70 |             <p><strong>Place of Birth:</strong> {{details[3]}} </p>
 71 |             <p> 
 72 |               <p><strong>Biography:</strong><p>
 73 |               {{details[4]}}
 74 |             </p>
 75 |           </div>
 76 |         </div>
 77 |         <div class="modal-footer">
 78 |           <button type="button" class="btn btn-secondary" data-dismiss="modal">Close</button>
 79 |         </div>
 80 |       </div>
 81 |     </div>
 82 |   </div>
 83 |   {% endfor %}
 84 | 
 85 |   <div class="container"> 
 86 | 
 87 |     {% if casts|length > 1 %}
 88 |       <div class="movie" style="color: #E8E8E8;">
 89 |         <center>
 90 |           <h2 style="font-family: 'Rowdies', cursive;">TOP CAST</h2>
 91 |           <h5>(Click on the cast to know more)</h5>
 92 |         </center>
 93 |       </div>
 94 | 
 95 |     
 96 |       <div class="movie-content">
 97 |         {% for name, details in casts.items() if not casts.hidden %}
 98 |           <div class="castcard card" style="width: 14rem;" title="Click to know more about {{name}}" data-toggle="modal" data-target="#{{details[0]}}">
 99 |             <div class="imghvr">
100 |               <img class="card-img-top cast-img" id="{{details[0]}}" height="360" width="240" alt="{{name}} - profile" src="{{details[2]}}">
101 |               <figcaption class="fig">
102 |                 <button class="card-btn btn btn-danger"> Know More </button>
103 |               </figcaption>
104 |             </div>
105 |             <div class="card-body" style="font-family: 'Rowdies', cursive;font-size: 18px;">
106 |               <h5 class="card-title">{{name|upper}}</h5>
107 |               <h5 class="card-title" style="font-size: 18px"><span style="color:#756969;font-size: 18px;">AS {{details[1]|upper}}</span></h5>
108 |             </div>
109 |           </div>
110 |         {% endfor %}
111 |       </div>
112 |     {% endif %}
113 |     <br/>
114 | 
115 |   <center>
116 |     {% if reviews %}
117 |     <h2 style="font-family: 'Rowdies', cursive;color:white">USER REVIEWS</h2>
118 |      <div class="col-md-12" style="margin: 0 auto; margin-top:25px;">
119 |         <table class="table table-bordered" bordercolor="white" style="color:white">
120 |             <thead>
121 |                 <tr>
122 |                   <th class="text-center" scope="col" style="width: 75%">Comments</th>
123 |                   <th class="text-center" scope="col">Sentiments</th>
124 |                 </tr>
125 |             </thead>
126 |     
127 |           <tbody>
128 | 	    {% for review, status in reviews.items() if not reviews.hidden %}
129 |     	        <tr style="background-color:#e5091485;">
130 |                 <td>{{review}}</td>
131 |                 <td>
132 |                   <center>
133 |                     {{status}} : 
134 |                     {% if status =='Positive' %}
135 |                       &#128515;
136 |                     {% else %}
137 |                       &#128534;
138 |                     {% endif %}
139 |                   </center>
140 |                 </td>
141 |             	</tr>
142 |       	    {% endfor %}
143 |     		  </tbody>
144 |  		    </table>
145 |      </div>
146 | 
147 |     {% if (curr_date) and (movie_rel_date) %}
148 |       {% elif curr_date < movie_rel_date %}
149 |       <div style="color:white;">
150 |         <h1 style="color:white"> This movie is not released yet. Stay tuned! </h1>
151 |       </div>
152 |       {% else %}
153 |       <div style="color:white;">
154 |         <h1 style="color:white"> Sorry, the reviews for this movie are not available! :( </h1>
155 |       </div>
156 |       {% endif %}
157 |     {% else %}
158 |       <div style="color:white;">
159 |         <h1 style="color:white"> Sorry, the reviews for this movie are not available! :( </h1>
160 |       </div>
161 |     {% endif %}
162 |   </center>
163 |   <br/>
164 |    
165 |  
166 |     {% if movie_cards|length > 1 %}
167 | 
168 |       <div class="movie" style="color: #E8E8E8;">
169 |         <center><h2 style="font-family: 'Rowdies', cursive;">RECOMMENDED MOVIES FOR YOU</h2><h5>(Click any of the movies to get recommendation)</h5></center>
170 |       </div>
171 | 
172 |       <div class="movie-content">
173 |         {% for poster, details in movie_cards.items() if not movie_cards.hidden %}
174 |           <div class="card" style="width: 14rem;" title="{{details[1]}}" onclick="recommendcard(this)">
175 |             <div class="imghvr">
176 |               <img class="card-img-top" height="360" width="240" alt="{{details[0]}} - poster" src={{poster}}>
177 |               <div class="card-img-overlay" >
178 |                 <span class="card-text" style="font-size:15px;background: #000000b8;color:white;padding:2px 5px;border-radius: 10px;"><span class="fa fa-star checked">&nbsp; {{details[2]}}/10</span></span>
179 |               </div>
180 |               <div class=".card-img-overlay" style="position: relative;">
181 |                 <span class="card-text" style="font-size:15px;position:absolute;bottom:20px;left:15px;background: #000000b8;color:white;padding: 5px;border-radius: 10px;">{{details[3]}}</span>
182 |               </div>
183 |               <figcaption class="fig">
184 |                 <button class="card-btn btn btn-danger"> Click Me </button>
185 |               </figcaption>
186 |             </div>
187 |             <div class="card-body">
188 |               <h5 class="card-title" style="font-family: 'Rowdies', cursive;font-size: 17px;">{{details[0]|upper}}</h5>
189 |             </div>
190 |           </div>
191 |         {% endfor %}
192 |       </div>
193 |     {% endif %}
194 | <br/><br/><br/><br/>
195 |   </div>
196 | 
197 |   <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
198 |   <script type="text/javascript" src="{{url_for('static', filename='recommend.js')}}"></script>
199 |   <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js" integrity="sha384-ApNbgh9B+Y1QKtv3Rn7W3mgPxhU9K/ScQsAP7hUibX39j7fakFPskvXusvfa0b4Q" crossorigin="anonymous"></script>
200 |   <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js" integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous"></script>
201 | 
202 | </body>
203 | </html>
204 | 


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/tranform.pkl:
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https://raw.githubusercontent.com/Tharun-tharun/Movie-Recommendation-System-with-Sentiment-Analysis/fc73e55a6dd98283c45aadcdd3fd43c8fc4f24d3/tranform.pkl


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