ApplicationML3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.Project Title: [Data Classificcation]\n",
    "___\n",
    "\n",
    "#### a. Introduction\n",
    "\n",
    "- **Objective:** Clearly state the goal of your project. What problem are you trying to solve?\n",
    "- **Background:** Provide context on why this problem is important or interesting. Mention any relevant research, datasets, or industry relevance.\n",
    "- **Scope:** Define the boundaries of your project. What will be included, and what will be out of scope?\n",
    "\n",
    "#### b. Project Overview\n",
    "\n",
    "- **Project Summary:** A brief overview of the project, including the main steps you will take to achieve the objective.\n",
    "- **Milestones:** Outline the key milestones or phases of the project. For example:\n",
    "  - Data Collection\n",
    "  - Data Preprocessing\n",
    "  - Model Selection\n",
    "  - Model Training and Evaluation\n",
    "  - Results and Conclusion\n",
    "\n",
    "\n",
    "#### c. About the Author\n",
    "\n",
    "- **Name:** [Ahmed Ferganey]\n",
    "- **Background:** Junior Data Scientist and Machine Learning Engineer with a strong foundation in embedded systems, industrial engineering, and supply chain management. Knowledgeable in statistical analysis, NLP, Computer Vision, and deep learning, with hands-on experience in Python, SQL, and Docker.\n",
    "- **Motivation:** Why are you interested in this project? What do you hope to learn or achieve?\n",
    "- **Contact:** [LinkedIn acc](https://www.linkedin.com/in/ahmed-ferganey/)\n",
    "\n",
    "\n",
    "\n",
    "#### d. Tools and Technologies\n",
    "\n",
    "- **Programming Languages:** List the programming languages you will use (e.g., Python).\n",
    "- **Libraries and Frameworks:** List the specific libraries and frameworks you will use (e.g., TensorFlow, scikit-learn).\n",
    "- **Software and Tools:** Mention any software or tools necessary for the project (e.g., Jupyter Notebook, Git).\n",
    "\n",
    "#### e. Dataset Description\n",
    "\n",
    "- **Dataset Name:** [Name of the Dataset]\n",
    "- **Source:** Where did you obtain the dataset? Include a link if possible.\n",
    "- **Description:** Briefly describe the dataset, including the number of features, the target variable, and any other important details.\n",
    "- **Data Preprocessing:** Outline any preprocessing steps you anticipate, such as data cleaning, normalization, or feature engineering.\n",
    "\n",
    "#### f. Methodology\n",
    "\n",
    "- **Model Selection:** Describe the types of models you are considering and why.\n",
    "- **Evaluation Metrics:** Define how you will evaluate your models' performance (e.g., accuracy, F1-score).\n",
    "- **Validation Strategy:** Explain how you will validate your models, such as cross-validation or a \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. importing libraries\n",
    "___\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "import io\n",
    "import sys\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', None)\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set(style=\"whitegrid\")\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_selection import SelectPercentile , f_classif ,SelectKBest\n",
    "from sklearn.feature_selection import chi2 , f_classif \n",
    "import plotly.express as px\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.linear_model import LogisticRegression,SGDClassifier\n",
    "from sklearn.naive_bayes import GaussianNB,BernoulliNB\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis,QuadraticDiscriminantAnalysis\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.decomposition import PCA\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. reading the raw data\n",
    "___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_path = '/media/ahmed-ferganey/AI4/01-Learning_AI'\n",
    "sub_folder_one = 'Movies'\n",
    "sub_folder_two = 'Json'\n",
    "MoviesFilesDir = f'{base_path}/MyGitHub/HeshamAsem_ML_App3/{sub_folder_one}'\n",
    "JsonFilesDir = f'{base_path}/MyGitHub/HeshamAsem_ML_App3/{sub_folder_two}'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def StringToDict(f) : \n",
    "    f = f.strip('\"[{').strip('}]\"')\n",
    "    f = f.split('}, {')\n",
    "    FinalList = []\n",
    "\n",
    "    for item in f : \n",
    "        \n",
    "        NewList = [i for i in [i.strip().split(':') for i in item.split(',')]]\n",
    "        \n",
    "        FinalList.append({i[0].replace(\"'\",\"\"):i[1].replace(\"'\",\"\") for i in NewList if len(i)>1 })\n",
    "\n",
    "    return FinalList\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['.ipynb_checkpoints',\n",
       " 'credits.csv',\n",
       " 'keywords.csv',\n",
       " 'links.csv',\n",
       " 'links_small.csv',\n",
       " 'Movies.ipynb',\n",
       " 'movies_metadata.csv',\n",
       " 'ratings.csv',\n",
       " 'ratings_small.csv']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(MoviesFilesDir)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_322504/2618754945.py:17: DtypeWarning: Columns (10) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  movies_metadata = pd.read_csv(movies_metadata_path)\n"
     ]
    }
   ],
   "source": [
    "# File paths\n",
    "keywords_path = f'{MoviesFilesDir}/keywords.csv'\n",
    "credits_path = f'{MoviesFilesDir}/credits.csv'\n",
    "links_path = f'{MoviesFilesDir}/links.csv'\n",
    "links_small_path = f'{MoviesFilesDir}/links_small.csv'\n",
    "movies_metadata_path = f'{MoviesFilesDir}/movies_metadata.csv'\n",
    "ratings_path = f'{MoviesFilesDir}/ratings.csv'\n",
    "ratings_small_path = f'{MoviesFilesDir}/ratings_small.csv'\n",
    "\n",
    "\n",
    "\n",
    "# Reading CSV files\n",
    "keywords        = pd.read_csv(keywords_path)\n",
    "credits         = pd.read_csv(credits_path)\n",
    "links           = pd.read_csv(links_path)\n",
    "links_small     = pd.read_csv(links_small_path)\n",
    "movies_metadata = pd.read_csv(movies_metadata_path)\n",
    "ratings         = pd.read_csv(ratings_path)\n",
    "ratings_small   = pd.read_csv(ratings_small_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>cast</th>\n",
       "      <th>crew</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>[{'cast_id': 14, 'character': 'Woody (voice)',...</td>\n",
       "      <td>[{'credit_id': '52fe4284c3a36847f8024f49', 'de...</td>\n",
       "      <td>862</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[{'cast_id': 1, 'character': 'Alan Parrish', '...</td>\n",
       "      <td>[{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...</td>\n",
       "      <td>8844</td>\n",
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       "      <th>2</th>\n",
       "      <td>[{'cast_id': 2, 'character': 'Max Goldman', 'c...</td>\n",
       "      <td>[{'credit_id': '52fe466a9251416c75077a89', 'de...</td>\n",
       "      <td>15602</td>\n",
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       "      <th>3</th>\n",
       "      <td>[{'cast_id': 1, 'character': \"Savannah 'Vannah...</td>\n",
       "      <td>[{'credit_id': '52fe44779251416c91011acb', 'de...</td>\n",
       "      <td>31357</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[{'cast_id': 1, 'character': 'George Banks', '...</td>\n",
       "      <td>[{'credit_id': '52fe44959251416c75039ed7', 'de...</td>\n",
       "      <td>11862</td>\n",
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       "      <td>[{'cast_id': 0, 'character': '', 'credit_id': ...</td>\n",
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       "      <td>439050</td>\n",
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       "    <tr>\n",
       "      <th>45472</th>\n",
       "      <td>[{'cast_id': 1002, 'character': 'Sister Angela...</td>\n",
       "      <td>[{'credit_id': '52fe4af1c3a36847f81e9b15', 'de...</td>\n",
       "      <td>111109</td>\n",
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       "      <th>45473</th>\n",
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       "      <td>67758</td>\n",
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       "      <td>227506</td>\n",
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       "    <tr>\n",
       "      <th>45475</th>\n",
       "      <td>[]</td>\n",
       "      <td>[{'credit_id': '593e676c92514105b702e68e', 'de...</td>\n",
       "      <td>461257</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45476 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    cast  \\\n",
       "0      [{'cast_id': 14, 'character': 'Woody (voice)',...   \n",
       "1      [{'cast_id': 1, 'character': 'Alan Parrish', '...   \n",
       "2      [{'cast_id': 2, 'character': 'Max Goldman', 'c...   \n",
       "3      [{'cast_id': 1, 'character': \"Savannah 'Vannah...   \n",
       "4      [{'cast_id': 1, 'character': 'George Banks', '...   \n",
       "...                                                  ...   \n",
       "45471  [{'cast_id': 0, 'character': '', 'credit_id': ...   \n",
       "45472  [{'cast_id': 1002, 'character': 'Sister Angela...   \n",
       "45473  [{'cast_id': 6, 'character': 'Emily Shaw', 'cr...   \n",
       "45474  [{'cast_id': 2, 'character': '', 'credit_id': ...   \n",
       "45475                                                 []   \n",
       "\n",
       "                                                    crew      id  \n",
       "0      [{'credit_id': '52fe4284c3a36847f8024f49', 'de...     862  \n",
       "1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...    8844  \n",
       "2      [{'credit_id': '52fe466a9251416c75077a89', 'de...   15602  \n",
       "3      [{'credit_id': '52fe44779251416c91011acb', 'de...   31357  \n",
       "4      [{'credit_id': '52fe44959251416c75039ed7', 'de...   11862  \n",
       "...                                                  ...     ...  \n",
       "45471  [{'credit_id': '5894a97d925141426c00818c', 'de...  439050  \n",
       "45472  [{'credit_id': '52fe4af1c3a36847f81e9b15', 'de...  111109  \n",
       "45473  [{'credit_id': '52fe4776c3a368484e0c8387', 'de...   67758  \n",
       "45474  [{'credit_id': '533bccebc3a36844cf0011a7', 'de...  227506  \n",
       "45475  [{'credit_id': '593e676c92514105b702e68e', 'de...  461257  \n",
       "\n",
       "[45476 rows x 3 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "credits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "credits['castlist'] = credits['cast'].apply( lambda x : StringToDict(x))\n",
    "credits['crewlist'] = credits['crew'].apply( lambda x : StringToDict(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <td>[{'cast_id': 1, 'character': 'Alan Parrish', '...</td>\n",
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       "      <td>[{'cast_id': 2, 'character': 'Max Goldman', 'c...</td>\n",
       "      <td>[{'credit_id': '52fe466a9251416c75077a89', 'de...</td>\n",
       "      <td>15602</td>\n",
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       "      <td>[{'credit_id': ' 52fe466a9251416c75077a89', 'd...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[{'cast_id': 1, 'character': \"Savannah 'Vannah...</td>\n",
       "      <td>[{'credit_id': '52fe44779251416c91011acb', 'de...</td>\n",
       "      <td>31357</td>\n",
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       "      <td>[{'credit_id': ' 52fe44779251416c91011acb', 'd...</td>\n",
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       "      <td>[{'cast_id': 1, 'character': 'George Banks', '...</td>\n",
       "      <td>[{'credit_id': '52fe44959251416c75039ed7', 'de...</td>\n",
       "      <td>11862</td>\n",
       "      <td>[{'cast_id': ' 1', 'character': ' George Banks...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>45472</th>\n",
       "      <td>[{'cast_id': 1002, 'character': 'Sister Angela...</td>\n",
       "      <td>[{'credit_id': '52fe4af1c3a36847f81e9b15', 'de...</td>\n",
       "      <td>111109</td>\n",
       "      <td>[{'cast_id': ' 1002', 'character': ' Sister An...</td>\n",
       "      <td>[{'credit_id': ' 52fe4af1c3a36847f81e9b15', 'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45473</th>\n",
       "      <td>[{'cast_id': 6, 'character': 'Emily Shaw', 'cr...</td>\n",
       "      <td>[{'credit_id': '52fe4776c3a368484e0c8387', 'de...</td>\n",
       "      <td>67758</td>\n",
       "      <td>[{'cast_id': ' 6', 'character': ' Emily Shaw',...</td>\n",
       "      <td>[{'credit_id': ' 52fe4776c3a368484e0c8387', 'd...</td>\n",
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       "    <tr>\n",
       "      <th>45474</th>\n",
       "      <td>[{'cast_id': 2, 'character': '', 'credit_id': ...</td>\n",
       "      <td>[{'credit_id': '533bccebc3a36844cf0011a7', 'de...</td>\n",
       "      <td>227506</td>\n",
       "      <td>[{'cast_id': ' 2', 'character': ' ', 'credit_i...</td>\n",
       "      <td>[{'credit_id': ' 533bccebc3a36844cf0011a7', 'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45475</th>\n",
       "      <td>[]</td>\n",
       "      <td>[{'credit_id': '593e676c92514105b702e68e', 'de...</td>\n",
       "      <td>461257</td>\n",
       "      <td>[{}]</td>\n",
       "      <td>[{'credit_id': ' 593e676c92514105b702e68e', 'd...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45476 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    cast  \\\n",
       "0      [{'cast_id': 14, 'character': 'Woody (voice)',...   \n",
       "1      [{'cast_id': 1, 'character': 'Alan Parrish', '...   \n",
       "2      [{'cast_id': 2, 'character': 'Max Goldman', 'c...   \n",
       "3      [{'cast_id': 1, 'character': \"Savannah 'Vannah...   \n",
       "4      [{'cast_id': 1, 'character': 'George Banks', '...   \n",
       "...                                                  ...   \n",
       "45471  [{'cast_id': 0, 'character': '', 'credit_id': ...   \n",
       "45472  [{'cast_id': 1002, 'character': 'Sister Angela...   \n",
       "45473  [{'cast_id': 6, 'character': 'Emily Shaw', 'cr...   \n",
       "45474  [{'cast_id': 2, 'character': '', 'credit_id': ...   \n",
       "45475                                                 []   \n",
       "\n",
       "                                                    crew      id  \\\n",
       "0      [{'credit_id': '52fe4284c3a36847f8024f49', 'de...     862   \n",
       "1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...    8844   \n",
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       "3      [{'credit_id': '52fe44779251416c91011acb', 'de...   31357   \n",
       "4      [{'credit_id': '52fe44959251416c75039ed7', 'de...   11862   \n",
       "...                                                  ...     ...   \n",
       "45471  [{'credit_id': '5894a97d925141426c00818c', 'de...  439050   \n",
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       "45475  [{'credit_id': '593e676c92514105b702e68e', 'de...  461257   \n",
       "\n",
       "                                                castlist  \\\n",
       "0      [{'cast_id': ' 14', 'character': ' Woody (voic...   \n",
       "1      [{'cast_id': ' 1', 'character': ' Alan Parrish...   \n",
       "2      [{'cast_id': ' 2', 'character': ' Max Goldman'...   \n",
       "3      [{'cast_id': ' 1', 'character': ' \"Savannah Va...   \n",
       "4      [{'cast_id': ' 1', 'character': ' George Banks...   \n",
       "...                                                  ...   \n",
       "45471  [{'cast_id': ' 0', 'character': ' ', 'credit_i...   \n",
       "45472  [{'cast_id': ' 1002', 'character': ' Sister An...   \n",
       "45473  [{'cast_id': ' 6', 'character': ' Emily Shaw',...   \n",
       "45474  [{'cast_id': ' 2', 'character': ' ', 'credit_i...   \n",
       "45475                                               [{}]   \n",
       "\n",
       "                                                crewlist  \n",
       "0      [{'credit_id': ' 52fe4284c3a36847f8024f49', 'd...  \n",
       "1      [{'credit_id': ' 52fe44bfc3a36847f80a7cd1', 'd...  \n",
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       "...                                                  ...  \n",
       "45471  [{'credit_id': ' 5894a97d925141426c00818c', 'd...  \n",
       "45472  [{'credit_id': ' 52fe4af1c3a36847f81e9b15', 'd...  \n",
       "45473  [{'credit_id': ' 52fe4776c3a368484e0c8387', 'd...  \n",
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       "45475  [{'credit_id': ' 593e676c92514105b702e68e', 'd...  \n",
       "\n",
       "[45476 rows x 5 columns]"
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   "source": [
    "credits"
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  {
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   "execution_count": 9,
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       "           id                                           keywords\n",
       "0         862  [{'id': 931, 'name': 'jealousy'}, {'id': 4290,...\n",
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       "46416   67758                                                 []\n",
       "46417  227506                                                 []\n",
       "46418  461257                                                 []\n",
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   "source": [
    "keywords"
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  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "<p>46419 rows × 3 columns</p>\n",
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      ],
      "text/plain": [
       "           id                                           keywords  \\\n",
       "0         862  [{'id': 931, 'name': 'jealousy'}, {'id': 4290,...   \n",
       "1        8844  [{'id': 10090, 'name': 'board game'}, {'id': 1...   \n",
       "2       15602  [{'id': 1495, 'name': 'fishing'}, {'id': 12392...   \n",
       "3       31357  [{'id': 818, 'name': 'based on novel'}, {'id':...   \n",
       "4       11862  [{'id': 1009, 'name': 'baby'}, {'id': 1599, 'n...   \n",
       "...       ...                                                ...   \n",
       "46414  439050             [{'id': 10703, 'name': 'tragic love'}]   \n",
       "46415  111109  [{'id': 2679, 'name': 'artist'}, {'id': 14531,...   \n",
       "46416   67758                                                 []   \n",
       "46417  227506                                                 []   \n",
       "46418  461257                                                 []   \n",
       "\n",
       "                                                 keylist  \n",
       "0      [{'id': ' 931', 'name': ' jealousy'}, {'id': '...  \n",
       "1      [{'id': ' 10090', 'name': ' board game'}, {'id...  \n",
       "2      [{'id': ' 1495', 'name': ' fishing'}, {'id': '...  \n",
       "3      [{'id': ' 818', 'name': ' based on novel'}, {'...  \n",
       "4      [{'id': ' 1009', 'name': ' baby'}, {'id': ' 15...  \n",
       "...                                                  ...  \n",
       "46414         [{'id': ' 10703', 'name': ' tragic love'}]  \n",
       "46415  [{'id': ' 2679', 'name': ' artist'}, {'id': ' ...  \n",
       "46416                                               [{}]  \n",
       "46417                                               [{}]  \n",
       "46418                                               [{}]  \n",
       "\n",
       "[46419 rows x 3 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keywords['keylist'] = keywords['keywords'].apply( lambda x : StringToDict(x))\n",
    "keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[           id                                           keywords  \\\n",
       " 0         862  [{'id': 931, 'name': 'jealousy'}, {'id': 4290,...   \n",
       " 1        8844  [{'id': 10090, 'name': 'board game'}, {'id': 1...   \n",
       " 2       15602  [{'id': 1495, 'name': 'fishing'}, {'id': 12392...   \n",
       " 3       31357  [{'id': 818, 'name': 'based on novel'}, {'id':...   \n",
       " 4       11862  [{'id': 1009, 'name': 'baby'}, {'id': 1599, 'n...   \n",
       " ...       ...                                                ...   \n",
       " 46414  439050             [{'id': 10703, 'name': 'tragic love'}]   \n",
       " 46415  111109  [{'id': 2679, 'name': 'artist'}, {'id': 14531,...   \n",
       " 46416   67758                                                 []   \n",
       " 46417  227506                                                 []   \n",
       " 46418  461257                                                 []   \n",
       " \n",
       "                                                  keylist  \n",
       " 0      [{'id': ' 931', 'name': ' jealousy'}, {'id': '...  \n",
       " 1      [{'id': ' 10090', 'name': ' board game'}, {'id...  \n",
       " 2      [{'id': ' 1495', 'name': ' fishing'}, {'id': '...  \n",
       " 3      [{'id': ' 818', 'name': ' based on novel'}, {'...  \n",
       " 4      [{'id': ' 1009', 'name': ' baby'}, {'id': ' 15...  \n",
       " ...                                                  ...  \n",
       " 46414         [{'id': ' 10703', 'name': ' tragic love'}]  \n",
       " 46415  [{'id': ' 2679', 'name': ' artist'}, {'id': ' ...  \n",
       " 46416                                               [{}]  \n",
       " 46417                                               [{}]  \n",
       " 46418                                               [{}]  \n",
       " \n",
       " [46419 rows x 3 columns],\n",
       "                                                     cast  \\\n",
       " 0      [{'cast_id': 14, 'character': 'Woody (voice)',...   \n",
       " 1      [{'cast_id': 1, 'character': 'Alan Parrish', '...   \n",
       " 2      [{'cast_id': 2, 'character': 'Max Goldman', 'c...   \n",
       " 3      [{'cast_id': 1, 'character': \"Savannah 'Vannah...   \n",
       " 4      [{'cast_id': 1, 'character': 'George Banks', '...   \n",
       " ...                                                  ...   \n",
       " 45471  [{'cast_id': 0, 'character': '', 'credit_id': ...   \n",
       " 45472  [{'cast_id': 1002, 'character': 'Sister Angela...   \n",
       " 45473  [{'cast_id': 6, 'character': 'Emily Shaw', 'cr...   \n",
       " 45474  [{'cast_id': 2, 'character': '', 'credit_id': ...   \n",
       " 45475                                                 []   \n",
       " \n",
       "                                                     crew      id  \\\n",
       " 0      [{'credit_id': '52fe4284c3a36847f8024f49', 'de...     862   \n",
       " 1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...    8844   \n",
       " 2      [{'credit_id': '52fe466a9251416c75077a89', 'de...   15602   \n",
       " 3      [{'credit_id': '52fe44779251416c91011acb', 'de...   31357   \n",
       " 4      [{'credit_id': '52fe44959251416c75039ed7', 'de...   11862   \n",
       " ...                                                  ...     ...   \n",
       " 45471  [{'credit_id': '5894a97d925141426c00818c', 'de...  439050   \n",
       " 45472  [{'credit_id': '52fe4af1c3a36847f81e9b15', 'de...  111109   \n",
       " 45473  [{'credit_id': '52fe4776c3a368484e0c8387', 'de...   67758   \n",
       " 45474  [{'credit_id': '533bccebc3a36844cf0011a7', 'de...  227506   \n",
       " 45475  [{'credit_id': '593e676c92514105b702e68e', 'de...  461257   \n",
       " \n",
       "                                                 castlist  \\\n",
       " 0      [{'cast_id': ' 14', 'character': ' Woody (voic...   \n",
       " 1      [{'cast_id': ' 1', 'character': ' Alan Parrish...   \n",
       " 2      [{'cast_id': ' 2', 'character': ' Max Goldman'...   \n",
       " 3      [{'cast_id': ' 1', 'character': ' \"Savannah Va...   \n",
       " 4      [{'cast_id': ' 1', 'character': ' George Banks...   \n",
       " ...                                                  ...   \n",
       " 45471  [{'cast_id': ' 0', 'character': ' ', 'credit_i...   \n",
       " 45472  [{'cast_id': ' 1002', 'character': ' Sister An...   \n",
       " 45473  [{'cast_id': ' 6', 'character': ' Emily Shaw',...   \n",
       " 45474  [{'cast_id': ' 2', 'character': ' ', 'credit_i...   \n",
       " 45475                                               [{}]   \n",
       " \n",
       "                                                 crewlist  \n",
       " 0      [{'credit_id': ' 52fe4284c3a36847f8024f49', 'd...  \n",
       " 1      [{'credit_id': ' 52fe44bfc3a36847f80a7cd1', 'd...  \n",
       " 2      [{'credit_id': ' 52fe466a9251416c75077a89', 'd...  \n",
       " 3      [{'credit_id': ' 52fe44779251416c91011acb', 'd...  \n",
       " 4      [{'credit_id': ' 52fe44959251416c75039ed7', 'd...  \n",
       " ...                                                  ...  \n",
       " 45471  [{'credit_id': ' 5894a97d925141426c00818c', 'd...  \n",
       " 45472  [{'credit_id': ' 52fe4af1c3a36847f81e9b15', 'd...  \n",
       " 45473  [{'credit_id': ' 52fe4776c3a368484e0c8387', 'd...  \n",
       " 45474  [{'credit_id': ' 533bccebc3a36844cf0011a7', 'd...  \n",
       " 45475  [{'credit_id': ' 593e676c92514105b702e68e', 'd...  \n",
       " \n",
       " [45476 rows x 5 columns],\n",
       "        movieId   imdbId    tmdbId\n",
       " 0            1   114709     862.0\n",
       " 1            2   113497    8844.0\n",
       " 2            3   113228   15602.0\n",
       " 3            4   114885   31357.0\n",
       " 4            5   113041   11862.0\n",
       " ...        ...      ...       ...\n",
       " 45838   176269  6209470  439050.0\n",
       " 45839   176271  2028550  111109.0\n",
       " 45840   176273   303758   67758.0\n",
       " 45841   176275     8536  227506.0\n",
       " 45842   176279  6980792  461257.0\n",
       " \n",
       " [45843 rows x 3 columns],\n",
       "        adult                              belongs_to_collection    budget  \\\n",
       " 0      False  {'id': 10194, 'name': 'Toy Story Collection', ...  30000000   \n",
       " 1      False                                                NaN  65000000   \n",
       " 2      False  {'id': 119050, 'name': 'Grumpy Old Men Collect...         0   \n",
       " 3      False                                                NaN  16000000   \n",
       " 4      False  {'id': 96871, 'name': 'Father of the Bride Col...         0   \n",
       " ...      ...                                                ...       ...   \n",
       " 45461  False                                                NaN         0   \n",
       " 45462  False                                                NaN         0   \n",
       " 45463  False                                                NaN         0   \n",
       " 45464  False                                                NaN         0   \n",
       " 45465  False                                                NaN         0   \n",
       " \n",
       "                                                   genres  \\\n",
       " 0      [{'id': 16, 'name': 'Animation'}, {'id': 35, '...   \n",
       " 1      [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...   \n",
       " 2      [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...   \n",
       " 3      [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...   \n",
       " 4                         [{'id': 35, 'name': 'Comedy'}]   \n",
       " ...                                                  ...   \n",
       " 45461  [{'id': 18, 'name': 'Drama'}, {'id': 10751, 'n...   \n",
       " 45462                      [{'id': 18, 'name': 'Drama'}]   \n",
       " 45463  [{'id': 28, 'name': 'Action'}, {'id': 18, 'nam...   \n",
       " 45464                                                 []   \n",
       " 45465                                                 []   \n",
       " \n",
       "                                    homepage      id    imdb_id  \\\n",
       " 0      http://toystory.disney.com/toy-story     862  tt0114709   \n",
       " 1                                       NaN    8844  tt0113497   \n",
       " 2                                       NaN   15602  tt0113228   \n",
       " 3                                       NaN   31357  tt0114885   \n",
       " 4                                       NaN   11862  tt0113041   \n",
       " ...                                     ...     ...        ...   \n",
       " 45461  http://www.imdb.com/title/tt6209470/  439050  tt6209470   \n",
       " 45462                                   NaN  111109  tt2028550   \n",
       " 45463                                   NaN   67758  tt0303758   \n",
       " 45464                                   NaN  227506  tt0008536   \n",
       " 45465                                   NaN  461257  tt6980792   \n",
       " \n",
       "       original_language               original_title  \\\n",
       " 0                    en                    Toy Story   \n",
       " 1                    en                      Jumanji   \n",
       " 2                    en             Grumpier Old Men   \n",
       " 3                    en            Waiting to Exhale   \n",
       " 4                    en  Father of the Bride Part II   \n",
       " ...                 ...                          ...   \n",
       " 45461                fa                      رگ خواب   \n",
       " 45462                tl          Siglo ng Pagluluwal   \n",
       " 45463                en                     Betrayal   \n",
       " 45464                en          Satana likuyushchiy   \n",
       " 45465                en                     Queerama   \n",
       " \n",
       "                                                 overview popularity  \\\n",
       " 0      Led by Woody, Andy's toys live happily in his ...  21.946943   \n",
       " 1      When siblings Judy and Peter discover an encha...  17.015539   \n",
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       " ...                                                  ...        ...   \n",
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       " 45462  An artist struggles to finish his work while a...   0.178241   \n",
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       " 45464  In a small town live two brothers, one a minis...   0.003503   \n",
       " 45465  50 years after decriminalisation of homosexual...   0.163015   \n",
       " \n",
       "                             poster_path  \\\n",
       " 0      /rhIRbceoE9lR4veEXuwCC2wARtG.jpg   \n",
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       " ...                                 ...   \n",
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       " \n",
       "                                     production_companies  \\\n",
       " 0         [{'name': 'Pixar Animation Studios', 'id': 3}]   \n",
       " 1      [{'name': 'TriStar Pictures', 'id': 559}, {'na...   \n",
       " 2      [{'name': 'Warner Bros.', 'id': 6194}, {'name'...   \n",
       " 3      [{'name': 'Twentieth Century Fox Film Corporat...   \n",
       " 4      [{'name': 'Sandollar Productions', 'id': 5842}...   \n",
       " ...                                                  ...   \n",
       " 45461                                                 []   \n",
       " 45462             [{'name': 'Sine Olivia', 'id': 19653}]   \n",
       " 45463  [{'name': 'American World Pictures', 'id': 6165}]   \n",
       " 45464               [{'name': 'Yermoliev', 'id': 88753}]   \n",
       " 45465                                                 []   \n",
       " \n",
       "                                     production_countries release_date  \\\n",
       " 0      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-10-30   \n",
       " 1      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-15   \n",
       " 2      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-22   \n",
       " 3      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-22   \n",
       " 4      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-02-10   \n",
       " ...                                                  ...          ...   \n",
       " 45461             [{'iso_3166_1': 'IR', 'name': 'Iran'}]          NaN   \n",
       " 45462      [{'iso_3166_1': 'PH', 'name': 'Philippines'}]   2011-11-17   \n",
       " 45463  [{'iso_3166_1': 'US', 'name': 'United States o...   2003-08-01   \n",
       " 45464           [{'iso_3166_1': 'RU', 'name': 'Russia'}]   1917-10-21   \n",
       " 45465   [{'iso_3166_1': 'GB', 'name': 'United Kingdom'}]   2017-06-09   \n",
       " \n",
       "            revenue  runtime  \\\n",
       " 0      373554033.0     81.0   \n",
       " 1      262797249.0    104.0   \n",
       " 2              0.0    101.0   \n",
       " 3       81452156.0    127.0   \n",
       " 4       76578911.0    106.0   \n",
       " ...            ...      ...   \n",
       " 45461          0.0     90.0   \n",
       " 45462          0.0    360.0   \n",
       " 45463          0.0     90.0   \n",
       " 45464          0.0     87.0   \n",
       " 45465          0.0     75.0   \n",
       " \n",
       "                                         spoken_languages    status  \\\n",
       " 0               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " 1      [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       " 2               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
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       " 4               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " ...                                                  ...       ...   \n",
       " 45461             [{'iso_639_1': 'fa', 'name': 'فارسی'}]  Released   \n",
       " 45462                  [{'iso_639_1': 'tl', 'name': ''}]  Released   \n",
       " 45463           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " 45464                                                 []  Released   \n",
       " 45465           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " \n",
       "                                                  tagline  \\\n",
       " 0                                                    NaN   \n",
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       " 3      Friends are the people who let you be yourself...   \n",
       " 4      Just When His World Is Back To Normal... He's ...   \n",
       " ...                                                  ...   \n",
       " 45461         Rising and falling between a man and woman   \n",
       " 45462                                                NaN   \n",
       " 45463                             A deadly game of wits.   \n",
       " 45464                                                NaN   \n",
       " 45465                                                NaN   \n",
       " \n",
       "                              title  video  vote_average  vote_count  \n",
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       " 1                          Jumanji  False           6.9      2413.0  \n",
       " 2                 Grumpier Old Men  False           6.5        92.0  \n",
       " 3                Waiting to Exhale  False           6.1        34.0  \n",
       " 4      Father of the Bride Part II  False           5.7       173.0  \n",
       " ...                            ...    ...           ...         ...  \n",
       " 45461                       Subdue  False           4.0         1.0  \n",
       " 45462          Century of Birthing  False           9.0         3.0  \n",
       " 45463                     Betrayal  False           3.8         6.0  \n",
       " 45464             Satan Triumphant  False           0.0         0.0  \n",
       " 45465                     Queerama  False           0.0         0.0  \n",
       " \n",
       " [45466 rows x 24 columns],\n",
       "           userId  movieId  rating   timestamp\n",
       " 0              1      110     1.0  1425941529\n",
       " 1              1      147     4.5  1425942435\n",
       " 2              1      858     5.0  1425941523\n",
       " 3              1     1221     5.0  1425941546\n",
       " 4              1     1246     5.0  1425941556\n",
       " ...          ...      ...     ...         ...\n",
       " 26024284  270896    58559     5.0  1257031564\n",
       " 26024285  270896    60069     5.0  1257032032\n",
       " 26024286  270896    63082     4.5  1257031764\n",
       " 26024287  270896    64957     4.5  1257033990\n",
       " 26024288  270896    71878     2.0  1257031858\n",
       " \n",
       " [26024289 rows x 4 columns],\n",
       "         userId  movieId  rating   timestamp\n",
       " 0            1       31     2.5  1260759144\n",
       " 1            1     1029     3.0  1260759179\n",
       " 2            1     1061     3.0  1260759182\n",
       " 3            1     1129     2.0  1260759185\n",
       " 4            1     1172     4.0  1260759205\n",
       " ...        ...      ...     ...         ...\n",
       " 99999      671     6268     2.5  1065579370\n",
       " 100000     671     6269     4.0  1065149201\n",
       " 100001     671     6365     4.0  1070940363\n",
       " 100002     671     6385     2.5  1070979663\n",
       " 100003     671     6565     3.5  1074784724\n",
       " \n",
       " [100004 rows x 4 columns]]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [keywords,credits,links,movies_metadata,ratings,ratings_small]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
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       "                                                    cast  \\\n",
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       "45475                                                 []   \n",
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       "\n",
       "                                                castlist  \\\n",
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       "...                                                  ...   \n",
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       "45474  [{'cast_id': ' 2', 'character': ' ', 'credit_i...   \n",
       "45475                                               [{}]   \n",
       "\n",
       "                                                crewlist  \n",
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  {
   "cell_type": "code",
   "execution_count": 13,
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       "           id                                           keywords  \\\n",
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       "...       ...                                                ...   \n",
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       "46416   67758                                                 []   \n",
       "46417  227506                                                 []   \n",
       "46418  461257                                                 []   \n",
       "\n",
       "                                                 keylist  \n",
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       "...                                                  ...  \n",
       "46414         [{'id': ' 10703', 'name': ' tragic love'}]  \n",
       "46415  [{'id': ' 2679', 'name': ' artist'}, {'id': ' ...  \n",
       "46416                                               [{}]  \n",
       "46417                                               [{}]  \n",
       "46418                                               [{}]  \n",
       "\n",
       "[46419 rows x 3 columns]"
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     },
     "execution_count": 13,
     "metadata": {},
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   ],
   "source": [
    "keywords\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
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       "       movieId   imdbId        id\n",
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    "links = links.rename(columns={'tmdbId':'id'})\n",
    "links"
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  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
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       "      <th>45465</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>461257</td>\n",
       "      <td>tt6980792</td>\n",
       "      <td>en</td>\n",
       "      <td>Queerama</td>\n",
       "      <td>50 years after decriminalisation of homosexual...</td>\n",
       "      <td>0.163015</td>\n",
       "      <td>/s5UkZt6NTsrS7ZF0Rh8nzupRlIU.jpg</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{'iso_3166_1': 'GB', 'name': 'United Kingdom'}]</td>\n",
       "      <td>2017-06-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Queerama</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45466 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       adult                              belongs_to_collection    budget  \\\n",
       "0      False  {'id': 10194, 'name': 'Toy Story Collection', ...  30000000   \n",
       "1      False                                                NaN  65000000   \n",
       "2      False  {'id': 119050, 'name': 'Grumpy Old Men Collect...         0   \n",
       "3      False                                                NaN  16000000   \n",
       "4      False  {'id': 96871, 'name': 'Father of the Bride Col...         0   \n",
       "...      ...                                                ...       ...   \n",
       "45461  False                                                NaN         0   \n",
       "45462  False                                                NaN         0   \n",
       "45463  False                                                NaN         0   \n",
       "45464  False                                                NaN         0   \n",
       "45465  False                                                NaN         0   \n",
       "\n",
       "                                                  genres  \\\n",
       "0      [{'id': 16, 'name': 'Animation'}, {'id': 35, '...   \n",
       "1      [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...   \n",
       "2      [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...   \n",
       "3      [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...   \n",
       "4                         [{'id': 35, 'name': 'Comedy'}]   \n",
       "...                                                  ...   \n",
       "45461  [{'id': 18, 'name': 'Drama'}, {'id': 10751, 'n...   \n",
       "45462                      [{'id': 18, 'name': 'Drama'}]   \n",
       "45463  [{'id': 28, 'name': 'Action'}, {'id': 18, 'nam...   \n",
       "45464                                                 []   \n",
       "45465                                                 []   \n",
       "\n",
       "                                   homepage      id    imdb_id  \\\n",
       "0      http://toystory.disney.com/toy-story     862  tt0114709   \n",
       "1                                       NaN    8844  tt0113497   \n",
       "2                                       NaN   15602  tt0113228   \n",
       "3                                       NaN   31357  tt0114885   \n",
       "4                                       NaN   11862  tt0113041   \n",
       "...                                     ...     ...        ...   \n",
       "45461  http://www.imdb.com/title/tt6209470/  439050  tt6209470   \n",
       "45462                                   NaN  111109  tt2028550   \n",
       "45463                                   NaN   67758  tt0303758   \n",
       "45464                                   NaN  227506  tt0008536   \n",
       "45465                                   NaN  461257  tt6980792   \n",
       "\n",
       "      original_language               original_title  \\\n",
       "0                    en                    Toy Story   \n",
       "1                    en                      Jumanji   \n",
       "2                    en             Grumpier Old Men   \n",
       "3                    en            Waiting to Exhale   \n",
       "4                    en  Father of the Bride Part II   \n",
       "...                 ...                          ...   \n",
       "45461                fa                      رگ خواب   \n",
       "45462                tl          Siglo ng Pagluluwal   \n",
       "45463                en                     Betrayal   \n",
       "45464                en          Satana likuyushchiy   \n",
       "45465                en                     Queerama   \n",
       "\n",
       "                                                overview popularity  \\\n",
       "0      Led by Woody, Andy's toys live happily in his ...  21.946943   \n",
       "1      When siblings Judy and Peter discover an encha...  17.015539   \n",
       "2      A family wedding reignites the ancient feud be...    11.7129   \n",
       "3      Cheated on, mistreated and stepped on, the wom...   3.859495   \n",
       "4      Just when George Banks has recovered from his ...   8.387519   \n",
       "...                                                  ...        ...   \n",
       "45461        Rising and falling between a man and woman.   0.072051   \n",
       "45462  An artist struggles to finish his work while a...   0.178241   \n",
       "45463  When one of her hits goes wrong, a professiona...   0.903007   \n",
       "45464  In a small town live two brothers, one a minis...   0.003503   \n",
       "45465  50 years after decriminalisation of homosexual...   0.163015   \n",
       "\n",
       "                            poster_path  \\\n",
       "0      /rhIRbceoE9lR4veEXuwCC2wARtG.jpg   \n",
       "1      /vzmL6fP7aPKNKPRTFnZmiUfciyV.jpg   \n",
       "2      /6ksm1sjKMFLbO7UY2i6G1ju9SML.jpg   \n",
       "3      /16XOMpEaLWkrcPqSQqhTmeJuqQl.jpg   \n",
       "4      /e64sOI48hQXyru7naBFyssKFxVd.jpg   \n",
       "...                                 ...   \n",
       "45461  /jldsYflnId4tTWPx8es3uzsB1I8.jpg   \n",
       "45462  /xZkmxsNmYXJbKVsTRLLx3pqGHx7.jpg   \n",
       "45463  /d5bX92nDsISNhu3ZT69uHwmfCGw.jpg   \n",
       "45464  /aorBPO7ak8e8iJKT5OcqYxU3jlK.jpg   \n",
       "45465  /s5UkZt6NTsrS7ZF0Rh8nzupRlIU.jpg   \n",
       "\n",
       "                                    production_companies  \\\n",
       "0         [{'name': 'Pixar Animation Studios', 'id': 3}]   \n",
       "1      [{'name': 'TriStar Pictures', 'id': 559}, {'na...   \n",
       "2      [{'name': 'Warner Bros.', 'id': 6194}, {'name'...   \n",
       "3      [{'name': 'Twentieth Century Fox Film Corporat...   \n",
       "4      [{'name': 'Sandollar Productions', 'id': 5842}...   \n",
       "...                                                  ...   \n",
       "45461                                                 []   \n",
       "45462             [{'name': 'Sine Olivia', 'id': 19653}]   \n",
       "45463  [{'name': 'American World Pictures', 'id': 6165}]   \n",
       "45464               [{'name': 'Yermoliev', 'id': 88753}]   \n",
       "45465                                                 []   \n",
       "\n",
       "                                    production_countries release_date  \\\n",
       "0      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-10-30   \n",
       "1      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-15   \n",
       "2      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-22   \n",
       "3      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-22   \n",
       "4      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-02-10   \n",
       "...                                                  ...          ...   \n",
       "45461             [{'iso_3166_1': 'IR', 'name': 'Iran'}]          NaN   \n",
       "45462      [{'iso_3166_1': 'PH', 'name': 'Philippines'}]   2011-11-17   \n",
       "45463  [{'iso_3166_1': 'US', 'name': 'United States o...   2003-08-01   \n",
       "45464           [{'iso_3166_1': 'RU', 'name': 'Russia'}]   1917-10-21   \n",
       "45465   [{'iso_3166_1': 'GB', 'name': 'United Kingdom'}]   2017-06-09   \n",
       "\n",
       "           revenue  runtime  \\\n",
       "0      373554033.0     81.0   \n",
       "1      262797249.0    104.0   \n",
       "2              0.0    101.0   \n",
       "3       81452156.0    127.0   \n",
       "4       76578911.0    106.0   \n",
       "...            ...      ...   \n",
       "45461          0.0     90.0   \n",
       "45462          0.0    360.0   \n",
       "45463          0.0     90.0   \n",
       "45464          0.0     87.0   \n",
       "45465          0.0     75.0   \n",
       "\n",
       "                                        spoken_languages    status  \\\n",
       "0               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "1      [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "2               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "3               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "4               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "...                                                  ...       ...   \n",
       "45461             [{'iso_639_1': 'fa', 'name': 'فارسی'}]  Released   \n",
       "45462                  [{'iso_639_1': 'tl', 'name': ''}]  Released   \n",
       "45463           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "45464                                                 []  Released   \n",
       "45465           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "\n",
       "                                                 tagline  \\\n",
       "0                                                    NaN   \n",
       "1              Roll the dice and unleash the excitement!   \n",
       "2      Still Yelling. Still Fighting. Still Ready for...   \n",
       "3      Friends are the people who let you be yourself...   \n",
       "4      Just When His World Is Back To Normal... He's ...   \n",
       "...                                                  ...   \n",
       "45461         Rising and falling between a man and woman   \n",
       "45462                                                NaN   \n",
       "45463                             A deadly game of wits.   \n",
       "45464                                                NaN   \n",
       "45465                                                NaN   \n",
       "\n",
       "                             title  video  vote_average  vote_count  \n",
       "0                        Toy Story  False           7.7      5415.0  \n",
       "1                          Jumanji  False           6.9      2413.0  \n",
       "2                 Grumpier Old Men  False           6.5        92.0  \n",
       "3                Waiting to Exhale  False           6.1        34.0  \n",
       "4      Father of the Bride Part II  False           5.7       173.0  \n",
       "...                            ...    ...           ...         ...  \n",
       "45461                       Subdue  False           4.0         1.0  \n",
       "45462          Century of Birthing  False           9.0         3.0  \n",
       "45463                     Betrayal  False           3.8         6.0  \n",
       "45464             Satan Triumphant  False           0.0         0.0  \n",
       "45465                     Queerama  False           0.0         0.0  \n",
       "\n",
       "[45466 rows x 24 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "          userId     id  rating   timestamp\n",
       "0              1    110     1.0  1425941529\n",
       "1              1    147     4.5  1425942435\n",
       "2              1    858     5.0  1425941523\n",
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       "4              1   1246     5.0  1425941556\n",
       "...          ...    ...     ...         ...\n",
       "26024284  270896  58559     5.0  1257031564\n",
       "26024285  270896  60069     5.0  1257032032\n",
       "26024286  270896  63082     4.5  1257031764\n",
       "26024287  270896  64957     4.5  1257033990\n",
       "26024288  270896  71878     2.0  1257031858\n",
       "\n",
       "[26024289 rows x 4 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings = ratings.rename(columns={'movieId':'id'})\n",
    "\n",
    "ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "        userId    id  rating   timestamp\n",
       "0            1    31     2.5  1260759144\n",
       "1            1  1029     3.0  1260759179\n",
       "2            1  1061     3.0  1260759182\n",
       "3            1  1129     2.0  1260759185\n",
       "4            1  1172     4.0  1260759205\n",
       "...        ...   ...     ...         ...\n",
       "99999      671  6268     2.5  1065579370\n",
       "100000     671  6269     4.0  1065149201\n",
       "100001     671  6365     4.0  1070940363\n",
       "100002     671  6385     2.5  1070979663\n",
       "100003     671  6565     3.5  1074784724\n",
       "\n",
       "[100004 rows x 4 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_small = ratings_small.rename(columns={'movieId':'id'})\n",
    "\n",
    "ratings_small"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45115"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings['id'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9066"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_small['id'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[                                                    cast  \\\n",
       " 0      [{'cast_id': 14, 'character': 'Woody (voice)',...   \n",
       " 1      [{'cast_id': 1, 'character': 'Alan Parrish', '...   \n",
       " 2      [{'cast_id': 2, 'character': 'Max Goldman', 'c...   \n",
       " 3      [{'cast_id': 1, 'character': \"Savannah 'Vannah...   \n",
       " 4      [{'cast_id': 1, 'character': 'George Banks', '...   \n",
       " ...                                                  ...   \n",
       " 45471  [{'cast_id': 0, 'character': '', 'credit_id': ...   \n",
       " 45472  [{'cast_id': 1002, 'character': 'Sister Angela...   \n",
       " 45473  [{'cast_id': 6, 'character': 'Emily Shaw', 'cr...   \n",
       " 45474  [{'cast_id': 2, 'character': '', 'credit_id': ...   \n",
       " 45475                                                 []   \n",
       " \n",
       "                                                     crew      id  \\\n",
       " 0      [{'credit_id': '52fe4284c3a36847f8024f49', 'de...     862   \n",
       " 1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...    8844   \n",
       " 2      [{'credit_id': '52fe466a9251416c75077a89', 'de...   15602   \n",
       " 3      [{'credit_id': '52fe44779251416c91011acb', 'de...   31357   \n",
       " 4      [{'credit_id': '52fe44959251416c75039ed7', 'de...   11862   \n",
       " ...                                                  ...     ...   \n",
       " 45471  [{'credit_id': '5894a97d925141426c00818c', 'de...  439050   \n",
       " 45472  [{'credit_id': '52fe4af1c3a36847f81e9b15', 'de...  111109   \n",
       " 45473  [{'credit_id': '52fe4776c3a368484e0c8387', 'de...   67758   \n",
       " 45474  [{'credit_id': '533bccebc3a36844cf0011a7', 'de...  227506   \n",
       " 45475  [{'credit_id': '593e676c92514105b702e68e', 'de...  461257   \n",
       " \n",
       "                                                 castlist  \\\n",
       " 0      [{'cast_id': ' 14', 'character': ' Woody (voic...   \n",
       " 1      [{'cast_id': ' 1', 'character': ' Alan Parrish...   \n",
       " 2      [{'cast_id': ' 2', 'character': ' Max Goldman'...   \n",
       " 3      [{'cast_id': ' 1', 'character': ' \"Savannah Va...   \n",
       " 4      [{'cast_id': ' 1', 'character': ' George Banks...   \n",
       " ...                                                  ...   \n",
       " 45471  [{'cast_id': ' 0', 'character': ' ', 'credit_i...   \n",
       " 45472  [{'cast_id': ' 1002', 'character': ' Sister An...   \n",
       " 45473  [{'cast_id': ' 6', 'character': ' Emily Shaw',...   \n",
       " 45474  [{'cast_id': ' 2', 'character': ' ', 'credit_i...   \n",
       " 45475                                               [{}]   \n",
       " \n",
       "                                                 crewlist  \n",
       " 0      [{'credit_id': ' 52fe4284c3a36847f8024f49', 'd...  \n",
       " 1      [{'credit_id': ' 52fe44bfc3a36847f80a7cd1', 'd...  \n",
       " 2      [{'credit_id': ' 52fe466a9251416c75077a89', 'd...  \n",
       " 3      [{'credit_id': ' 52fe44779251416c91011acb', 'd...  \n",
       " 4      [{'credit_id': ' 52fe44959251416c75039ed7', 'd...  \n",
       " ...                                                  ...  \n",
       " 45471  [{'credit_id': ' 5894a97d925141426c00818c', 'd...  \n",
       " 45472  [{'credit_id': ' 52fe4af1c3a36847f81e9b15', 'd...  \n",
       " 45473  [{'credit_id': ' 52fe4776c3a368484e0c8387', 'd...  \n",
       " 45474  [{'credit_id': ' 533bccebc3a36844cf0011a7', 'd...  \n",
       " 45475  [{'credit_id': ' 593e676c92514105b702e68e', 'd...  \n",
       " \n",
       " [45476 rows x 5 columns],\n",
       "            id                                           keywords  \\\n",
       " 0         862  [{'id': 931, 'name': 'jealousy'}, {'id': 4290,...   \n",
       " 1        8844  [{'id': 10090, 'name': 'board game'}, {'id': 1...   \n",
       " 2       15602  [{'id': 1495, 'name': 'fishing'}, {'id': 12392...   \n",
       " 3       31357  [{'id': 818, 'name': 'based on novel'}, {'id':...   \n",
       " 4       11862  [{'id': 1009, 'name': 'baby'}, {'id': 1599, 'n...   \n",
       " ...       ...                                                ...   \n",
       " 46414  439050             [{'id': 10703, 'name': 'tragic love'}]   \n",
       " 46415  111109  [{'id': 2679, 'name': 'artist'}, {'id': 14531,...   \n",
       " 46416   67758                                                 []   \n",
       " 46417  227506                                                 []   \n",
       " 46418  461257                                                 []   \n",
       " \n",
       "                                                  keylist  \n",
       " 0      [{'id': ' 931', 'name': ' jealousy'}, {'id': '...  \n",
       " 1      [{'id': ' 10090', 'name': ' board game'}, {'id...  \n",
       " 2      [{'id': ' 1495', 'name': ' fishing'}, {'id': '...  \n",
       " 3      [{'id': ' 818', 'name': ' based on novel'}, {'...  \n",
       " 4      [{'id': ' 1009', 'name': ' baby'}, {'id': ' 15...  \n",
       " ...                                                  ...  \n",
       " 46414         [{'id': ' 10703', 'name': ' tragic love'}]  \n",
       " 46415  [{'id': ' 2679', 'name': ' artist'}, {'id': ' ...  \n",
       " 46416                                               [{}]  \n",
       " 46417                                               [{}]  \n",
       " 46418                                               [{}]  \n",
       " \n",
       " [46419 rows x 3 columns],\n",
       "        movieId   imdbId        id\n",
       " 0            1   114709     862.0\n",
       " 1            2   113497    8844.0\n",
       " 2            3   113228   15602.0\n",
       " 3            4   114885   31357.0\n",
       " 4            5   113041   11862.0\n",
       " ...        ...      ...       ...\n",
       " 45838   176269  6209470  439050.0\n",
       " 45839   176271  2028550  111109.0\n",
       " 45840   176273   303758   67758.0\n",
       " 45841   176275     8536  227506.0\n",
       " 45842   176279  6980792  461257.0\n",
       " \n",
       " [45843 rows x 3 columns],\n",
       "        adult                              belongs_to_collection    budget  \\\n",
       " 0      False  {'id': 10194, 'name': 'Toy Story Collection', ...  30000000   \n",
       " 1      False                                                NaN  65000000   \n",
       " 2      False  {'id': 119050, 'name': 'Grumpy Old Men Collect...         0   \n",
       " 3      False                                                NaN  16000000   \n",
       " 4      False  {'id': 96871, 'name': 'Father of the Bride Col...         0   \n",
       " ...      ...                                                ...       ...   \n",
       " 45461  False                                                NaN         0   \n",
       " 45462  False                                                NaN         0   \n",
       " 45463  False                                                NaN         0   \n",
       " 45464  False                                                NaN         0   \n",
       " 45465  False                                                NaN         0   \n",
       " \n",
       "                                                   genres  \\\n",
       " 0      [{'id': 16, 'name': 'Animation'}, {'id': 35, '...   \n",
       " 1      [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...   \n",
       " 2      [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...   \n",
       " 3      [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...   \n",
       " 4                         [{'id': 35, 'name': 'Comedy'}]   \n",
       " ...                                                  ...   \n",
       " 45461  [{'id': 18, 'name': 'Drama'}, {'id': 10751, 'n...   \n",
       " 45462                      [{'id': 18, 'name': 'Drama'}]   \n",
       " 45463  [{'id': 28, 'name': 'Action'}, {'id': 18, 'nam...   \n",
       " 45464                                                 []   \n",
       " 45465                                                 []   \n",
       " \n",
       "                                    homepage      id    imdb_id  \\\n",
       " 0      http://toystory.disney.com/toy-story     862  tt0114709   \n",
       " 1                                       NaN    8844  tt0113497   \n",
       " 2                                       NaN   15602  tt0113228   \n",
       " 3                                       NaN   31357  tt0114885   \n",
       " 4                                       NaN   11862  tt0113041   \n",
       " ...                                     ...     ...        ...   \n",
       " 45461  http://www.imdb.com/title/tt6209470/  439050  tt6209470   \n",
       " 45462                                   NaN  111109  tt2028550   \n",
       " 45463                                   NaN   67758  tt0303758   \n",
       " 45464                                   NaN  227506  tt0008536   \n",
       " 45465                                   NaN  461257  tt6980792   \n",
       " \n",
       "       original_language               original_title  \\\n",
       " 0                    en                    Toy Story   \n",
       " 1                    en                      Jumanji   \n",
       " 2                    en             Grumpier Old Men   \n",
       " 3                    en            Waiting to Exhale   \n",
       " 4                    en  Father of the Bride Part II   \n",
       " ...                 ...                          ...   \n",
       " 45461                fa                      رگ خواب   \n",
       " 45462                tl          Siglo ng Pagluluwal   \n",
       " 45463                en                     Betrayal   \n",
       " 45464                en          Satana likuyushchiy   \n",
       " 45465                en                     Queerama   \n",
       " \n",
       "                                                 overview popularity  \\\n",
       " 0      Led by Woody, Andy's toys live happily in his ...  21.946943   \n",
       " 1      When siblings Judy and Peter discover an encha...  17.015539   \n",
       " 2      A family wedding reignites the ancient feud be...    11.7129   \n",
       " 3      Cheated on, mistreated and stepped on, the wom...   3.859495   \n",
       " 4      Just when George Banks has recovered from his ...   8.387519   \n",
       " ...                                                  ...        ...   \n",
       " 45461        Rising and falling between a man and woman.   0.072051   \n",
       " 45462  An artist struggles to finish his work while a...   0.178241   \n",
       " 45463  When one of her hits goes wrong, a professiona...   0.903007   \n",
       " 45464  In a small town live two brothers, one a minis...   0.003503   \n",
       " 45465  50 years after decriminalisation of homosexual...   0.163015   \n",
       " \n",
       "                             poster_path  \\\n",
       " 0      /rhIRbceoE9lR4veEXuwCC2wARtG.jpg   \n",
       " 1      /vzmL6fP7aPKNKPRTFnZmiUfciyV.jpg   \n",
       " 2      /6ksm1sjKMFLbO7UY2i6G1ju9SML.jpg   \n",
       " 3      /16XOMpEaLWkrcPqSQqhTmeJuqQl.jpg   \n",
       " 4      /e64sOI48hQXyru7naBFyssKFxVd.jpg   \n",
       " ...                                 ...   \n",
       " 45461  /jldsYflnId4tTWPx8es3uzsB1I8.jpg   \n",
       " 45462  /xZkmxsNmYXJbKVsTRLLx3pqGHx7.jpg   \n",
       " 45463  /d5bX92nDsISNhu3ZT69uHwmfCGw.jpg   \n",
       " 45464  /aorBPO7ak8e8iJKT5OcqYxU3jlK.jpg   \n",
       " 45465  /s5UkZt6NTsrS7ZF0Rh8nzupRlIU.jpg   \n",
       " \n",
       "                                     production_companies  \\\n",
       " 0         [{'name': 'Pixar Animation Studios', 'id': 3}]   \n",
       " 1      [{'name': 'TriStar Pictures', 'id': 559}, {'na...   \n",
       " 2      [{'name': 'Warner Bros.', 'id': 6194}, {'name'...   \n",
       " 3      [{'name': 'Twentieth Century Fox Film Corporat...   \n",
       " 4      [{'name': 'Sandollar Productions', 'id': 5842}...   \n",
       " ...                                                  ...   \n",
       " 45461                                                 []   \n",
       " 45462             [{'name': 'Sine Olivia', 'id': 19653}]   \n",
       " 45463  [{'name': 'American World Pictures', 'id': 6165}]   \n",
       " 45464               [{'name': 'Yermoliev', 'id': 88753}]   \n",
       " 45465                                                 []   \n",
       " \n",
       "                                     production_countries release_date  \\\n",
       " 0      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-10-30   \n",
       " 1      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-15   \n",
       " 2      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-22   \n",
       " 3      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-22   \n",
       " 4      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-02-10   \n",
       " ...                                                  ...          ...   \n",
       " 45461             [{'iso_3166_1': 'IR', 'name': 'Iran'}]          NaN   \n",
       " 45462      [{'iso_3166_1': 'PH', 'name': 'Philippines'}]   2011-11-17   \n",
       " 45463  [{'iso_3166_1': 'US', 'name': 'United States o...   2003-08-01   \n",
       " 45464           [{'iso_3166_1': 'RU', 'name': 'Russia'}]   1917-10-21   \n",
       " 45465   [{'iso_3166_1': 'GB', 'name': 'United Kingdom'}]   2017-06-09   \n",
       " \n",
       "            revenue  runtime  \\\n",
       " 0      373554033.0     81.0   \n",
       " 1      262797249.0    104.0   \n",
       " 2              0.0    101.0   \n",
       " 3       81452156.0    127.0   \n",
       " 4       76578911.0    106.0   \n",
       " ...            ...      ...   \n",
       " 45461          0.0     90.0   \n",
       " 45462          0.0    360.0   \n",
       " 45463          0.0     90.0   \n",
       " 45464          0.0     87.0   \n",
       " 45465          0.0     75.0   \n",
       " \n",
       "                                         spoken_languages    status  \\\n",
       " 0               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " 1      [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       " 2               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " 3               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " 4               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " ...                                                  ...       ...   \n",
       " 45461             [{'iso_639_1': 'fa', 'name': 'فارسی'}]  Released   \n",
       " 45462                  [{'iso_639_1': 'tl', 'name': ''}]  Released   \n",
       " 45463           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " 45464                                                 []  Released   \n",
       " 45465           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       " \n",
       "                                                  tagline  \\\n",
       " 0                                                    NaN   \n",
       " 1              Roll the dice and unleash the excitement!   \n",
       " 2      Still Yelling. Still Fighting. Still Ready for...   \n",
       " 3      Friends are the people who let you be yourself...   \n",
       " 4      Just When His World Is Back To Normal... He's ...   \n",
       " ...                                                  ...   \n",
       " 45461         Rising and falling between a man and woman   \n",
       " 45462                                                NaN   \n",
       " 45463                             A deadly game of wits.   \n",
       " 45464                                                NaN   \n",
       " 45465                                                NaN   \n",
       " \n",
       "                              title  video  vote_average  vote_count  \n",
       " 0                        Toy Story  False           7.7      5415.0  \n",
       " 1                          Jumanji  False           6.9      2413.0  \n",
       " 2                 Grumpier Old Men  False           6.5        92.0  \n",
       " 3                Waiting to Exhale  False           6.1        34.0  \n",
       " 4      Father of the Bride Part II  False           5.7       173.0  \n",
       " ...                            ...    ...           ...         ...  \n",
       " 45461                       Subdue  False           4.0         1.0  \n",
       " 45462          Century of Birthing  False           9.0         3.0  \n",
       " 45463                     Betrayal  False           3.8         6.0  \n",
       " 45464             Satan Triumphant  False           0.0         0.0  \n",
       " 45465                     Queerama  False           0.0         0.0  \n",
       " \n",
       " [45466 rows x 24 columns],\n",
       "           userId     id  rating   timestamp\n",
       " 0              1    110     1.0  1425941529\n",
       " 1              1    147     4.5  1425942435\n",
       " 2              1    858     5.0  1425941523\n",
       " 3              1   1221     5.0  1425941546\n",
       " 4              1   1246     5.0  1425941556\n",
       " ...          ...    ...     ...         ...\n",
       " 26024284  270896  58559     5.0  1257031564\n",
       " 26024285  270896  60069     5.0  1257032032\n",
       " 26024286  270896  63082     4.5  1257031764\n",
       " 26024287  270896  64957     4.5  1257033990\n",
       " 26024288  270896  71878     2.0  1257031858\n",
       " \n",
       " [26024289 rows x 4 columns]]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [credits,keywords,links,movies_metadata,ratings]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1425941529</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>1425942435</td>\n",
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       "      <th>26024286</th>\n",
       "      <td>270896</td>\n",
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       "      <td>4.5</td>\n",
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       "          userId     id  rating   timestamp\n",
       "0              1    110     1.0  1425941529\n",
       "1              1    147     4.5  1425942435\n",
       "2              1    858     5.0  1425941523\n",
       "3              1   1221     5.0  1425941546\n",
       "4              1   1246     5.0  1425941556\n",
       "...          ...    ...     ...         ...\n",
       "26024284  270896  58559     5.0  1257031564\n",
       "26024285  270896  60069     5.0  1257032032\n",
       "26024286  270896  63082     4.5  1257031764\n",
       "26024287  270896  64957     4.5  1257033990\n",
       "26024288  270896  71878     2.0  1257031858\n",
       "\n",
       "[26024289 rows x 4 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings"
   ]
  },
  {
   "cell_type": "code",
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
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   "cell_type": "code",
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. data analysis\n",
    "___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.016057252826558"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings[ratings['id'] == 110]['rating'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "RatingMeansWithID = ratings.groupby(['id']).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. data cleaning\n",
    "___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "RatingMeansWithID['id'] = RatingMeansWithID.index\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rating</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.888157</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.236953</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.175550</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.875713</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3.079565</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176267</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>176267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176269</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>176269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176271</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>176271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176273</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>176273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176275</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>176275</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45115 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          rating      id\n",
       "id                      \n",
       "1       3.888157       1\n",
       "2       3.236953       2\n",
       "3       3.175550       3\n",
       "4       2.875713       4\n",
       "5       3.079565       5\n",
       "...          ...     ...\n",
       "176267  4.000000  176267\n",
       "176269  3.500000  176269\n",
       "176271  5.000000  176271\n",
       "176273  1.000000  176273\n",
       "176275  3.000000  176275\n",
       "\n",
       "[45115 rows x 2 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RatingMeansWithID.drop(['timestamp','userId'], axis=1, inplace=True)\n",
    "RatingMeansWithID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(45476, 5), (46419, 3), (45843, 3), (45466, 24), (45115, 2)]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [credits,keywords,links,movies_metadata,RatingMeansWithID]\n",
    "[i.shape for i in data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(45432, 45432, 45813, 45436, 45115)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CList= set(credits              ['id'].tolist()    )                        \n",
    "KList= set(keywords             ['id'].tolist()    )         \n",
    "LList= set(links                ['id'].tolist())\n",
    "MList= set(movies_metadata      ['id'].tolist())\n",
    "RList= set(RatingMeansWithID    ['id'].tolist())\n",
    "\n",
    "len(CList),len(KList),len(LList),len(MList),len(RList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CommonIDList= list(set(CList).intersection(KList).intersection(LList).intersection(MList).intersection(RList))\n",
    "len(CommonIDList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(45432, 45432, 45813, 45433, 45115)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CList= set(credits['id'].tolist()    )                        \n",
    "KList= set(keywords['id'].tolist()    )         \n",
    "LList= set(links['id'].tolist())\n",
    "MList= set(movies_metadata['id'].tolist())\n",
    "RList= set(RatingMeansWithID['id'].tolist())\n",
    "\n",
    "\n",
    "CList= [float(i) for i in CList]                   \n",
    "KList= [float(i) for i in KList]    \n",
    "LList= [float(i) for i in LList]\n",
    "MList= [float(i) for i in MList if not '-' in i]\n",
    "RList= [float(i) for i in RList]\n",
    "\n",
    "len(CList),len(KList),len(LList),len(MList),len(RList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7565"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CommonIDList= list(set(CList).intersection(KList).intersection(LList).intersection(MList).intersection(RList))\n",
    "len(CommonIDList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " ...]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CommonIDList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.1 finding nulls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2 outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.3 feature extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.4 feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(45476, 5), (46419, 3), (45843, 3), (45466, 24), (45115, 2)]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [credits,keywords,links,movies_metadata,RatingMeansWithID]\n",
    "[i.shape for i in data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(45476, 5)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "credits.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
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       "      <td>[{'cast_id': 14, 'character': 'Woody (voice)',...</td>\n",
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       "      <td>111109</td>\n",
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       "      <th>45473</th>\n",
       "      <td>[{'cast_id': 6, 'character': 'Emily Shaw', 'cr...</td>\n",
       "      <td>[{'credit_id': '52fe4776c3a368484e0c8387', 'de...</td>\n",
       "      <td>67758</td>\n",
       "      <td>[{'cast_id': ' 6', 'character': ' Emily Shaw',...</td>\n",
       "      <td>[{'credit_id': ' 52fe4776c3a368484e0c8387', 'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45474</th>\n",
       "      <td>[{'cast_id': 2, 'character': '', 'credit_id': ...</td>\n",
       "      <td>[{'credit_id': '533bccebc3a36844cf0011a7', 'de...</td>\n",
       "      <td>227506</td>\n",
       "      <td>[{'cast_id': ' 2', 'character': ' ', 'credit_i...</td>\n",
       "      <td>[{'credit_id': ' 533bccebc3a36844cf0011a7', 'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45475</th>\n",
       "      <td>[]</td>\n",
       "      <td>[{'credit_id': '593e676c92514105b702e68e', 'de...</td>\n",
       "      <td>461257</td>\n",
       "      <td>[{}]</td>\n",
       "      <td>[{'credit_id': ' 593e676c92514105b702e68e', 'd...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45476 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    cast  \\\n",
       "0      [{'cast_id': 14, 'character': 'Woody (voice)',...   \n",
       "1      [{'cast_id': 1, 'character': 'Alan Parrish', '...   \n",
       "2      [{'cast_id': 2, 'character': 'Max Goldman', 'c...   \n",
       "3      [{'cast_id': 1, 'character': \"Savannah 'Vannah...   \n",
       "4      [{'cast_id': 1, 'character': 'George Banks', '...   \n",
       "...                                                  ...   \n",
       "45471  [{'cast_id': 0, 'character': '', 'credit_id': ...   \n",
       "45472  [{'cast_id': 1002, 'character': 'Sister Angela...   \n",
       "45473  [{'cast_id': 6, 'character': 'Emily Shaw', 'cr...   \n",
       "45474  [{'cast_id': 2, 'character': '', 'credit_id': ...   \n",
       "45475                                                 []   \n",
       "\n",
       "                                                    crew      id  \\\n",
       "0      [{'credit_id': '52fe4284c3a36847f8024f49', 'de...     862   \n",
       "1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...    8844   \n",
       "2      [{'credit_id': '52fe466a9251416c75077a89', 'de...   15602   \n",
       "3      [{'credit_id': '52fe44779251416c91011acb', 'de...   31357   \n",
       "4      [{'credit_id': '52fe44959251416c75039ed7', 'de...   11862   \n",
       "...                                                  ...     ...   \n",
       "45471  [{'credit_id': '5894a97d925141426c00818c', 'de...  439050   \n",
       "45472  [{'credit_id': '52fe4af1c3a36847f81e9b15', 'de...  111109   \n",
       "45473  [{'credit_id': '52fe4776c3a368484e0c8387', 'de...   67758   \n",
       "45474  [{'credit_id': '533bccebc3a36844cf0011a7', 'de...  227506   \n",
       "45475  [{'credit_id': '593e676c92514105b702e68e', 'de...  461257   \n",
       "\n",
       "                                                castlist  \\\n",
       "0      [{'cast_id': ' 14', 'character': ' Woody (voic...   \n",
       "1      [{'cast_id': ' 1', 'character': ' Alan Parrish...   \n",
       "2      [{'cast_id': ' 2', 'character': ' Max Goldman'...   \n",
       "3      [{'cast_id': ' 1', 'character': ' \"Savannah Va...   \n",
       "4      [{'cast_id': ' 1', 'character': ' George Banks...   \n",
       "...                                                  ...   \n",
       "45471  [{'cast_id': ' 0', 'character': ' ', 'credit_i...   \n",
       "45472  [{'cast_id': ' 1002', 'character': ' Sister An...   \n",
       "45473  [{'cast_id': ' 6', 'character': ' Emily Shaw',...   \n",
       "45474  [{'cast_id': ' 2', 'character': ' ', 'credit_i...   \n",
       "45475                                               [{}]   \n",
       "\n",
       "                                                crewlist  \n",
       "0      [{'credit_id': ' 52fe4284c3a36847f8024f49', 'd...  \n",
       "1      [{'credit_id': ' 52fe44bfc3a36847f80a7cd1', 'd...  \n",
       "2      [{'credit_id': ' 52fe466a9251416c75077a89', 'd...  \n",
       "3      [{'credit_id': ' 52fe44779251416c91011acb', 'd...  \n",
       "4      [{'credit_id': ' 52fe44959251416c75039ed7', 'd...  \n",
       "...                                                  ...  \n",
       "45471  [{'credit_id': ' 5894a97d925141426c00818c', 'd...  \n",
       "45472  [{'credit_id': ' 52fe4af1c3a36847f81e9b15', 'd...  \n",
       "45473  [{'credit_id': ' 52fe4776c3a368484e0c8387', 'd...  \n",
       "45474  [{'credit_id': ' 533bccebc3a36844cf0011a7', 'd...  \n",
       "45475  [{'credit_id': ' 593e676c92514105b702e68e', 'd...  \n",
       "\n",
       "[45476 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "credits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 35,
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   ],
   "source": [
    "CommonIDList = [int(i) for i in CommonIDList]\n",
    "CommonIDList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "Final_Credit= credits[credits['id'].isin(CommonIDList)]\n",
    "Final_Keyword= keywords[keywords['id'].isin(CommonIDList)]\n",
    "Final_Links= links[links['id'].isin(CommonIDList)]\n",
    "\n",
    "\n",
    "#Common_ID_Data = [Final_Credit,Final_Keyword,Final_Links,Final_Movies_metadata,Final_RatingMeansWithID]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
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       "                                                    cast  \\\n",
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       "...                                                  ...   \n",
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       "45443  [{'cast_id': ' 12', 'character': ' princezna H...   \n",
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       "\n",
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   "source": [
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  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
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       "  </tbody>\n",
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       "<p>7668 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id                                           keywords  \\\n",
       "0         862  [{'id': 931, 'name': 'jealousy'}, {'id': 4290,...   \n",
       "1        8844  [{'id': 10090, 'name': 'board game'}, {'id': 1...   \n",
       "5         949  [{'id': 642, 'name': 'robbery'}, {'id': 703, '...   \n",
       "9         710  [{'id': 701, 'name': 'cuba'}, {'id': 769, 'nam...   \n",
       "14       1408  [{'id': 911, 'name': 'exotic island'}, {'id': ...   \n",
       "...       ...                                                ...   \n",
       "46359   98604                                                 []   \n",
       "46386    5589  [{'id': 3205, 'name': 'fairy tale'}, {'id': 13...   \n",
       "46389   45527                                                 []   \n",
       "46403   49280                                                 []   \n",
       "46415  111109  [{'id': 2679, 'name': 'artist'}, {'id': 14531,...   \n",
       "\n",
       "                                                 keylist  \n",
       "0      [{'id': ' 931', 'name': ' jealousy'}, {'id': '...  \n",
       "1      [{'id': ' 10090', 'name': ' board game'}, {'id...  \n",
       "5      [{'id': ' 642', 'name': ' robbery'}, {'id': ' ...  \n",
       "9      [{'id': ' 701', 'name': ' cuba'}, {'id': ' 769...  \n",
       "14     [{'id': ' 911', 'name': ' exotic island'}, {'i...  \n",
       "...                                                  ...  \n",
       "46359                                               [{}]  \n",
       "46386  [{'id': ' 3205', 'name': ' fairy tale'}, {'id'...  \n",
       "46389                                               [{}]  \n",
       "46403                                               [{}]  \n",
       "46415  [{'id': ' 2679', 'name': ' artist'}, {'id': ' ...  \n",
       "\n",
       "[7668 rows x 3 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Final_Keyword"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movieId</th>\n",
       "      <th>imdbId</th>\n",
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       "      <td>949.0</td>\n",
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       "      <td>5589.0</td>\n",
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       "      <td>176237</td>\n",
       "      <td>135453</td>\n",
       "      <td>49280.0</td>\n",
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       "    <tr>\n",
       "      <th>45839</th>\n",
       "      <td>176271</td>\n",
       "      <td>2028550</td>\n",
       "      <td>111109.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7569 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       movieId   imdbId        id\n",
       "0            1   114709     862.0\n",
       "1            2   113497    8844.0\n",
       "5            6   113277     949.0\n",
       "9           10   113189     710.0\n",
       "14          15   112760    1408.0\n",
       "...        ...      ...       ...\n",
       "45783   176143  2147597   98604.0\n",
       "45810   176201   232750    5589.0\n",
       "45813   176207  1331329   45527.0\n",
       "45827   176237   135453   49280.0\n",
       "45839   176271  2028550  111109.0\n",
       "\n",
       "[7569 rows x 3 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Final_Links\n",
    "\n",
    "#here id is float not int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Final_Movies_metadata= movies_metadata[movies_metadata['id'].isin(CommonIDList)]\n",
    "#Final_RatingMeansWithID= RatingMeansWithID[RatingMeansWithID['id'].isin(CommonIDList)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Final_Movies_metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "Final_Movies_metadata = movies_metadata[movies_metadata['id'].isin(CommonIDList)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>adult</th>\n",
       "      <th>belongs_to_collection</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>poster_path</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>production_countries</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>video</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [adult, belongs_to_collection, budget, genres, homepage, id, imdb_id, original_language, original_title, overview, popularity, poster_path, production_companies, production_countries, release_date, revenue, runtime, spoken_languages, status, tagline, title, video, vote_average, vote_count]\n",
       "Index: []"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Final_Movies_metadata.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0      862\n",
      "1     8844\n",
      "2    15602\n",
      "3    31357\n",
      "4    11862\n",
      "Name: id, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(movies_metadata['id'].head())  # Print the first few IDs in movies_metadata\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               id title\n",
      "19730  1997-08-20   NaN\n",
      "29503  2012-09-29   NaN\n",
      "35587  2014-01-01   NaN\n"
     ]
    }
   ],
   "source": [
    "non_numeric_ids = movies_metadata[~movies_metadata['id'].str.isnumeric()]\n",
    "print(non_numeric_ids[['id', 'title']])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies_metadata = movies_metadata[movies_metadata['id'].str.isnumeric()]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_322504/3525865833.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  movies_metadata['id'] = movies_metadata['id'].astype(int)\n"
     ]
    }
   ],
   "source": [
    "movies_metadata['id'] = movies_metadata['id'].astype(int)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of common IDs: 7565\n"
     ]
    },
    {
     "data": {
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       "      <td>ru</td>\n",
       "      <td>Zolushka</td>\n",
       "      <td>Masha Krapivina - is yet beautiful, and not th...</td>\n",
       "      <td>0.803588</td>\n",
       "      <td>/cBFOyxe5HzIOIjJhipKQuslZsuV.jpg</td>\n",
       "      <td>[{'name': 'Channel One Russia', 'id': 1039}, {...</td>\n",
       "      <td>[{'iso_3166_1': 'RU', 'name': 'Russia'}]</td>\n",
       "      <td>2012-02-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>[{'iso_639_1': 'ru', 'name': 'Pусский'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cinderella</td>\n",
       "      <td>False</td>\n",
       "      <td>4.6</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45433</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 10402, 'name': 'Music'}, {'id': 35, 'n...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5589</td>\n",
       "      <td>tt0232750</td>\n",
       "      <td>cs</td>\n",
       "      <td>Šíleně smutná princezna</td>\n",
       "      <td>No overview found.</td>\n",
       "      <td>0.375001</td>\n",
       "      <td>/9h5eegOHh1zoaHJCwu9meyVdQJk.jpg</td>\n",
       "      <td>[{'name': 'Filmové Studio Barrandov', 'id': 19...</td>\n",
       "      <td>[{'iso_3166_1': 'CZ', 'name': 'Czech Republic'}]</td>\n",
       "      <td>1968-06-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>[{'iso_639_1': 'cs', 'name': 'Český'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Šíleně smutná princezna</td>\n",
       "      <td>False</td>\n",
       "      <td>6.1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45436</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 28, 'name': 'Action'}, {'id': 9648, 'n...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45527</td>\n",
       "      <td>tt1331329</td>\n",
       "      <td>en</td>\n",
       "      <td>The Final Storm</td>\n",
       "      <td>A stranger named Silas flees from a devastatin...</td>\n",
       "      <td>1.270832</td>\n",
       "      <td>/sEP5bLtK5IyQxOFtq5AYz4kUpzD.jpg</td>\n",
       "      <td>[{'name': 'Boll Kino Beteiligungs GmbH &amp; Co. K...</td>\n",
       "      <td>[{'iso_3166_1': 'CA', 'name': 'Canada'}, {'iso...</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Action, Horror</td>\n",
       "      <td>The Final Storm</td>\n",
       "      <td>False</td>\n",
       "      <td>3.7</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45450</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 14, 'name': 'Fantasy'}, {'id': 28, 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49280</td>\n",
       "      <td>tt0135453</td>\n",
       "      <td>fr</td>\n",
       "      <td>L'Homme orchestre</td>\n",
       "      <td>A band-leader has arranged seven chairs for th...</td>\n",
       "      <td>1.109068</td>\n",
       "      <td>/ZLOgI7KjtWby1NEg2pjU2Id60W.jpg</td>\n",
       "      <td>[{'name': 'Star Film Company', 'id': 45867}]</td>\n",
       "      <td>[{'iso_3166_1': 'FR', 'name': 'France'}]</td>\n",
       "      <td>1900-01-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[{'iso_639_1': 'xx', 'name': 'No Language'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The One-Man Band</td>\n",
       "      <td>False</td>\n",
       "      <td>6.5</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45462</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 18, 'name': 'Drama'}]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111109</td>\n",
       "      <td>tt2028550</td>\n",
       "      <td>tl</td>\n",
       "      <td>Siglo ng Pagluluwal</td>\n",
       "      <td>An artist struggles to finish his work while a...</td>\n",
       "      <td>0.178241</td>\n",
       "      <td>/xZkmxsNmYXJbKVsTRLLx3pqGHx7.jpg</td>\n",
       "      <td>[{'name': 'Sine Olivia', 'id': 19653}]</td>\n",
       "      <td>[{'iso_3166_1': 'PH', 'name': 'Philippines'}]</td>\n",
       "      <td>2011-11-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>[{'iso_639_1': 'tl', 'name': ''}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Century of Birthing</td>\n",
       "      <td>False</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7569 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       adult                              belongs_to_collection    budget  \\\n",
       "0      False  {'id': 10194, 'name': 'Toy Story Collection', ...  30000000   \n",
       "1      False                                                NaN  65000000   \n",
       "5      False                                                NaN  60000000   \n",
       "9      False  {'id': 645, 'name': 'James Bond Collection', '...  58000000   \n",
       "14     False                                                NaN  98000000   \n",
       "...      ...                                                ...       ...   \n",
       "45406  False                                                NaN         0   \n",
       "45433  False                                                NaN         0   \n",
       "45436  False                                                NaN         0   \n",
       "45450  False                                                NaN         0   \n",
       "45462  False                                                NaN         0   \n",
       "\n",
       "                                                  genres  \\\n",
       "0      [{'id': 16, 'name': 'Animation'}, {'id': 35, '...   \n",
       "1      [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...   \n",
       "5      [{'id': 28, 'name': 'Action'}, {'id': 80, 'nam...   \n",
       "9      [{'id': 12, 'name': 'Adventure'}, {'id': 28, '...   \n",
       "14     [{'id': 28, 'name': 'Action'}, {'id': 12, 'nam...   \n",
       "...                                                  ...   \n",
       "45406  [{'id': 35, 'name': 'Comedy'}, {'id': 10749, '...   \n",
       "45433  [{'id': 10402, 'name': 'Music'}, {'id': 35, 'n...   \n",
       "45436  [{'id': 28, 'name': 'Action'}, {'id': 9648, 'n...   \n",
       "45450  [{'id': 14, 'name': 'Fantasy'}, {'id': 28, 'na...   \n",
       "45462                      [{'id': 18, 'name': 'Drama'}]   \n",
       "\n",
       "                                           homepage      id    imdb_id  \\\n",
       "0              http://toystory.disney.com/toy-story     862  tt0114709   \n",
       "1                                               NaN    8844  tt0113497   \n",
       "5                                               NaN     949  tt0113277   \n",
       "9      http://www.mgm.com/view/movie/757/Goldeneye/     710  tt0113189   \n",
       "14                                              NaN    1408  tt0112760   \n",
       "...                                             ...     ...        ...   \n",
       "45406                                           NaN   98604  tt2147597   \n",
       "45433                                           NaN    5589  tt0232750   \n",
       "45436                                           NaN   45527  tt1331329   \n",
       "45450                                           NaN   49280  tt0135453   \n",
       "45462                                           NaN  111109  tt2028550   \n",
       "\n",
       "      original_language           original_title  \\\n",
       "0                    en                Toy Story   \n",
       "1                    en                  Jumanji   \n",
       "5                    en                     Heat   \n",
       "9                    en                GoldenEye   \n",
       "14                   en         Cutthroat Island   \n",
       "...                 ...                      ...   \n",
       "45406                ru                 Zolushka   \n",
       "45433                cs  Šíleně smutná princezna   \n",
       "45436                en          The Final Storm   \n",
       "45450                fr        L'Homme orchestre   \n",
       "45462                tl      Siglo ng Pagluluwal   \n",
       "\n",
       "                                                overview popularity  \\\n",
       "0      Led by Woody, Andy's toys live happily in his ...  21.946943   \n",
       "1      When siblings Judy and Peter discover an encha...  17.015539   \n",
       "5      Obsessive master thief, Neil McCauley leads a ...  17.924927   \n",
       "9      James Bond must unmask the mysterious head of ...  14.686036   \n",
       "14     Morgan Adams and her slave, William Shaw, are ...   7.284477   \n",
       "...                                                  ...        ...   \n",
       "45406  Masha Krapivina - is yet beautiful, and not th...   0.803588   \n",
       "45433                                 No overview found.   0.375001   \n",
       "45436  A stranger named Silas flees from a devastatin...   1.270832   \n",
       "45450  A band-leader has arranged seven chairs for th...   1.109068   \n",
       "45462  An artist struggles to finish his work while a...   0.178241   \n",
       "\n",
       "                            poster_path  \\\n",
       "0      /rhIRbceoE9lR4veEXuwCC2wARtG.jpg   \n",
       "1      /vzmL6fP7aPKNKPRTFnZmiUfciyV.jpg   \n",
       "5      /zMyfPUelumio3tiDKPffaUpsQTD.jpg   \n",
       "9      /5c0ovjT41KnYIHYuF4AWsTe3sKh.jpg   \n",
       "14     /odM9973kIv9hcjfHPp6g6BlyTIJ.jpg   \n",
       "...                                 ...   \n",
       "45406  /cBFOyxe5HzIOIjJhipKQuslZsuV.jpg   \n",
       "45433  /9h5eegOHh1zoaHJCwu9meyVdQJk.jpg   \n",
       "45436  /sEP5bLtK5IyQxOFtq5AYz4kUpzD.jpg   \n",
       "45450   /ZLOgI7KjtWby1NEg2pjU2Id60W.jpg   \n",
       "45462  /xZkmxsNmYXJbKVsTRLLx3pqGHx7.jpg   \n",
       "\n",
       "                                    production_companies  \\\n",
       "0         [{'name': 'Pixar Animation Studios', 'id': 3}]   \n",
       "1      [{'name': 'TriStar Pictures', 'id': 559}, {'na...   \n",
       "5      [{'name': 'Regency Enterprises', 'id': 508}, {...   \n",
       "9      [{'name': 'United Artists', 'id': 60}, {'name'...   \n",
       "14     [{'name': 'Le Studio Canal+', 'id': 183}, {'na...   \n",
       "...                                                  ...   \n",
       "45406  [{'name': 'Channel One Russia', 'id': 1039}, {...   \n",
       "45433  [{'name': 'Filmové Studio Barrandov', 'id': 19...   \n",
       "45436  [{'name': 'Boll Kino Beteiligungs GmbH & Co. K...   \n",
       "45450       [{'name': 'Star Film Company', 'id': 45867}]   \n",
       "45462             [{'name': 'Sine Olivia', 'id': 19653}]   \n",
       "\n",
       "                                    production_countries release_date  \\\n",
       "0      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-10-30   \n",
       "1      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-15   \n",
       "5      [{'iso_3166_1': 'US', 'name': 'United States o...   1995-12-15   \n",
       "9      [{'iso_3166_1': 'GB', 'name': 'United Kingdom'...   1995-11-16   \n",
       "14     [{'iso_3166_1': 'FR', 'name': 'France'}, {'iso...   1995-12-22   \n",
       "...                                                  ...          ...   \n",
       "45406           [{'iso_3166_1': 'RU', 'name': 'Russia'}]   2012-02-14   \n",
       "45433   [{'iso_3166_1': 'CZ', 'name': 'Czech Republic'}]   1968-06-07   \n",
       "45436  [{'iso_3166_1': 'CA', 'name': 'Canada'}, {'iso...   2010-01-01   \n",
       "45450           [{'iso_3166_1': 'FR', 'name': 'France'}]   1900-01-01   \n",
       "45462      [{'iso_3166_1': 'PH', 'name': 'Philippines'}]   2011-11-17   \n",
       "\n",
       "           revenue  runtime  \\\n",
       "0      373554033.0     81.0   \n",
       "1      262797249.0    104.0   \n",
       "5      187436818.0    170.0   \n",
       "9      352194034.0    130.0   \n",
       "14      10017322.0    119.0   \n",
       "...            ...      ...   \n",
       "45406          0.0     91.0   \n",
       "45433          0.0     73.0   \n",
       "45436          0.0     92.0   \n",
       "45450          0.0      1.0   \n",
       "45462          0.0    360.0   \n",
       "\n",
       "                                        spoken_languages    status  \\\n",
       "0               [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "1      [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "5      [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "9      [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "14     [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "...                                                  ...       ...   \n",
       "45406           [{'iso_639_1': 'ru', 'name': 'Pусский'}]  Released   \n",
       "45433             [{'iso_639_1': 'cs', 'name': 'Český'}]  Released   \n",
       "45436           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "45450       [{'iso_639_1': 'xx', 'name': 'No Language'}]  Released   \n",
       "45462                  [{'iso_639_1': 'tl', 'name': ''}]  Released   \n",
       "\n",
       "                                                 tagline  \\\n",
       "0                                                    NaN   \n",
       "1              Roll the dice and unleash the excitement!   \n",
       "5                               A Los Angeles Crime Saga   \n",
       "9                   No limits. No fears. No substitutes.   \n",
       "14     The Course Has Been Set. There Is No Turning B...   \n",
       "...                                                  ...   \n",
       "45406                                                NaN   \n",
       "45433                                                NaN   \n",
       "45436                                     Action, Horror   \n",
       "45450                                                NaN   \n",
       "45462                                                NaN   \n",
       "\n",
       "                         title  video  vote_average  vote_count  \n",
       "0                    Toy Story  False           7.7      5415.0  \n",
       "1                      Jumanji  False           6.9      2413.0  \n",
       "5                         Heat  False           7.7      1886.0  \n",
       "9                    GoldenEye  False           6.6      1194.0  \n",
       "14            Cutthroat Island  False           5.7       137.0  \n",
       "...                        ...    ...           ...         ...  \n",
       "45406               Cinderella  False           4.6         6.0  \n",
       "45433  Šíleně smutná princezna  False           6.1         4.0  \n",
       "45436          The Final Storm  False           3.7        11.0  \n",
       "45450         The One-Man Band  False           6.5        22.0  \n",
       "45462      Century of Birthing  False           9.0         3.0  \n",
       "\n",
       "[7569 rows x 24 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "common_ids_in_metadata = set(CommonIDList) & set(movies_metadata['id'].tolist())\n",
    "print(f'Number of common IDs: {len(common_ids_in_metadata)}')\n",
    "\n",
    "# Filter the movies_metadata based on CommonIDList\n",
    "Final_Movies_metadata = movies_metadata[movies_metadata['id'].isin(CommonIDList)]\n",
    "Final_Movies_metadata\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0      862\n",
      "1     8844\n",
      "5      949\n",
      "9      710\n",
      "14    1408\n",
      "Name: id, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(Final_Movies_metadata['id'].head()) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Final_RatingMeansWithID= RatingMeansWithID[RatingMeansWithID['id'].isin(CommonIDList)]\n",
    "#Final_RatingMeansWithID.head()\n",
    "Final_RatingMeansWithID = RatingMeansWithID[RatingMeansWithID['id'].isin(CommonIDList)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      rating  id\n",
      "id              \n",
      "1   3.888157   1\n",
      "2   3.236953   2\n",
      "3   3.175550   3\n",
      "4   2.875713   4\n",
      "5   3.079565   5\n"
     ]
    }
   ],
   "source": [
    "print(RatingMeansWithID.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rating</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.236953</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.175550</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3.079565</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3.841764</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3.660591</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176077</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>176077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176085</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>176085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176143</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>176143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176167</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>176167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176273</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>176273</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7565 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          rating      id\n",
       "id                      \n",
       "2       3.236953       2\n",
       "3       3.175550       3\n",
       "5       3.079565       5\n",
       "6       3.841764       6\n",
       "11      3.660591      11\n",
       "...          ...     ...\n",
       "176077  3.500000  176077\n",
       "176085  3.000000  176085\n",
       "176143  3.500000  176143\n",
       "176167  3.000000  176167\n",
       "176273  1.000000  176273\n",
       "\n",
       "[7565 rows x 2 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Final_RatingMeansWithID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
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    "\"\"\"\"\n",
    "\n",
    "Now we need create one dataset that combine all of these :\n",
    "\n",
    "                Final_RatingMeansWithID        \n",
    "                Final_Credit      \n",
    "                Final_Keyword       \n",
    "                Final_Links      \n",
    "                Final_Movies_metadata\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "DataPrepared = pd.DataFrame()\n",
    "DataPrepared\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
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       "          id\n",
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       "4          6\n",
       "...      ...\n",
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     "metadata": {},
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   "source": [
    "DataPrepared['id'] = CommonIDList\n",
    "DataPrepared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
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       "                                                    cast  \\\n",
       "0      [{'cast_id': 14, 'character': 'Woody (voice)',...   \n",
       "1      [{'cast_id': 1, 'character': 'Alan Parrish', '...   \n",
       "5      [{'cast_id': 25, 'character': 'Lt. Vincent Han...   \n",
       "9      [{'cast_id': 1, 'character': 'James Bond', 'cr...   \n",
       "14     [{'cast_id': 1, 'character': 'Morgan Adams', '...   \n",
       "...                                                  ...   \n",
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       "45460  [{'cast_id': 3, 'character': 'All the members ...   \n",
       "45472  [{'cast_id': 1002, 'character': 'Sister Angela...   \n",
       "\n",
       "                                                    crew      id  \\\n",
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       "1      [{'credit_id': '52fe44bfc3a36847f80a7cd1', 'de...    8844   \n",
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       "14     [{'credit_id': '52fe42f4c3a36847f802f69f', 'de...    1408   \n",
       "...                                                  ...     ...   \n",
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       "\n",
       "                                                castlist  \\\n",
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       "1      [{'cast_id': ' 1', 'character': ' Alan Parrish...   \n",
       "5      [{'cast_id': ' 25', 'character': ' Lt. Vincent...   \n",
       "9      [{'cast_id': ' 1', 'character': ' James Bond',...   \n",
       "14     [{'cast_id': ' 1', 'character': ' Morgan Adams...   \n",
       "...                                                  ...   \n",
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       "\n",
       "                                                crewlist  \n",
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     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "Final_Credit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
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       "           id                                           keywords  \\\n",
       "0         862  [{'id': 931, 'name': 'jealousy'}, {'id': 4290,...   \n",
       "1        8844  [{'id': 10090, 'name': 'board game'}, {'id': 1...   \n",
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       "9         710  [{'id': 701, 'name': 'cuba'}, {'id': 769, 'nam...   \n",
       "14       1408  [{'id': 911, 'name': 'exotic island'}, {'id': ...   \n",
       "...       ...                                                ...   \n",
       "46359   98604                                                 []   \n",
       "46386    5589  [{'id': 3205, 'name': 'fairy tale'}, {'id': 13...   \n",
       "46389   45527                                                 []   \n",
       "46403   49280                                                 []   \n",
       "46415  111109  [{'id': 2679, 'name': 'artist'}, {'id': 14531,...   \n",
       "\n",
       "                                                 keylist  \n",
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       "...                                                  ...  \n",
       "46359                                               [{}]  \n",
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       "46389                                               [{}]  \n",
       "46403                                               [{}]  \n",
       "46415  [{'id': ' 2679', 'name': ' artist'}, {'id': ' ...  \n",
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       "[7668 rows x 3 columns]"
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     },
     "execution_count": 56,
     "metadata": {},
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   ],
   "source": [
    "Final_Keyword"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "IDtoCastList = {k:v for k,v in zip (Final_Credit['id'].tolist() , Final_Credit['castlist'].tolist())}\n",
    "IDtoCrewList = {k:v for k,v in zip (Final_Credit['id'].tolist() , Final_Credit['crewlist'].tolist())}\n",
    "IDtoKeyList  = {k:v for k,v in zip (Final_Keyword['id'].tolist() , Final_Keyword['keylist'].tolist())}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
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       "        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",
       "      <th>castlist</th>\n",
       "      <th>crewlist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4342</th>\n",
       "      <td>[{'cast_id': 3, 'character': 'Taisto Olavi Kas...</td>\n",
       "      <td>[{'credit_id': '52fe420dc3a36847f800001f', 'de...</td>\n",
       "      <td>2</td>\n",
       "      <td>[{'cast_id': ' 3', 'character': ' Taisto Olavi...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f800001f', 'd...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   cast  \\\n",
       "4342  [{'cast_id': 3, 'character': 'Taisto Olavi Kas...   \n",
       "\n",
       "                                                   crew  id  \\\n",
       "4342  [{'credit_id': '52fe420dc3a36847f800001f', 'de...   2   \n",
       "\n",
       "                                               castlist  \\\n",
       "4342  [{'cast_id': ' 3', 'character': ' Taisto Olavi...   \n",
       "\n",
       "                                               crewlist  \n",
       "4342  [{'credit_id': ' 52fe420dc3a36847f800001f', 'd...  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Final_Credit[Final_Credit['id'] == 2] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>[{'cast_id': ' 3', 'character': ' Taisto Olavi...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f800001f', 'd...</td>\n",
       "      <td>[{'id': ' 240', 'name': ' underdog'}, {'id': '...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>[{'cast_id': ' 5', 'character': ' Nikander', '...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f8000077', 'd...</td>\n",
       "      <td>[{'id': ' 1361', 'name': ' salesclerk'}, {'id'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>131074</td>\n",
       "      <td>[{'cast_id': ' 2', 'character': ' Chris Lloyd'...</td>\n",
       "      <td>[{'credit_id': ' 52fe4b6dc3a368484e18897b', 'd...</td>\n",
       "      <td>[{'id': ' 9937', 'name': ' suspense'}, {'id': ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>[{'cast_id': ' 42', 'character': ' Ted the Bel...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f800011b', 'd...</td>\n",
       "      <td>[{'id': ' 612', 'name': ' hotel'}, {'id': ' 61...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>[{'cast_id': ' 7', 'character': ' Frank Wyatt'...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f800023d', 'd...</td>\n",
       "      <td>[{'id': ' 520', 'name': ' chicago'}, {'id': ' ...</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>7560</th>\n",
       "      <td>131027</td>\n",
       "      <td>[{'cast_id': ' 4', 'character': ' Csontváry / ...</td>\n",
       "      <td>[{'credit_id': ' 52fe4b6cc3a368484e188547', 'd...</td>\n",
       "      <td>[{'id': ' 437', 'name': ' painter'}, {'id': ' ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7561</th>\n",
       "      <td>32728</td>\n",
       "      <td>[{'cast_id': ' 3', 'character': ' Himself - wr...</td>\n",
       "      <td>[{'credit_id': ' 52fe44e69251416c91020be1', 'd...</td>\n",
       "      <td>[{'id': ' 9682', 'name': ' history'}, {'id': '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7562</th>\n",
       "      <td>98273</td>\n",
       "      <td>[{'cast_id': ' 2', 'character': ' Martha', 'cr...</td>\n",
       "      <td>[{'credit_id': ' 52fe4a0a9251416c750dbab5', 'd...</td>\n",
       "      <td>[{'id': ' 13142', 'name': ' gangster'}, {'id':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7563</th>\n",
       "      <td>98277</td>\n",
       "      <td>[{'cast_id': ' 11', 'character': ' Nora', 'cre...</td>\n",
       "      <td>[{'credit_id': ' 52fe4a0a9251416c750dbb21', 'd...</td>\n",
       "      <td>[{'id': ' 90', 'name': ' paris'}, {'id': ' 254...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7564</th>\n",
       "      <td>65521</td>\n",
       "      <td>[{'cast_id': ' 4', 'character': ' Rajat / Rajj...</td>\n",
       "      <td>[{'credit_id': ' 52fe470ec3a368484e0b27cf', 'd...</td>\n",
       "      <td>[{}]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7565 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                           castlist  \\\n",
       "0          2  [{'cast_id': ' 3', 'character': ' Taisto Olavi...   \n",
       "1          3  [{'cast_id': ' 5', 'character': ' Nikander', '...   \n",
       "2     131074  [{'cast_id': ' 2', 'character': ' Chris Lloyd'...   \n",
       "3          5  [{'cast_id': ' 42', 'character': ' Ted the Bel...   \n",
       "4          6  [{'cast_id': ' 7', 'character': ' Frank Wyatt'...   \n",
       "...      ...                                                ...   \n",
       "7560  131027  [{'cast_id': ' 4', 'character': ' Csontváry / ...   \n",
       "7561   32728  [{'cast_id': ' 3', 'character': ' Himself - wr...   \n",
       "7562   98273  [{'cast_id': ' 2', 'character': ' Martha', 'cr...   \n",
       "7563   98277  [{'cast_id': ' 11', 'character': ' Nora', 'cre...   \n",
       "7564   65521  [{'cast_id': ' 4', 'character': ' Rajat / Rajj...   \n",
       "\n",
       "                                               crewlist  \\\n",
       "0     [{'credit_id': ' 52fe420dc3a36847f800001f', 'd...   \n",
       "1     [{'credit_id': ' 52fe420dc3a36847f8000077', 'd...   \n",
       "2     [{'credit_id': ' 52fe4b6dc3a368484e18897b', 'd...   \n",
       "3     [{'credit_id': ' 52fe420dc3a36847f800011b', 'd...   \n",
       "4     [{'credit_id': ' 52fe420dc3a36847f800023d', 'd...   \n",
       "...                                                 ...   \n",
       "7560  [{'credit_id': ' 52fe4b6cc3a368484e188547', 'd...   \n",
       "7561  [{'credit_id': ' 52fe44e69251416c91020be1', 'd...   \n",
       "7562  [{'credit_id': ' 52fe4a0a9251416c750dbab5', 'd...   \n",
       "7563  [{'credit_id': ' 52fe4a0a9251416c750dbb21', 'd...   \n",
       "7564  [{'credit_id': ' 52fe470ec3a368484e0b27cf', 'd...   \n",
       "\n",
       "                                                keylist  \n",
       "0     [{'id': ' 240', 'name': ' underdog'}, {'id': '...  \n",
       "1     [{'id': ' 1361', 'name': ' salesclerk'}, {'id'...  \n",
       "2     [{'id': ' 9937', 'name': ' suspense'}, {'id': ...  \n",
       "3     [{'id': ' 612', 'name': ' hotel'}, {'id': ' 61...  \n",
       "4     [{'id': ' 520', 'name': ' chicago'}, {'id': ' ...  \n",
       "...                                                 ...  \n",
       "7560  [{'id': ' 437', 'name': ' painter'}, {'id': ' ...  \n",
       "7561  [{'id': ' 9682', 'name': ' history'}, {'id': '...  \n",
       "7562  [{'id': ' 13142', 'name': ' gangster'}, {'id':...  \n",
       "7563  [{'id': ' 90', 'name': ' paris'}, {'id': ' 254...  \n",
       "7564                                               [{}]  \n",
       "\n",
       "[7565 rows x 4 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DataPrepared['castlist'] = DataPrepared['id'].map(IDtoCastList)\n",
    "DataPrepared['crewlist'] = DataPrepared['id'].map(IDtoCrewList)\n",
    "DataPrepared['keylist'] = DataPrepared['id'].map(IDtoKeyList)\n",
    "\n",
    "DataPrepared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. visualization and analysis\n",
    "___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>[{'cast_id': ' 3', 'character': ' Taisto Olavi...</td>\n",
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       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>[{'cast_id': ' 5', 'character': ' Nikander', '...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f8000077', 'd...</td>\n",
       "      <td>[{'id': ' 1361', 'name': ' salesclerk'}, {'id'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>131074</td>\n",
       "      <td>[{'cast_id': ' 2', 'character': ' Chris Lloyd'...</td>\n",
       "      <td>[{'credit_id': ' 52fe4b6dc3a368484e18897b', 'd...</td>\n",
       "      <td>[{'id': ' 9937', 'name': ' suspense'}, {'id': ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>[{'cast_id': ' 42', 'character': ' Ted the Bel...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f800011b', 'd...</td>\n",
       "      <td>[{'id': ' 612', 'name': ' hotel'}, {'id': ' 61...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>[{'cast_id': ' 7', 'character': ' Frank Wyatt'...</td>\n",
       "      <td>[{'credit_id': ' 52fe420dc3a36847f800023d', 'd...</td>\n",
       "      <td>[{'id': ' 520', 'name': ' chicago'}, {'id': ' ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                                           castlist  \\\n",
       "0       2  [{'cast_id': ' 3', 'character': ' Taisto Olavi...   \n",
       "1       3  [{'cast_id': ' 5', 'character': ' Nikander', '...   \n",
       "2  131074  [{'cast_id': ' 2', 'character': ' Chris Lloyd'...   \n",
       "3       5  [{'cast_id': ' 42', 'character': ' Ted the Bel...   \n",
       "4       6  [{'cast_id': ' 7', 'character': ' Frank Wyatt'...   \n",
       "\n",
       "                                            crewlist  \\\n",
       "0  [{'credit_id': ' 52fe420dc3a36847f800001f', 'd...   \n",
       "1  [{'credit_id': ' 52fe420dc3a36847f8000077', 'd...   \n",
       "2  [{'credit_id': ' 52fe4b6dc3a368484e18897b', 'd...   \n",
       "3  [{'credit_id': ' 52fe420dc3a36847f800011b', 'd...   \n",
       "4  [{'credit_id': ' 52fe420dc3a36847f800023d', 'd...   \n",
       "\n",
       "                                             keylist  \n",
       "0  [{'id': ' 240', 'name': ' underdog'}, {'id': '...  \n",
       "1  [{'id': ' 1361', 'name': ' salesclerk'}, {'id'...  \n",
       "2  [{'id': ' 9937', 'name': ' suspense'}, {'id': ...  \n",
       "3  [{'id': ' 612', 'name': ' hotel'}, {'id': ' 61...  \n",
       "4  [{'id': ' 520', 'name': ' chicago'}, {'id': ' ...  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DataPrepared.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7. building the model\n",
    "___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8. evaluation the model\n",
    "___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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