collabrative_learning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9b78f765",
   "metadata": {},
   "source": [
    "# Collabrative learning Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a0d02e29",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import difflib\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ae04baeb",
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "      <th>userId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "      <td>5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>847434962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "      <td>7</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1106635946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "      <td>15</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1510577970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "      <td>17</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1305696483</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  movieId             title  \\\n",
       "0           0        1  Toy Story (1995)   \n",
       "1           1        1  Toy Story (1995)   \n",
       "2           2        1  Toy Story (1995)   \n",
       "3           3        1  Toy Story (1995)   \n",
       "4           4        1  Toy Story (1995)   \n",
       "\n",
       "                                        genres  userId  rating   timestamp  \n",
       "0  Adventure|Animation|Children|Comedy|Fantasy       1     4.0   964982703  \n",
       "1  Adventure|Animation|Children|Comedy|Fantasy       5     4.0   847434962  \n",
       "2  Adventure|Animation|Children|Comedy|Fantasy       7     4.5  1106635946  \n",
       "3  Adventure|Animation|Children|Comedy|Fantasy      15     2.5  1510577970  \n",
       "4  Adventure|Animation|Children|Comedy|Fantasy      17     4.5  1305696483  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# loading the dataset\n",
    "#cmovies_df = pd.read_csv(\"huge_cmovies_dataset.csv\")\n",
    "cmovies_df = pd.read_csv(\"cmovies_dataset.csv\")\n",
    "cmovies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "85605e19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
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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>Unnamed: 0</th>\n",
       "      <th>movieId</th>\n",
       "      <th>userId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>100836.000000</td>\n",
       "      <td>100836.000000</td>\n",
       "      <td>100836.000000</td>\n",
       "      <td>100836.000000</td>\n",
       "      <td>1.008360e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>50417.500000</td>\n",
       "      <td>19435.295718</td>\n",
       "      <td>326.127564</td>\n",
       "      <td>3.501557</td>\n",
       "      <td>1.205946e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>29108.990209</td>\n",
       "      <td>35530.987199</td>\n",
       "      <td>182.618491</td>\n",
       "      <td>1.042529</td>\n",
       "      <td>2.162610e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>8.281246e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>25208.750000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>177.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.019124e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>50417.500000</td>\n",
       "      <td>2991.000000</td>\n",
       "      <td>325.000000</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>1.186087e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>75626.250000</td>\n",
       "      <td>8122.000000</td>\n",
       "      <td>477.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.435994e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100835.000000</td>\n",
       "      <td>193609.000000</td>\n",
       "      <td>610.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.537799e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Unnamed: 0        movieId         userId         rating  \\\n",
       "count  100836.000000  100836.000000  100836.000000  100836.000000   \n",
       "mean    50417.500000   19435.295718     326.127564       3.501557   \n",
       "std     29108.990209   35530.987199     182.618491       1.042529   \n",
       "min         0.000000       1.000000       1.000000       0.500000   \n",
       "25%     25208.750000    1199.000000     177.000000       3.000000   \n",
       "50%     50417.500000    2991.000000     325.000000       3.500000   \n",
       "75%     75626.250000    8122.000000     477.000000       4.000000   \n",
       "max    100835.000000  193609.000000     610.000000       5.000000   \n",
       "\n",
       "          timestamp  \n",
       "count  1.008360e+05  \n",
       "mean   1.205946e+09  \n",
       "std    2.162610e+08  \n",
       "min    8.281246e+08  \n",
       "25%    1.019124e+09  \n",
       "50%    1.186087e+09  \n",
       "75%    1.435994e+09  \n",
       "max    1.537799e+09  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmovies_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "de49969c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 9719 entries, '71 (2014) to À nous la liberté (Freedom for Us) (1931)\n",
      "Data columns (total 1 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   rating  9719 non-null   float64\n",
      "dtypes: float64(1)\n",
      "memory usage: 151.9+ KB\n"
     ]
    }
   ],
   "source": [
    "ratings = pd.DataFrame(cmovies_df.groupby('title')['rating'].mean())\n",
    "ratings.info()\n",
    "#ratings.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bdebd9d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rating</th>\n",
       "      <th>number_of_ratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>'71 (2014)</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Hellboy': The Seeds of Creation (2004)</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Round Midnight (1986)</th>\n",
       "      <td>3.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Salem's Lot (2004)</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Til There Was You (1997)</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         rating  number_of_ratings\n",
       "title                                                             \n",
       "'71 (2014)                                  4.0                  1\n",
       "'Hellboy': The Seeds of Creation (2004)     4.0                  1\n",
       "'Round Midnight (1986)                      3.5                  2\n",
       "'Salem's Lot (2004)                         5.0                  1\n",
       "'Til There Was You (1997)                   4.0                  2"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings['number_of_ratings'] = cmovies_df.groupby('title')['rating'].count()\n",
    "ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4d411b9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ratings['rating'].hist(bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "883fa935",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ratings['number_of_ratings'].hist(bins=60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ab488a29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x1adb8f08580>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='rating', y='number_of_ratings', data=ratings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fac01eb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>title</th>\n",
       "      <th>'71 (2014)</th>\n",
       "      <th>'Hellboy': The Seeds of Creation (2004)</th>\n",
       "      <th>'Round Midnight (1986)</th>\n",
       "      <th>'Salem's Lot (2004)</th>\n",
       "      <th>'Til There Was You (1997)</th>\n",
       "      <th>'Tis the Season for Love (2015)</th>\n",
       "      <th>'burbs, The (1989)</th>\n",
       "      <th>'night Mother (1986)</th>\n",
       "      <th>(500) Days of Summer (2009)</th>\n",
       "      <th>*batteries not included (1987)</th>\n",
       "      <th>...</th>\n",
       "      <th>Zulu (2013)</th>\n",
       "      <th>[REC] (2007)</th>\n",
       "      <th>[REC]² (2009)</th>\n",
       "      <th>[REC]³ 3 Génesis (2012)</th>\n",
       "      <th>anohana: The Flower We Saw That Day - The Movie (2013)</th>\n",
       "      <th>eXistenZ (1999)</th>\n",
       "      <th>xXx (2002)</th>\n",
       "      <th>xXx: State of the Union (2005)</th>\n",
       "      <th>¡Three Amigos! (1986)</th>\n",
       "      <th>À nous la liberté (Freedom for Us) (1931)</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>5 rows × 9719 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "title   '71 (2014)  'Hellboy': The Seeds of Creation (2004)  \\\n",
       "userId                                                        \n",
       "1              NaN                                      NaN   \n",
       "2              NaN                                      NaN   \n",
       "3              NaN                                      NaN   \n",
       "4              NaN                                      NaN   \n",
       "5              NaN                                      NaN   \n",
       "\n",
       "title   'Round Midnight (1986)  'Salem's Lot (2004)  \\\n",
       "userId                                                \n",
       "1                          NaN                  NaN   \n",
       "2                          NaN                  NaN   \n",
       "3                          NaN                  NaN   \n",
       "4                          NaN                  NaN   \n",
       "5                          NaN                  NaN   \n",
       "\n",
       "title   'Til There Was You (1997)  'Tis the Season for Love (2015)  \\\n",
       "userId                                                               \n",
       "1                             NaN                              NaN   \n",
       "2                             NaN                              NaN   \n",
       "3                             NaN                              NaN   \n",
       "4                             NaN                              NaN   \n",
       "5                             NaN                              NaN   \n",
       "\n",
       "title   'burbs, The (1989)  'night Mother (1986)  (500) Days of Summer (2009)  \\\n",
       "userId                                                                          \n",
       "1                      NaN                   NaN                          NaN   \n",
       "2                      NaN                   NaN                          NaN   \n",
       "3                      NaN                   NaN                          NaN   \n",
       "4                      NaN                   NaN                          NaN   \n",
       "5                      NaN                   NaN                          NaN   \n",
       "\n",
       "title   *batteries not included (1987)  ...  Zulu (2013)  [REC] (2007)  \\\n",
       "userId                                  ...                              \n",
       "1                                  NaN  ...          NaN           NaN   \n",
       "2                                  NaN  ...          NaN           NaN   \n",
       "3                                  NaN  ...          NaN           NaN   \n",
       "4                                  NaN  ...          NaN           NaN   \n",
       "5                                  NaN  ...          NaN           NaN   \n",
       "\n",
       "title   [REC]² (2009)  [REC]³ 3 Génesis (2012)  \\\n",
       "userId                                           \n",
       "1                 NaN                      NaN   \n",
       "2                 NaN                      NaN   \n",
       "3                 NaN                      NaN   \n",
       "4                 NaN                      NaN   \n",
       "5                 NaN                      NaN   \n",
       "\n",
       "title   anohana: The Flower We Saw That Day - The Movie (2013)  \\\n",
       "userId                                                           \n",
       "1                                                     NaN        \n",
       "2                                                     NaN        \n",
       "3                                                     NaN        \n",
       "4                                                     NaN        \n",
       "5                                                     NaN        \n",
       "\n",
       "title   eXistenZ (1999)  xXx (2002)  xXx: State of the Union (2005)  \\\n",
       "userId                                                                \n",
       "1                   NaN         NaN                             NaN   \n",
       "2                   NaN         NaN                             NaN   \n",
       "3                   NaN         NaN                             NaN   \n",
       "4                   NaN         NaN                             NaN   \n",
       "5                   NaN         NaN                             NaN   \n",
       "\n",
       "title   ¡Three Amigos! (1986)  À nous la liberté (Freedom for Us) (1931)  \n",
       "userId                                                                    \n",
       "1                         4.0                                        NaN  \n",
       "2                         NaN                                        NaN  \n",
       "3                         NaN                                        NaN  \n",
       "4                         NaN                                        NaN  \n",
       "5                         NaN                                        NaN  \n",
       "\n",
       "[5 rows x 9719 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cretaing a matrix or table with rows consisting of all users in the data set\n",
    "# and coloumns consisting of all the movies in the dataset\n",
    "movie_matrix = cmovies_df.pivot_table(index='userId', columns='title', values='rating')\n",
    "movie_matrix.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "198384f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>rating</th>\n",
       "      <th>number_of_ratings</th>\n",
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       "      <th>Forrest Gump (1994)</th>\n",
       "      <td>4.164134</td>\n",
       "      <td>329</td>\n",
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       "    <tr>\n",
       "      <th>Shawshank Redemption, The (1994)</th>\n",
       "      <td>4.429022</td>\n",
       "      <td>317</td>\n",
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       "    <tr>\n",
       "      <th>Pulp Fiction (1994)</th>\n",
       "      <td>4.197068</td>\n",
       "      <td>307</td>\n",
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       "    <tr>\n",
       "      <th>Silence of the Lambs, The (1991)</th>\n",
       "      <td>4.161290</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>Star Wars: Episode IV - A New Hope (1977)</th>\n",
       "      <td>4.231076</td>\n",
       "      <td>251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jurassic Park (1993)</th>\n",
       "      <td>3.750000</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Braveheart (1995)</th>\n",
       "      <td>4.031646</td>\n",
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       "    <tr>\n",
       "      <th>Terminator 2: Judgment Day (1991)</th>\n",
       "      <td>3.970982</td>\n",
       "      <td>224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Schindler's List (1993)</th>\n",
       "      <td>4.225000</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fight Club (1999)</th>\n",
       "      <td>4.272936</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toy Story (1995)</th>\n",
       "      <td>3.920930</td>\n",
       "      <td>215</td>\n",
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       "    <tr>\n",
       "      <th>Star Wars: Episode V - The Empire Strikes Back (1980)</th>\n",
       "      <td>4.215640</td>\n",
       "      <td>211</td>\n",
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       "    <tr>\n",
       "      <th>Usual Suspects, The (1995)</th>\n",
       "      <td>4.237745</td>\n",
       "      <td>204</td>\n",
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       "    <tr>\n",
       "      <th>American Beauty (1999)</th>\n",
       "      <td>4.056373</td>\n",
       "      <td>204</td>\n",
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       "      <th>Seven (a.k.a. Se7en) (1995)</th>\n",
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       "      <td>203</td>\n",
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       "    <tr>\n",
       "      <th>Independence Day (a.k.a. ID4) (1996)</th>\n",
       "      <td>3.445545</td>\n",
       "      <td>202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apollo 13 (1995)</th>\n",
       "      <td>3.845771</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Raiders of the Lost Ark (Indiana Jones and the Raiders of the Lost Ark) (1981)</th>\n",
       "      <td>4.207500</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lord of the Rings: The Fellowship of the Ring, The (2001)</th>\n",
       "      <td>4.106061</td>\n",
       "      <td>198</td>\n",
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       "    <tr>\n",
       "      <th>Star Wars: Episode VI - Return of the Jedi (1983)</th>\n",
       "      <td>4.137755</td>\n",
       "      <td>196</td>\n",
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       "    <tr>\n",
       "      <th>Godfather, The (1972)</th>\n",
       "      <td>4.289062</td>\n",
       "      <td>192</td>\n",
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       "      <th>Fugitive, The (1993)</th>\n",
       "      <td>3.992105</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Batman (1989)</th>\n",
       "      <td>3.428571</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saving Private Ryan (1998)</th>\n",
       "      <td>4.146277</td>\n",
       "      <td>188</td>\n",
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       "    <tr>\n",
       "      <th>Lord of the Rings: The Two Towers, The (2002)</th>\n",
       "      <td>4.021277</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lord of the Rings: The Return of the King, The (2003)</th>\n",
       "      <td>4.118919</td>\n",
       "      <td>185</td>\n",
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       "    <tr>\n",
       "      <th>Aladdin (1992)</th>\n",
       "      <td>3.792350</td>\n",
       "      <td>183</td>\n",
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       "      <th>Fargo (1996)</th>\n",
       "      <td>4.116022</td>\n",
       "      <td>181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sixth Sense, The (1999)</th>\n",
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       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                                                      rating  \\\n",
       "title                                                          \n",
       "Forrest Gump (1994)                                 4.164134   \n",
       "Shawshank Redemption, The (1994)                    4.429022   \n",
       "Pulp Fiction (1994)                                 4.197068   \n",
       "Silence of the Lambs, The (1991)                    4.161290   \n",
       "Matrix, The (1999)                                  4.192446   \n",
       "Star Wars: Episode IV - A New Hope (1977)           4.231076   \n",
       "Jurassic Park (1993)                                3.750000   \n",
       "Braveheart (1995)                                   4.031646   \n",
       "Terminator 2: Judgment Day (1991)                   3.970982   \n",
       "Schindler's List (1993)                             4.225000   \n",
       "Fight Club (1999)                                   4.272936   \n",
       "Toy Story (1995)                                    3.920930   \n",
       "Star Wars: Episode V - The Empire Strikes Back ...  4.215640   \n",
       "Usual Suspects, The (1995)                          4.237745   \n",
       "American Beauty (1999)                              4.056373   \n",
       "Seven (a.k.a. Se7en) (1995)                         3.975369   \n",
       "Independence Day (a.k.a. ID4) (1996)                3.445545   \n",
       "Apollo 13 (1995)                                    3.845771   \n",
       "Raiders of the Lost Ark (Indiana Jones and the ...  4.207500   \n",
       "Lord of the Rings: The Fellowship of the Ring, ...  4.106061   \n",
       "Star Wars: Episode VI - Return of the Jedi (1983)   4.137755   \n",
       "Godfather, The (1972)                               4.289062   \n",
       "Fugitive, The (1993)                                3.992105   \n",
       "Batman (1989)                                       3.428571   \n",
       "Saving Private Ryan (1998)                          4.146277   \n",
       "Lord of the Rings: The Two Towers, The (2002)       4.021277   \n",
       "Lord of the Rings: The Return of the King, The ...  4.118919   \n",
       "Aladdin (1992)                                      3.792350   \n",
       "Fargo (1996)                                        4.116022   \n",
       "Sixth Sense, The (1999)                             3.893855   \n",
       "\n",
       "                                                    number_of_ratings  \n",
       "title                                                                  \n",
       "Forrest Gump (1994)                                               329  \n",
       "Shawshank Redemption, The (1994)                                  317  \n",
       "Pulp Fiction (1994)                                               307  \n",
       "Silence of the Lambs, The (1991)                                  279  \n",
       "Matrix, The (1999)                                                278  \n",
       "Star Wars: Episode IV - A New Hope (1977)                         251  \n",
       "Jurassic Park (1993)                                              238  \n",
       "Braveheart (1995)                                                 237  \n",
       "Terminator 2: Judgment Day (1991)                                 224  \n",
       "Schindler's List (1993)                                           220  \n",
       "Fight Club (1999)                                                 218  \n",
       "Toy Story (1995)                                                  215  \n",
       "Star Wars: Episode V - The Empire Strikes Back ...                211  \n",
       "Usual Suspects, The (1995)                                        204  \n",
       "American Beauty (1999)                                            204  \n",
       "Seven (a.k.a. Se7en) (1995)                                       203  \n",
       "Independence Day (a.k.a. ID4) (1996)                              202  \n",
       "Apollo 13 (1995)                                                  201  \n",
       "Raiders of the Lost Ark (Indiana Jones and the ...                200  \n",
       "Lord of the Rings: The Fellowship of the Ring, ...                198  \n",
       "Star Wars: Episode VI - Return of the Jedi (1983)                 196  \n",
       "Godfather, The (1972)                                             192  \n",
       "Fugitive, The (1993)                                              190  \n",
       "Batman (1989)                                                     189  \n",
       "Saving Private Ryan (1998)                                        188  \n",
       "Lord of the Rings: The Two Towers, The (2002)                     188  \n",
       "Lord of the Rings: The Return of the King, The ...                185  \n",
       "Aladdin (1992)                                                    183  \n",
       "Fargo (1996)                                                      181  \n",
       "Sixth Sense, The (1999)                                           179  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.sort_values('number_of_ratings', ascending=False).head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6ddb517f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Whats that movie which revolves always in you're head? : ice age\n",
      "['Ice Age (2002)', 'Ice Age (2002)', 'Ice Age (2002)']\n"
     ]
    }
   ],
   "source": [
    "user_fav_movie = input(\"Whats that movie which revolves always in you're head? : \")\n",
    "close_match = difflib.get_close_matches(user_fav_movie.title(), list(cmovies_df['title']))\n",
    "if bool(close_match):\n",
    "    user_fav_movie_ratings = movie_matrix[close_match[0]]\n",
    "    print(close_match)\n",
    "else:\n",
    "    print(\"couldn't find any matches!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cd516e3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "userId\n",
       "1     NaN\n",
       "2     NaN\n",
       "3     NaN\n",
       "4     NaN\n",
       "5     NaN\n",
       "6     NaN\n",
       "7     3.5\n",
       "8     NaN\n",
       "9     4.0\n",
       "10    NaN\n",
       "Name: Ice Age (2002), dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_fav_movie_ratings.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "46a2d7a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sasiv\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:2634: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  c = cov(x, y, rowvar, dtype=dtype)\n",
      "C:\\Users\\sasiv\\anaconda3\\lib\\site-packages\\numpy\\lib\\function_base.py:2493: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  c *= np.true_divide(1, fact)\n"
     ]
    }
   ],
   "source": [
    "similar_to_user_fav_movie = movie_matrix.corrwith(user_fav_movie_ratings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a9082b8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "'71 (2014)                                          NaN\n",
       "'Hellboy': The Seeds of Creation (2004)             NaN\n",
       "'Round Midnight (1986)                              NaN\n",
       "'Salem's Lot (2004)                                 NaN\n",
       "'Til There Was You (1997)                           NaN\n",
       "'Tis the Season for Love (2015)                     NaN\n",
       "'burbs, The (1989)                            -0.654654\n",
       "'night Mother (1986)                                NaN\n",
       "(500) Days of Summer (2009)                    0.376976\n",
       "*batteries not included (1987)                      NaN\n",
       "...All the Marbles (1981)                           NaN\n",
       "...And Justice for All (1979)                  1.000000\n",
       "00 Schneider - Jagd auf Nihil Baxter (1994)         NaN\n",
       "1-900 (06) (1994)                                   NaN\n",
       "10 (1979)                                           NaN\n",
       "10 Cent Pistol (2015)                               NaN\n",
       "10 Cloverfield Lane (2016)                     0.555556\n",
       "10 Items or Less (2006)                        1.000000\n",
       "10 Things I Hate About You (1999)              0.225707\n",
       "10 Years (2011)                                     NaN\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similar_to_user_fav_movie.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8b4edc85",
   "metadata": {},
   "outputs": [
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       "      <th>101 Dalmatians (One Hundred and One Dalmatians) (1961)</th>\n",
       "      <td>-0.262381</td>\n",
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       "    <tr>\n",
       "      <th>102 Dalmatians (2000)</th>\n",
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       "      <td>-0.333498</td>\n",
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       "      <td>0.300943</td>\n",
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       "      <td>0.721037</td>\n",
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      "text/plain": [
       "                                                    correlation\n",
       "title                                                          \n",
       "'burbs, The (1989)                                    -0.654654\n",
       "(500) Days of Summer (2009)                            0.376976\n",
       "...And Justice for All (1979)                          1.000000\n",
       "10 Cloverfield Lane (2016)                             0.555556\n",
       "10 Items or Less (2006)                                1.000000\n",
       "10 Things I Hate About You (1999)                      0.225707\n",
       "10,000 BC (2008)                                       0.618853\n",
       "101 Dalmatians (1996)                                  0.002602\n",
       "101 Dalmatians (One Hundred and One Dalmatians)...    -0.262381\n",
       "102 Dalmatians (2000)                                  0.126886\n",
       "11:14 (2003)                                           0.500000\n",
       "12 Angry Men (1957)                                   -0.333498\n",
       "12 Years a Slave (2013)                                0.398836\n",
       "127 Hours (2010)                                       0.906747\n",
       "13 Going on 30 (2004)                                  0.530330\n",
       "13 Hours (2016)                                        1.000000\n",
       "13th Warrior, The (1999)                              -0.039647\n",
       "1408 (2007)                                            0.300943\n",
       "15 Minutes (2001)                                      0.721037\n",
       "16 Blocks (2006)                                       0.301511"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_user_fav_movie = pd.DataFrame(similar_to_user_fav_movie, columns=['correlation'])\n",
    "corr_user_fav_movie.dropna(inplace=True)\n",
    "corr_user_fav_movie.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "51dde745",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>correlation</th>\n",
       "      <th>number_of_ratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>'burbs, The (1989)</th>\n",
       "      <td>-0.654654</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(500) Days of Summer (2009)</th>\n",
       "      <td>0.376976</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...And Justice for All (1979)</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10 Cloverfield Lane (2016)</th>\n",
       "      <td>0.555556</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10 Items or Less (2006)</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10 Things I Hate About You (1999)</th>\n",
       "      <td>0.225707</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10,000 BC (2008)</th>\n",
       "      <td>0.618853</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101 Dalmatians (1996)</th>\n",
       "      <td>0.002602</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101 Dalmatians (One Hundred and One Dalmatians) (1961)</th>\n",
       "      <td>-0.262381</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102 Dalmatians (2000)</th>\n",
       "      <td>0.126886</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11:14 (2003)</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Angry Men (1957)</th>\n",
       "      <td>-0.333498</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Years a Slave (2013)</th>\n",
       "      <td>0.398836</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127 Hours (2010)</th>\n",
       "      <td>0.906747</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13 Going on 30 (2004)</th>\n",
       "      <td>0.530330</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13 Hours (2016)</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13th Warrior, The (1999)</th>\n",
       "      <td>-0.039647</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1408 (2007)</th>\n",
       "      <td>0.300943</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15 Minutes (2001)</th>\n",
       "      <td>0.721037</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16 Blocks (2006)</th>\n",
       "      <td>0.301511</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    correlation  \\\n",
       "title                                                             \n",
       "'burbs, The (1989)                                    -0.654654   \n",
       "(500) Days of Summer (2009)                            0.376976   \n",
       "...And Justice for All (1979)                          1.000000   \n",
       "10 Cloverfield Lane (2016)                             0.555556   \n",
       "10 Items or Less (2006)                                1.000000   \n",
       "10 Things I Hate About You (1999)                      0.225707   \n",
       "10,000 BC (2008)                                       0.618853   \n",
       "101 Dalmatians (1996)                                  0.002602   \n",
       "101 Dalmatians (One Hundred and One Dalmatians)...    -0.262381   \n",
       "102 Dalmatians (2000)                                  0.126886   \n",
       "11:14 (2003)                                           0.500000   \n",
       "12 Angry Men (1957)                                   -0.333498   \n",
       "12 Years a Slave (2013)                                0.398836   \n",
       "127 Hours (2010)                                       0.906747   \n",
       "13 Going on 30 (2004)                                  0.530330   \n",
       "13 Hours (2016)                                        1.000000   \n",
       "13th Warrior, The (1999)                              -0.039647   \n",
       "1408 (2007)                                            0.300943   \n",
       "15 Minutes (2001)                                      0.721037   \n",
       "16 Blocks (2006)                                       0.301511   \n",
       "\n",
       "                                                    number_of_ratings  \n",
       "title                                                                  \n",
       "'burbs, The (1989)                                                 17  \n",
       "(500) Days of Summer (2009)                                        42  \n",
       "...And Justice for All (1979)                                       3  \n",
       "10 Cloverfield Lane (2016)                                         14  \n",
       "10 Items or Less (2006)                                             3  \n",
       "10 Things I Hate About You (1999)                                  54  \n",
       "10,000 BC (2008)                                                   17  \n",
       "101 Dalmatians (1996)                                              47  \n",
       "101 Dalmatians (One Hundred and One Dalmatians)...                 44  \n",
       "102 Dalmatians (2000)                                               9  \n",
       "11:14 (2003)                                                        4  \n",
       "12 Angry Men (1957)                                                57  \n",
       "12 Years a Slave (2013)                                            16  \n",
       "127 Hours (2010)                                                   18  \n",
       "13 Going on 30 (2004)                                              21  \n",
       "13 Hours (2016)                                                     5  \n",
       "13th Warrior, The (1999)                                           26  \n",
       "1408 (2007)                                                        25  \n",
       "15 Minutes (2001)                                                  10  \n",
       "16 Blocks (2006)                                                    9  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_user_fav_movie = corr_user_fav_movie.join(ratings['number_of_ratings'])\n",
    "corr_user_fav_movie.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2a2ad67f",
   "metadata": {},
   "outputs": [],
   "source": [
    "recommendation_movies = corr_user_fav_movie[corr_user_fav_movie['number_of_ratings'] > 100].sort_values(by='correlation', ascending=False).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "554e8998",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>correlation</th>\n",
       "      <th>number_of_ratings</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cliffhanger (1993)</th>\n",
       "      <td>0.794624</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clear and Present Danger (1994)</th>\n",
       "      <td>0.763763</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crimson Tide (1995)</th>\n",
       "      <td>0.622171</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inception (2010)</th>\n",
       "      <td>0.618368</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beautiful Mind, A (2001)</th>\n",
       "      <td>0.565357</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Batman Begins (2005)</th>\n",
       "      <td>0.556918</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Die Hard: With a Vengeance (1995)</th>\n",
       "      <td>0.548173</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shrek (2001)</th>\n",
       "      <td>0.514254</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finding Nemo (2003)</th>\n",
       "      <td>0.495855</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outbreak (1995)</th>\n",
       "      <td>0.482445</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Firm, The (1993)</th>\n",
       "      <td>0.477110</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lion King, The (1994)</th>\n",
       "      <td>0.476813</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fugitive, The (1993)</th>\n",
       "      <td>0.462770</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Memento (2000)</th>\n",
       "      <td>0.453741</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sleepless in Seattle (1993)</th>\n",
       "      <td>0.437665</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rock, The (1996)</th>\n",
       "      <td>0.430794</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ocean's Eleven (2001)</th>\n",
       "      <td>0.418247</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Usual Suspects, The (1995)</th>\n",
       "      <td>0.415175</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eternal Sunshine of the Spotless Mind (2004)</th>\n",
       "      <td>0.410861</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Twister (1996)</th>\n",
       "      <td>0.410511</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              correlation  number_of_ratings\n",
       "title                                                                       \n",
       "Cliffhanger (1993)                               0.794624                101\n",
       "Clear and Present Danger (1994)                  0.763763                110\n",
       "Crimson Tide (1995)                              0.622171                103\n",
       "Inception (2010)                                 0.618368                143\n",
       "Beautiful Mind, A (2001)                         0.565357                123\n",
       "Batman Begins (2005)                             0.556918                116\n",
       "Die Hard: With a Vengeance (1995)                0.548173                144\n",
       "Shrek (2001)                                     0.514254                170\n",
       "Finding Nemo (2003)                              0.495855                141\n",
       "Outbreak (1995)                                  0.482445                101\n",
       "Firm, The (1993)                                 0.477110                101\n",
       "Lion King, The (1994)                            0.476813                172\n",
       "Fugitive, The (1993)                             0.462770                190\n",
       "Memento (2000)                                   0.453741                159\n",
       "Sleepless in Seattle (1993)                      0.437665                106\n",
       "Rock, The (1996)                                 0.430794                121\n",
       "Ocean's Eleven (2001)                            0.418247                119\n",
       "Usual Suspects, The (1995)                       0.415175                204\n",
       "Eternal Sunshine of the Spotless Mind (2004)     0.410861                131\n",
       "Twister (1996)                                   0.410511                123"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommendation_movies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "82178109",
   "metadata": {},
   "outputs": [],
   "source": [
    "final = recommendation_movies.iloc[:11,:0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "dc07c49a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cliffhanger (1993)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clear and Present Danger (1994)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crimson Tide (1995)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inception (2010)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beautiful Mind, A (2001)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Batman Begins (2005)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Die Hard: With a Vengeance (1995)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shrek (2001)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finding Nemo (2003)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Outbreak (1995)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Firm, The (1993)</th>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [Cliffhanger (1993), Clear and Present Danger (1994), Crimson Tide (1995), Inception (2010), Beautiful Mind, A (2001), Batman Begins (2005), Die Hard: With a Vengeance (1995), Shrek (2001), Finding Nemo (2003), Outbreak (1995), Firm, The (1993)]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final.iloc[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c52fc264",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Clear and Present Danger (1994)',\n",
       " 'Crimson Tide (1995)',\n",
       " 'Inception (2010)',\n",
       " 'Beautiful Mind, A (2001)',\n",
       " 'Batman Begins (2005)',\n",
       " 'Die Hard: With a Vengeance (1995)',\n",
       " 'Shrek (2001)',\n",
       " 'Finding Nemo (2003)',\n",
       " 'Outbreak (1995)',\n",
       " 'Firm, The (1993)']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_list=[]\n",
    "for i in range(1,11):\n",
    "    row = final.index[i]\n",
    "    final_list.append(row)\n",
    "final_list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc6e269d",
   "metadata": {},
   "source": [
    "# The End Bixchh"
   ]
  }
 ],
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