Task_BalakaBiswas.ipynb

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  "metadata": {
    "colab": {
      "name": "Internship 1.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "YagwnctZaaRN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 118
        },
        "outputId": "1ab156e1-2e7f-47d9-a6f1-3c924a21b9e2"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1hxtIwD-adlJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import json,ast\n",
        "from scipy.sparse import csr_matrix as csr\n",
        "# SKLEARN\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n",
        "from sklearn.metrics.pairwise import linear_kernel, pairwise_distances\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.neighbors import NearestNeighbors"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j0NHicVAa6j8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "outputId": "2cd88cc0-8468-4799-c8e2-b8cac2b83232"
      },
      "source": [
        "movies = pd.read_csv('/content/drive/My Drive/movies_dataset.zip (Unzipped Files)/movies_data.csv')\n",
        "print(movies.head(10))\n",
        "ratings = pd.read_csv('/content/drive/My Drive/movies_dataset.zip (Unzipped Files)/ratings.csv')\n",
        "print(ratings.head(10))"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                              genres  ...                                              title\n",
            "0  [{'id': 14, 'name': 'Fantasy'}, {'id': 35, 'na...  ...                                           Reckless\n",
            "1  [{'id': 10749, 'name': 'Romance'}, {'id': 12, ...  ...                               Girl in the Cadillac\n",
            "2                [{'id': 99, 'name': 'Documentary'}]  ...           The Haunted World of Edward D. Wood, Jr.\n",
            "3                [{'id': 99, 'name': 'Documentary'}]  ...             Carmen Miranda: Bananas Is My Business\n",
            "4                      [{'id': 18, 'name': 'Drama'}]  ...                           Other Voices Other Rooms\n",
            "5  [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...  ...                              Dancer, Texas Pop. 81\n",
            "6                      [{'id': 18, 'name': 'Drama'}]  ...                                  The Farmer's Wife\n",
            "7                     [{'id': 35, 'name': 'Comedy'}]  ...                                   Stiff Upper Lips\n",
            "8  [{'id': 18, 'name': 'Drama'}, {'id': 28, 'name...  ...                                          Ten Benny\n",
            "9                [{'id': 99, 'name': 'Documentary'}]  ...  Gendernauts: A Journey Through Shifting Identi...\n",
            "\n",
            "[10 rows x 4 columns]\n",
            "   userId  movieId  rating\n",
            "0       2       17     5.0\n",
            "1       2       39     5.0\n",
            "2       2      150     5.0\n",
            "3       2      222     5.0\n",
            "4       2      265     5.0\n",
            "5       2      266     5.0\n",
            "6       2      551     5.0\n",
            "7       2      585     5.0\n",
            "8       2      589     5.0\n",
            "9       2      590     5.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J2x2Esb6wRuB",
        "colab_type": "text"
      },
      "source": [
        "Preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aj5qTdUEa9nV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        },
        "outputId": "3ac987f4-6dd8-4d4d-c9d4-1704004ec96c"
      },
      "source": [
        "print(movies.shape,\"\\n\")\n",
        "movies.info()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(45466, 4) \n",
            "\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 45466 entries, 0 to 45465\n",
            "Data columns (total 4 columns):\n",
            " #   Column    Non-Null Count  Dtype \n",
            "---  ------    --------------  ----- \n",
            " 0   genres    45466 non-null  object\n",
            " 1   id        45466 non-null  object\n",
            " 2   overview  44512 non-null  object\n",
            " 3   title     45460 non-null  object\n",
            "dtypes: object(4)\n",
            "memory usage: 1.4+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H8stEQuobDAh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "3b15d8ab-8d1f-4e09-9789-031df22bb3e4"
      },
      "source": [
        "# movies['movieId'] = [int(eval(s)[0]['id']) if len(eval(s))>0 else 0 for s in movies['genres'].values]\n",
        "# Extracting the genres\n",
        "def extractGenre(s):\n",
        "  lst = eval(s)\n",
        "  if len(lst) > 0:\n",
        "    return lst[0]['name']\n",
        "  else:\n",
        "    return ''\n",
        "# Removing NaN\n",
        "def delNan(cell):\n",
        "  if type(cell) == float:\n",
        "    return ''\n",
        "  else:\n",
        "    return cell\n",
        "# Test run\n",
        "'''print(extractGenre([{'id': 14, 'name': 'Fantasy'}, {'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}]))'''\n",
        "\n",
        "movies['genres'] = movies['genres'].apply(extractGenre)\n",
        "movies['title'] = movies['title'].apply(delNan)\n",
        "movies['overview'] = movies['overview'].apply(delNan)\n",
        "movies"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>genres</th>\n",
              "      <th>id</th>\n",
              "      <th>overview</th>\n",
              "      <th>title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Fantasy</td>\n",
              "      <td>58372</td>\n",
              "      <td>On Christmas eve, a relentlessly cheerful woma...</td>\n",
              "      <td>Reckless</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Romance</td>\n",
              "      <td>278939</td>\n",
              "      <td>A runaway teenage girl and a drifter rob a ban...</td>\n",
              "      <td>Girl in the Cadillac</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Documentary</td>\n",
              "      <td>73183</td>\n",
              "      <td>The strange life and the wonderfully awful fil...</td>\n",
              "      <td>The Haunted World of Edward D. Wood, Jr.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Documentary</td>\n",
              "      <td>255546</td>\n",
              "      <td>A biography of the Portuguese-Brazilian singer...</td>\n",
              "      <td>Carmen Miranda: Bananas Is My Business</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Drama</td>\n",
              "      <td>64562</td>\n",
              "      <td>Truman Capote's semi-autobiographical first no...</td>\n",
              "      <td>Other Voices Other Rooms</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>45461</th>\n",
              "      <td>Carousel Productions</td>\n",
              "      <td>20-08-1997</td>\n",
              "      <td>Released</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45462</th>\n",
              "      <td>Animation</td>\n",
              "      <td>122662</td>\n",
              "      <td>Third film of the Mardock Scramble series.</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45463</th>\n",
              "      <td>Aniplex</td>\n",
              "      <td>29-09-2012</td>\n",
              "      <td>Released</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45464</th>\n",
              "      <td>TV Movie</td>\n",
              "      <td>249260</td>\n",
              "      <td>A group of skiers are terrorized during spring...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45465</th>\n",
              "      <td>Odyssey Media</td>\n",
              "      <td>01-01-2014</td>\n",
              "      <td>Released</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45466 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                     genres  ...                                     title\n",
              "0                   Fantasy  ...                                  Reckless\n",
              "1                   Romance  ...                      Girl in the Cadillac\n",
              "2               Documentary  ...  The Haunted World of Edward D. Wood, Jr.\n",
              "3               Documentary  ...    Carmen Miranda: Bananas Is My Business\n",
              "4                     Drama  ...                  Other Voices Other Rooms\n",
              "...                     ...  ...                                       ...\n",
              "45461  Carousel Productions  ...                                          \n",
              "45462             Animation  ...                                          \n",
              "45463               Aniplex  ...                                          \n",
              "45464              TV Movie  ...                                          \n",
              "45465         Odyssey Media  ...                                          \n",
              "\n",
              "[45466 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b1Fh44V4bGmP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 895
        },
        "outputId": "d4b09b41-f34b-4711-9d16-03b84792b962"
      },
      "source": [
        "# Movies without titles have no relevance in recommendation systems. So, since the number of movies with missing title are only 6 out of the 45466 movies, we remove them\n",
        "movies.drop(index=[45460,45461,45462,45463,45464,45465],inplace=True)\n",
        "movies['id'] = movies['id'].astype(int)\n",
        "# Merging genres and overview together so that our recommender system is based on both the overview and genre\n",
        "movies['genre+overview'] = [\",\".join([movies.iloc[i,0].lower(),movies.iloc[i,2].lower()]) for i in range(movies.shape[0])]\n",
        "# Counting the number of movies under each genre\n",
        "print(movies['genres'].value_counts(),\"\\n\")\n",
        "mov_enc = movies.copy()\n",
        "# Label Encoding the genres\n",
        "le = LabelEncoder()\n",
        "mov_enc['genres'] = le.fit_transform(mov_enc['genres'])\n",
        "print(\"ORIGINAL :\\n\",movies,\"\\n\\nENCODED GENRES :\\n\",mov_enc)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drama              11966\n",
            "Comedy              8820\n",
            "Action              4488\n",
            "Documentary         3415\n",
            "Horror              2619\n",
            "                    2442\n",
            "Crime               1685\n",
            "Thriller            1665\n",
            "Adventure           1514\n",
            "Romance             1191\n",
            "Animation           1123\n",
            "Fantasy              704\n",
            "Science Fiction      647\n",
            "Mystery              554\n",
            "Family               524\n",
            "Music                487\n",
            "Western              451\n",
            "TV Movie             389\n",
            "War                  379\n",
            "History              279\n",
            "Foreign              118\n",
            "Name: genres, dtype: int64 \n",
            "\n",
            "ORIGINAL :\n",
            "             genres  ...                                     genre+overview\n",
            "0          Fantasy  ...  fantasy,on christmas eve, a relentlessly cheer...\n",
            "1          Romance  ...  romance,a runaway teenage girl and a drifter r...\n",
            "2      Documentary  ...  documentary,the strange life and the wonderful...\n",
            "3      Documentary  ...  documentary,a biography of the portuguese-braz...\n",
            "4            Drama  ...  drama,truman capote's semi-autobiographical fi...\n",
            "...            ...  ...                                                ...\n",
            "45455  Documentary  ...  documentary,this film records a 12 day ritual ...\n",
            "45456               ...  ,young aladdin (donald o'connor) has a series ...\n",
            "45457  Documentary  ...  documentary,deep hearts is a film about the bo...\n",
            "45458               ...  ,in a small town live two brothers, one a mini...\n",
            "45459               ...  ,50 years after decriminalisation of homosexua...\n",
            "\n",
            "[45460 rows x 5 columns] \n",
            "\n",
            "ENCODED GENRES :\n",
            "        genres  ...                                     genre+overview\n",
            "0           9  ...  fantasy,on christmas eve, a relentlessly cheer...\n",
            "1          15  ...  romance,a runaway teenage girl and a drifter r...\n",
            "2           6  ...  documentary,the strange life and the wonderful...\n",
            "3           6  ...  documentary,a biography of the portuguese-braz...\n",
            "4           7  ...  drama,truman capote's semi-autobiographical fi...\n",
            "...       ...  ...                                                ...\n",
            "45455       6  ...  documentary,this film records a 12 day ritual ...\n",
            "45456       0  ...  ,young aladdin (donald o'connor) has a series ...\n",
            "45457       6  ...  documentary,deep hearts is a film about the bo...\n",
            "45458       0  ...  ,in a small town live two brothers, one a mini...\n",
            "45459       0  ...  ,50 years after decriminalisation of homosexua...\n",
            "\n",
            "[45460 rows x 5 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "63sKdgcpwXDX",
        "colab_type": "text"
      },
      "source": [
        "Training the model for content based recommendation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pnEVKtVhbWE1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Training the tf-idf model on the genre+overview column for a subset of the data\n",
        "movies_new = movies.iloc[:35001,:]\n",
        "tfidf = TfidfVectorizer(analyzer='word',ngram_range=(1,3),stop_words='english',lowercase=True,encoding='utf-8')\n",
        "tfidf_matrix = tfidf.fit_transform(movies_new['genre+overview'])\n",
        "sim_scores = linear_kernel(tfidf_matrix,tfidf_matrix)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j0rQUXWfNMiZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "outputId": "3207b120-82f0-4504-8bc1-42b37e25c680"
      },
      "source": [
        "# Function for recommending movies\n",
        "indices = pd.Series(movies_new.index,index=movies_new['id']).drop_duplicates()\n",
        "def rec_movie(movieId,similarity=sim_scores):\n",
        "  # User input is mapped to the corresponding movie id\n",
        "  index = indices[movieId]\n",
        "  # Pairwise score evaluation\n",
        "  similar = list(enumerate(similarity[index]))\n",
        "  # Sort in decreasing order\n",
        "  similar = sorted(similar, key = lambda x: x[1], reverse=True)\n",
        "  # Fetch the top 10 movies\n",
        "  mov10_ind = [i[0] for i in similar[1:11]]\n",
        "  recommended = pd.DataFrame()\n",
        "  recommended['movieId'],recommended['title'],recommended['genre+overview'] = movies_new['id'].iloc[mov10_ind],movies_new['title'].iloc[mov10_ind],movies_new['genre+overview'].iloc[mov10_ind]\n",
        "  return recommended\n",
        "\n",
        "# Test for Despicable Me\n",
        "print(\"ORIGINAL MOVIE : \", movies_new['title'].iloc[indices[20352]],\"\\nGENRE + OVERVIEW : \", movies_new['genre+overview'].iloc[indices[20352]])\n",
        "print(\"\\n\\n10 RECOMMENDED MOVIES :\\n\")\n",
        "rec_movie(20352)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ORIGINAL MOVIE :  Despicable Me \n",
            "GENRE + OVERVIEW :  animation,villainous gru lives up to his reputation as a despicable, deplorable and downright unlikable guy when he hatches a plan to steal the moon from the sky. but he has a tough time staying on task after three orphans land in his care.\n",
            "\n",
            "\n",
            "10 RECOMMENDED MOVIES :\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movieId</th>\n",
              "      <th>title</th>\n",
              "      <th>genre+overview</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>20438</th>\n",
              "      <td>288710</td>\n",
              "      <td>The Frontier</td>\n",
              "      <td>crime,a desperate young woman, on the run from...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>389</th>\n",
              "      <td>448879</td>\n",
              "      <td>Приключения Домовёнка</td>\n",
              "      <td>animation,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>84774</td>\n",
              "      <td>Alice in Wonderland</td>\n",
              "      <td>animation,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15768</th>\n",
              "      <td>221171</td>\n",
              "      <td>Kilplased</td>\n",
              "      <td>animation,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19201</th>\n",
              "      <td>213321</td>\n",
              "      <td>Investigation Held by Kolobki</td>\n",
              "      <td>animation,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29559</th>\n",
              "      <td>343693</td>\n",
              "      <td>Aladin</td>\n",
              "      <td>animation,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29784</th>\n",
              "      <td>44486</td>\n",
              "      <td>Mars</td>\n",
              "      <td>animation,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12190</th>\n",
              "      <td>46059</td>\n",
              "      <td>The Hot Rock</td>\n",
              "      <td>crime,dortmunder and his pals plan to steal a ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34547</th>\n",
              "      <td>93556</td>\n",
              "      <td>Prairie Love</td>\n",
              "      <td>drama,as a mysterious high plains drifter trav...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19302</th>\n",
              "      <td>15171</td>\n",
              "      <td>Charlotte's Web</td>\n",
              "      <td>animation,wilbur the pig is scared of the end ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       movieId  ...                                     genre+overview\n",
              "20438   288710  ...  crime,a desperate young woman, on the run from...\n",
              "389     448879  ...                                         animation,\n",
              "460      84774  ...                                         animation,\n",
              "15768   221171  ...                                         animation,\n",
              "19201   213321  ...                                         animation,\n",
              "29559   343693  ...                                         animation,\n",
              "29784    44486  ...                                         animation,\n",
              "12190    46059  ...  crime,dortmunder and his pals plan to steal a ...\n",
              "34547    93556  ...  drama,as a mysterious high plains drifter trav...\n",
              "19302    15171  ...  animation,wilbur the pig is scared of the end ...\n",
              "\n",
              "[10 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yMyx5eD1wfJu",
        "colab_type": "text"
      },
      "source": [
        "Predicting ratings"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JOHiE0ntWSDm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 212
        },
        "outputId": "67dccf52-6dd2-45ba-8a6e-72e567031cd1"
      },
      "source": [
        "print(ratings.shape,\"\\n\")\n",
        "ratings.info()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(100004, 3) \n",
            "\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 100004 entries, 0 to 100003\n",
            "Data columns (total 3 columns):\n",
            " #   Column   Non-Null Count   Dtype  \n",
            "---  ------   --------------   -----  \n",
            " 0   userId   100004 non-null  int64  \n",
            " 1   movieId  100004 non-null  int64  \n",
            " 2   rating   100004 non-null  float64\n",
            "dtypes: float64(1), int64(2)\n",
            "memory usage: 2.3 MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w5SjDeHAnolU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "outputId": "df5e0734-e802-4678-c25d-245598ac4427"
      },
      "source": [
        "# Using a subset of the data due to RAM limitations\n",
        "ratings_new = ratings.iloc[:20001,:]\n",
        "# Splitting to train and test data\n",
        "train,test = ratings_new.iloc[:(int(0.8*ratings_new.shape[0])+1),:],ratings_new.iloc[(int(0.8*ratings_new.shape[0])+1):,:]\n",
        "print(\"TRAIN :\\n\",train,\"\\n\\nTEST :\\n\",test)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "TRAIN :\n",
            "        userId  movieId  rating\n",
            "0           2       17     5.0\n",
            "1           2       39     5.0\n",
            "2           2      150     5.0\n",
            "3           2      222     5.0\n",
            "4           2      265     5.0\n",
            "...       ...      ...     ...\n",
            "15996      77     3070     4.5\n",
            "15997      77     3275     4.5\n",
            "15998      77     3421     4.5\n",
            "15999      77     3994     4.5\n",
            "16000      77     4011     4.5\n",
            "\n",
            "[16001 rows x 3 columns] \n",
            "\n",
            "TEST :\n",
            "        userId  movieId  rating\n",
            "16001      77     4499     4.5\n",
            "16002      77     6755     4.5\n",
            "16003      77     7099     4.5\n",
            "16004      77     7387     4.5\n",
            "16005      77     7649     4.5\n",
            "...       ...      ...     ...\n",
            "19996     442      597     4.5\n",
            "19997     442      858     4.5\n",
            "19998     442     1035     4.5\n",
            "19999     442     1036     4.5\n",
            "20000     442     1049     4.5\n",
            "\n",
            "[4000 rows x 3 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6RnKsBtAom0c",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "outputId": "150342b8-ee0e-44a3-c396-ee3a8a1d26c8"
      },
      "source": [
        "userID,movieId = 2,222\n",
        "test1 = rec_movie(movieId)\n",
        "test1"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>movieId</th>\n",
              "      <th>title</th>\n",
              "      <th>genre+overview</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>8930</td>\n",
              "      <td>Modern Life</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>632</th>\n",
              "      <td>130638</td>\n",
              "      <td>Hitler - Never Heard of Him</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1439</th>\n",
              "      <td>2692</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1660</th>\n",
              "      <td>359807</td>\n",
              "      <td>Chico - Artista Brasileiro</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1842</th>\n",
              "      <td>449863</td>\n",
              "      <td>Cantábrico: Los dominios del oso pardo</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3964</th>\n",
              "      <td>32547</td>\n",
              "      <td>Social Genocide</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4892</th>\n",
              "      <td>292539</td>\n",
              "      <td>Food Chains</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4929</th>\n",
              "      <td>150049</td>\n",
              "      <td>The New Watchdogs</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8569</th>\n",
              "      <td>62130</td>\n",
              "      <td>El Big Bang de Tunguska</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9468</th>\n",
              "      <td>408550</td>\n",
              "      <td>Les Pépites</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      movieId                                   title genre+overview\n",
              "219      8930                             Modern Life   documentary,\n",
              "632    130638             Hitler - Never Heard of Him   documentary,\n",
              "1439     2692                           The Red Elvis   documentary,\n",
              "1660   359807              Chico - Artista Brasileiro   documentary,\n",
              "1842   449863  Cantábrico: Los dominios del oso pardo   documentary,\n",
              "3964    32547                         Social Genocide   documentary,\n",
              "4892   292539                             Food Chains   documentary,\n",
              "4929   150049                       The New Watchdogs   documentary,\n",
              "8569    62130                 El Big Bang de Tunguska   documentary,\n",
              "9468   408550                             Les Pépites   documentary,"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H8iKem5zwp61",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "5b3e2d9f-05be-4ea5-aac0-7510cf64ddbf"
      },
      "source": [
        "final1 = ratings.merge(test1,on='movieId')\n",
        "final1"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>userId</th>\n",
              "      <th>movieId</th>\n",
              "      <th>rating</th>\n",
              "      <th>title</th>\n",
              "      <th>genre+overview</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>23</td>\n",
              "      <td>2692</td>\n",
              "      <td>5.0</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>75</td>\n",
              "      <td>2692</td>\n",
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              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>99</td>\n",
              "      <td>2692</td>\n",
              "      <td>5.0</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>111</td>\n",
              "      <td>2692</td>\n",
              "      <td>5.0</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>118</td>\n",
              "      <td>2692</td>\n",
              "      <td>5.0</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>77</th>\n",
              "      <td>94</td>\n",
              "      <td>2692</td>\n",
              "      <td>2.5</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <td>265</td>\n",
              "      <td>2692</td>\n",
              "      <td>2.0</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>133</td>\n",
              "      <td>2692</td>\n",
              "      <td>0.5</td>\n",
              "      <td>The Red Elvis</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80</th>\n",
              "      <td>481</td>\n",
              "      <td>8930</td>\n",
              "      <td>4.5</td>\n",
              "      <td>Modern Life</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>15</td>\n",
              "      <td>8930</td>\n",
              "      <td>2.5</td>\n",
              "      <td>Modern Life</td>\n",
              "      <td>documentary,</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>82 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    userId  movieId  rating          title genre+overview\n",
              "0       23     2692     5.0  The Red Elvis   documentary,\n",
              "1       75     2692     5.0  The Red Elvis   documentary,\n",
              "2       99     2692     5.0  The Red Elvis   documentary,\n",
              "3      111     2692     5.0  The Red Elvis   documentary,\n",
              "4      118     2692     5.0  The Red Elvis   documentary,\n",
              "..     ...      ...     ...            ...            ...\n",
              "77      94     2692     2.5  The Red Elvis   documentary,\n",
              "78     265     2692     2.0  The Red Elvis   documentary,\n",
              "79     133     2692     0.5  The Red Elvis   documentary,\n",
              "80     481     8930     4.5    Modern Life   documentary,\n",
              "81      15     8930     2.5    Modern Life   documentary,\n",
              "\n",
              "[82 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-AryMhf5yQkj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "3c696b9a-a4a4-4a1d-f2b0-94a782951f19"
      },
      "source": [
        "pred = final1['rating'].median()\n",
        "pred"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MnAjiaIGCEzB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "15af18cf-9965-48ee-a271-d8e3841e3c71"
      },
      "source": [
        "test2 = ratings.merge(movies_new,left_on='movieId',right_on='id')\n",
        "test2"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .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>userId</th>\n",
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              "      <th>genres</th>\n",
              "      <th>id</th>\n",
              "      <th>overview</th>\n",
              "      <th>title</th>\n",
              "      <th>genre+overview</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
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              "      <td>17</td>\n",
              "      <td>Adèle and her daughter Sarah are traveling on ...</td>\n",
              "      <td>The Dark</td>\n",
              "      <td>horror,adèle and her daughter sarah are travel...</td>\n",
              "    </tr>\n",
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              "      <th>1</th>\n",
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              "      <td>5.0</td>\n",
              "      <td>Horror</td>\n",
              "      <td>17</td>\n",
              "      <td>Adèle and her daughter Sarah are traveling on ...</td>\n",
              "      <td>The Dark</td>\n",
              "      <td>horror,adèle and her daughter sarah are travel...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>86</td>\n",
              "      <td>17</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Horror</td>\n",
              "      <td>17</td>\n",
              "      <td>Adèle and her daughter Sarah are traveling on ...</td>\n",
              "      <td>The Dark</td>\n",
              "      <td>horror,adèle and her daughter sarah are travel...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>121</td>\n",
              "      <td>17</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Horror</td>\n",
              "      <td>17</td>\n",
              "      <td>Adèle and her daughter Sarah are traveling on ...</td>\n",
              "      <td>The Dark</td>\n",
              "      <td>horror,adèle and her daughter sarah are travel...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>161</td>\n",
              "      <td>17</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Horror</td>\n",
              "      <td>17</td>\n",
              "      <td>Adèle and her daughter Sarah are traveling on ...</td>\n",
              "      <td>The Dark</td>\n",
              "      <td>horror,adèle and her daughter sarah are travel...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42829</th>\n",
              "      <td>581</td>\n",
              "      <td>2191</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Thriller</td>\n",
              "      <td>2191</td>\n",
              "      <td>A team of astronauts on the first mission to M...</td>\n",
              "      <td>Stranded</td>\n",
              "      <td>thriller,a team of astronauts on the first mis...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42830</th>\n",
              "      <td>581</td>\n",
              "      <td>5413</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Drama</td>\n",
              "      <td>5413</td>\n",
              "      <td>The movie starts at the 1998 bomb attack by th...</td>\n",
              "      <td>Omagh</td>\n",
              "      <td>drama,the movie starts at the 1998 bomb attack...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42831</th>\n",
              "      <td>581</td>\n",
              "      <td>54768</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>54768</td>\n",
              "      <td>A new kid moves into school, making enemies wi...</td>\n",
              "      <td>Zapped Again!</td>\n",
              "      <td>comedy,a new kid moves into school, making ene...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42832</th>\n",
              "      <td>624</td>\n",
              "      <td>3933</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Romance</td>\n",
              "      <td>3933</td>\n",
              "      <td>Set in a 19th-century european village, this s...</td>\n",
              "      <td>Corpse Bride</td>\n",
              "      <td>romance,set in a 19th-century european village...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42833</th>\n",
              "      <td>624</td>\n",
              "      <td>8290</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>8290</td>\n",
              "      <td>During World War II, two French civilians and ...</td>\n",
              "      <td>Don't Look Now: We're Being Shot At</td>\n",
              "      <td>comedy,during world war ii, two french civilia...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>42834 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       userId  ...                                     genre+overview\n",
              "0           2  ...  horror,adèle and her daughter sarah are travel...\n",
              "1          57  ...  horror,adèle and her daughter sarah are travel...\n",
              "2          86  ...  horror,adèle and her daughter sarah are travel...\n",
              "3         121  ...  horror,adèle and her daughter sarah are travel...\n",
              "4         161  ...  horror,adèle and her daughter sarah are travel...\n",
              "...       ...  ...                                                ...\n",
              "42829     581  ...  thriller,a team of astronauts on the first mis...\n",
              "42830     581  ...  drama,the movie starts at the 1998 bomb attack...\n",
              "42831     581  ...  comedy,a new kid moves into school, making ene...\n",
              "42832     624  ...  romance,set in a 19th-century european village...\n",
              "42833     624  ...  comedy,during world war ii, two french civilia...\n",
              "\n",
              "[42834 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gWWu-VqkK_4i",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "68db1a35-63f6-4d0c-dab5-aaee23452afe"
      },
      "source": [
        "temp = train.merge(movies_new,left_on='movieId',right_on='id')\n",
        "temp"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>movieId</th>\n",
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              "      <td>59995</td>\n",
              "      <td>A lyrical telling of the coming of age of a 13...</td>\n",
              "      <td>Wild Tigers I Have Known</td>\n",
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              "      <td>72733</td>\n",
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              "      <td>Bringing his unique sense of humor to this biz...</td>\n",
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            "text/plain": [
              "      userId  ...                                     genre+overview\n",
              "0          2  ...  horror,adèle and her daughter sarah are travel...\n",
              "1         57  ...  horror,adèle and her daughter sarah are travel...\n",
              "2         86  ...  horror,adèle and her daughter sarah are travel...\n",
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              "7346      77  ...  crime,when the body of army capt. elizabeth ca...\n",
              "\n",
              "[7347 rows x 8 columns]"
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          "metadata": {
            "tags": []
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          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O33ve8qHMk1d",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 440
        },
        "outputId": "5773a712-c347-40af-9138-de3b48855533"
      },
      "source": [
        "pvt = ratings_new.pivot_table(index='userId',columns='movieId',values='rating')\n",
        "pvt.fillna(0,inplace=True)\n",
        "pvt"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>667</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>668</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>660 rows × 3723 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "movieId  1       2       3       5       ...  161944  162376  162542  163949\n",
              "userId                                   ...                                \n",
              "2           0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "3           0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "4           0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "5           0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "6           0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "...         ...     ...     ...     ...  ...     ...     ...     ...     ...\n",
              "667         0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "668         0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "669         0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "670         0.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "671         5.0     0.0     0.0     0.0  ...     0.0     0.0     0.0     0.0\n",
              "\n",
              "[660 rows x 3723 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O8Ky3Bwz2_xD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        },
        "outputId": "8c9ecece-acbb-4be7-d770-35267c4680c2"
      },
      "source": [
        "cosine_sim = 1-pairwise_distances(pvt, metric=\"cosine\")\n",
        "cosine_sim"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.        , 0.        , 0.0276395 , ..., 0.        , 0.        ,\n",
              "        0.13834289],\n",
              "       [0.        , 1.        , 0.09261065, ..., 0.17418325, 0.10503645,\n",
              "        0.15984152],\n",
              "       [0.0276395 , 0.09261065, 1.        , ..., 0.09166985, 0.        ,\n",
              "        0.14721354],\n",
              "       ...,\n",
              "       [0.        , 0.17418325, 0.09166985, ..., 1.        , 0.        ,\n",
              "        0.11470787],\n",
              "       [0.        , 0.10503645, 0.        , ..., 0.        , 1.        ,\n",
              "        0.06917145],\n",
              "       [0.13834289, 0.15984152, 0.14721354, ..., 0.11470787, 0.06917145,\n",
              "        1.        ]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DV2-zjNY3Qda",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        },
        "outputId": "de6345c6-dfc4-4c82-e6e5-789b6f2d067f"
      },
      "source": [
        "pearson_sim = 1-pairwise_distances(pvt, metric=\"correlation\")\n",
        "pearson_sim"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1.        , -0.00267612,  0.01824194, ..., -0.00178529,\n",
              "        -0.00296336,  0.13500379],\n",
              "       [-0.00267612,  1.        ,  0.08530793, ...,  0.17287512,\n",
              "         0.10264289,  0.15692357],\n",
              "       [ 0.01824194,  0.08530793,  1.        , ...,  0.08726173,\n",
              "        -0.00989176,  0.13699313],\n",
              "       ...,\n",
              "       [-0.00178529,  0.17287512,  0.08726173, ...,  1.        ,\n",
              "        -0.00178529,  0.11271466],\n",
              "       [-0.00296336,  0.10264289, -0.00989176, ..., -0.00178529,\n",
              "         1.        ,  0.06555248],\n",
              "       [ 0.13500379,  0.15692357,  0.13699313, ...,  0.11271466,\n",
              "         0.06555248,  1.        ]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SW4gScXD3ZRg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "0ace4b9d-f580-482a-e6d2-7e1591bcac2d"
      },
      "source": [
        "# Get 10 similar users by nearest neighbors algorithm, defaulting to Pearson correlation coefficient metric\n",
        "def sim10_users(user_id,pvt,metric=\"correlation\",k=10):\n",
        "  indices_sim = []\n",
        "  knn = NearestNeighbors(metric = metric, algorithm = 'brute') \n",
        "  knn.fit(pvt)\n",
        "  distances, indices_sim = knn.kneighbors(pvt.iloc[user_id - 1, :].values.reshape(1, -1), n_neighbors = k+1)\n",
        "  sims = 1 - distances.flatten()\n",
        "  return sims,indices_sim\n",
        "\n",
        "# Predict ratings\n",
        "'''ALGORITHM :\n",
        "1. Get 10 simialr users\n",
        "2. Get the mean of all user ratings for that userId\n",
        "3. Find sum of all ratings of the similar users obtained.\n",
        "4. for all similar users:\n",
        "    --> Find rating_diff = (Rating by user j on movie i) - (mean of all user ratings by that user)\n",
        "    --> Get updated_rating = updated_rating + (rating_diff * similarity_score(of user j))\n",
        "5. Predicted rating = (((step 2.)*updated_rating + step 3.) + 1)\n",
        "'''\n",
        "def predict_rating(user_id, movie_id, pvt, metric = \"correlation\", k = 10):\n",
        "    pred = 0\n",
        "    indices_mov = list(pvt.columns)\n",
        "    indexm = indices_mov.index(movie_id)\n",
        "    # STEP 1\n",
        "    sims, indices = sim10_users(user_id, pvt, metric, k)\n",
        "    # STEP 2\n",
        "    mean_rating = pvt.loc[user_id,:].mean()     # Adjusting for zero based indexing\n",
        "    # STEP 3\n",
        "    rtSum = np.sum(sims) - 1\n",
        "    pdt,updated_rating = 1,0           # Initializing product and updated rating\n",
        "    # STEP 4\n",
        "    for i in range(0, len(indices.flatten())):\n",
        "        if (indices.flatten()[i] + 1) == user_id:\n",
        "            continue\n",
        "        else: \n",
        "            rating_diff = abs(pvt.iloc[indices.flatten()[i],indexm]-np.mean(pvt.iloc[indices.flatten()[i],:]))\n",
        "            pdt = rating_diff * (sims[i])\n",
        "            updated_rating = updated_rating + pdt\n",
        "    \n",
        "    pred = pred + ((mean_rating*updated_rating + rtSum) + 1)\n",
        "    return pred\n",
        "# Test\n",
        "predict_rating(77, 4499, pvt)"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3.103773280334006"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JIpa8iODwjDQ",
        "colab_type": "text"
      },
      "source": [
        "Final test runs for :\n",
        "\n",
        "1. Berlin : Symphony of a Great City\n",
        "2. Pepi, Luci, Bom"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P6cGbuRBkBRg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 586
        },
        "outputId": "e68c7466-f222-4f6c-dff7-67952f9448c3"
      },
      "source": [
        "def predictRating_combined(userId,movieId,pvt=pvt,metric=\"correlation\",k=10):\n",
        "  testdf1 = rec_movie(movieId)\n",
        "  finaldf1 = ratings.merge(testdf1,on='movieId')\n",
        "  if len(list(finaldf1.index)) > 0 :\n",
        "    pred = final1['rating'].median()\n",
        "    return pred,testdf1\n",
        "  else:\n",
        "    pred2 = predict_rating(userId,movieId,pvt=pvt,metric=\"correlation\",k=10)\n",
        "    return pred2,testdf1\n",
        "\n",
        "# Final function for predicting user rating and recommended movies\n",
        "def recommend(userId,movieId,movies_new = movies_new):\n",
        "  indices = pd.Series(movies_new.index,index=movies_new['id']).drop_duplicates()\n",
        "  predicted_rating,rec = predictRating_combined(userId,movieId)\n",
        "  print('\\nRECOMMENDED MOVIES for the movie {} : \\n\\n{}\\n\\n=== Predicted rating for user {} -> movie {}: {:.1f} ==='.format(movies_new['title'].iloc[indices[movieId]],rec,userId,movieId,predicted_rating))\n",
        "\n",
        "# Test run 1\n",
        "recommend(2,222)\n",
        "print('-'*90)\n",
        "# Test run 2\n",
        "recommend(77,4499)"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "RECOMMENDED MOVIES for the movie Berlin: Symphony of a Great City : \n",
            "\n",
            "      movieId                                   title genre+overview\n",
            "219      8930                             Modern Life   documentary,\n",
            "632    130638             Hitler - Never Heard of Him   documentary,\n",
            "1439     2692                           The Red Elvis   documentary,\n",
            "1660   359807              Chico - Artista Brasileiro   documentary,\n",
            "1842   449863  Cantábrico: Los dominios del oso pardo   documentary,\n",
            "3964    32547                         Social Genocide   documentary,\n",
            "4892   292539                             Food Chains   documentary,\n",
            "4929   150049                       The New Watchdogs   documentary,\n",
            "8569    62130                 El Big Bang de Tunguska   documentary,\n",
            "9468   408550                             Les Pépites   documentary,\n",
            "\n",
            "=== Predicted rating for user 2 -> movie 222: 4.5 ===\n",
            "------------------------------------------------------------------------------------------\n",
            "\n",
            "RECOMMENDED MOVIES for the movie Pepi, Luci, Bom : \n",
            "\n",
            "       movieId  ...                                     genre+overview\n",
            "29600   254582  ...  drama,on what seems to be just another ordinar...\n",
            "250     155426  ...                                            comedy,\n",
            "380      65010  ...                                            comedy,\n",
            "518      52920  ...                                            comedy,\n",
            "860     428645  ...                                            comedy,\n",
            "975      54769  ...                                            comedy,\n",
            "1105     58007  ...                                            comedy,\n",
            "1538    284189  ...                                            comedy,\n",
            "1645     58074  ...                                            comedy,\n",
            "1646     56068  ...                                            comedy,\n",
            "\n",
            "[10 rows x 3 columns]\n",
            "\n",
            "=== Predicted rating for user 77 -> movie 4499: 3.1 ===\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1KEE4swcvOmp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}