PIP_CollaborativeFiltering_MovieLens100k_Imputed.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/SoudeepGhoshal/ColabFiltering/blob/main/PIP_CollaborativeFiltering_MovieLens100k_Imputed.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "outputId": "618f15d4-f664-4d2a-a55a-38d5e6e970c8"
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "from sklearn.metrics import pairwise_distances\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "A7h9RRs-z48w",
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          "height": 614
        },
        "outputId": "31228fec-bc56-49ce-9040-d3b51d8d6a74"
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      "outputs": [
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          "data": {
            "text/plain": [
              "     movie_id                                          title release_date  \\\n",
              "0           1                               Toy Story (1995)  01-Jan-1995   \n",
              "1           4                              Get Shorty (1995)  01-Jan-1995   \n",
              "2           5                                 Copycat (1995)  01-Jan-1995   \n",
              "3           7                          Twelve Monkeys (1995)  01-Jan-1995   \n",
              "4           8                                    Babe (1995)  01-Jan-1995   \n",
              "..        ...                                            ...          ...   \n",
              "495       214                   Pink Floyd - The Wall (1982)  01-Jan-1982   \n",
              "496       222                Star Trek: First Contact (1996)  22-Nov-1996   \n",
              "497       227  Star Trek VI: The Undiscovered Country (1991)  01-Jan-1991   \n",
              "498       228            Star Trek: The Wrath of Khan (1982)  01-Jan-1982   \n",
              "499       234                                    Jaws (1975)  01-Jan-1975   \n",
              "\n",
              "     video_release_date                                           imdb_url  \\\n",
              "0                   NaN  http://us.imdb.com/M/title-exact?Toy%20Story%2...   \n",
              "1                   NaN  http://us.imdb.com/M/title-exact?Get%20Shorty%...   \n",
              "2                   NaN  http://us.imdb.com/M/title-exact?Copycat%20(1995)   \n",
              "3                   NaN  http://us.imdb.com/M/title-exact?Twelve%20Monk...   \n",
              "4                   NaN     http://us.imdb.com/M/title-exact?Babe%20(1995)   \n",
              "..                  ...                                                ...   \n",
              "495                 NaN  http://us.imdb.com/M/title-exact?Pink%20Floyd%...   \n",
              "496                 NaN  http://us.imdb.com/M/title-exact?Star%20Trek:%...   \n",
              "497                 NaN  http://us.imdb.com/M/title-exact?Star%20Trek%2...   \n",
              "498                 NaN  http://us.imdb.com/M/title-exact?Star%20Trek:%...   \n",
              "499                 NaN     http://us.imdb.com/M/title-exact?Jaws%20(1975)   \n",
              "\n",
              "     user_id  rating  timestamp  age sex occupation zip_code  \n",
              "0        308       4  887736532   60   M    retired    95076  \n",
              "1        308       5  887737890   60   M    retired    95076  \n",
              "2        308       4  887739608   60   M    retired    95076  \n",
              "3        308       4  887738847   60   M    retired    95076  \n",
              "4        308       5  887736696   60   M    retired    95076  \n",
              "..       ...     ...        ...  ...  ..        ...      ...  \n",
              "495      148       5  877019882   33   M   engineer    97006  \n",
              "496      148       4  877398901   33   M   engineer    97006  \n",
              "497      148       4  877399083   33   M   engineer    97006  \n",
              "498      148       4  877016514   33   M   engineer    97006  \n",
              "499      148       3  877020297   33   M   engineer    97006  \n",
              "\n",
              "[500 rows x 12 columns]"
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              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "cols_u = ['user_id', 'age', 'sex', 'occupation', 'zip_code']\n",
        "users=pd.read_csv('/content/drive/MyDrive/ml-100k/u.user', sep='|', names=cols_u, encoding='latin-1', parse_dates=True)\n",
        "\n",
        "ratings_u = ['user_id', 'movie_id', 'rating', 'timestamp']\n",
        "ratings=pd.read_csv('/content/drive/MyDrive/ml-100k/u.data', sep='\\t', names=ratings_u, encoding='latin-1')\n",
        "\n",
        "movies_u = ['movie_id' , 'title', 'release_date', 'video_release_date', 'imdb_url']\n",
        "movies = pd.read_csv('/content/drive/MyDrive/ml-100k/u.item', sep='|', names=movies_u, usecols=range(5), encoding='latin-1')\n",
        "\n",
        "movie_ratings=pd.merge(movies,ratings)\n",
        "movie_df=pd.merge(movie_ratings,users)\n",
        "\n",
        "movie_df.head(500)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "y_mSrvIGhzaZ"
      },
      "outputs": [],
      "source": [
        "#only for the normalization\n",
        "#min_rating = ratings['rating'].min()\n",
        "#max_rating = ratings['rating'].max()\n",
        "\n",
        "#ratings['rating'] = (ratings['rating'] - min_rating) / (max_rating - min_rating)\n",
        "\n",
        "#ratings.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "5Q3veHlM0FDw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "94d04792-5c0d-4bab-c343-bc623e75064b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 100000 entries, 0 to 99999\n",
            "Data columns (total 9 columns):\n",
            " #   Column        Non-Null Count   Dtype \n",
            "---  ------        --------------   ----- \n",
            " 0   movie_id      100000 non-null  int64 \n",
            " 1   title         100000 non-null  object\n",
            " 2   release_date  99991 non-null   object\n",
            " 3   user_id       100000 non-null  int64 \n",
            " 4   rating        100000 non-null  int64 \n",
            " 5   age           100000 non-null  int64 \n",
            " 6   sex           100000 non-null  object\n",
            " 7   occupation    100000 non-null  object\n",
            " 8   zip_code      100000 non-null  object\n",
            "dtypes: int64(4), object(5)\n",
            "memory usage: 7.6+ MB\n"
          ]
        }
      ],
      "source": [
        "movie_df.drop(movie_df.columns[[3,4,7]], axis=1, inplace=True)\n",
        "ratings.drop(\"timestamp\", inplace=True, axis=1)\n",
        "movies.drop(movies.columns[[3,4]], inplace=True, axis=1)\n",
        "movie_df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
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        },
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      },
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            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "user_input_percent = 0.3\n",
        "subset_percent = 0.7\n",
        "\n",
        "num_ratings = len(ratings)\n",
        "num_user_input = int(num_ratings * user_input_percent)\n",
        "num_subset = int(num_ratings * subset_percent)\n",
        "\n",
        "user_input_ratings = ratings.sample(n=num_user_input, random_state=42)\n",
        "subset_ratings = ratings.drop(user_input_ratings.index)\n",
        "user_input_ratings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "AyGyhHdu0IyR"
      },
      "outputs": [],
      "source": [
        "# movies['title'] = movies['title'].str.replace(r'\\(\\d\\d\\d\\d\\)', '')\n",
        "# movies['title'] = movies['title'].apply(lambda x: x.strip())\n",
        "# movies.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "BJzyvFWK0LXX"
      },
      "outputs": [],
      "source": [
        "# userInput = [\n",
        "#             {'title':'Breakfast Club, The', 'rating':5},\n",
        "#             {'title':'Toy Story', 'rating':3.5},\n",
        "#             {'title':'Jumanji', 'rating':2},\n",
        "#             {'title':\"Pulp Fiction\", 'rating':5},\n",
        "#             {'title':'Akira', 'rating':4.5}\n",
        "#          ]\n",
        "# inputMovies = pd.DataFrame(userInput)\n",
        "# inputMovies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "yZmBvYF50Nco"
      },
      "outputs": [],
      "source": [
        "# # inputId = movies[movies['title'].isin(inputMovies['title'].tolist())]\n",
        "# # inputMovies = pd.merge(inputId, inputMovies)\n",
        "# inputMovies = inputMovies.drop('release_date', 1)\n",
        "# inputMovies"
      ]
    },
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      "cell_type": "code",
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        "outputId": "43ed310d-f972-4b29-f56d-1c5e87d14026"
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              "   user_id  movie_id  rating\n",
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              "    }\n",
              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-15810f0c-c271-4f58-af64-8021b965b804 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-15810f0c-c271-4f58-af64-8021b965b804');\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-aac9fde0-bf3c-4c36-8141-d567edb53647 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "userSubset = subset_ratings[subset_ratings['movie_id'].isin(user_input_ratings['movie_id'].tolist())]\n",
        "userSubset.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "sa1GXdLp0uGc"
      },
      "outputs": [],
      "source": [
        "userSubsetGroup = userSubset.groupby(['user_id'])\n",
        "userSubsetGroup.get_group(222)\n",
        "mu_k=userSubsetGroup['rating'].mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "Rzg3VqRP0whQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "719b478f-8d0f-43e9-fd73-561ad1133940"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-11-5489e10f2460>:1: FutureWarning: In a future version of pandas, a length 1 tuple will be returned when iterating over a groupby with a grouper equal to a list of length 1. Don't supply a list with a single grouper to avoid this warning.\n",
            "  userSubsetGroup=sorted(userSubsetGroup,key=lambda x: len(x[1]), reverse=True)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(405,\n",
              "         user_id  movie_id  rating\n",
              "  12383      405       592       1\n",
              "  12449      405       171       1\n",
              "  12460      405       580       1\n",
              "  12607      405       387       1\n",
              "  12731      405       190       2\n",
              "  ...        ...       ...     ...\n",
              "  98635      405      1475       1\n",
              "  98717      405       513       1\n",
              "  98956      405       375       1\n",
              "  98978      405       445       4\n",
              "  99756      405       958       1\n",
              "  \n",
              "  [458 rows x 3 columns]),\n",
              " (655,\n",
              "         user_id  movie_id  rating\n",
              "  39347      655       274       3\n",
              "  39490      655       126       2\n",
              "  39693      655       670       3\n",
              "  39780      655       523       3\n",
              "  39786      655       736       3\n",
              "  ...        ...       ...     ...\n",
              "  98813      655       155       4\n",
              "  98839      655       558       4\n",
              "  99071      655       143       4\n",
              "  99365      655       649       3\n",
              "  99418      655       305       4\n",
              "  \n",
              "  [443 rows x 3 columns]),\n",
              " (13,\n",
              "         user_id  movie_id  rating\n",
              "  63          13       526       3\n",
              "  145         13       272       4\n",
              "  185         13        98       4\n",
              "  205         13       360       4\n",
              "  392         13       344       2\n",
              "  ...        ...       ...     ...\n",
              "  98320       13       166       5\n",
              "  98615       13       822       3\n",
              "  99170       13       432       4\n",
              "  99306       13       904       1\n",
              "  99998       13       225       2\n",
              "  \n",
              "  [434 rows x 3 columns])]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "userSubsetGroup=sorted(userSubsetGroup,key=lambda x: len(x[1]), reverse=True)\n",
        "userSubsetGroup[0:3]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "CtGt5q6J0y10"
      },
      "outputs": [],
      "source": [
        "userSubsetGroup=userSubsetGroup[0:500]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "RNUHgLK7Ia6v",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "30de5b3c-8c1a-4977-846a-421f795412ab"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4.0\n"
          ]
        }
      ],
      "source": [
        "ratings_median=ratings['rating'].median()\n",
        "print(ratings_median)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "fSREXmrlHhzC"
      },
      "outputs": [],
      "source": [
        "def agreement(rating1, rating2, rating_median):\n",
        "    rating1 = np.asarray(rating1)\n",
        "    rating2 = np.asarray(rating2)\n",
        "\n",
        "    above_median1 = rating1 > rating_median\n",
        "    below_median1 = rating1 < rating_median\n",
        "    above_median2 = rating2 > rating_median\n",
        "    below_median2 = rating2 < rating_median\n",
        "\n",
        "    agreement_condition1 = np.logical_and(above_median1, below_median2)\n",
        "    agreement_condition2 = np.logical_and(below_median1, above_median2)\n",
        "\n",
        "    return np.logical_or(agreement_condition1, agreement_condition2).any()\n",
        "\n",
        "def proximity(rating1, rating2, rating_max, rating_min, rating_median):\n",
        "    rating1 = np.asarray(rating1)\n",
        "    rating2 = np.asarray(rating2)\n",
        "\n",
        "    agree = agreement(rating1, rating2, rating_median)\n",
        "    dist = np.where(agree, np.absolute(rating1 - rating2), 2 * np.absolute(rating1 - rating2))\n",
        "    prox = ((2 * (rating_max - rating_min) + 1) - dist) ** 2\n",
        "    return prox\n",
        "\n",
        "def impact(rating1, rating2, rating_median):\n",
        "    rating1 = np.asarray(rating1)\n",
        "    rating2 = np.asarray(rating2)\n",
        "\n",
        "    impact_score = (np.absolute(rating1 - rating_median) + 1) * (np.absolute(rating2 - rating_median) + 1)\n",
        "    agree = agreement(rating1, rating2, rating_median)\n",
        "    impact_result = np.where(agree, impact_score, 1 / impact_score)\n",
        "    return impact_result\n",
        "\n",
        "def popularity(rating1, rating2, mu_k):\n",
        "    pop = np.where(\n",
        "        (rating1 > mu_k) & (rating2 > mu_k) | (rating1 < mu_k) & (rating2 < mu_k),\n",
        "        1 + ((rating1 + rating2) / 2 - mu_k) ** 2,\n",
        "        1\n",
        "    )\n",
        "    return pop"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import math\n",
        "def agreement(rating1, rating2, rating_median):\n",
        "    rating1 = np.asarray(rating1)\n",
        "    rating2 = np.asarray(rating2)\n",
        "\n",
        "    above_median1 = rating1 > rating_median\n",
        "    below_median1 = rating1 < rating_median\n",
        "    above_median2 = rating2 > rating_median\n",
        "    below_median2 = rating2 < rating_median\n",
        "\n",
        "    agreement_condition1 = np.logical_and(above_median1, below_median2)\n",
        "    agreement_condition2 = np.logical_and(below_median1, above_median2)\n",
        "\n",
        "    return np.logical_or(agreement_condition1, agreement_condition2).any()\n",
        "\n",
        "def proximity(rating1, rating2, rating_max, rating_min, rating_median):\n",
        "    D = np.abs(rating1 - rating2)\n",
        "    med_plus = (rating_max + rating_median) / 2\n",
        "    med_minus = (rating_min + rating_median) / 2\n",
        "    Rmax_minus_Rmin_squared = (rating_max - rating_min) ** 2\n",
        "\n",
        "    agree = agreement(rating1, rating2, rating_median)\n",
        "    prox = (D - med_plus + med_minus) ** 2 / Rmax_minus_Rmin_squared\n",
        "    delta = 0.75 if np.abs(rating1 - rating2) > rating_median else (0.5 if np.abs(rating1 - rating2) == rating_median else 0.25)\n",
        "    return prox if agree else (delta * 1 / (D *  Rmax_minus_Rmin_squared))\n",
        "\n",
        "def impact(rating1, rating2, rating_median):\n",
        "    agree = agreement(rating1, rating2, rating_median)\n",
        "    impact1= math.exp(-1 / ((np.abs(rating1 - rating_median) + 1) * (np.abs(rating2 - rating_median) + 1)))\n",
        "    impact2= math.exp(1 / ((np.abs(rating1 - rating_median) + 1) * (np.abs(rating2 - rating_median) + 1)))\n",
        "    return impact1 if agree else impact2\n",
        "\n",
        "def proposed_popularity(rating1, rating2,rIi):\n",
        "    if (rating1 > rIi and rating2 > rIi) or (rating1 < rIi and rating2 < rIi):\n",
        "        return math.log10(2 + (((rating1 + rating2) / 2) - rIi) ** 2)\n",
        "    else:\n",
        "        return 0.3010\n"
      ],
      "metadata": {
        "id": "Yc44oUwnqeGB"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "MDuagmjM02Z4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3e190457-f4c1-4b0a-c8a6-8ced4510149c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-15-d47755b63b66>:25: RuntimeWarning: divide by zero encountered in divide\n",
            "  return prox if agree else (delta * 1 / (D *  Rmax_minus_Rmin_squared))\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "inf\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "def pip_similarity(tempRatingList, tempGroupList, rating_max, rating_min, rating_median, mu_k):\n",
        "    pip_similarity_sum = 0\n",
        "    n_ratings = 0\n",
        "\n",
        "    for rating1, rating2 in zip(tempRatingList, tempGroupList):\n",
        "        if not np.isnan(rating1) and not np.isnan(rating2):\n",
        "            prox = proximity(rating1, rating2, rating_max, rating_min, rating_median)\n",
        "            imp = impact(rating1, rating2, rating_median)\n",
        "            pop = popularity(rating1, rating2,rating_median )\n",
        "\n",
        "            pip_similarity_sum += prox * imp * pop\n",
        "            n_ratings += 1\n",
        "\n",
        "    if n_ratings == 0:\n",
        "        return 0\n",
        "\n",
        "    pip_similarity_value = pip_similarity_sum / n_ratings\n",
        "    return pip_similarity_value\n",
        "\n",
        "PIPdict = {}\n",
        "\n",
        "rating_max = 5\n",
        "rating_min = 0\n",
        "\n",
        "for name, group in userSubsetGroup:\n",
        "\n",
        "    group = group.sort_values(by='movie_id')\n",
        "    inputMovies = user_input_ratings.sort_values(by='movie_id')\n",
        "    temp_df = inputMovies[inputMovies['movie_id'].isin(group['movie_id'].tolist())]\n",
        "    tempRatingList = temp_df['rating'].tolist()\n",
        "    tempGroupList = group['rating'].tolist()\n",
        "    pip_similarity_value = pip_similarity(tempRatingList, tempGroupList, rating_max, rating_min, ratings_median, mu_k)\n",
        "    PIPdict[name] = pip_similarity_value.mean()\n",
        "\n",
        "print(PIPdict[1])"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "def pip_similarity(tempRatingList, tempGroupList, rating_max, rating_min, rating_median, mu_k):\n",
        "    pip_similarity_sum = 0\n",
        "    n_ratings = 0\n",
        "\n",
        "    for rating1, rating2 in zip(tempRatingList, tempGroupList):\n",
        "        if not np.isnan(rating1) and not np.isnan(rating2):\n",
        "            prox = proximity(rating1, rating2, rating_max, rating_min, rating_median)\n",
        "            imp = impact(rating1, rating2, rating_median)\n",
        "            pop = popularity(rating1, rating2,rating_median )\n",
        "\n",
        "            pip_similarity_sum += prox * imp * pop\n",
        "            n_ratings += 1\n",
        "\n",
        "    if n_ratings == 0:\n",
        "        return 0\n",
        "\n",
        "    pip_similarity_value = pip_similarity_sum / n_ratings\n",
        "    return pip_similarity_value\n",
        "\n",
        "PIPdict = {}\n",
        "\n",
        "rating_max = 5\n",
        "rating_min = 0\n",
        "\n",
        "for name, group in userSubsetGroup:\n",
        "  group = group.sort_values(by='movie_id')\n",
        "  inputMovies = user_input_ratings.sort_values(by='movie_id')\n",
        "  temp_df = inputMovies[inputMovies['movie_id'].isin(group['movie_id'].tolist())]\n",
        "  tempRatingList = temp_df['rating'].tolist()\n",
        "  tempGroupList = group['rating'].tolist()\n",
        "\n",
        "  similarity_values = []\n",
        "\n",
        "  for temp_rating, group_rating in zip(tempRatingList, tempGroupList):\n",
        "      pip_similarity_value = pip_similarity([temp_rating], [group_rating], rating_max, rating_min, ratings_median, mu_k)\n",
        "      similarity_values.append(pip_similarity_value)\n",
        "\n",
        "print(similarity_values)"
      ],
      "metadata": {
        "id": "xis0aonlP0ST",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "780b9ca5-7dd6-4ad8-8830-aa03feb2a536"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-15-d47755b63b66>:25: RuntimeWarning: divide by zero encountered in divide\n",
            "  return prox if agree else (delta * 1 / (D *  Rmax_minus_Rmin_squared))\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.007788007830714049, 0.007788007830714049, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, inf, 0.007788007830714049, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, inf, 0.01648721270700128, 0.007788007830714049, 0.0042800847222924715, 0.01648721270700128, inf, 0.01648721270700128, 0.007788007830714049, inf, 0.07942472123261358, 0.0042800847222924715, inf, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, 0.01648721270700128, inf, inf, 0.007788007830714049, 0.007788007830714049, inf, inf, 0.01648721270700128, 0.01648721270700128, 0.03839421341813349, 0.01648721270700128, 0.01648721270700128, 0.008464817248906142]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
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          "height": 206
        },
        "outputId": "ddab03c9-8c16-4a79-a025-2e114b47fb13"
      },
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   similarityIndex  userId\n",
              "0         0.007788       0\n",
              "1         0.007788       1\n",
              "2         0.016487       2\n",
              "3         0.016487       3\n",
              "4         0.016487       4"
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            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "#PIP_DF = pd.DataFrame.from_dict(PIPdict, orient='index')\n",
        "PIP_DF = pd.DataFrame(similarity_values, columns=['Similarity'])\n",
        "PIP_DF.columns = ['similarityIndex']\n",
        "PIP_DF['userId'] = PIP_DF.index\n",
        "PIP_DF.index = range(len(PIP_DF))\n",
        "\n",
        "#removing the inf values\n",
        "\n",
        "PIP_DF['similarityIndex'] = PIP_DF['similarityIndex'].replace([np.inf, -np.inf], 0)\n",
        "PIP_DF.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "ZheJRZxockQ0",
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          "base_uri": "https://localhost:8080/",
          "height": 1000
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        "outputId": "b9a11659-6afb-45bb-9f32-c8d234ebf96b"
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      "outputs": [
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          "data": {
            "text/plain": [
              "    similarityIndex  userId\n",
              "22         0.079425      22\n",
              "37         0.038394      37\n",
              "12         0.016487      12\n",
              "25         0.016487      25\n",
              "27         0.016487      27\n",
              "28         0.016487      28\n",
              "19         0.016487      19\n",
              "17         0.016487      17\n",
              "35         0.016487      35\n",
              "36         0.016487      36\n",
              "14         0.016487      14\n",
              "26         0.016487      26\n",
              "11         0.016487      11\n",
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              "8          0.016487       8\n",
              "7          0.016487       7\n",
              "38         0.016487      38\n",
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              "2          0.016487       2\n",
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              "31         0.007788      31\n",
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              "1          0.007788       1\n",
              "15         0.007788      15\n",
              "6          0.007788       6\n",
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              "23         0.004280      23\n",
              "16         0.004280      16\n",
              "24         0.000000      24\n",
              "21         0.000000      21\n",
              "29         0.000000      29\n",
              "30         0.000000      30\n",
              "18         0.000000      18\n",
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              "5          0.000000       5"
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              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.007788</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>0.007788</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>0.004280</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0.004280</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1dd9bd5a-db5a-403f-b5b0-a2de2d31a1ca')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-1dd9bd5a-db5a-403f-b5b0-a2de2d31a1ca button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-1dd9bd5a-db5a-403f-b5b0-a2de2d31a1ca');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-4f1b408c-f89f-41a7-8fcc-0e9281dd0055\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4f1b408c-f89f-41a7-8fcc-0e9281dd0055')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4f1b408c-f89f-41a7-8fcc-0e9281dd0055 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "topUsers=PIP_DF.sort_values(by='similarityIndex', ascending=False)\n",
        "topUsers.head(100)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "r8KX8MpVe5Nd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e5df5566-d5a1-4eda-9837-73e0cc8a25d6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "similarityIndex    0\n",
              "userId             0\n",
              "user_id            0\n",
              "movie_id           0\n",
              "rating             0\n",
              "weightedRating     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "topUsersRating=topUsers.merge(ratings, left_on='userId', right_on='user_id', how='inner')\n",
        "topUsersRating['weightedRating'] = topUsersRating['similarityIndex']*topUsersRating['rating']\n",
        "#topUsersRating.head(18000)\n",
        "topUsersRating.head(1352)\n",
        "topUsersRating.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "SbI0hDaIfCDa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "d387f8bd-610a-47d9-c3b3-c1fa977366c1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          weighted average recommendation score  movieID\n",
              "movie_id                                                \n",
              "1034                                        1.0     1034\n",
              "1035                                        5.0     1035\n",
              "1036                                        4.0     1036\n",
              "1037                                        4.0     1037\n",
              "1038                                        1.0     1038"
            ],
            "text/html": [
              "\n",
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              "    <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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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>weighted average recommendation score</th>\n",
              "      <th>movieID</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>movie_id</th>\n",
              "      <th></th>\n",
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              "      <th>1034</th>\n",
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              "    <tr>\n",
              "      <th>1035</th>\n",
              "      <td>5.0</td>\n",
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              "      <th>1036</th>\n",
              "      <td>4.0</td>\n",
              "      <td>1036</td>\n",
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              "      <th>1037</th>\n",
              "      <td>4.0</td>\n",
              "      <td>1037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1038</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1038</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
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              "      background-color: #E2EBFA;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-15936b91-a485-426c-bbbb-c0d24d5f8cca button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-15936b91-a485-426c-bbbb-c0d24d5f8cca');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "\n",
              "\n",
              "<div id=\"df-8976229e-7e42-4a6a-aa4c-00b11418ce6c\">\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8976229e-7e42-4a6a-aa4c-00b11418ce6c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "tempTopUsersRating = topUsersRating.groupby('movie_id').sum()[['similarityIndex','weightedRating']]\n",
        "tempTopUsersRating.columns = ['sum_similarityIndex','sum_weightedRating']\n",
        "recommendation_df = pd.DataFrame()\n",
        "recommendation_df['weighted average recommendation score'] = tempTopUsersRating['sum_weightedRating']/tempTopUsersRating['sum_similarityIndex']\n",
        "#handled the zero division error bug\n",
        "recommendation_df.loc[tempTopUsersRating['sum_similarityIndex'] == 0, 'weighted average recommendation score'] = 0\n",
        "recommendation_df.fillna(0, inplace=True)\n",
        "##\n",
        "recommendation_df['movieID'] = tempTopUsersRating.index\n",
        "recommendation_df.tail()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "olsO8OSQfErk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "71741e96-3b7b-4579-fa3a-287f7d211ed6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          sum_similarityIndex  sum_weightedRating\n",
              "movie_id                                         \n",
              "1                    0.138635            0.556225\n",
              "2                    0.087213            0.182213\n",
              "3                    0.007788            0.031152\n",
              "4                    0.157442            0.738658\n",
              "5                    0.024275            0.072826\n",
              "...                       ...                 ...\n",
              "969                  0.016487            0.049462\n",
              "970                  0.000000            0.000000\n",
              "971                  0.000000            0.000000\n",
              "972                  0.000000            0.000000\n",
              "973                  0.000000            0.000000\n",
              "\n",
              "[973 rows x 2 columns]"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sum_similarityIndex</th>\n",
              "      <th>sum_weightedRating</th>\n",
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              "      <th>movie_id</th>\n",
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              "      <th>1</th>\n",
              "      <td>0.138635</td>\n",
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              "      <td>0.087213</td>\n",
              "      <td>0.182213</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.007788</td>\n",
              "      <td>0.031152</td>\n",
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              "      <td>0.157442</td>\n",
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              "      <td>0.024275</td>\n",
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              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <th>969</th>\n",
              "      <td>0.016487</td>\n",
              "      <td>0.049462</td>\n",
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              "    <tr>\n",
              "      <th>970</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "    <tr>\n",
              "      <th>971</th>\n",
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              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>972</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>973</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>973 rows × 2 columns</p>\n",
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              "\n",
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              "\n",
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              "        document.querySelector('#df-941652eb-eb4d-46fe-be97-32652afd8c91 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-941652eb-eb4d-46fe-be97-32652afd8c91');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    width: 32px;\n",
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              "\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "  @keyframes spin {\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2e0dcdc6-63c3-4359-89c4-bb7a2866a6db button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "tempTopUsersRating.head(973)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "v6WbXJyRfIFl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "d43ee4e9-93f0-47e9-bd4a-0257f8913ed4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          weighted average recommendation score  movieID\n",
              "movie_id                                                \n",
              "165                                    5.000000      165\n",
              "119                                    5.000000      119\n",
              "108                                    5.000000      108\n",
              "1022                                   5.000000     1022\n",
              "1019                                   5.000000     1019\n",
              "...                                         ...      ...\n",
              "523                                    4.725641      523\n",
              "285                                    4.713412      285\n",
              "99                                     4.698281       99\n",
              "4                                      4.691629        4\n",
              "85                                     4.690808       85\n",
              "\n",
              "[100 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>weighted average recommendation score</th>\n",
              "      <th>movieID</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>movie_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
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              "      <th>165</th>\n",
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              "      <th>108</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>108</td>\n",
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              "    <tr>\n",
              "      <th>1022</th>\n",
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              "      <td>1022</td>\n",
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              "    <tr>\n",
              "      <th>1019</th>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>523</th>\n",
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              "      <td>523</td>\n",
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              "    <tr>\n",
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              "      <th>99</th>\n",
              "      <td>4.698281</td>\n",
              "      <td>99</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4.691629</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>4.690808</td>\n",
              "      <td>85</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 2 columns</p>\n",
              "</div>\n",
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              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f51a8a3f-62f7-4047-ab95-956c0d188118 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f51a8a3f-62f7-4047-ab95-956c0d188118');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f6fc38c7-cc15-4b1a-b2f4-b0281d794641\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f6fc38c7-cc15-4b1a-b2f4-b0281d794641')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f6fc38c7-cc15-4b1a-b2f4-b0281d794641 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "recommendation_df = recommendation_df.sort_values(by='weighted average recommendation score', ascending=False)\n",
        "recommendation_df.head(100)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "pGofsuSVfJr-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f624d778-e7a5-47f6-90d5-3ce57cfa2f35"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "          weighted average recommendation score  movieID\n",
            "movie_id                                                \n",
            "593                                         5.0      593\n",
            "614                                         5.0      614\n",
            "601                                         5.0      601\n",
            "768                                         5.0      768\n",
            "617                                         5.0      617\n",
            "...                                         ...      ...\n",
            "908                                         0.0      908\n",
            "909                                         0.0      909\n",
            "910                                         0.0      910\n",
            "911                                         0.0      911\n",
            "364                                         0.0      364\n",
            "\n",
            "[1029 rows x 2 columns]\n"
          ]
        }
      ],
      "source": [
        "recommendation_df = recommendation_df[(recommendation_df['weighted average recommendation score'] <= 5) &\n",
        " (recommendation_df['weighted average recommendation score'] >= 0) &\n",
        " (recommendation_df['weighted average recommendation score'].notnull())]\n",
        "print(recommendation_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "I0t3oXxcfLPP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4189066b-627f-4aed-edc0-25310c2b03b8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "weighted average recommendation score    0\n",
            "movieID                                  0\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "print(recommendation_df.isnull().sum())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "9zIlvwN8fOda",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "2b6a7f58-2bf9-403a-dba3-eca56c4646b0"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          weighted average recommendation score  movieID\n",
              "movie_id                                                \n",
              "593                                         5.0      593\n",
              "614                                         5.0      614\n",
              "601                                         5.0      601\n",
              "768                                         5.0      768\n",
              "617                                         5.0      617\n",
              "753                                         5.0      753\n",
              "224                                         5.0      224\n",
              "362                                         5.0      362\n",
              "581                                         5.0      581\n",
              "589                                         5.0      589"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c8c3c01b-2348-49aa-9ba4-08d1a8f83386\" class=\"colab-df-container\">\n",
              "    <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>weighted average recommendation score</th>\n",
              "      <th>movieID</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>movie_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>593</th>\n",
              "      <td>5.0</td>\n",
              "      <td>593</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>614</th>\n",
              "      <td>5.0</td>\n",
              "      <td>614</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>601</th>\n",
              "      <td>5.0</td>\n",
              "      <td>601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>768</th>\n",
              "      <td>5.0</td>\n",
              "      <td>768</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>617</th>\n",
              "      <td>5.0</td>\n",
              "      <td>617</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>753</th>\n",
              "      <td>5.0</td>\n",
              "      <td>753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>5.0</td>\n",
              "      <td>224</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>362</th>\n",
              "      <td>5.0</td>\n",
              "      <td>362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>581</th>\n",
              "      <td>5.0</td>\n",
              "      <td>581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>589</th>\n",
              "      <td>5.0</td>\n",
              "      <td>589</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c8c3c01b-2348-49aa-9ba4-08d1a8f83386')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-c8c3c01b-2348-49aa-9ba4-08d1a8f83386 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c8c3c01b-2348-49aa-9ba4-08d1a8f83386');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-8e035110-52d2-4661-8e26-72268f96b802\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8e035110-52d2-4661-8e26-72268f96b802')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8e035110-52d2-4661-8e26-72268f96b802 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ],
      "source": [
        "recommendation_df.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "4G8u5LMfn4Dp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362
        },
        "outputId": "6e3d0ef0-7168-40d7-bb80-71ec77260053"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     movie_id                                      title release_date\n",
              "223       224                            Ridicule (1996)  27-Nov-1996\n",
              "361       362                 Blues Brothers 2000 (1998)  06-Feb-1998\n",
              "580       581                          Kalifornia (1993)  01-Jan-1993\n",
              "588       589                     Wild Bunch, The (1969)  01-Jan-1969\n",
              "592       593                          Stalingrad (1993)  01-Jan-1993\n",
              "600       601             For Whom the Bell Tolls (1943)  01-Jan-1943\n",
              "613       614                               Giant (1956)  01-Jan-1956\n",
              "616       617  Blue Angel, The (Blaue Engel, Der) (1930)  01-Jan-1930\n",
              "752       753                    Burnt By the Sun (1994)  01-Jan-1994\n",
              "767       768                              Casper (1995)  01-Jan-1995"
            ],
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ffe417a5-1a7a-4f58-8e4b-7608ce13356f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
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              "\n",
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              "\n",
              "  @keyframes spin {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d2bf9580-2a9d-48ae-b2a6-5bc0ba506757 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "movies.loc[movies['movie_id'].isin(recommendation_df.head(10)['movieID'].tolist())]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "ii2gIAjMoAaf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "ce892200-6cd1-4c9b-a361-5b7c0dd64bdd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   movie_id              title release_date\n",
              "0         1   Toy Story (1995)  01-Jan-1995\n",
              "1         2   GoldenEye (1995)  01-Jan-1995\n",
              "2         3  Four Rooms (1995)  01-Jan-1995\n",
              "3         4  Get Shorty (1995)  01-Jan-1995\n",
              "4         5     Copycat (1995)  01-Jan-1995"
            ],
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              "      <td>Four Rooms (1995)</td>\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-13691625-fa61-47ca-b8e2-22b0e623aeec');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-894e6c25-cd33-4b1d-93d1-39ef3913cf28\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-894e6c25-cd33-4b1d-93d1-39ef3913cf28')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-894e6c25-cd33-4b1d-93d1-39ef3913cf28 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "movies.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "id": "x_12tja_fPrd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4e4a2a54-9252-434a-dc43-5ce1eeb87d80"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "RMSE Score: 1.3545939448111404\n"
          ]
        }
      ],
      "source": [
        "from math import sqrt\n",
        "merged_ratings = pd.merge(recommendation_df, ratings,on='movie_id')\n",
        "merged_ratings['squared_diff'] = (merged_ratings['weighted average recommendation score'] - merged_ratings['rating']) ** 2\n",
        "mean_squared_diff = merged_ratings['squared_diff'].mean()\n",
        "mean_squared_diff\n",
        "rmse_score = sqrt(mean_squared_diff)\n",
        "print(\"RMSE Score:\", rmse_score)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "id": "hG1nVkbufREN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6159cb10-e542-4276-cd7e-b308f8401a5d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "MAE Score: 1.0160955739878432\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "from math import sqrt\n",
        "merged_ratings = pd.merge(recommendation_df, ratings, on='movie_id')\n",
        "\n",
        "merged_ratings['abs_diff'] = abs(merged_ratings['weighted average recommendation score'] - merged_ratings['rating'])\n",
        "\n",
        "mae_score = merged_ratings['abs_diff'].mean()\n",
        "\n",
        "print(\"MAE Score:\", mae_score)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#addressing sparsity issue hereon"
      ],
      "metadata": {
        "id": "wAkDnXNipDQU"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "userItemMatrix = ratings.pivot_table(index='user_id', columns='movie_id', values='rating')\n",
        "userItemMatrix"
      ],
      "metadata": {
        "id": "MrcqZgGtj7Es",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "8d7893d6-56d2-4f69-a847-32add9f987fa"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "movie_id  1     2     3     4     5     6     7     8     9     10    ...  \\\n",
              "user_id                                                               ...   \n",
              "1          5.0   3.0   4.0   3.0   3.0   5.0   4.0   1.0   5.0   3.0  ...   \n",
              "2          4.0   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   2.0  ...   \n",
              "3          NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  ...   \n",
              "4          NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  ...   \n",
              "5          4.0   3.0   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  ...   \n",
              "...        ...   ...   ...   ...   ...   ...   ...   ...   ...   ...  ...   \n",
              "939        NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   5.0   NaN  ...   \n",
              "940        NaN   NaN   NaN   2.0   NaN   NaN   4.0   5.0   3.0   NaN  ...   \n",
              "941        5.0   NaN   NaN   NaN   NaN   NaN   4.0   NaN   NaN   NaN  ...   \n",
              "942        NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  ...   \n",
              "943        NaN   5.0   NaN   NaN   NaN   NaN   NaN   NaN   3.0   NaN  ...   \n",
              "\n",
              "movie_id  1673  1674  1675  1676  1677  1678  1679  1680  1681  1682  \n",
              "user_id                                                               \n",
              "1          NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
              "2          NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
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              "5          NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
              "...        ...   ...   ...   ...   ...   ...   ...   ...   ...   ...  \n",
              "939        NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
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              "941        NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
              "942        NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
              "943        NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  \n",
              "\n",
              "[943 rows x 1682 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9f320ddb-f967-480e-9902-d21da141b6d1\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
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              "    .dataframe tbody tr th {\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th>movie_id</th>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</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",
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              "    <tr>\n",
              "      <th>942</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>943</th>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</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>3.0</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",
              "  </tbody>\n",
              "</table>\n",
              "<p>943 rows × 1682 columns</p>\n",
              "</div>\n",
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              "      display:flex;\n",
              "      gap: 12px;\n",
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              "      border: none;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "      background-color: #434B5C;\n",
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-9f320ddb-f967-480e-9902-d21da141b6d1 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-9f320ddb-f967-480e-9902-d21da141b6d1');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
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              "  </button>\n",
              "\n",
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              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
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              "\n",
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              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "null_values = userItemMatrix.isnull().sum().sum()\n",
        "print(f\"Total number of null values: {null_values}\")\n"
      ],
      "metadata": {
        "id": "E8IxVdJIodGK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dd6a84bf-a7c9-4cba-b670-0f2996179d68"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total number of null values: 1486126\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.impute import SimpleImputer\n",
        "\n",
        "# Create a copy of the userItemMatrix\n",
        "userItemMatrix_imputed = userItemMatrix.copy()\n",
        "\n",
        "# Calculate the total number of null values in the table\n",
        "total_null_values = userItemMatrix_imputed.isnull().sum().sum()\n",
        "\n",
        "# Calculate the threshold for the number of null values to be imputed\n",
        "null_threshold = int(total_null_values * 0.60)\n",
        "\n",
        "imputer = SimpleImputer(missing_values=np.nan, strategy='median')\n",
        "\n",
        "# Iterate over each row\n",
        "for index, row in userItemMatrix_imputed.iterrows():\n",
        "    # Calculate the number of null values in each row\n",
        "    row_null_values = row.isnull().sum()\n",
        "\n",
        "    # If the number of null values in the row is less than the threshold, skip imputation for this row\n",
        "    if row_null_values == 0 or row_null_values > null_threshold:\n",
        "        continue\n",
        "\n",
        "    # Create a mask for 60% of the null values in this row\n",
        "    row_mask = np.random.choice([True, False], len(row), p=[0.6, 0.4])\n",
        "\n",
        "    # Apply imputation for the selected 60% of null values in this row\n",
        "    row_values = row.values\n",
        "    row_values[row_mask] = imputer.fit_transform(row_values[row_mask].reshape(-1, 1)).ravel()\n",
        "\n",
        "    # Update the values in the DataFrame for this row\n",
        "    userItemMatrix_imputed.loc[index] = row_values\n",
        "\n",
        "# Calculate the number of null values after imputation\n",
        "remaining_null_values = userItemMatrix_imputed.isnull().sum().sum()\n",
        "\n",
        "# Calculate the number of null values that have been imputed\n",
        "imputed_values = total_null_values - remaining_null_values\n",
        "\n",
        "# Calculate the percentage of null values imputed\n",
        "percent_imputed = (imputed_values / total_null_values) * 100\n",
        "\n",
        "print(f\"Percentage of null values imputed: {percent_imputed:.2f}%\")\n",
        "print(f\"Remaining null values: {remaining_null_values}\")"
      ],
      "metadata": {
        "id": "Ie1GRbl3poCi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4bf10063-7693-42ac-ae83-68d737058493"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Percentage of null values imputed: 59.97%\n",
            "Remaining null values: 594826\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#cpmare table sizes for any anomaly\n",
        "print(userItemMatrix_imputed.shape[1])\n",
        "print(userItemMatrix.shape[1])"
      ],
      "metadata": {
        "id": "lPRNYkb2vM4a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "76829f57-8e6d-4912-be0a-7dd95f209c12"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1682\n",
            "1682\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(ratings))"
      ],
      "metadata": {
        "id": "p_pl6Q9owd6Y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "489e23dd-f7fe-4949-f39f-0d522372209e"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "100000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ratings_series = userItemMatrix_imputed.stack()\n",
        "ratings_imputed = ratings_series.reset_index()\n",
        "ratings_imputed.columns = ['user_id', 'movie_id', 'rating']"
      ],
      "metadata": {
        "id": "U2-sDCNjxZ2G"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(ratings_imputed))"
      ],
      "metadata": {
        "id": "5u3zaswpxn2Q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "33e02947-efbf-4292-ba1a-97906d511ff4"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "991300\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#testing for newer values"
      ],
      "metadata": {
        "id": "1hnQ4nSsyeUj"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "userItemMatrix_imputed"
      ],
      "metadata": {
        "id": "nHwjS_RKyvfR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "4264ee27-1214-4817-cdf3-0146d0476e34"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "movie_id  1     2     3     4     5     6     7     8     9     10    ...  \\\n",
              "user_id                                                               ...   \n",
              "1          5.0   3.0   4.0   3.0   3.0   5.0   4.0   1.0   5.0   3.0  ...   \n",
              "2          4.0   NaN   NaN   NaN   4.0   4.0   NaN   4.0   4.0   2.0  ...   \n",
              "3          2.0   2.0   NaN   2.0   2.0   NaN   NaN   2.0   2.0   2.0  ...   \n",
              "4          4.5   NaN   4.5   4.5   4.5   4.5   4.5   4.5   NaN   4.5  ...   \n",
              "5          4.0   3.0   3.0   3.0   NaN   3.0   NaN   NaN   3.0   NaN  ...   \n",
              "...        ...   ...   ...   ...   ...   ...   ...   ...   ...   ...  ...   \n",
              "939        NaN   5.0   5.0   5.0   NaN   5.0   NaN   5.0   5.0   5.0  ...   \n",
              "940        4.0   4.0   4.0   2.0   NaN   4.0   4.0   5.0   3.0   4.0  ...   \n",
              "941        5.0   4.0   4.0   4.0   NaN   NaN   4.0   NaN   4.0   NaN  ...   \n",
              "942        NaN   4.0   4.0   4.0   NaN   4.0   4.0   4.0   NaN   4.0  ...   \n",
              "943        NaN   5.0   NaN   NaN   4.0   4.0   NaN   NaN   3.0   NaN  ...   \n",
              "\n",
              "movie_id  1673  1674  1675  1676  1677  1678  1679  1680  1681  1682  \n",
              "user_id                                                               \n",
              "1          4.0   4.0   NaN   NaN   4.0   NaN   4.0   4.0   NaN   NaN  \n",
              "2          4.0   NaN   NaN   4.0   NaN   NaN   4.0   NaN   NaN   4.0  \n",
              "3          2.0   2.0   2.0   2.0   2.0   NaN   2.0   2.0   2.0   NaN  \n",
              "4          NaN   4.5   NaN   NaN   4.5   NaN   4.5   NaN   NaN   4.5  \n",
              "5          NaN   NaN   3.0   3.0   3.0   3.0   3.0   3.0   3.0   3.0  \n",
              "...        ...   ...   ...   ...   ...   ...   ...   ...   ...   ...  \n",
              "939        5.0   5.0   5.0   5.0   5.0   5.0   5.0   5.0   5.0   NaN  \n",
              "940        4.0   NaN   NaN   NaN   NaN   4.0   4.0   NaN   NaN   4.0  \n",
              "941        NaN   4.0   NaN   4.0   4.0   4.0   4.0   NaN   4.0   4.0  \n",
              "942        4.0   4.0   NaN   NaN   4.0   4.0   4.0   4.0   4.0   4.0  \n",
              "943        4.0   NaN   4.0   NaN   4.0   4.0   NaN   NaN   4.0   4.0  \n",
              "\n",
              "[943 rows x 1682 columns]"
            ],
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              "      <th>movie_id</th>\n",
              "      <th>1</th>\n",
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              "      <th>1681</th>\n",
              "      <th>1682</th>\n",
              "    </tr>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
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              "    </tr>\n",
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              "      <th>1</th>\n",
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              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
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              "      <td>...</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
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              "      <td>NaN</td>\n",
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              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
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              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>4.5</td>\n",
              "      <td>4.5</td>\n",
              "      <td>4.5</td>\n",
              "      <td>4.5</td>\n",
              "      <td>4.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>939</th>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>...</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>940</th>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>941</th>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>942</th>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>943</th>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>943 rows × 1682 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a81db3bb-41fd-4481-93d9-c4fabd2b8d4b')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a81db3bb-41fd-4481-93d9-c4fabd2b8d4b button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a81db3bb-41fd-4481-93d9-c4fabd2b8d4b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-9dd5d295-2913-4777-9754-a0c2ba88aa28\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9dd5d295-2913-4777-9754-a0c2ba88aa28')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-9dd5d295-2913-4777-9754-a0c2ba88aa28 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "user_input_percent = 0.3\n",
        "subset_percent = 0.7\n",
        "\n",
        "num_ratings = len(ratings_imputed)\n",
        "num_user_input = int(num_ratings * user_input_percent)\n",
        "num_subset = int(num_ratings * subset_percent)\n",
        "\n",
        "user_input_ratings = ratings.sample(n=num_user_input, replace=True, random_state=42)\n",
        "subset_ratings = ratings.drop(user_input_ratings.index)\n",
        "user_input_ratings"
      ],
      "metadata": {
        "id": "uuB8Y4j3xuZM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "474afbb6-1629-48f3-8957-5bd4e96023b2"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       user_id  movie_id  rating\n",
              "15795      222       200       3\n",
              "860        284       322       3\n",
              "76820      437       475       3\n",
              "54886      343       276       5\n",
              "6265       216       231       2\n",
              "...        ...       ...     ...\n",
              "57582      795       200       3\n",
              "28631      358       213       5\n",
              "92849      634       284       4\n",
              "68292      758       955       2\n",
              "87075      806       143       5\n",
              "\n",
              "[297390 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-dd8ef868-4978-48f1-ac8a-f6b5e86c6866\" class=\"colab-df-container\">\n",
              "    <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>user_id</th>\n",
              "      <th>movie_id</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>15795</th>\n",
              "      <td>222</td>\n",
              "      <td>200</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>860</th>\n",
              "      <td>284</td>\n",
              "      <td>322</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76820</th>\n",
              "      <td>437</td>\n",
              "      <td>475</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54886</th>\n",
              "      <td>343</td>\n",
              "      <td>276</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6265</th>\n",
              "      <td>216</td>\n",
              "      <td>231</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57582</th>\n",
              "      <td>795</td>\n",
              "      <td>200</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28631</th>\n",
              "      <td>358</td>\n",
              "      <td>213</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92849</th>\n",
              "      <td>634</td>\n",
              "      <td>284</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68292</th>\n",
              "      <td>758</td>\n",
              "      <td>955</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>87075</th>\n",
              "      <td>806</td>\n",
              "      <td>143</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>297390 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dd8ef868-4978-48f1-ac8a-f6b5e86c6866')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-dd8ef868-4978-48f1-ac8a-f6b5e86c6866 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-dd8ef868-4978-48f1-ac8a-f6b5e86c6866');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-cf5c7891-91da-43a8-bc9f-4f0b55bff6dc\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cf5c7891-91da-43a8-bc9f-4f0b55bff6dc')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-cf5c7891-91da-43a8-bc9f-4f0b55bff6dc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "LH0a9w1Nyqcu"
      },
      "execution_count": 41,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}