(KDT)TMDB컨텐츠 기반 영화 추천.ipynb

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      "name": "(KDT) TMDB 컨텐츠 기반 영화 추천\u001c",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/learn-programmers/programmers_kdt_II/blob/main/(KDT)TMDB%EC%BB%A8%ED%85%90%EC%B8%A0%20%EA%B8%B0%EB%B0%98%20%EC%98%81%ED%99%94%20%EC%B6%94%EC%B2%9C%1C.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rBPspcq8cfC0"
      },
      "source": [
        "# 컨텐츠 기반 영화 추천 시스템을 만들어 보자\n",
        "\n",
        "https://www.kaggle.com/tmdb/tmdb-movie-metadata\n",
        "\n",
        "이 데이터셋은 영화에 대한 정보(예산, 장르, 평점, 런닝시간, 제목, 키워드 등등)와 영화 연출팀과 배우들에 대한 별도 정보로 구성되어 있으며 일반 사용자들이 이 정보를 입력하여 구성되었다 (위키와 흡사)\n",
        "\n",
        "내가 좋아한 (리뷰를 좋게 준) 영화와 비슷한 영화들(컨텐츠 측면에서)을 찾아서 추천"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Txl6fsdQb9kF"
      },
      "source": [
        "## 입력 데이터 로딩\n",
        "\n",
        "*   영화 정보는 tmdb_5000_movies.csv라는 파일에 있다. 이 파일만 사용할 예정\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y0D6ujudb98S"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9rkuVyb3cEEA"
      },
      "source": [
        "movies = pd.read_csv(\"https://grepp-reco-test.s3.ap-northeast-2.amazonaws.com/tmdb_5000_movies.csv\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "blpvnvHPcSzq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 652
        },
        "outputId": "be367b47-daef-4144-c669-1cc73b0966a3"
      },
      "source": [
        "movies.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th {\n",
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              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>budget</th>\n",
              "      <th>genres</th>\n",
              "      <th>homepage</th>\n",
              "      <th>id</th>\n",
              "      <th>keywords</th>\n",
              "      <th>original_language</th>\n",
              "      <th>original_title</th>\n",
              "      <th>overview</th>\n",
              "      <th>popularity</th>\n",
              "      <th>production_companies</th>\n",
              "      <th>production_countries</th>\n",
              "      <th>release_date</th>\n",
              "      <th>revenue</th>\n",
              "      <th>runtime</th>\n",
              "      <th>spoken_languages</th>\n",
              "      <th>status</th>\n",
              "      <th>tagline</th>\n",
              "      <th>title</th>\n",
              "      <th>vote_average</th>\n",
              "      <th>vote_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>237000000</td>\n",
              "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
              "      <td>http://www.avatarmovie.com/</td>\n",
              "      <td>19995</td>\n",
              "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
              "      <td>en</td>\n",
              "      <td>Avatar</td>\n",
              "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
              "      <td>150.437577</td>\n",
              "      <td>[{\"name\": \"Ingenious Film Partners\", \"id\": 289...</td>\n",
              "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
              "      <td>2009-12-10</td>\n",
              "      <td>2787965087</td>\n",
              "      <td>162.0</td>\n",
              "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
              "      <td>Released</td>\n",
              "      <td>Enter the World of Pandora.</td>\n",
              "      <td>Avatar</td>\n",
              "      <td>7.2</td>\n",
              "      <td>11800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>300000000</td>\n",
              "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
              "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
              "      <td>285</td>\n",
              "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
              "      <td>en</td>\n",
              "      <td>Pirates of the Caribbean: At World's End</td>\n",
              "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
              "      <td>139.082615</td>\n",
              "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
              "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
              "      <td>2007-05-19</td>\n",
              "      <td>961000000</td>\n",
              "      <td>169.0</td>\n",
              "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
              "      <td>Released</td>\n",
              "      <td>At the end of the world, the adventure begins.</td>\n",
              "      <td>Pirates of the Caribbean: At World's End</td>\n",
              "      <td>6.9</td>\n",
              "      <td>4500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>245000000</td>\n",
              "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
              "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
              "      <td>206647</td>\n",
              "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
              "      <td>en</td>\n",
              "      <td>Spectre</td>\n",
              "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
              "      <td>107.376788</td>\n",
              "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...</td>\n",
              "      <td>[{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"...</td>\n",
              "      <td>2015-10-26</td>\n",
              "      <td>880674609</td>\n",
              "      <td>148.0</td>\n",
              "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
              "      <td>Released</td>\n",
              "      <td>A Plan No One Escapes</td>\n",
              "      <td>Spectre</td>\n",
              "      <td>6.3</td>\n",
              "      <td>4466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>250000000</td>\n",
              "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
              "      <td>http://www.thedarkknightrises.com/</td>\n",
              "      <td>49026</td>\n",
              "      <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
              "      <td>en</td>\n",
              "      <td>The Dark Knight Rises</td>\n",
              "      <td>Following the death of District Attorney Harve...</td>\n",
              "      <td>112.312950</td>\n",
              "      <td>[{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...</td>\n",
              "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
              "      <td>2012-07-16</td>\n",
              "      <td>1084939099</td>\n",
              "      <td>165.0</td>\n",
              "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
              "      <td>Released</td>\n",
              "      <td>The Legend Ends</td>\n",
              "      <td>The Dark Knight Rises</td>\n",
              "      <td>7.6</td>\n",
              "      <td>9106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>260000000</td>\n",
              "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
              "      <td>http://movies.disney.com/john-carter</td>\n",
              "      <td>49529</td>\n",
              "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
              "      <td>en</td>\n",
              "      <td>John Carter</td>\n",
              "      <td>John Carter is a war-weary, former military ca...</td>\n",
              "      <td>43.926995</td>\n",
              "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}]</td>\n",
              "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
              "      <td>2012-03-07</td>\n",
              "      <td>284139100</td>\n",
              "      <td>132.0</td>\n",
              "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
              "      <td>Released</td>\n",
              "      <td>Lost in our world, found in another.</td>\n",
              "      <td>John Carter</td>\n",
              "      <td>6.1</td>\n",
              "      <td>2124</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      budget  ... vote_count\n",
              "0  237000000  ...      11800\n",
              "1  300000000  ...       4500\n",
              "2  245000000  ...       4466\n",
              "3  250000000  ...       9106\n",
              "4  260000000  ...       2124\n",
              "\n",
              "[5 rows x 20 columns]"
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          },
          "metadata": {
            "tags": []
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          "execution_count": 26
        }
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      "cell_type": "code",
      "metadata": {
        "id": "pxSppRXbccNr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "99574cb0-0db2-4690-98f8-834981a5411b"
      },
      "source": [
        "movies.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4803, 20)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iVYfiao_salu"
      },
      "source": [
        "import json\n",
        "\n",
        "def f(j):\n",
        "    genres = []\n",
        "    ar = json.loads(j)\n",
        "    for a in ar:\n",
        "        genres.append(a.get(\"name\"))\n",
        "    return \" \".join(sorted(genres))\n",
        "\n",
        "movies['genres_name'] = movies.apply(lambda x: f(x.genres), axis=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FhePVFKzvV2J",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "outputId": "674dfad7-44e6-4512-9269-655fbaf41090"
      },
      "source": [
        "movies[['genres_name']].head()   # vs. movies['genres_name'].head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>genres_name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Action Adventure Fantasy Science Fiction</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Action Adventure Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Action Adventure Crime</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Action Crime Drama Thriller</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Action Adventure Science Fiction</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                genres_name\n",
              "0  Action Adventure Fantasy Science Fiction\n",
              "1                  Action Adventure Fantasy\n",
              "2                    Action Adventure Crime\n",
              "3               Action Crime Drama Thriller\n",
              "4          Action Adventure Science Fiction"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UaBocamo0c7E",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cbe0d2fb-0219-42af-b7d4-2d6912ca65c5"
      },
      "source": [
        "movies['genres_name'].nunique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "638"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WVmQd9Gh2HKj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9ea6fbd4-0dee-4de1-a4d9-05cff53ad3d9"
      },
      "source": [
        "movies.groupby('genres_name').size()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "genres_name\n",
              "                                            28\n",
              "Action                                      21\n",
              "Action Adventure                            15\n",
              "Action Adventure Animation                   1\n",
              "Action Adventure Animation Comedy Family     5\n",
              "                                            ..\n",
              "Science Fiction Thriller                    12\n",
              "Thriller                                    23\n",
              "War                                          2\n",
              "War Western                                  1\n",
              "Western                                     18\n",
              "Length: 638, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Df1sRrzO_Ssd"
      },
      "source": [
        "## 여러 텍스트 필드들을 모아서 텍스트 유사도에 사용할 텍스트 필드 하나를 생성"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QnFoa1oqAs5t"
      },
      "source": [
        "for f in ['original_title','overview','genres_name']:\n",
        "  movies[f] = movies[f].fillna('')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HL4vR-tH_GyM"
      },
      "source": [
        "def combine_features(row):\n",
        "\ttry:\n",
        "\t\treturn row['original_title']+\" \"+row['overview']+\" \"+row[\"genres_name\"]\n",
        "\texcept:\n",
        "\t\tprint (\"Error:\", row)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jve2kIG8B1Px"
      },
      "source": [
        "movies[\"combined_features\"] = movies.apply(combine_features,axis=1)\n",
        "movies = movies.reset_index()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L_BiVL4YjtPM",
        "outputId": "98b9a315-1bc3-4cc6-bfc1-97bd5aed8c51"
      },
      "source": [
        "movies[\"combined_features\"].head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    Avatar In the 22nd century, a paraplegic Marin...\n",
              "1    Pirates of the Caribbean: At World's End Capta...\n",
              "2    Spectre A cryptic message from Bond’s past sen...\n",
              "3    The Dark Knight Rises Following the death of D...\n",
              "4    John Carter John Carter is a war-weary, former...\n",
              "Name: combined_features, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XW9vpC7iHuFw"
      },
      "source": [
        "## TF-IDF 기반 벡터 생성 후 코사인 유사도로 영화들간의 유사도 계산"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TbY_Ictt-aLx"
      },
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.metrics.pairwise import cosine_similarity"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dFeI1fOACDhP"
      },
      "source": [
        "tfidfvectorizer = TfidfVectorizer(analyzer='word', stop_words='english', norm='l2')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ezr5zEinCGNx"
      },
      "source": [
        "tfidf_matrix = tfidfvectorizer.fit_transform(movies[\"combined_features\"])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Sw2_jChiHRvC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0b4bd980-8b70-44cf-a48f-829c431bdb7e"
      },
      "source": [
        "tfidf_matrix.shape    #  min_df 파라미터!!!"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4803, 22179)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OpiZRLBiCRZz"
      },
      "source": [
        "cosine_sim = cosine_similarity(tfidf_matrix) # linear_kernel을 사용해도 동일함. tfidf 벡터가 생성될 때 L2 normalization이 되었기 때문"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 244
        },
        "id": "qUdIwf59s-up",
        "outputId": "67c812fc-fa1d-49f8-a0f1-dfffcfd91349"
      },
      "source": [
        "df_cosine_sim = pd.DataFrame(data = cosine_sim)\n",
        "df_cosine_sim.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>4782</th>\n",
              "      <th>4783</th>\n",
              "      <th>4784</th>\n",
              "      <th>4785</th>\n",
              "      <th>4786</th>\n",
              "      <th>4787</th>\n",
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              "      <td>0.013909</td>\n",
              "      <td>0.026299</td>\n",
              "      <td>0.029273</td>\n",
              "      <td>0.046984</td>\n",
              "      <td>0.003855</td>\n",
              "      <td>0.068451</td>\n",
              "      <td>0.020614</td>\n",
              "      <td>0.020293</td>\n",
              "      <td>0.042341</td>\n",
              "      <td>0.027007</td>\n",
              "      <td>0.031619</td>\n",
              "      <td>0.010129</td>\n",
              "      <td>0.060413</td>\n",
              "      <td>0.013328</td>\n",
              "      <td>0.036371</td>\n",
              "      <td>0.028507</td>\n",
              "      <td>0.021622</td>\n",
              "      <td>0.017544</td>\n",
              "      <td>0.015891</td>\n",
              "      <td>0.013011</td>\n",
              "      <td>0.019884</td>\n",
              "      <td>0.028896</td>\n",
              "      <td>0.014555</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.062389</td>\n",
              "      <td>0.066969</td>\n",
              "      <td>0.031541</td>\n",
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              "      <td>0.022223</td>\n",
              "      <td>0.099964</td>\n",
              "      <td>0.013279</td>\n",
              "      <td>0.043265</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.086387</td>\n",
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              "      <td>0.031826</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.073544</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.003744</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.004791</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.005286</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.016091</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.026697</td>\n",
              "      <td>0.057602</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.003941</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
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              "    <tr>\n",
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              "      <td>0.047903</td>\n",
              "      <td>0.023093</td>\n",
              "      <td>0.004040</td>\n",
              "      <td>0.039814</td>\n",
              "      <td>0.021603</td>\n",
              "      <td>0.029597</td>\n",
              "      <td>0.024507</td>\n",
              "      <td>0.011009</td>\n",
              "      <td>0.231140</td>\n",
              "      <td>0.010615</td>\n",
              "      <td>0.077998</td>\n",
              "      <td>0.019808</td>\n",
              "      <td>0.026244</td>\n",
              "      <td>0.148229</td>\n",
              "      <td>0.012018</td>\n",
              "      <td>0.033808</td>\n",
              "      <td>0.022021</td>\n",
              "      <td>0.013635</td>\n",
              "      <td>0.020837</td>\n",
              "      <td>0.030282</td>\n",
              "      <td>0.015253</td>\n",
              "      <td>0.004337</td>\n",
              "      <td>0.082871</td>\n",
              "      <td>0.018004</td>\n",
              "      <td>0.032389</td>\n",
              "      <td>0.018082</td>\n",
              "      <td>0.023289</td>\n",
              "      <td>0.034059</td>\n",
              "      <td>0.020987</td>\n",
              "      <td>0.018008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.026065</td>\n",
              "      <td>0.028898</td>\n",
              "      <td>0.019648</td>\n",
              "      <td>0.040240</td>\n",
              "      <td>0.022964</td>\n",
              "      <td>...</td>\n",
              "      <td>0.016563</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.003923</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.005021</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007513</td>\n",
              "      <td>0.010284</td>\n",
              "      <td>0.019026</td>\n",
              "      <td>0.021126</td>\n",
              "      <td>0.008742</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.013901</td>\n",
              "      <td>0.007392</td>\n",
              "      <td>0.014459</td>\n",
              "      <td>0.019402</td>\n",
              "      <td>0.008273</td>\n",
              "      <td>0.005133</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.012301</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.016368</td>\n",
              "      <td>0.044292</td>\n",
              "      <td>0.006000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.004130</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.022717</td>\n",
              "      <td>0.016449</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.013909</td>\n",
              "      <td>0.014576</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.008018</td>\n",
              "      <td>0.009303</td>\n",
              "      <td>0.009417</td>\n",
              "      <td>0.003084</td>\n",
              "      <td>0.041851</td>\n",
              "      <td>0.023712</td>\n",
              "      <td>0.008672</td>\n",
              "      <td>0.009994</td>\n",
              "      <td>0.147890</td>\n",
              "      <td>0.013512</td>\n",
              "      <td>0.008105</td>\n",
              "      <td>0.014259</td>\n",
              "      <td>0.004219</td>\n",
              "      <td>0.011559</td>\n",
              "      <td>0.058507</td>\n",
              "      <td>0.032881</td>\n",
              "      <td>0.007497</td>\n",
              "      <td>0.006791</td>\n",
              "      <td>0.010411</td>\n",
              "      <td>0.006294</td>\n",
              "      <td>0.028365</td>\n",
              "      <td>0.011646</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010323</td>\n",
              "      <td>0.007930</td>\n",
              "      <td>0.010024</td>\n",
              "      <td>0.127351</td>\n",
              "      <td>0.009497</td>\n",
              "      <td>0.015002</td>\n",
              "      <td>0.004203</td>\n",
              "      <td>0.013750</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.070328</td>\n",
              "      <td>0.021493</td>\n",
              "      <td>0.005935</td>\n",
              "      <td>0.019287</td>\n",
              "      <td>0.010115</td>\n",
              "      <td>...</td>\n",
              "      <td>0.015361</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.053921</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.002996</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.009354</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.032268</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010986</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.017742</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.030868</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.013227</td>\n",
              "      <td>0.022647</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015928</td>\n",
              "      <td>0.007694</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.011636</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.026299</td>\n",
              "      <td>0.004304</td>\n",
              "      <td>0.008018</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.011748</td>\n",
              "      <td>0.007161</td>\n",
              "      <td>0.014069</td>\n",
              "      <td>0.027766</td>\n",
              "      <td>0.028148</td>\n",
              "      <td>0.158541</td>\n",
              "      <td>0.002951</td>\n",
              "      <td>0.008398</td>\n",
              "      <td>0.003990</td>\n",
              "      <td>0.002393</td>\n",
              "      <td>0.004210</td>\n",
              "      <td>0.003437</td>\n",
              "      <td>0.022549</td>\n",
              "      <td>0.002756</td>\n",
              "      <td>0.008791</td>\n",
              "      <td>0.020681</td>\n",
              "      <td>0.008575</td>\n",
              "      <td>0.032636</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.021938</td>\n",
              "      <td>0.017890</td>\n",
              "      <td>0.019519</td>\n",
              "      <td>0.004551</td>\n",
              "      <td>0.012709</td>\n",
              "      <td>0.028688</td>\n",
              "      <td>0.018194</td>\n",
              "      <td>0.030973</td>\n",
              "      <td>0.019660</td>\n",
              "      <td>0.007890</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.003664</td>\n",
              "      <td>0.037372</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.029989</td>\n",
              "      <td>0.012772</td>\n",
              "      <td>...</td>\n",
              "      <td>0.012644</td>\n",
              "      <td>0.005399</td>\n",
              "      <td>0.019117</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.055842</td>\n",
              "      <td>0.002294</td>\n",
              "      <td>0.008172</td>\n",
              "      <td>0.012819</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.025729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.002874</td>\n",
              "      <td>0.001481</td>\n",
              "      <td>0.002028</td>\n",
              "      <td>0.006361</td>\n",
              "      <td>0.011386</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015288</td>\n",
              "      <td>0.048358</td>\n",
              "      <td>0.001457</td>\n",
              "      <td>0.012909</td>\n",
              "      <td>0.001086</td>\n",
              "      <td>0.001631</td>\n",
              "      <td>0.018049</td>\n",
              "      <td>0.002363</td>\n",
              "      <td>0.004615</td>\n",
              "      <td>0.002446</td>\n",
              "      <td>0.002511</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.012086</td>\n",
              "      <td>0.002655</td>\n",
              "      <td>0.003020</td>\n",
              "      <td>0.001183</td>\n",
              "      <td>0.004516</td>\n",
              "      <td>0.001678</td>\n",
              "      <td>0.007343</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.029067</td>\n",
              "      <td>0.038273</td>\n",
              "      <td>0.019549</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.029273</td>\n",
              "      <td>0.047903</td>\n",
              "      <td>0.009303</td>\n",
              "      <td>0.011748</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.007872</td>\n",
              "      <td>0.011027</td>\n",
              "      <td>0.054503</td>\n",
              "      <td>0.005454</td>\n",
              "      <td>0.019947</td>\n",
              "      <td>0.037146</td>\n",
              "      <td>0.007027</td>\n",
              "      <td>0.036121</td>\n",
              "      <td>0.006775</td>\n",
              "      <td>0.038753</td>\n",
              "      <td>0.003527</td>\n",
              "      <td>0.063569</td>\n",
              "      <td>0.029411</td>\n",
              "      <td>0.028792</td>\n",
              "      <td>0.020497</td>\n",
              "      <td>0.013656</td>\n",
              "      <td>0.037662</td>\n",
              "      <td>0.005261</td>\n",
              "      <td>0.010957</td>\n",
              "      <td>0.023419</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.093862</td>\n",
              "      <td>0.073594</td>\n",
              "      <td>0.061275</td>\n",
              "      <td>0.020900</td>\n",
              "      <td>0.007939</td>\n",
              "      <td>0.040770</td>\n",
              "      <td>0.021906</td>\n",
              "      <td>0.028938</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.036683</td>\n",
              "      <td>0.049722</td>\n",
              "      <td>0.004961</td>\n",
              "      <td>0.006438</td>\n",
              "      <td>0.039374</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015767</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.002504</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.013706</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.004590</td>\n",
              "      <td>0.003535</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015872</td>\n",
              "      <td>0.007706</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010763</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010447</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.013190</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.002636</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.004744</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 4803 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       0         1         2         3     ...  4799      4800      4801      4802\n",
              "0  1.000000  0.034109  0.013909  0.026299  ...   0.0  0.000000  0.000000  0.000000\n",
              "1  0.034109  1.000000  0.014576  0.004304  ...   0.0  0.022717  0.016449  0.000000\n",
              "2  0.013909  0.014576  1.000000  0.008018  ...   0.0  0.011636  0.000000  0.000000\n",
              "3  0.026299  0.004304  0.008018  1.000000  ...   0.0  0.029067  0.038273  0.019549\n",
              "4  0.029273  0.047903  0.009303  0.011748  ...   0.0  0.004744  0.000000  0.000000\n",
              "\n",
              "[5 rows x 4803 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8E8XkgRiH21M"
      },
      "source": [
        "## 컨텐츠 기반 추천 함수 만들기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "owmSw3l4Eoua"
      },
      "source": [
        "def get_title_from_index(df, index):\n",
        "\treturn df[df.index == index][\"original_title\"].values[0]\n",
        "\n",
        "def get_index_from_title(df, title):\n",
        "\treturn df[df.original_title == title][\"index\"].values[0]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YfLzyDJRAUZe",
        "outputId": "fcc8bf3b-a2db-4740-d113-0163c6cdebc8"
      },
      "source": [
        "cosine_sim[0]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1.        , 0.03410854, 0.01390903, ..., 0.        , 0.        ,\n",
              "       0.        ])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I3hj7s-i6x8h",
        "outputId": "f883f2ec-775b-490c-8a55-48ac7d39bfcb"
      },
      "source": [
        "for cs in enumerate(cosine_sim[0]):\n",
        "  print(cs)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(0, 1.0)\n",
            "(1, 0.03410853782660229)\n",
            "(2, 0.01390902783347693)\n",
            "(3, 0.026299406427582796)\n",
            "(4, 0.029272658943387597)\n",
            "(5, 0.04698429164961723)\n",
            "(6, 0.0038547145246063336)\n",
            "(7, 0.06845111489143474)\n",
            "(8, 0.02061425771572521)\n",
            "(9, 0.02029251436658916)\n",
            "(10, 0.042340784794744034)\n",
            "(11, 0.027006676853799448)\n",
            "(12, 0.03161857450875023)\n",
            "(13, 0.01012938358302969)\n",
            "(14, 0.06041309047742964)\n",
            "(15, 0.013328113123785311)\n",
            "(16, 0.036370965857215116)\n",
            "(17, 0.028506554034230434)\n",
            "(18, 0.021621957314996235)\n",
            "(19, 0.017543907763833053)\n",
            "(20, 0.015890840282328227)\n",
            "(21, 0.013010542711001)\n",
            "(22, 0.019883591520990392)\n",
            "(23, 0.02889593817447864)\n",
            "(24, 0.014554529088866432)\n",
            "(25, 0.0)\n",
            "(26, 0.06238914032771084)\n",
            "(27, 0.06696897035188898)\n",
            "(28, 0.03154135084595286)\n",
            "(29, 0.033028070957875535)\n",
            "(30, 0.02222324724238147)\n",
            "(31, 0.09996364525205159)\n",
            "(32, 0.01327863170477505)\n",
            "(33, 0.043265033860517235)\n",
            "(34, 0.0)\n",
            "(35, 0.039051333415229664)\n",
            "(36, 0.08638691814794394)\n",
            "(37, 0.018748545946612044)\n",
            "(38, 0.01802380787810684)\n",
            "(39, 0.031825548096633724)\n",
            "(40, 0.015433237420097019)\n",
            "(41, 0.025674437650790034)\n",
            "(42, 0.0)\n",
            "(43, 0.04306412469507269)\n",
            "(44, 0.009470265874905992)\n",
            "(45, 0.07621308668368848)\n",
            "(46, 0.05522057691241832)\n",
            "(47, 0.05765275787669277)\n",
            "(48, 0.014132440528384749)\n",
            "(49, 0.0)\n",
            "(50, 0.023102130694825425)\n",
            "(51, 0.018697926741646227)\n",
            "(52, 0.07088979499054691)\n",
            "(53, 0.009469709195410346)\n",
            "(54, 0.01260604105196419)\n",
            "(55, 0.013778388580333433)\n",
            "(56, 0.04467626476495244)\n",
            "(57, 0.0)\n",
            "(58, 0.009884582969069017)\n",
            "(59, 0.021216123864259008)\n",
            "(60, 0.0)\n",
            "(61, 0.052007182327351145)\n",
            "(62, 0.01737006832095739)\n",
            "(63, 0.013123026930223618)\n",
            "(64, 0.027235730800554175)\n",
            "(65, 0.004796823549306464)\n",
            "(66, 0.007820405317249238)\n",
            "(67, 0.027632827303563545)\n",
            "(68, 0.09173891416915263)\n",
            "(69, 0.008405068759813415)\n",
            "(70, 0.02939012028735769)\n",
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            "(72, 0.04229247614192269)\n",
            "(73, 0.014197750270890687)\n",
            "(74, 0.07430483210649079)\n",
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            "(76, 0.031032838335357315)\n",
            "(77, 0.0)\n",
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            "(79, 0.028019026686822112)\n",
            "(80, 0.012123093029683826)\n",
            "(81, 0.012000190899448426)\n",
            "(82, 0.029548262137839183)\n",
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            "(84, 0.028332842030645476)\n",
            "(85, 0.020518006918414565)\n",
            "(86, 0.01658693767455608)\n",
            "(87, 0.044362660740464424)\n",
            "(88, 0.016003979380626684)\n",
            "(89, 0.01639024159466219)\n",
            "(90, 0.024821337693962903)\n",
            "(91, 0.06313440768927514)\n",
            "(92, 0.01585842991102098)\n",
            "(93, 0.02106952642621956)\n",
            "(94, 0.03959906596096448)\n",
            "(95, 0.026170703449667224)\n",
            "(96, 0.03056072005729975)\n",
            "(97, 0.02760661235350037)\n",
            "(98, 0.02655680737406723)\n",
            "(99, 0.005015464907270503)\n",
            "(100, 0.014461358221454113)\n",
            "(101, 0.03630181940050768)\n",
            "(102, 0.036846721852360376)\n",
            "(103, 0.02608438805357851)\n",
            "(104, 0.017961425528859466)\n",
            "(105, 0.021533322894685444)\n",
            "(106, 0.01796437388855908)\n",
            "(107, 0.06402947364910108)\n",
            "(108, 0.031216845745826505)\n",
            "(109, 0.020453325472844203)\n",
            "(110, 0.0)\n",
            "(111, 0.034213470378442905)\n",
            "(112, 0.014088166064339023)\n",
            "(113, 0.017598207687418068)\n",
            "(114, 0.01582662299222437)\n",
            "(115, 0.013625541983091825)\n",
            "(116, 0.02358114373494842)\n",
            "(117, 0.023539306654948217)\n",
            "(118, 0.0067272934329133645)\n",
            "(119, 0.0060187654427807475)\n",
            "(120, 0.0)\n",
            "(121, 0.019848514436581324)\n",
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            "(128, 0.0)\n",
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            "(135, 0.0)\n",
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            "(140, 0.04501741640105263)\n",
            "(141, 0.009643060297198764)\n",
            "(142, 0.011818828161418753)\n",
            "(143, 0.022313195556981205)\n",
            "(144, 0.017793976775927183)\n",
            "(145, 0.004856472425465959)\n",
            "(146, 0.0)\n",
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            "(148, 0.050282129087940684)\n",
            "(149, 0.06286044041504021)\n",
            "(150, 0.08429749159760387)\n",
            "(151, 0.06781689293926835)\n",
            "(152, 0.017550569113238833)\n",
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            "(154, 0.013905793896913713)\n",
            "(155, 0.0)\n",
            "(156, 0.0046670325303077)\n",
            "(157, 0.014207955719576636)\n",
            "(158, 0.03329732158078364)\n",
            "(159, 0.023218354014195502)\n",
            "(160, 0.01679134195046747)\n",
            "(161, 0.018927001778576886)\n",
            "(162, 0.007796920620323124)\n",
            "(163, 0.02514758801295693)\n",
            "(164, 0.013517589196037037)\n",
            "(165, 0.030119194258684326)\n",
            "(166, 0.03747851062843148)\n",
            "(167, 0.014034990200172652)\n",
            "(168, 0.048521641097873706)\n",
            "(169, 0.028191756081603857)\n",
            "(170, 0.03252281716319176)\n",
            "(171, 0.006854399048798034)\n",
            "(172, 0.02325130352471754)\n",
            "(173, 0.0)\n",
            "(174, 0.08042959693087047)\n",
            "(175, 0.01273540424661053)\n",
            "(176, 0.010915604067899093)\n",
            "(177, 0.0)\n",
            "(178, 0.00651977768177497)\n",
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            "(189, 0.01238825879676101)\n",
            "(190, 0.008226691095288556)\n",
            "(191, 0.01871348994213453)\n",
            "(192, 0.0)\n",
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            "(194, 0.0)\n",
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            "(200, 0.03919596354913121)\n",
            "(201, 0.0)\n",
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            "(205, 0.014992442308713518)\n",
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            "(212, 0.02895535809038137)\n",
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            "(226, 0.0)\n",
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          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9gZWp5vQoB75"
      },
      "source": [
        "def reco_top_similar_movies(movie_title, n=10):\n",
        "  movie_index = get_index_from_title(movies, movie_title)\n",
        "  similar_movies =  enumerate(cosine_sim[movie_index])\n",
        "  sorted_similar_movies = sorted(similar_movies, key=lambda x:x[1], reverse=True)\n",
        "\n",
        "  ret_movies = []\n",
        "  i = 0\n",
        "  for element in sorted_similar_movies:\n",
        "    title = get_title_from_index(movies, element[0])\n",
        "    ret_movies.append(title)\n",
        "    i=i+1\n",
        "    if i >= n:\n",
        "      break\n",
        "  return ret_movies"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3QKiQLllq8mC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1e098f53-3e34-4756-a576-3fac5dba1125"
      },
      "source": [
        "print(reco_top_similar_movies('Avatar', 5))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['Avatar', 'Apollo 18', 'The American', 'Obitaemyy Ostrov', 'The Matrix']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6FEkcquGxnKx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2f74fcda-575a-4659-91a2-359c77540a5f"
      },
      "source": [
        "print(reco_top_similar_movies('Minions', 5))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['Minions', 'Despicable Me 2', 'Stuart Little 2', 'Stuart Little', 'Austin Powers: The Spy Who Shagged Me']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mXeckDoSHJJO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c3147b43-2770-446b-a900-4ec03d703023"
      },
      "source": [
        "print(reco_top_similar_movies('Harry Potter and the Half-Blood Prince', 5))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['Harry Potter and the Half-Blood Prince', 'Harry Potter and the Goblet of Fire', 'Harry Potter and the Order of the Phoenix', 'Harry Potter and the Chamber of Secrets', 'Harry Potter and the Prisoner of Azkaban']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xjjZcc_OHLlk"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}