Exploratory Data Analysis of two datasets of movies.ipynb

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      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "movies = pd.read_csv('tmdb_5000_movies.csv')\n",
        "credits = pd.read_csv('tmdb_5000_credits.csv')"
      ],
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        "id": "4c3q0LUHxp5w"
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      "source": [
        "movies.head()"
      ],
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              "      budget                                             genres  \\\n",
              "0  237000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
              "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
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              "3  250000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
              "4  260000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
              "\n",
              "                                       homepage      id  \\\n",
              "0                   http://www.avatarmovie.com/   19995   \n",
              "1  http://disney.go.com/disneypictures/pirates/     285   \n",
              "2   http://www.sonypictures.com/movies/spectre/  206647   \n",
              "3            http://www.thedarkknightrises.com/   49026   \n",
              "4          http://movies.disney.com/john-carter   49529   \n",
              "\n",
              "                                            keywords original_language  \\\n",
              "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en   \n",
              "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...                en   \n",
              "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...                en   \n",
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              "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...                en   \n",
              "\n",
              "                             original_title  \\\n",
              "0                                    Avatar   \n",
              "1  Pirates of the Caribbean: At World's End   \n",
              "2                                   Spectre   \n",
              "3                     The Dark Knight Rises   \n",
              "4                               John Carter   \n",
              "\n",
              "                                            overview  popularity  \\\n",
              "0  In the 22nd century, a paraplegic Marine is di...  150.437577   \n",
              "1  Captain Barbossa, long believed to be dead, ha...  139.082615   \n",
              "2  A cryptic message from Bond’s past sends him o...  107.376788   \n",
              "3  Following the death of District Attorney Harve...  112.312950   \n",
              "4  John Carter is a war-weary, former military ca...   43.926995   \n",
              "\n",
              "                                production_companies  \\\n",
              "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...   \n",
              "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...   \n",
              "2  [{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...   \n",
              "3  [{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...   \n",
              "4        [{\"name\": \"Walt Disney Pictures\", \"id\": 2}]   \n",
              "\n",
              "                                production_countries release_date     revenue  \\\n",
              "0  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2009-12-10  2787965087   \n",
              "1  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2007-05-19   961000000   \n",
              "2  [{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"...   2015-10-26   880674609   \n",
              "3  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-07-16  1084939099   \n",
              "4  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-03-07   284139100   \n",
              "\n",
              "   runtime                                   spoken_languages    status  \\\n",
              "0    162.0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
              "1    169.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
              "2    148.0  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
              "3    165.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
              "4    132.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
              "\n",
              "                                          tagline  \\\n",
              "0                     Enter the World of Pandora.   \n",
              "1  At the end of the world, the adventure begins.   \n",
              "2                           A Plan No One Escapes   \n",
              "3                                 The Legend Ends   \n",
              "4            Lost in our world, found in another.   \n",
              "\n",
              "                                      title  vote_average  vote_count  \n",
              "0                                    Avatar           7.2       11800  \n",
              "1  Pirates of the Caribbean: At World's End           6.9        4500  \n",
              "2                                   Spectre           6.3        4466  \n",
              "3                     The Dark Knight Rises           7.6        9106  \n",
              "4                               John Carter           6.1        2124  "
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              "   movie_id                                     title  \\\n",
              "0     19995                                    Avatar   \n",
              "1       285  Pirates of the Caribbean: At World's End   \n",
              "2    206647                                   Spectre   \n",
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              "                                                cast  \\\n",
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          },
          "metadata": {},
          "execution_count": 238
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "movies_merge = movies.merge(credits,on='title')"
      ],
      "metadata": {
        "id": "ymjkYMgGyZwb"
      },
      "execution_count": 239,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "movies_merge.head()"
      ],
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          "height": 803
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        "id": "Ej33MFKLzi50",
        "outputId": "1dda62fc-6bc7-497c-f403-2e54227ffb53"
      },
      "execution_count": 240,
      "outputs": [
        {
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          "data": {
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              "      budget                                             genres  \\\n",
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              "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
              "2  245000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
              "3  250000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
              "4  260000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
              "\n",
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              "3            http://www.thedarkknightrises.com/   49026   \n",
              "4          http://movies.disney.com/john-carter   49529   \n",
              "\n",
              "                                            keywords original_language  \\\n",
              "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en   \n",
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              "                             original_title  \\\n",
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              "\n",
              "                                production_companies  ... runtime  \\\n",
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              "4        [{\"name\": \"Walt Disney Pictures\", \"id\": 2}]  ...   132.0   \n",
              "\n",
              "                                    spoken_languages    status  \\\n",
              "0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released   \n",
              "1           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
              "2  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
              "3           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
              "4           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
              "\n",
              "                                          tagline  \\\n",
              "0                     Enter the World of Pandora.   \n",
              "1  At the end of the world, the adventure begins.   \n",
              "2                           A Plan No One Escapes   \n",
              "3                                 The Legend Ends   \n",
              "4            Lost in our world, found in another.   \n",
              "\n",
              "                                      title vote_average vote_count movie_id  \\\n",
              "0                                    Avatar          7.2      11800    19995   \n",
              "1  Pirates of the Caribbean: At World's End          6.9       4500      285   \n",
              "2                                   Spectre          6.3       4466   206647   \n",
              "3                     The Dark Knight Rises          7.6       9106    49026   \n",
              "4                               John Carter          6.1       2124    49529   \n",
              "\n",
              "                                                cast  \\\n",
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              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4d99c9dc-e1b6-405f-892d-4eec0cbb6707');\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",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 240
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "movies_merge.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EIRfMt23z-Rq",
        "outputId": "7e7a071d-8df3-446f-ca1b-8be825e60240"
      },
      "execution_count": 241,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 4809 entries, 0 to 4808\n",
            "Data columns (total 23 columns):\n",
            " #   Column                Non-Null Count  Dtype  \n",
            "---  ------                --------------  -----  \n",
            " 0   budget                4809 non-null   int64  \n",
            " 1   genres                4809 non-null   object \n",
            " 2   homepage              1713 non-null   object \n",
            " 3   id                    4809 non-null   int64  \n",
            " 4   keywords              4809 non-null   object \n",
            " 5   original_language     4809 non-null   object \n",
            " 6   original_title        4809 non-null   object \n",
            " 7   overview              4806 non-null   object \n",
            " 8   popularity            4809 non-null   float64\n",
            " 9   production_companies  4809 non-null   object \n",
            " 10  production_countries  4809 non-null   object \n",
            " 11  release_date          4808 non-null   object \n",
            " 12  revenue               4809 non-null   int64  \n",
            " 13  runtime               4807 non-null   float64\n",
            " 14  spoken_languages      4809 non-null   object \n",
            " 15  status                4809 non-null   object \n",
            " 16  tagline               3965 non-null   object \n",
            " 17  title                 4809 non-null   object \n",
            " 18  vote_average          4809 non-null   float64\n",
            " 19  vote_count            4809 non-null   int64  \n",
            " 20  movie_id              4809 non-null   int64  \n",
            " 21  cast                  4809 non-null   object \n",
            " 22  crew                  4809 non-null   object \n",
            "dtypes: float64(3), int64(5), object(15)\n",
            "memory usage: 901.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In the above column we get to know that coulumn is essential for the model training and which is un essential so drop the rest of useless columns"
      ],
      "metadata": {
        "id": "JDCPjXme05iP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge = movies_merge[['id','title','overview','genres','keywords','cast','crew']]"
      ],
      "metadata": {
        "id": "3i4Tl9F51Mx9"
      },
      "execution_count": 242,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "ySv90qkl2Hph",
        "outputId": "6d275094-ecdb-442c-98ce-a276c5cb0c81"
      },
      "execution_count": 243,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
              "0  In the 22nd century, a paraplegic Marine is di...   \n",
              "1  Captain Barbossa, long believed to be dead, ha...   \n",
              "2  A cryptic message from Bond’s past sends him o...   \n",
              "3  Following the death of District Attorney Harve...   \n",
              "4  John Carter is a war-weary, former military ca...   \n",
              "\n",
              "                                              genres  \\\n",
              "0  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
              "1  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
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              "3  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
              "4  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
              "\n",
              "                                            keywords  \\\n",
              "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...   \n",
              "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...   \n",
              "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...   \n",
              "3  [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...   \n",
              "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   \n",
              "\n",
              "                                                cast  \\\n",
              "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...   \n",
              "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
              "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...   \n",
              "3  [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...   \n",
              "4  [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...   \n",
              "\n",
              "                                                crew  \n",
              "0  [{\"credit_id\": \"52fe48009251416c750aca23\", \"de...  \n",
              "1  [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...  \n",
              "2  [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...  \n",
              "3  [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...  \n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 243
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets find the null values if there is any raw or null data lets drop them from the data."
      ],
      "metadata": {
        "id": "5Edw_BacIs5j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RaZp_Ed_I4il",
        "outputId": "4574d7b2-918b-47a7-8496-abe2623f7998"
      },
      "execution_count": 244,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id          0\n",
              "title       0\n",
              "overview    3\n",
              "genres      0\n",
              "keywords    0\n",
              "cast        0\n",
              "crew        0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 244
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "So the overview section have 3 null values lets drop them"
      ],
      "metadata": {
        "id": "FyJ5XqrVLHwW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge.dropna(inplace=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-wnSxOvNLPSw",
        "outputId": "821b8613-8ea7-4ee2-e2c8-a3deba135244"
      },
      "execution_count": 245,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-245-351882be4243>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_movies_merge.dropna(inplace=True)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TgN1-P0RLnWV",
        "outputId": "7d774feb-bc67-4cbc-94bc-0c8ee72ed3d8"
      },
      "execution_count": 246,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id          0\n",
              "title       0\n",
              "overview    0\n",
              "genres      0\n",
              "keywords    0\n",
              "cast        0\n",
              "crew        0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 246
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "So there is no raw/null values with us in above cell you can see."
      ],
      "metadata": {
        "id": "TmLKNYfeLshc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets weather there is duplicated data or not lets check "
      ],
      "metadata": {
        "id": "0QsntUrtL7uq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yydskIShMB9F",
        "outputId": "4f87ad92-5fd0-4581-8d60-2f4ccb6b7173"
      },
      "execution_count": 247,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 247
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets do some preprocessing on the different colums to get some insights from the data that is suitable for the data modeling"
      ],
      "metadata": {
        "id": "tlsMAk3XM80m"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge.iloc[0].genres"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "kJGhuSHtNM1E",
        "outputId": "dee82ae2-6bd6-4561-ed4d-76f88d3c34ab"
      },
      "execution_count": 248,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"name\": \"Fantasy\"}, {\"id\": 878, \"name\": \"Science Fiction\"}]'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 248
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "So from the above list we just want to get the eact title weather the movies is action adventures or fantacy, so lets perform some operations."
      ],
      "metadata": {
        "id": "-Bc-YXsGNZHW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import ast\n",
        "def convert(obj):\n",
        "    l = []\n",
        "    for i in ast.literal_eval(obj):\n",
        "        l.append(i['name'])\n",
        "    return l\n"
      ],
      "metadata": {
        "id": "w6g5vF1-NweG"
      },
      "execution_count": 249,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_movies_merge['genres'] = updated_movies_merge['genres'].apply(convert)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MAUEmYdvO9WF",
        "outputId": "2348c453-e7fd-4977-b8d3-6306cb3765d4"
      },
      "execution_count": 250,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-250-441836fba695>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_movies_merge['genres'] = updated_movies_merge['genres'].apply(convert)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_genres = updated_movies_merge"
      ],
      "metadata": {
        "id": "0_SzfuMIPf0a"
      },
      "execution_count": 251,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_genres.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "a62UN75TPpqK",
        "outputId": "09f94a5e-db68-4c62-afba-84139341e82a"
      },
      "execution_count": 252,
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        {
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            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
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              "1  Captain Barbossa, long believed to be dead, ha...   \n",
              "2  A cryptic message from Bond’s past sends him o...   \n",
              "3  Following the death of District Attorney Harve...   \n",
              "4  John Carter is a war-weary, former military ca...   \n",
              "\n",
              "                                          genres  \\\n",
              "0  [Action, Adventure, Fantasy, Science Fiction]   \n",
              "1                   [Adventure, Fantasy, Action]   \n",
              "2                     [Action, Adventure, Crime]   \n",
              "3               [Action, Crime, Drama, Thriller]   \n",
              "4           [Action, Adventure, Science Fiction]   \n",
              "\n",
              "                                            keywords  \\\n",
              "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...   \n",
              "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...   \n",
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              "3  [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...   \n",
              "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...   \n",
              "\n",
              "                                                cast  \\\n",
              "0  [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...   \n",
              "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
              "2  [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...   \n",
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              "4  [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...   \n",
              "\n",
              "                                                crew  \n",
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              "      <td>285</td>\n",
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              "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
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              "      <th>3</th>\n",
              "      <td>49026</td>\n",
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              "      <td>[Action, Crime, Drama, Thriller]</td>\n",
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              "      <th>4</th>\n",
              "      <td>49529</td>\n",
              "      <td>John Carter</td>\n",
              "      <td>John Carter is a war-weary, former military ca...</td>\n",
              "      <td>[Action, Adventure, Science Fiction]</td>\n",
              "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
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              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a51773c9-1e73-4df1-b56f-431d51d111c0')\"\n",
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              "  </svg>\n",
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              "      \n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a51773c9-1e73-4df1-b56f-431d51d111c0 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-a51773c9-1e73-4df1-b56f-431d51d111c0');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 252
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets update the keywords so that we can get some insights of the data"
      ],
      "metadata": {
        "id": "xtW_-ogYT8N9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_genres['keywords'] = updated_genres['keywords'].apply(convert)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5pUUOkcuUFvQ",
        "outputId": "45fdb1b5-8b6e-4d6f-9b18-b5a6990b3f3e"
      },
      "execution_count": 253,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-253-c5632bf9262d>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_genres['keywords'] = updated_genres['keywords'].apply(convert)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_keywords = updated_genres"
      ],
      "metadata": {
        "id": "HzCh3E_6UWA2"
      },
      "execution_count": 254,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_keywords.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "KiHNpGMXUeOF",
        "outputId": "a74f3f79-1071-489a-e007-3a75418559ef"
      },
      "execution_count": 255,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
              "0  In the 22nd century, a paraplegic Marine is di...   \n",
              "1  Captain Barbossa, long believed to be dead, ha...   \n",
              "2  A cryptic message from Bond’s past sends him o...   \n",
              "3  Following the death of District Attorney Harve...   \n",
              "4  John Carter is a war-weary, former military ca...   \n",
              "\n",
              "                                          genres  \\\n",
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              "1                   [Adventure, Fantasy, Action]   \n",
              "2                     [Action, Adventure, Crime]   \n",
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              "4           [Action, Adventure, Science Fiction]   \n",
              "\n",
              "                                            keywords  \\\n",
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              "1  [ocean, drug abuse, exotic island, east india ...   \n",
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              "\n",
              "                                                cast  \\\n",
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              "1  [{\"cast_id\": 4, \"character\": \"Captain Jack Spa...   \n",
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              "4  [{\"cast_id\": 5, \"character\": \"John Carter\", \"c...   \n",
              "\n",
              "                                                crew  \n",
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              "      background-color: #434B5C;\n",
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              "\n",
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              "\n",
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              "          const element = document.querySelector('#df-5440d201-eb36-448b-9198-c58e26b9a1c9');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 255
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets work on the cast of the movies data. we only want to get the first three lists of the cast to get the info of top three actors of the movies"
      ],
      "metadata": {
        "id": "r1fFksKhbGvC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def convert3(obj):\n",
        "    l = []\n",
        "    counter = 0\n",
        "    for i in ast.literal_eval(obj):\n",
        "        if counter != 3:\n",
        "           l.append(i['name'])\n",
        "           counter+=1\n",
        "        else:\n",
        "            break   \n",
        "    return l"
      ],
      "metadata": {
        "id": "sYK7VKd2bgGU"
      },
      "execution_count": 256,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_keywords['cast'] = updated_keywords['cast'].apply(convert3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "67cCBtyPdALs",
        "outputId": "40ae0858-8574-47bf-a8ea-dcc27c7082c0"
      },
      "execution_count": 257,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-257-db0d2303272d>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_keywords['cast'] = updated_keywords['cast'].apply(convert3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_cast = updated_keywords"
      ],
      "metadata": {
        "id": "iu_q9pb3daKL"
      },
      "execution_count": 258,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_cast.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "N6_ufb6Rdgg6",
        "outputId": "cc28a2a9-e643-48b6-9d25-ee9d934f80a4"
      },
      "execution_count": 259,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
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              "                                          genres  \\\n",
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              "                                            keywords  \\\n",
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              "4  [based on novel, mars, medallion, space travel...   \n",
              "\n",
              "                                               cast  \\\n",
              "0  [Sam Worthington, Zoe Saldana, Sigourney Weaver]   \n",
              "1     [Johnny Depp, Orlando Bloom, Keira Knightley]   \n",
              "2      [Daniel Craig, Christoph Waltz, Léa Seydoux]   \n",
              "3      [Christian Bale, Michael Caine, Gary Oldman]   \n",
              "4    [Taylor Kitsch, Lynn Collins, Samantha Morton]   \n",
              "\n",
              "                                                crew  \n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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            ]
          },
          "metadata": {},
          "execution_count": 259
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now we have to clean the data of the crew column in which we get the insights of the job discription which is director."
      ],
      "metadata": {
        "id": "-F2-n4Jq4qBe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def find_director(obj):\n",
        "    l = []\n",
        "    for i in ast.literal_eval(obj):\n",
        "        if i['job'] == 'Director':\n",
        "           l.append(i['name'])\n",
        "           break\n",
        "    return l\n"
      ],
      "metadata": {
        "id": "5LMSrK8g443k"
      },
      "execution_count": 260,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_cast['crew'] = updated_cast['crew'].apply(find_director)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Iqajc9IZ5lwU",
        "outputId": "75fa5ba8-936e-4405-aea4-b722c6cba443"
      },
      "execution_count": 261,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-261-0b5a0990a6e9>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_cast['crew'] = updated_cast['crew'].apply(find_director)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_crew = updated_cast"
      ],
      "metadata": {
        "id": "9c-LghpA78RO"
      },
      "execution_count": 262,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_crew.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "UA4lxRAP8EG6",
        "outputId": "e5c32f07-47e2-4bed-a35f-804409e3d296"
      },
      "execution_count": 263,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
              "0  In the 22nd century, a paraplegic Marine is di...   \n",
              "1  Captain Barbossa, long believed to be dead, ha...   \n",
              "2  A cryptic message from Bond’s past sends him o...   \n",
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              "                                          genres  \\\n",
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              "1                   [Adventure, Fantasy, Action]   \n",
              "2                     [Action, Adventure, Crime]   \n",
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              "                                            keywords  \\\n",
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              "                                               cast                 crew  \n",
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              "      <td>[Sam Mendes]</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>49026</td>\n",
              "      <td>The Dark Knight Rises</td>\n",
              "      <td>Following the death of District Attorney Harve...</td>\n",
              "      <td>[Action, Crime, Drama, Thriller]</td>\n",
              "      <td>[dc comics, crime fighter, terrorist, secret i...</td>\n",
              "      <td>[Christian Bale, Michael Caine, Gary Oldman]</td>\n",
              "      <td>[Christopher Nolan]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>49529</td>\n",
              "      <td>John Carter</td>\n",
              "      <td>John Carter is a war-weary, former military ca...</td>\n",
              "      <td>[Action, Adventure, Science Fiction]</td>\n",
              "      <td>[based on novel, mars, medallion, space travel...</td>\n",
              "      <td>[Taylor Kitsch, Lynn Collins, Samantha Morton]</td>\n",
              "      <td>[Andrew Stanton]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-92bfd144-aff0-4104-b5e6-32b48409d2e5')\"\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-92bfd144-aff0-4104-b5e6-32b48409d2e5 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-92bfd144-aff0-4104-b5e6-32b48409d2e5');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 263
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets work on the overview so the we can get the overview of each movie in a separate list"
      ],
      "metadata": {
        "id": "mgtrhucW9YBf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_crew['overview'] = updated_crew['overview'].apply(lambda x:x.split())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4Dzpq-9L87UQ",
        "outputId": "c2245cfa-8097-479c-e58c-4fd9025bb151"
      },
      "execution_count": 264,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-264-bd066672107f>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_crew['overview'] = updated_crew['overview'].apply(lambda x:x.split())\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_overview = updated_crew"
      ],
      "metadata": {
        "id": "DDQz1OS19WMa"
      },
      "execution_count": 265,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_overview.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "-tDfNPoL9reH",
        "outputId": "5184198b-f5e1-4ad6-bde6-7d05eddca043"
      },
      "execution_count": 266,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
              "0  [In, the, 22nd, century,, a, paraplegic, Marin...   \n",
              "1  [Captain, Barbossa,, long, believed, to, be, d...   \n",
              "2  [A, cryptic, message, from, Bond’s, past, send...   \n",
              "3  [Following, the, death, of, District, Attorney...   \n",
              "4  [John, Carter, is, a, war-weary,, former, mili...   \n",
              "\n",
              "                                          genres  \\\n",
              "0  [Action, Adventure, Fantasy, Science Fiction]   \n",
              "1                   [Adventure, Fantasy, Action]   \n",
              "2                     [Action, Adventure, Crime]   \n",
              "3               [Action, Crime, Drama, Thriller]   \n",
              "4           [Action, Adventure, Science Fiction]   \n",
              "\n",
              "                                            keywords  \\\n",
              "0  [culture clash, future, space war, space colon...   \n",
              "1  [ocean, drug abuse, exotic island, east india ...   \n",
              "2  [spy, based on novel, secret agent, sequel, mi...   \n",
              "3  [dc comics, crime fighter, terrorist, secret i...   \n",
              "4  [based on novel, mars, medallion, space travel...   \n",
              "\n",
              "                                               cast                 crew  \n",
              "0  [Sam Worthington, Zoe Saldana, Sigourney Weaver]      [James Cameron]  \n",
              "1     [Johnny Depp, Orlando Bloom, Keira Knightley]     [Gore Verbinski]  \n",
              "2      [Daniel Craig, Christoph Waltz, Léa Seydoux]         [Sam Mendes]  \n",
              "3      [Christian Bale, Michael Caine, Gary Oldman]  [Christopher Nolan]  \n",
              "4    [Taylor Kitsch, Lynn Collins, Samantha Morton]     [Andrew Stanton]  "
            ],
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              "      <td>285</td>\n",
              "      <td>Pirates of the Caribbean: At World's End</td>\n",
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              "      <td>[Adventure, Fantasy, Action]</td>\n",
              "      <td>[ocean, drug abuse, exotic island, east india ...</td>\n",
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              "      <th>2</th>\n",
              "      <td>206647</td>\n",
              "      <td>Spectre</td>\n",
              "      <td>[A, cryptic, message, from, Bond’s, past, send...</td>\n",
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              "      <td>[spy, based on novel, secret agent, sequel, mi...</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>49026</td>\n",
              "      <td>The Dark Knight Rises</td>\n",
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              "      <td>[Action, Crime, Drama, Thriller]</td>\n",
              "      <td>[dc comics, crime fighter, terrorist, secret i...</td>\n",
              "      <td>[Christian Bale, Michael Caine, Gary Oldman]</td>\n",
              "      <td>[Christopher Nolan]</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>49529</td>\n",
              "      <td>John Carter</td>\n",
              "      <td>[John, Carter, is, a, war-weary,, former, mili...</td>\n",
              "      <td>[Action, Adventure, Science Fiction]</td>\n",
              "      <td>[based on novel, mars, medallion, space travel...</td>\n",
              "      <td>[Taylor Kitsch, Lynn Collins, Samantha Morton]</td>\n",
              "      <td>[Andrew Stanton]</td>\n",
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              "\n",
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              "\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",
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              "\n",
              "      <script>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d9daab11-abba-4a41-908d-3e0f1bbbc3cd');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 266
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets concatinate the names of the few columns because our model gets inturrupted by the two name which beginning is same but its ending is diferent so by concatenating the model will results some actionable insights "
      ],
      "metadata": {
        "id": "x6K1yIEk-T1O"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_crew['genres'] = updated_crew['genres'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
        "updated_crew['keywords'] = updated_crew['keywords'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
        "updated_crew['cast'] = updated_crew['cast'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
        "updated_crew['crew'] = updated_crew['crew'].apply(lambda x:[i.replace(\" \",\"\") for i in x])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9WG8ZWul-wMK",
        "outputId": "0d2fd2bc-9a78-437a-a229-366a7158d238"
      },
      "execution_count": 267,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-267-60bd155cc0b0>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_crew['genres'] = updated_crew['genres'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
            "<ipython-input-267-60bd155cc0b0>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_crew['keywords'] = updated_crew['keywords'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
            "<ipython-input-267-60bd155cc0b0>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_crew['cast'] = updated_crew['cast'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
            "<ipython-input-267-60bd155cc0b0>:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_crew['crew'] = updated_crew['crew'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "updated_concatenation = updated_crew"
      ],
      "metadata": {
        "id": "b7cvrZH9AScn"
      },
      "execution_count": 268,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "updated_concatenation.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "id": "w3trY7avAeDA",
        "outputId": "6a9cf13c-a086-4cc4-9e01-5bf1792f86ca"
      },
      "execution_count": 269,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                            overview  \\\n",
              "0  [In, the, 22nd, century,, a, paraplegic, Marin...   \n",
              "1  [Captain, Barbossa,, long, believed, to, be, d...   \n",
              "2  [A, cryptic, message, from, Bond’s, past, send...   \n",
              "3  [Following, the, death, of, District, Attorney...   \n",
              "4  [John, Carter, is, a, war-weary,, former, mili...   \n",
              "\n",
              "                                         genres  \\\n",
              "0  [Action, Adventure, Fantasy, ScienceFiction]   \n",
              "1                  [Adventure, Fantasy, Action]   \n",
              "2                    [Action, Adventure, Crime]   \n",
              "3              [Action, Crime, Drama, Thriller]   \n",
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              "                                            keywords  \\\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 269
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "lets make a new column of tags of concatenate the whole columns into the one column which is known as tags. for furthur modeling of data"
      ],
      "metadata": {
        "id": "RhreYhkvBNFt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "updated_concatenation['tags'] = updated_concatenation['overview'] + updated_concatenation['genres'] + updated_concatenation['keywords'] + updated_concatenation['cast'] + updated_concatenation['crew']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BAQzRDMfBf_O",
        "outputId": "deb0360d-33e1-4a3b-e10b-907bd6c72fee"
      },
      "execution_count": 270,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-270-a6534d9d0769>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  updated_concatenation['tags'] = updated_concatenation['overview'] + updated_concatenation['genres'] + updated_concatenation['keywords'] + updated_concatenation['cast'] + updated_concatenation['crew']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tags_column = updated_concatenation"
      ],
      "metadata": {
        "id": "cmTS13gYCV1m"
      },
      "execution_count": 271,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tags_column.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "IZeJRjCTCcTx",
        "outputId": "bca8b102-49ee-452b-c367-6e00caed7803"
      },
      "execution_count": 272,
      "outputs": [
        {
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              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "metadata": {},
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      "cell_type": "code",
      "source": [
        "new_df = tags_column[['id', 'title', 'tags']]"
      ],
      "metadata": {
        "id": "4eQKhdgWE5If"
      },
      "execution_count": 273,
      "outputs": []
    },
    {
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        "new_df"
      ],
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              "          id                                     title  \\\n",
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              "                                                     [key], {});\n",
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              "\n",
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      "source": [
        "new_df['tags'] = new_df['tags'].apply(lambda x:' '.join(x))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WyTMurQcFkSq",
        "outputId": "e3be0be7-bd1e-4b9b-cce8-c5c8ab89f441"
      },
      "execution_count": 275,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-275-68a616cd60db>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  new_df['tags'] = new_df['tags'].apply(lambda x:' '.join(x))\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_df.head()"
      ],
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        "colab": {
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          "height": 206
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        "id": "ZucSsdKIF7at",
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      "execution_count": 276,
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        {
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              "       id                                     title  \\\n",
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              "                                                tags  \n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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      "cell_type": "code",
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        "new_df['tags'][0]"
      ],
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        },
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        "outputId": "722814d9-1232-4bd4-b2b7-0e2d0959254f"
      },
      "execution_count": 277,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization. Action Adventure Fantasy ScienceFiction cultureclash future spacewar spacecolony society spacetravel futuristic romance space alien tribe alienplanet cgi marine soldier battle loveaffair antiwar powerrelations mindandsoul 3d SamWorthington ZoeSaldana SigourneyWeaver JamesCameron'"
            ],
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      },
      "execution_count": 277,
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      "cell_type": "code",
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        "new_df['tags'] = new_df['tags'].apply(lambda x:x.lower())"
      ],
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          "base_uri": "https://localhost:8080/"
        },
        "id": "BowMzvUXG7tK",
        "outputId": "a48734ee-a2d4-462a-e25f-666b7432eee5"
      },
      "execution_count": 278,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-278-8b60b591a07f>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  new_df['tags'] = new_df['tags'].apply(lambda x:x.lower())\n"
          ]
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "os7jnwWAHTFb",
        "outputId": "7b5f0cc0-165c-4381-bbbb-51ed73c62e4c"
      },
      "execution_count": 279,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       id                                     title  \\\n",
              "0   19995                                    Avatar   \n",
              "1     285  Pirates of the Caribbean: At World's End   \n",
              "2  206647                                   Spectre   \n",
              "3   49026                     The Dark Knight Rises   \n",
              "4   49529                               John Carter   \n",
              "\n",
              "                                                tags  \n",
              "0  in the 22nd century, a paraplegic marine is di...  \n",
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              "                                                     [key], {});\n",
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            ]
          },
          "metadata": {},
          "execution_count": 279
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import nltk"
      ],
      "metadata": {
        "id": "55co8Xaq-q1I"
      },
      "execution_count": 280,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from nltk.stem.porter import PorterStemmer\n",
        "ps = PorterStemmer()"
      ],
      "metadata": {
        "id": "JlbgUzet-w6E"
      },
      "execution_count": 281,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def stem(text):\n",
        "    y = []\n",
        "\n",
        "    for i in text.split():\n",
        "        y.append(ps.stem(i))\n",
        "    return ' '.join(y)    "
      ],
      "metadata": {
        "id": "VLexUHZG_No3"
      },
      "execution_count": 282,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "new_df['tags'] = new_df['tags'].apply(stem)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dVLX-rp9A6Hs",
        "outputId": "d74db75b-1d42-4000-8736-96672fab4816"
      },
      "execution_count": 283,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-283-be18a4346d89>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  new_df['tags'] = new_df['tags'].apply(stem)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_df['tags'][0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "id": "oUjVdzqC5FN-",
        "outputId": "5ffd57df-2981-49e7-c315-9e075f950896"
      },
      "execution_count": 284,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'in the 22nd century, a parapleg marin is dispatch to the moon pandora on a uniqu mission, but becom torn between follow order and protect an alien civilization. action adventur fantasi sciencefict cultureclash futur spacewar spacecoloni societi spacetravel futurist romanc space alien tribe alienplanet cgi marin soldier battl loveaffair antiwar powerrel mindandsoul 3d samworthington zoesaldana sigourneyweav jamescameron'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 284
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_df['tags'][1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "id": "YNtjajpc5Kp7",
        "outputId": "2b25a29a-5a31-4543-a69c-557885cbe469"
      },
      "execution_count": 285,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"captain barbossa, long believ to be dead, ha come back to life and is head to the edg of the earth with will turner and elizabeth swann. but noth is quit as it seems. adventur fantasi action ocean drugabus exoticisland eastindiatradingcompani loveofone'slif traitor shipwreck strongwoman ship allianc calypso afterlif fighter pirat swashbuckl aftercreditssting johnnydepp orlandobloom keiraknightley goreverbinski\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 285
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "cv = CountVectorizer(max_features = 5000, stop_words = 'english')"
      ],
      "metadata": {
        "id": "Jp_LGI0o7AVp"
      },
      "execution_count": 286,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "vector = cv.fit_transform(new_df['tags']).toarray()"
      ],
      "metadata": {
        "id": "fzwiPjKi8C55"
      },
      "execution_count": 287,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "vector"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RG_674IS8pER",
        "outputId": "2f4f2160-4cb0-4d3a-b1be-22db350b2255"
      },
      "execution_count": 288,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0, 0, 0, ..., 0, 0, 0],\n",
              "       [0, 0, 0, ..., 0, 0, 0],\n",
              "       [0, 0, 0, ..., 0, 0, 0],\n",
              "       ...,\n",
              "       [0, 0, 0, ..., 0, 0, 0],\n",
              "       [0, 0, 0, ..., 0, 0, 0],\n",
              "       [0, 0, 0, ..., 0, 0, 0]])"
            ]
          },
          "metadata": {},
          "execution_count": 288
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vector[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bxEkqPqkBtp0",
        "outputId": "06e6ae0f-871e-4e1c-a9e7-9977ac124542"
      },
      "execution_count": 289,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 0, ..., 0, 0, 0])"
            ]
          },
          "metadata": {},
          "execution_count": 289
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ps.stem('loving')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "SsT7VWRxAstn",
        "outputId": "87f5bc47-69a1-43c3-ad66-93868f3646c6"
      },
      "execution_count": 290,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'love'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 290
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics.pairwise import cosine_similarity"
      ],
      "metadata": {
        "id": "GtVq55DqELah"
      },
      "execution_count": 291,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "similarity = cosine_similarity(vector)"
      ],
      "metadata": {
        "id": "K51JVacUE1_n"
      },
      "execution_count": 292,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sorted(list(enumerate(similarity[0])), reverse=True, key = lambda x:x[1])[1:6]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hD6fppqVSVXy",
        "outputId": "ac1aceb7-6b6a-4004-d8b5-a13cd4735470"
      },
      "execution_count": 293,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(1216, 0.28676966733820225),\n",
              " (2409, 0.26901379342448517),\n",
              " (3730, 0.2605130246476754),\n",
              " (507, 0.255608593705383),\n",
              " (539, 0.25038669783359574)]"
            ]
          },
          "metadata": {},
          "execution_count": 293
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "similarity\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DDxLeHwRGZ7N",
        "outputId": "62bda136-8243-4ddd-fac9-baa5bf7e591f"
      },
      "execution_count": 294,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.        , 0.08346223, 0.0860309 , ..., 0.04499213, 0.        ,\n",
              "        0.        ],\n",
              "       [0.08346223, 1.        , 0.06063391, ..., 0.02378257, 0.        ,\n",
              "        0.02615329],\n",
              "       [0.0860309 , 0.06063391, 1.        , ..., 0.02451452, 0.        ,\n",
              "        0.        ],\n",
              "       ...,\n",
              "       [0.04499213, 0.02378257, 0.02451452, ..., 1.        , 0.03962144,\n",
              "        0.04229549],\n",
              "       [0.        , 0.        , 0.        , ..., 0.03962144, 1.        ,\n",
              "        0.08714204],\n",
              "       [0.        , 0.02615329, 0.        , ..., 0.04229549, 0.08714204,\n",
              "        1.        ]])"
            ]
          },
          "metadata": {},
          "execution_count": 294
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def recommend(movie):\n",
        "    movie_index = new_df[new_df['title'] == movie].index[0]\n",
        "    distances = similarity[movie_index]\n",
        "    movies_list = sorted(list(enumerate(distances)), reverse=True, key = lambda x:x[1])[1:6]\n",
        "\n",
        "    for i in movies_list:\n",
        "        print(new_df.iloc[i[0]].title)\n",
        "        "
      ],
      "metadata": {
        "id": "6LrWU4rkGcHW"
      },
      "execution_count": 301,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "recommend('Superman')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JkIVsqjSU8mc",
        "outputId": "76c7ddfe-99ee-48a3-9ca2-269abe38430b"
      },
      "execution_count": 308,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Superman Returns\n",
            "Superman II\n",
            "Iron Man 2\n",
            "Superman III\n",
            "Superman IV: The Quest for Peace\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new_df['title'].values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "te5Xh1h95q5Z",
        "outputId": "08b82ad1-3e47-4d61-a4d0-48698a41c50f"
      },
      "execution_count": 303,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Avatar', \"Pirates of the Caribbean: At World's End\", 'Spectre',\n",
              "       ..., 'Signed, Sealed, Delivered', 'Shanghai Calling',\n",
              "       'My Date with Drew'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 303
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pickle"
      ],
      "metadata": {
        "id": "rhr7pKp780hs"
      },
      "execution_count": 304,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pickle.dump(new_df.to_dict(),open('movie_dict.pkl','wb'))"
      ],
      "metadata": {
        "id": "3hwyrH3t6pr8"
      },
      "execution_count": 305,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pickle.dump(similarity,open('similarity.pkl','wb'))"
      ],
      "metadata": {
        "id": "3L8ElOWS2pxo"
      },
      "execution_count": 306,
      "outputs": []
    }
  ]
}