disney.ipynb

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      "metadata": {
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      "outputs": [],
      "source": [
        "#@title Load Project"
      ]
    },
    {
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      "metadata": {
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      "source": [
        "#@title Load data\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from mlxtend.preprocessing import TransactionEncoder\n",
        "import re\n",
        "from sklearn.preprocessing import MultiLabelBinarizer \n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.multiclass import OneVsRestClassifier\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.naive_bayes import BernoulliNB\n",
        "from tqdm import tqdm\n",
        "import pickle\n",
        "\n",
        "import csv\n",
        "path = '/content/movies_metadata.csv'\n",
        "dataframe = pd.read_csv(path,delimiter = ',')"
      ]
    },
    {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>genres</th>\n",
              "      <th>original_title</th>\n",
              "      <th>overview</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[{'id': 16, 'name': 'Animation'}, {'id': 35, '...</td>\n",
              "      <td>Toy Story</td>\n",
              "      <td>Led by Woody, Andy's toys live happily in his ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[{'id': 12, 'name': 'Adventure'}, {'id': 14, '...</td>\n",
              "      <td>Jumanji</td>\n",
              "      <td>When siblings Judy and Peter discover an encha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[{'id': 10749, 'name': 'Romance'}, {'id': 35, ...</td>\n",
              "      <td>Grumpier Old Men</td>\n",
              "      <td>A family wedding reignites the ancient feud be...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...</td>\n",
              "      <td>Waiting to Exhale</td>\n",
              "      <td>Cheated on, mistreated and stepped on, the wom...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[{'id': 35, 'name': 'Comedy'}]</td>\n",
              "      <td>Father of the Bride Part II</td>\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            "text/plain": [
              "                                              genres  ...                                           overview\n",
              "0  [{'id': 16, 'name': 'Animation'}, {'id': 35, '...  ...  Led by Woody, Andy's toys live happily in his ...\n",
              "1  [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...  ...  When siblings Judy and Peter discover an encha...\n",
              "2  [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...  ...  A family wedding reignites the ancient feud be...\n",
              "3  [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...  ...  Cheated on, mistreated and stepped on, the wom...\n",
              "4                     [{'id': 35, 'name': 'Comedy'}]  ...  Just when George Banks has recovered from his ...\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "execution_count": 4,
          "metadata": {},
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      ],
      "source": [
        "#@title Sample data\n",
        "\n",
        "dataframe.head()"
      ]
    },
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          "text": [
            "100%|██████████| 45466/45466 [00:22<00:00, 2065.61it/s]\n",
            "100%|██████████| 45466/45466 [00:29<00:00, 1545.81it/s]\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:17: 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"
          ]
        }
      ],
      "source": [
        "#@title Text preprocessing\n",
        "\n",
        "dataframe['genres']=dataframe['genres'].apply(str)\n",
        "\n",
        "for i in tqdm(range(len(dataframe))):\n",
        "  dataframe['genres'][i] = re.sub(\"[^a-zA-Z]\",\" \",dataframe['genres'][i])\n",
        "\n",
        "for i in tqdm(range(len(dataframe))):\n",
        "  dataframe['genres'][i] = dataframe['genres'][i].replace(\"id\",\"\")\n",
        "  dataframe['genres'][i] = dataframe['genres'][i].replace(\"name\",\"\")\n",
        "\n",
        "\n",
        "genre =  [a.split() for a in dataframe['genres']]\n",
        "\n",
        "data = dataframe[['overview']]\n",
        "\n",
        "data['genre'] = genre"
      ]
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      "source": [
        "dataframe['genres']=dataframe['genres'].apply(str)"
      ]
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          "text": [
            "100%|██████████| 45466/45466 [00:15<00:00, 2996.55it/s]\n"
          ]
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      "source": [
        "for i in tqdm(range(len(dataframe))):\n",
        "  dataframe['genres'][i] = re.sub(\"[^a-zA-Z]\",\" \",dataframe['genres'][i])"
      ]
    },
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      "cell_type": "code",
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          "text": [
            "100%|██████████| 45466/45466 [00:30<00:00, 1509.22it/s]\n"
          ]
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      "source": [
        "for i in tqdm(range(len(dataframe))):\n",
        "  dataframe['genres'][i] = dataframe['genres'][i].replace(\"id\",\"\")\n",
        "  dataframe['genres'][i] = dataframe['genres'][i].replace(\"name\",\"\")\n",
        "  \n",
        "  "
      ]
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              "0                       Animation                  Come...\n",
              "1                       Adventure                  Fant...\n",
              "2                          Romance                  Com...\n",
              "3                       Comedy                  Drama  ...\n",
              "4                                                Comedy   \n",
              "                               ...                        \n",
              "45461                   Drama                     Famil...\n",
              "45462                                             Drama   \n",
              "45463                   Action                  Drama  ...\n",
              "45464                                                     \n",
              "45465                                                     \n",
              "Name: genres, Length: 45466, dtype: object"
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 45466 entries, 0 to 45465\n",
            "Data columns (total 3 columns):\n",
            " #   Column          Non-Null Count  Dtype \n",
            "---  ------          --------------  ----- \n",
            " 0   genres          45466 non-null  object\n",
            " 1   original_title  45466 non-null  object\n",
            " 2   overview        44512 non-null  object\n",
            "dtypes: object(3)\n",
            "memory usage: 1.0+ MB\n"
          ]
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      ],
      "source": [
        "dataframe.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-J3GUN5CPKdJ"
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      "source": [
        "genre =  [a.split() for a in dataframe['genres']]"
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        "data = dataframe[['overview']]"
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f258882c-cbf8-44aa-9914-18dcbe335a0a 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-f258882c-cbf8-44aa-9914-18dcbe335a0a');\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",
              "  "
            ],
            "text/plain": [
              "                                            overview                         genre\n",
              "0  Led by Woody, Andy's toys live happily in his ...   [Animation, Comedy, Family]\n",
              "1  When siblings Judy and Peter discover an encha...  [Adventure, Fantasy, Family]\n",
              "2  A family wedding reignites the ancient feud be...             [Romance, Comedy]\n",
              "3  Cheated on, mistreated and stepped on, the wom...      [Comedy, Drama, Romance]\n",
              "4  Just when George Banks has recovered from his ...                      [Comedy]"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data.dropna(inplace=True)\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KRNpaKp8-6Jr"
      },
      "outputs": [],
      "source": [
        "multilabel_binarizer = MultiLabelBinarizer()\n",
        "multilabel_binarizer.fit(data['genre'])\n",
        "y = multilabel_binarizer.transform(data['genre'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pEpwTGfV_SR0"
      },
      "outputs": [],
      "source": [
        "xtrain, xval, ytrain, yval = train_test_split(data['overview'], y, test_size=0.2, random_state=9)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6G6Z4SPL_RvK"
      },
      "outputs": [],
      "source": [
        "tfidf_vectorizer = TfidfVectorizer(max_df=0.8, max_features=10000)\n",
        "xtrain_tfidf = tfidf_vectorizer.fit_transform(xtrain)\n",
        "xval_tfidf = tfidf_vectorizer.transform(xval)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fY8HmGv5_jcS",
        "outputId": "7ff8f94d-9a04-4781-8681-ed41ba9b3489"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 5 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 6 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 12 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 16 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 20 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 24 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 28 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 30 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 31 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 32 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 37 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 39 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 40 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 42 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/multiclass.py:80: UserWarning: Label not 43 is present in all training examples.\n",
            "  \"Label %s is present in all training examples.\" % str(classes[c])\n"
          ]
        }
      ],
      "source": [
        "\n",
        "clf = OneVsRestClassifier(BernoulliNB())\n",
        "clf.fit(xtrain_tfidf.toarray(), ytrain)\n",
        "y_pred = clf.predict(xval_tfidf.toarray())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W6kSoqyxADR8",
        "outputId": "d91712b4-80c3-443e-d60a-0fa1c125a63d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "8903"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(multilabel_binarizer.inverse_transform(y_pred))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ph5zu9LaAkwi",
        "outputId": "bc51facd-2e17-4477-e11a-96f93d183c13"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['It has been eight years since Batman (Christian Bale), in collusion with Commissioner Gordon (Gary Oldman), vanished into the night. Assuming responsibility for the death of Harvey Dent, Batman sacrificed everything for what he and Gordon hoped would be the greater good. However, the arrival of a cunning cat burglar (Anne Hathaway) and a merciless terrorist named Bane (Tom Hardy) force Batman out of exile and into a battle he may not be able to win.']"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "string = [\"It has been eight years since Batman (Christian Bale), in collusion with Commissioner Gordon (Gary Oldman), vanished into the night. Assuming responsibility for the death of Harvey Dent, Batman sacrificed everything for what he and Gordon hoped would be the greater good. However, the arrival of a cunning cat burglar (Anne Hathaway) and a merciless terrorist named Bane (Tom Hardy) force Batman out of exile and into a battle he may not be able to win.\"]\n",
        "string"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8LokolpWCWwz",
        "outputId": "b2028d43-bb36-44ae-c4d3-1f342adcde6c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([[0., 0., 0., ..., 0., 0., 0.]])"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tfidf_vectorizer.transform(string).toarray()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dXktp4WBBW7i",
        "outputId": "52f1fa2a-affe-48cb-9fc8-5644c932521b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[('Action', 'Animation', 'Crime', 'Thriller')]"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "multilabel_binarizer.inverse_transform(clf.predict(tfidf_vectorizer.transform(string).toarray()))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1yJW_XtBdmj_"
      },
      "outputs": [],
      "source": [
        "pickle.dump(clf,open('movie_model.pkl','wb'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7I8qHATrWU0N"
      },
      "outputs": [],
      "source": [
        "pickle.dump(multilabel_binarizer,open('target_label.pkl','wb'))\n",
        "pickle.dump(tfidf_vectorizer,open('vectorizer.pkl','wb'))"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "disney.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.10.6 64-bit",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.10.6"
    },
    "vscode": {
      "interpreter": {
        "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}