data.ipynb

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  "metadata": {
    "colab": {
      "name": "tempo.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AliAkbarBadri/topics-for-types/blob/main/data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "35118jEtNm5E"
      },
      "source": [
        "# Setup"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nF-7m57sBgdp"
      },
      "source": [
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras.layers import Embedding, LSTM, Dense, Dropout, Bidirectional, GRU\n",
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "from tensorflow.keras import regularizers\n",
        "import tensorflow.keras.utils as ku "
      ],
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bxA_PSMaBhzU"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import re\n",
        "import matplotlib.pyplot as plt\n",
        "import os"
      ],
      "execution_count": 75,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LCVAXfOLRn17",
        "outputId": "4a023f53-b101-475b-f09b-1168688f2f9e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vOESHfVEtL1V"
      },
      "source": [
        "# EDA"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DV_x9XoPBlJM"
      },
      "source": [
        "questions = pd.read_csv(\"/content/drive/My Drive/topics-for-types/result.csv\", delimiter=\";\")"
      ],
      "execution_count": 77,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TLz9bs76Cbk2",
        "outputId": "0f40a8cf-10e6-4d44-fcbe-9250e4742bee",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 581
        }
      },
      "source": [
        "print(questions.shape)\n",
        "questions.head()"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(2799, 21)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>title</th>\n",
              "      <th>sentence</th>\n",
              "      <th>subject1</th>\n",
              "      <th>subject2</th>\n",
              "      <th>subject3</th>\n",
              "      <th>subject_notsure</th>\n",
              "      <th>suggested_subject</th>\n",
              "      <th>type1</th>\n",
              "      <th>type2</th>\n",
              "      <th>type3</th>\n",
              "      <th>type_notsure</th>\n",
              "      <th>suggested_type</th>\n",
              "      <th>s1 score</th>\n",
              "      <th>s2 score</th>\n",
              "      <th>s3 score</th>\n",
              "      <th>t1 score</th>\n",
              "      <th>t2 score</th>\n",
              "      <th>t3 score</th>\n",
              "      <th>Avg_sbj_num</th>\n",
              "      <th>Avg_typ_num</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>تفاوت ترمز عقب دیسکی و کاسه ای چیست؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>خرید</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>تعریف</td>\n",
              "      <td>نظر</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29</td>\n",
              "      <td>28</td>\n",
              "      <td>8</td>\n",
              "      <td>19</td>\n",
              "      <td>10</td>\n",
              "      <td>8</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>1.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>آیا ترمز ضدقفل ABS در همه چرخ ها عمل می کند؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>بله/خیر</td>\n",
              "      <td>نظر</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29</td>\n",
              "      <td>28</td>\n",
              "      <td>8</td>\n",
              "      <td>30</td>\n",
              "      <td>9</td>\n",
              "      <td>8</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>1.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>چرا باوجود نصب بودن ترمز ABS بر روی خودرو، ترم...</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>دلیل</td>\n",
              "      <td>نظر</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29</td>\n",
              "      <td>28</td>\n",
              "      <td>8</td>\n",
              "      <td>30</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>چرا با وجود نصب بودن Airbag بر روی خودرو، در ه...</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>دلیل</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>نظر</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29</td>\n",
              "      <td>28</td>\n",
              "      <td>8</td>\n",
              "      <td>30</td>\n",
              "      <td>18</td>\n",
              "      <td>16</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>2.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>کلاس های مختلف خودرو چگونه شناسایی می شوند؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>خرید</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>نظر</td>\n",
              "      <td>لیست</td>\n",
              "      <td>تعریف</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>30</td>\n",
              "      <td>18</td>\n",
              "      <td>8</td>\n",
              "      <td>17</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>2.333333</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id title  ... Avg_sbj_num Avg_typ_num\n",
              "0   1   NaN  ...    2.333333    1.333333\n",
              "1   2   NaN  ...    2.333333    1.666667\n",
              "2   3   NaN  ...    2.333333    2.000000\n",
              "3   4   NaN  ...    2.333333    2.333333\n",
              "4   5   NaN  ...    2.333333    2.333333\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XqqPXjFASMob",
        "outputId": "7210ad53-3cbc-494e-fc54-ce90ddc48eea",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "subjects_unique = len(set(np.concatenate((questions.subject1, questions.subject2,questions.subject3), axis=None)))\n",
        "types_unique = len(set(np.concatenate((questions.type1, questions.type2,questions.type3), axis=None)))\n",
        "print(\"number of subjects: \" + str(subjects_unique) + \", number of types: \" + str(types_unique))"
      ],
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "number of subjects: 24, number of types: 13\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K1JLM_K5O_fz"
      },
      "source": [
        "chosen_columns = ['sentence','subject1',\t'subject2',\t'subject3',  'type1',\t'type2',\t'type3']"
      ],
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9UyhEnMiNtzK",
        "outputId": "577168b9-7c19-4903-c1e0-63560e6d8e84",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df_questions = questions[chosen_columns]\n",
        "df_questions.head()"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sentence</th>\n",
              "      <th>subject1</th>\n",
              "      <th>subject2</th>\n",
              "      <th>subject3</th>\n",
              "      <th>type1</th>\n",
              "      <th>type2</th>\n",
              "      <th>type3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>تفاوت ترمز عقب دیسکی و کاسه ای چیست؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>خرید</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>تعریف</td>\n",
              "      <td>نظر</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>آیا ترمز ضدقفل ABS در همه چرخ ها عمل می کند؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>بله/خیر</td>\n",
              "      <td>نظر</td>\n",
              "      <td>توضیح</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>چرا باوجود نصب بودن ترمز ABS بر روی خودرو، ترم...</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>دلیل</td>\n",
              "      <td>نظر</td>\n",
              "      <td>توضیح</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>چرا با وجود نصب بودن Airbag بر روی خودرو، در ه...</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>دلیل</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>نظر</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>کلاس های مختلف خودرو چگونه شناسایی می شوند؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>خرید</td>\n",
              "      <td>نظر</td>\n",
              "      <td>لیست</td>\n",
              "      <td>تعریف</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                            sentence subject1  ...  type2  type3\n",
              "0              تفاوت ترمز عقب دیسکی و کاسه ای چیست؟     ماشین  ...  تعریف    نظر\n",
              "1     آیا ترمز ضدقفل ABS در همه چرخ ها عمل می کند؟      ماشین  ...    نظر  توضیح\n",
              "2  چرا باوجود نصب بودن ترمز ABS بر روی خودرو، ترم...    ماشین  ...    نظر  توضیح\n",
              "3  چرا با وجود نصب بودن Airbag بر روی خودرو، در ه...    ماشین  ...  توضیح    نظر\n",
              "4       کلاس های مختلف خودرو چگونه شناسایی می شوند؟     ماشین  ...   لیست  تعریف\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ctZgKg_dVRXj",
        "outputId": "41d22a97-e884-47c9-a04d-13a2a2dac368",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        }
      },
      "source": [
        "df_questions[['subject1',\t'subject2',\t'subject3']].isna().sum(axis=1)"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       0\n",
              "1       0\n",
              "2       0\n",
              "3       0\n",
              "4       0\n",
              "       ..\n",
              "2794    1\n",
              "2795    3\n",
              "2796    3\n",
              "2797    3\n",
              "2798    3\n",
              "Length: 2799, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GvO0_V7nWVMC",
        "outputId": "a9341606-2e14-429c-c59c-6bed3c06e2a2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        }
      },
      "source": [
        "df_questions[['type1',\t'type2',\t'type3']].isna().sum(axis=1)"
      ],
      "execution_count": 137,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       0\n",
              "1       0\n",
              "2       0\n",
              "3       0\n",
              "4       0\n",
              "       ..\n",
              "2794    1\n",
              "2795    2\n",
              "2796    2\n",
              "2797    3\n",
              "2798    1\n",
              "Length: 2799, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 137
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dKY6NIl6tBJe"
      },
      "source": [
        "# Convert topics and types to multiple columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NSDy4StVUHp2",
        "outputId": "58746338-d6cb-4491-9b3c-dec53f96f870",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        }
      },
      "source": [
        "df_questions['topics'] = df_questions[['subject1',\t'subject2',\t'subject3']].apply(\n",
        "    lambda x: '|'.join(x.astype(str)),\n",
        "    axis=1\n",
        ")\n",
        "df_questions['types'] = df_questions[['type1',\t'type2',\t'type3']].apply(\n",
        "    lambda x: '|'.join(x.astype(str)),\n",
        "    axis=1\n",
        ")"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py: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",
            "  This is separate from the ipykernel package so we can avoid doing imports until\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:7: 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",
            "  import sys\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gcyN4ugJU8Hm",
        "outputId": "1de68293-63fe-4548-afa6-1f48c082a1f7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df_questions.head()"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "      <th>subject2</th>\n",
              "      <th>subject3</th>\n",
              "      <th>type1</th>\n",
              "      <th>type2</th>\n",
              "      <th>type3</th>\n",
              "      <th>topics</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>تفاوت ترمز عقب دیسکی و کاسه ای چیست؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>خرید</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>تعریف</td>\n",
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              "      <td>توضیح|تعریف|نظر</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>آیا ترمز ضدقفل ABS در همه چرخ ها عمل می کند؟</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>چرا باوجود نصب بودن ترمز ABS بر روی خودرو، ترم...</td>\n",
              "      <td>ماشین</td>\n",
              "      <td>فنی</td>\n",
              "      <td>کار</td>\n",
              "      <td>دلیل</td>\n",
              "      <td>نظر</td>\n",
              "      <td>توضیح</td>\n",
              "      <td>ماشین|فنی|کار</td>\n",
              "      <td>دلیل|نظر|توضیح</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
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              "      <td>کلاس های مختلف خودرو چگونه شناسایی می شوند؟</td>\n",
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            ],
            "text/plain": [
              "                                            sentence  ...              types\n",
              "0              تفاوت ترمز عقب دیسکی و کاسه ای چیست؟   ...    توضیح|تعریف|نظر\n",
              "1     آیا ترمز ضدقفل ABS در همه چرخ ها عمل می کند؟    ...  بله/خیر|نظر|توضیح\n",
              "2  چرا باوجود نصب بودن ترمز ABS بر روی خودرو، ترم...  ...     دلیل|نظر|توضیح\n",
              "3  چرا با وجود نصب بودن Airbag بر روی خودرو، در ه...  ...     دلیل|توضیح|نظر\n",
              "4       کلاس های مختلف خودرو چگونه شناسایی می شوند؟   ...     نظر|لیست|تعریف\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
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    {
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        "df_questions['types'].str.get_dummies('|')"
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      "execution_count": 86,
      "outputs": [
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              "      nan  انتخاب  بله/خیر  ترجمه  تعامل  ...  ریاضی  لیست  نظر  واقعیت  پیشنهاد\n",
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      },
      "source": [
        "df_questions['topics'].str.get_dummies('|')"
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      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      nan  اقتصاد  بازی  برنامه‌نویسی  ...  کار  کامپیوتر/موبایل  کودکان  گیاهان\n",
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              "4       0       0     0             0  ...    0                0       0       0\n",
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              "2797    1       0     0             0  ...    0                0       0       0\n",
              "2798    1       0     0             0  ...    0                0       0       0\n",
              "\n",
              "[2799 rows x 24 columns]"
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          "metadata": {
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          "execution_count": 87
        }
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    {
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      "metadata": {
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        "outputId": "ec879aee-92f1-4141-8f34-e1b515e9a4e3",
        "colab": {
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          "height": 564
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      "source": [
        "df_topics = pd.concat([df_questions['sentence'], df_questions['topics'].str.get_dummies('|')],  axis=1, sort=False)\n",
        "df_topics = df_topics[df_topics[df_topics.columns[2:]].sum(axis=1)!=0]\n",
        "df_topics.drop(columns=['nan'],inplace=True, axis=1)\n",
        "df_topics.head()"
      ],
      "execution_count": 132,
      "outputs": [
        {
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              "                                            sentence  اقتصاد  ...  کودکان  گیاهان\n",
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              "3  چرا با وجود نصب بودن Airbag بر روی خودرو، در ه...       0  ...       0       0\n",
              "4       کلاس های مختلف خودرو چگونه شناسایی می شوند؟        0  ...       0       0\n",
              "\n",
              "[5 rows x 24 columns]"
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          "metadata": {
            "tags": []
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          "execution_count": 132
        }
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    {
      "cell_type": "code",
      "metadata": {
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        "outputId": "cecea3ba-e560-4cda-9250-7f950ffb6e94",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df_types = pd.concat([df_questions['sentence'], df_questions['types'].str.get_dummies('|')],  axis=1, sort=False)\n",
        "df_types = df_types[df_types[df_types.columns[2:]].sum(axis=1)!=0]\n",
        "df_types.drop(columns=['nan'],inplace=True, axis=1)\n",
        "df_types.head()"
      ],
      "execution_count": 144,
      "outputs": [
        {
          "output_type": "execute_result",
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            "text/plain": [
              "                                            sentence  انتخاب  ...  واقعیت  پیشنهاد\n",
              "0              تفاوت ترمز عقب دیسکی و کاسه ای چیست؟        0  ...       0        0\n",
              "1     آیا ترمز ضدقفل ABS در همه چرخ ها عمل می کند؟         0  ...       0        0\n",
              "2  چرا باوجود نصب بودن ترمز ABS بر روی خودرو، ترم...       0  ...       0        0\n",
              "3  چرا با وجود نصب بودن Airbag بر روی خودرو، در ه...       0  ...       0        0\n",
              "4       کلاس های مختلف خودرو چگونه شناسایی می شوند؟        0  ...       0        0\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 144
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WivmmpKNtbsU"
      },
      "source": [
        "df_topics.to_csv(\"/content/drive/My Drive/topics-for-types/df_topics.csv\", index=False)\n",
        "df_types.to_csv(\"/content/drive/My Drive/topics-for-types/df_types.csv\", index=False)"
      ],
      "execution_count": 149,
      "outputs": []
    }
  ]
}