EDA1.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install contractions"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N0hVJ-_bQs9F",
        "outputId": "9f0c26a2-760e-445d-e2cd-10ba4d29c26f"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: contractions in /usr/local/lib/python3.9/dist-packages (0.1.73)\n",
            "Requirement already satisfied: textsearch>=0.0.21 in /usr/local/lib/python3.9/dist-packages (from contractions) (0.0.24)\n",
            "Requirement already satisfied: anyascii in /usr/local/lib/python3.9/dist-packages (from textsearch>=0.0.21->contractions) (0.3.1)\n",
            "Requirement already satisfied: pyahocorasick in /usr/local/lib/python3.9/dist-packages (from textsearch>=0.0.21->contractions) (2.0.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import contractions\n",
        "import nltk\n",
        "import string\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "from collections import Counter\n",
        "nltk.download('punkt')\n",
        "nltk.download('stopwords')\n",
        "nltk.download('averaged_perceptron_tagger')\n",
        "nltk.download('wordnet')\n",
        "nltk.download('omw-1.4')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wge3XkbAMB8R",
        "outputId": "cffe76f6-7654-49fa-c650-19faf7692523"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     /root/nltk_data...\n",
            "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
            "[nltk_data]       date!\n",
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n",
            "[nltk_data]   Package omw-1.4 is already up-to-date!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "ussHBl6FLKRS"
      },
      "outputs": [],
      "source": [
        "training_set = pd.read_json('./data/train_set.json')\n",
        "test_set = pd.read_json('./data/test_set.json')\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_set.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "BG2aqBtFMCF6",
        "outputId": "293b5308-04a0-4896-9bfb-b5ea433b3673"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id                                               text  label\n",
              "0   0  Remains dating to the 5th century were found i...      1\n",
              "1   1  Professional Identification is a type of socia...      1\n",
              "2   2  A magistrate has refused a media ban on the tr...      1\n",
              "3   3  The Conservation Commons is the expression of ...      1\n",
              "4   4  Myer is holding a 75 per cent of designer labe...      0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e3a6fbc6-b4ba-4087-b970-4c6ff205dd40\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>text</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Remains dating to the 5th century were found i...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Professional Identification is a type of socia...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>A magistrate has refused a media ban on the tr...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>The Conservation Commons is the expression of ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>Myer is holding a 75 per cent of designer labe...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e3a6fbc6-b4ba-4087-b970-4c6ff205dd40')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e3a6fbc6-b4ba-4087-b970-4c6ff205dd40 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-e3a6fbc6-b4ba-4087-b970-4c6ff205dd40');\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": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_set.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "A0YuRQosMd-J",
        "outputId": "93cd7b24-35c7-49e6-91dd-51382e37469b"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id                                               text\n",
              "0   0  David Cameron revealed he and his wife Samanth...\n",
              "1   1  David Cameron appeared to forget which footbal...\n",
              "2   2  Ebola tests for a senior doctor has come back ...\n",
              "3   3  Celebrity chef's Fat Duck named eighth best re...\n",
              "4   4  Navinder Singh Sarao , 36 , is accused of maki..."
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b51fc4df-58e1-4003-9aa7-ea208c134862\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>David Cameron revealed he and his wife Samanth...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>David Cameron appeared to forget which footbal...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>Ebola tests for a senior doctor has come back ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>Celebrity chef's Fat Duck named eighth best re...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>Navinder Singh Sarao , 36 , is accused of maki...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b51fc4df-58e1-4003-9aa7-ea208c134862')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b51fc4df-58e1-4003-9aa7-ea208c134862 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-b51fc4df-58e1-4003-9aa7-ea208c134862');\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": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ta = training_set.copy() # training text analyse\n"
      ],
      "metadata": {
        "id": "HoqvGvM_Mhbx"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## label distribution"
      ],
      "metadata": {
        "id": "RMK2hOOseC2x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ta['label'].value_counts().plot.pie()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "2XpOCWK9Nj-A",
        "outputId": "5561960d-e28e-4688-b635-8548689261a5"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## text length"
      ],
      "metadata": {
        "id": "nNm6Ig5TeHd2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ta['no_contract'] = ta['text'].apply(lambda x: contractions.fix(x))\n",
        "ta['tokenized'] = ta['no_contract'].apply(nltk.word_tokenize)"
      ],
      "metadata": {
        "id": "EKbg4GT6PzDf"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "punc = string.punctuation\n",
        "ta['no_punc'] = ta['tokenized'].apply(lambda x: [word for word in x if word not in punc])\n",
        "ta['punc'] = ta['tokenized'].apply(lambda x: [word for word in x if word in punc])\n",
        "ta['lower'] = ta['no_punc'].apply(lambda x: [word.lower() for word in x])\n",
        "\n",
        "stop_words = set(nltk.corpus.stopwords.words('english'))\n",
        "ta['stopwords_removed'] = ta['lower'].apply(lambda x: [word for word in x if word not in stop_words])"
      ],
      "metadata": {
        "id": "qTlSs6vdU3JD"
      },
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ta['with_stop_word_count'] = ta['lower'].apply(len)\n",
        "ta['with_stop_word_count'].plot.hist()\n",
        "plt.show()\n",
        "ta['with_stop_word_count'].mean(), ta['with_stop_word_count'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "k6Z39NlhMhUQ",
        "outputId": "795cb005-7600-46e8-e1a1-52b8e9162644"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(97.62325, 521)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ta['without_stop_word_count'] = ta['stopwords_removed'].apply(len)\n",
        "ta['without_stop_word_count'].plot.hist()\n",
        "plt.show()\n",
        "ta['without_stop_word_count'].mean(), ta['without_stop_word_count'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "X3SyLGB0O70h",
        "outputId": "2df31cd6-80d0-4467-c098-5920a523a2b1"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAD4CAYAAAAdIcpQAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAAsTAAALEwEAmpwYAAAT6ElEQVR4nO3df7DddX3n8edLQPAHLVBSlgLbgJOtm7aKaUR2tF2rIz9bozvWhW1rxnGaTgszOu3OGuxOYdthhu6s0LJjabFmBasi/qqppksDMnX6Bz8CRgggJZUwJEaSSgtYO1DwvX+cz4Wz8d77OUnuuefE+3zMnDnf7/v7/Z7vOx+4eeX7435PqgpJkubzokk3IEmafoaFJKnLsJAkdRkWkqQuw0KS1HX4pBsYh+OPP76WL18+6TYk6ZBy1113/UNVLZtt2Q9kWCxfvpwtW7ZMug1JOqQkeWSuZZ6GkiR1GRaSpC7DQpLUZVhIkrrGFhZJTklya5L7k9yX5L2tflmSXUm2ttd5Q9tckmR7kgeTnD1UP6fVtidZP66eJUmzG+fdUM8Cv11Vdyc5Grgryea27Kqq+l/DKydZCVwA/CTwY8DNSf5dW/wh4C3ATuDOJBur6v4x9i5JGjK2sKiq3cDuNv1UkgeAk+bZZA1wQ1U9DTycZDtwRlu2vaq+AZDkhrauYSFJi2RRrlkkWQ68Bri9lS5Ock+SDUmObbWTgEeHNtvZanPVJUmLZOxhkeTlwGeB91XVk8A1wCuA0xkceXxwgfazLsmWJFv27t27EB8pSWrG+hvcSY5gEBQfr6rPAVTVY0PLPwx8sc3uAk4Z2vzkVmOe+vOq6lrgWoDVq1cf1Dc6LV//pYPZ/IDtuOL8iexXknrGeTdUgI8AD1TVlUP1E4dWezuwrU1vBC5IcmSSU4EVwB3AncCKJKcmeTGDi+Abx9W3JOn7jfPI4vXArwL3Jtnaah8ALkxyOlDADuDXAarqviQ3Mrhw/SxwUVU9B5DkYuAm4DBgQ1XdN8a+JUn7GOfdUH8LZJZFm+bZ5nLg8lnqm+bbTpI0Xv4GtySpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqWtsYZHklCS3Jrk/yX1J3tvqxyXZnOSh9n5sqyfJ1Um2J7knyaqhz1rb1n8oydpx9SxJmt04jyyeBX67qlYCZwIXJVkJrAduqaoVwC1tHuBcYEV7rQOugUG4AJcCrwPOAC6dCRhJ0uIYW1hU1e6qurtNPwU8AJwErAGua6tdB7ytTa8Brq+B24BjkpwInA1srqrHq+ofgc3AOePqW5L0/RblmkWS5cBrgNuBE6pqd1v0LeCENn0S8OjQZjtbba76vvtYl2RLki179+5d2D+AJC1xYw+LJC8HPgu8r6qeHF5WVQXUQuynqq6tqtVVtXrZsmUL8ZGSpGasYZHkCAZB8fGq+lwrP9ZOL9He97T6LuCUoc1PbrW56pKkRTLOu6ECfAR4oKquHFq0EZi5o2kt8IWh+rvaXVFnAk+001U3AWclObZd2D6r1SRJi+TwMX7264FfBe5NsrXVPgBcAdyY5D3AI8A727JNwHnAduC7wLsBqurxJL8P3NnW+72qenyMfUuS9jG2sKiqvwUyx+I3z7J+ARfN8VkbgA0L150kaX/4G9ySpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoaKSyS/PS4G5EkTa9Rjyz+OMkdSX4zyQ+PtSNJ0tQZKSyq6meBXwZOAe5K8okkbxlrZ5KkqTHyNYuqegj478D7gf8IXJ3k60n+07iakyRNh1GvWbwqyVXAA8CbgF+sqn/fpq+aY5sNSfYk2TZUuyzJriRb2+u8oWWXJNme5MEkZw/Vz2m17UnWH+CfU5J0EEY9svjfwN3Aq6vqoqq6G6CqvsngaGM2HwXOmaV+VVWd3l6bAJKsBC4AfrJt88dJDktyGPAh4FxgJXBhW1eStIgOH3G984F/qarnAJK8CDiqqr5bVR+bbYOq+kqS5SN+/hrghqp6Gng4yXbgjLZse1V9o+33hrbu/SN+riRpAYx6ZHEz8JKh+Ze22oG4OMk97TTVsa12EvDo0Do7W22u+vdJsi7JliRb9u7de4CtSZJmM2pYHFVV35mZadMvPYD9XQO8Ajgd2A188AA+Y1ZVdW1Vra6q1cuWLVuoj5UkMXpY/HOSVTMzSX4G+Jf93VlVPVZVz1XV94AP88Kppl0MbsudcXKrzVWXJC2iUa9ZvA/4dJJvAgH+DfCf93dnSU6sqt1t9u3AzJ1SG4FPJLkS+DFgBXBH29eKJKcyCIkLgP+yv/uVJB2ckcKiqu5M8krgJ1rpwar61/m2SfJJ4I3A8Ul2ApcCb0xyOlDADuDX2+ffl+RGBheunwUuGrqYfjFwE3AYsKGq7tufP6Ak6eCNemQB8FpgedtmVRKq6vq5Vq6qC2cpf2Se9S8HLp+lvgnYtB99SpIW2EhhkeRjDC5MbwWea+UC5gwLSdIPjlGPLFYDK6uqxtmMJGk6jXo31DYGF7UlSUvQqEcWxwP3J7kDeHqmWFVvHUtXkqSpMmpYXDbOJiRJ023UW2f/JsmPAyuq6uYkL2VwK6skaQkY9RHlvwZ8BvjTVjoJ+Isx9SRJmjKjXuC+CHg98CQ8/0VIPzqupiRJ02XUsHi6qp6ZmUlyOIPfs5AkLQGjhsXfJPkA8JL23dufBv5yfG1JkqbJqGGxHtgL3MvgeU6bmPsb8iRJP2BGvRtq5pHiHx5vO5KkaTTqs6EeZpZrFFV12oJ3JEmaOvvzbKgZRwG/BBy38O1IkqbRSNcsqurbQ69dVfWHwPnjbU2SNC1GPQ21amj2RQyONPbnuzAkSYewUf/C/+DQ9LMMvuXunQvejSRpKo16N9TPj7sRSdL0GvU01G/Nt7yqrlyYdiRJ02h/7oZ6LbCxzf8icAfw0DiakiRNl1HD4mRgVVU9BZDkMuBLVfUr42pMkjQ9Rn3cxwnAM0Pzz7SaJGkJGPXI4nrgjiSfb/NvA64bS0eSpKkz6t1Qlyf5K+BnW+ndVfXV8bUlSZomo56GAngp8GRV/RGwM8mpY+pJkjRlRv1a1UuB9wOXtNIRwJ+PqylJ0nQZ9cji7cBbgX8GqKpvAkePqylJ0nQZNSyeqaqiPaY8ycvG15IkadqMGhY3JvlT4JgkvwbcjF+EJElLRvduqCQBPgW8EngS+Angd6tq85h7kyRNiW5YVFUl2VRVPw0YEJK0BI16GuruJK8dayeSpKk1ali8Drgtyd8nuSfJvUnumW+DJBuS7Emybah2XJLNSR5q78e2epJcnWR7+/xVQ9usbes/lGTtgfwhJUkHZ96wSPJv2+TZwGnAmxg8cfYX2vt8Pgqcs09tPXBLVa0AbmnzAOcCK9prHXBN2/9xwKUMwuoM4NKZgJEkLZ7ekcVfAFTVI8CVVfXI8Gu+DavqK8Dj+5TX8MIzpa5j8Iypmfr1NXAbg7uuTmQQUpur6vGq+kcG10z2DSBJ0pj1wiJD06ctwP5OqKrdbfpbvPDk2pOAR4fW29lqc9W/v9FkXZItSbbs3bt3AVqVJM3ohUXNMX3Qhn/Jb4E+79qqWl1Vq5ctW7ZQHytJoh8Wr07yZJKngFe16SeTPJXkyQPY32Pt9BLtfU+r7wJOGVrv5Fabqy5JWkTzhkVVHVZVP1RVR1fV4W16Zv6HDmB/G4GZO5rWAl8Yqr+r3RV1JvBEO111E3BWkmPbhe2zWk2StIhG/fKj/Zbkk8AbgeOT7GRwV9MVDB4d8h7gEeCdbfVNwHnAduC7wLsBqurxJL8P3NnW+72q2veiuSRpzMYWFlV14RyL3jzLugVcNMfnbAA2LGBrkqT9tD9ffiRJWqIMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUtfYHvehQ8vy9V+ayH53XHH+RPYraf94ZCFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktQ1kbBIsiPJvUm2JtnSascl2ZzkofZ+bKsnydVJtie5J8mqSfQsSUvZJI8sfr6qTq+q1W1+PXBLVa0AbmnzAOcCK9prHXDNoncqSUvcNJ2GWgNc16avA942VL++Bm4Djkly4gT6k6Qla1JhUcBfJ7krybpWO6GqdrfpbwEntOmTgEeHtt3Zav+fJOuSbEmyZe/evePqW5KWpMMntN83VNWuJD8KbE7y9eGFVVVJan8+sKquBa4FWL169X5tK0ma30SOLKpqV3vfA3weOAN4bOb0Unvf01bfBZwytPnJrSZJWiSLHhZJXpbk6Jlp4CxgG7ARWNtWWwt8oU1vBN7V7oo6E3hi6HSVJGkRTOI01AnA55PM7P8TVfV/k9wJ3JjkPcAjwDvb+puA84DtwHeBdy9+y5K0tC16WFTVN4BXz1L/NvDmWeoFXLQIrUmS5jCpC9wSAMvXf2ki+91xxfkT2a90qJqm37OQJE0pw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcvvs5gik/puB0nq8chCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqSuQ+bLj5KcA/wRcBjwZ1V1xYRb0iFskl80teOK8ye2b+lAHRJHFkkOAz4EnAusBC5MsnKyXUnS0nFIhAVwBrC9qr5RVc8ANwBrJtyTJC0Zh8ppqJOAR4fmdwKvG14hyTpgXZv9TpIHO595PPAPC9bhwpvm/qa5N5ju/o7PH0xtbzDdYwfT3d809waj9ffjcy04VMKiq6quBa4ddf0kW6pq9RhbOijT3N809wbT3d809wb2dzCmuTc4+P4OldNQu4BThuZPbjVJ0iI4VMLiTmBFklOTvBi4ANg44Z4kack4JE5DVdWzSS4GbmJw6+yGqrrvID925FNWEzLN/U1zbzDd/U1zb2B/B2Oae4OD7C9VtVCNSJJ+QB0qp6EkSRNkWEiSupZkWCQ5J8mDSbYnWT8F/exIcm+SrUm2tNpxSTYneai9H7uI/WxIsifJtqHarP1k4Oo2lvckWTWh/i5LsquN4dYk5w0tu6T192CSs8fc2ylJbk1yf5L7kry31Sc+fvP0Ni1jd1SSO5J8rfX3P1r91CS3tz4+1W5yIcmRbX57W758Ar19NMnDQ2N3eqsv+s9F2+9hSb6a5IttfuHGrqqW1IvBBfK/B04DXgx8DVg54Z52AMfvU/ufwPo2vR74g0Xs5+eAVcC2Xj/AecBfAQHOBG6fUH+XAf91lnVXtv/GRwKntv/2h42xtxOBVW36aODvWg8TH795epuWsQvw8jZ9BHB7G5MbgQta/U+A32jTvwn8SZu+APjUBHr7KPCOWdZf9J+Ltt/fAj4BfLHNL9jYLcUji0Pl0SFrgOva9HXA2xZrx1X1FeDxEftZA1xfA7cBxyQ5cQL9zWUNcENVPV1VDwPbGfw/MK7edlfV3W36KeABBk8gmPj4zdPbXBZ77KqqvtNmj2ivAt4EfKbV9x27mTH9DPDmJFnk3uay6D8XSU4Gzgf+rM2HBRy7pRgWsz06ZL4fmMVQwF8nuSuDx5YAnFBVu9v0t4ATJtPa8+bqZ5rG8+J2yL9h6LTdxPprh/avYfCv0Kkav316gykZu3YaZSuwB9jM4Gjmn6rq2Vl6eL6/tvwJ4EcWq7eqmhm7y9vYXZXkyH17m6XvcflD4L8B32vzP8ICjt1SDItp9IaqWsXgqboXJfm54YU1OFacmnucp62f5hrgFcDpwG7gg5NsJsnLgc8C76uqJ4eXTXr8Zultasauqp6rqtMZPKXhDOCVk+plX/v2luSngEsY9Pha4Djg/ZPoLckvAHuq6q5x7WMphsXUPTqkqna19z3A5xn8kDw2c9ja3vdMrkOYp5+pGM+qeqz9MH8P+DAvnC5Z9P6SHMHgL+OPV9XnWnkqxm+23qZp7GZU1T8BtwL/gcEpnJlfIB7u4fn+2vIfBr69iL2d007tVVU9DfwfJjd2rwfemmQHg1Prb2Lw/T8LNnZLMSym6tEhSV6W5OiZaeAsYFvraW1bbS3whcl0+Ly5+tkIvKvd/XEm8MTQ6ZZFs8/54LczGMOZ/i5od3+cCqwA7hhjHwE+AjxQVVcOLZr4+M3V2xSN3bIkx7TplwBvYXBd5VbgHW21fcduZkzfAXy5HbUtVm9fH/oHQBhcDxgeu0X7uaiqS6rq5KpazuDvtC9X1S+zkGM37qvz0/hicKfC3zE4H/o7E+7lNAZ3nHwNuG+mHwbnD28BHgJuBo5bxJ4+yeB0xL8yOM/5nrn6YXC3x4faWN4LrJ5Qfx9r+7+n/SCcOLT+77T+HgTOHXNvb2BwiukeYGt7nTcN4zdPb9Mydq8Cvtr62Ab87tDPyB0MLrB/Gjiy1Y9q89vb8tMm0NuX29htA/6cF+6YWvSfi6Fe38gLd0Mt2Nj5uA9JUtdSPA0lSdpPhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lS1/8DRkksuns3s1UAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(59.94875, 393)"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ta['punc_count'] = ta['punc'].apply(len)\n",
        "ta['punc_count'].plot.hist()\n",
        "plt.show()\n",
        "ta['punc_count'].mean(), ta['punc_count'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "Pxjr0QZQXAG7",
        "outputId": "bddee9a3-1606-4fc8-cab6-16a68fb5fa19"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(12.53925, 168)"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correlation = ta[['label', 'with_stop_word_count', 'without_stop_word_count', 'punc_count']].corr()\n",
        "mask = np.zeros_like(correlation, dtype=bool)\n",
        "mask[np.triu_indices_from(mask)] = True\n",
        "sns.heatmap(correlation, cmap='coolwarm', annot=True, linewidths=10, vmin=-1.5, mask=mask)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "DdLCjwyteAGF",
        "outputId": "e7fb75ca-3c0d-4f5c-ea61-d2b39080018f"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## word frequency"
      ],
      "metadata": {
        "id": "167ZSjjIfkJ1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ta['pos_tags'] = ta['stopwords_removed'].apply(nltk.tag.pos_tag)\n",
        "def get_wordnet_pos(tag):\n",
        "    if tag.startswith('J'):\n",
        "        return nltk.corpus.wordnet.ADJ\n",
        "    elif tag.startswith('V'):\n",
        "        return nltk.corpus.wordnet.VERB\n",
        "    elif tag.startswith('N'):\n",
        "        return nltk.corpus.wordnet.NOUN\n",
        "    elif tag.startswith('R'):\n",
        "        return nltk.corpus.wordnet.ADV\n",
        "    else:\n",
        "        return nltk.corpus.wordnet.NOUN\n",
        "ta['wordnet_pos'] = ta['pos_tags'].apply(lambda x: [(word, get_wordnet_pos(pos_tag)) for (word, pos_tag) in x])\n",
        "wnl = nltk.stem.WordNetLemmatizer()\n",
        "ta['lemmatized'] = ta['wordnet_pos'].apply(lambda x: [wnl.lemmatize(word, tag) for word, tag in x])"
      ],
      "metadata": {
        "id": "7fTiQTX0b6rX"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "words = ta['lemmatized']\n",
        "allwords = []\n",
        "for wordlist in words:\n",
        "    allwords += wordlist\n",
        "print(allwords[:100])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wErsQT8NbkiQ",
        "outputId": "a144806e-e9d9-47fe-c006-2a9d4608d00e"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['remains', 'date', '5th', 'century', 'find', 'tomb', 'hwangnam-dong', 'show', 'man', \"'s\", 'bone', 'top', 'woman', \"'s\", 'bury', 'jewellery', 'expert', 'believe', 'silla', 'dynasty-era', 'tomb', 'build', 'noblewoman', 'lover', 'bodyguard', 'sacrifice', 'bury', 'top', \"'s\", 'suggestion', 'set-up', 'may', 'design', 'show', 'two', 'people', 'sex', 'silla', 'know', 'explicit', 'pottery', 'professional', 'identification', 'type', 'social', 'identification', 'sense', 'oneness', 'individual', 'profession', 'e.g', 'law', 'medicine', 'degree', 'individual', 'define', 'profession', 'member', 'professional', 'identity', 'consist', 'individual', \"'s\", 'alignment', 'role', 'responsibility', 'value', 'ethical', 'standard', 'consistent', 'practice', 'accept', 'specific', 'profession', 'source', 'professional', 'identification', 'researcher', 'find', 'desire', 'quality', 'rather', 'profit', 'associate', 'professional', 'identification', 'organization', 'tend', 'concerned', 'efficiency', 'profitability', 'whereas', 'profession', 'care', 'mainly', 'provide', 'highest-quality', 'service', 'define', 'profession']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mostcommon_small = nltk.probability.FreqDist(allwords).most_common(25)\n",
        "x, y = zip(*mostcommon_small)\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(x, y)\n",
        "plt.xlabel('Words', fontsize=10)\n",
        "plt.ylabel('Frequency of Words', fontsize=10)\n",
        "plt.yticks(fontsize=8)\n",
        "plt.xticks(rotation=60, fontsize=8)\n",
        "plt.title('Frequency of 25 Most Common Words', fontsize=12)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 433
        },
        "id": "vSUv1sKtdjRO",
        "outputId": "4b636f77-d4a7-43d4-f2b7-89ca9bc017d9"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "words = ta[ta['label']==1]['lemmatized']\n",
        "allwords_1 = []\n",
        "for wordlist in words:\n",
        "    allwords_1 += wordlist\n",
        "print(allwords_1[:100])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z90y2O3Gg9NP",
        "outputId": "01f95e26-88f7-4d6b-9a9f-a6307eee9617"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['remains', 'date', '5th', 'century', 'find', 'tomb', 'hwangnam-dong', 'show', 'man', \"'s\", 'bone', 'top', 'woman', \"'s\", 'bury', 'jewellery', 'expert', 'believe', 'silla', 'dynasty-era', 'tomb', 'build', 'noblewoman', 'lover', 'bodyguard', 'sacrifice', 'bury', 'top', \"'s\", 'suggestion', 'set-up', 'may', 'design', 'show', 'two', 'people', 'sex', 'silla', 'know', 'explicit', 'pottery', 'professional', 'identification', 'type', 'social', 'identification', 'sense', 'oneness', 'individual', 'profession', 'e.g', 'law', 'medicine', 'degree', 'individual', 'define', 'profession', 'member', 'professional', 'identity', 'consist', 'individual', \"'s\", 'alignment', 'role', 'responsibility', 'value', 'ethical', 'standard', 'consistent', 'practice', 'accept', 'specific', 'profession', 'source', 'professional', 'identification', 'researcher', 'find', 'desire', 'quality', 'rather', 'profit', 'associate', 'professional', 'identification', 'organization', 'tend', 'concerned', 'efficiency', 'profitability', 'whereas', 'profession', 'care', 'mainly', 'provide', 'highest-quality', 'service', 'define', 'profession']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mostcommon_small = nltk.probability.FreqDist(allwords_1).most_common(25)\n",
        "x, y = zip(*mostcommon_small)\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(x, y)\n",
        "plt.xlabel('Words', fontsize=10)\n",
        "plt.ylabel('Frequency of Words', fontsize=10)\n",
        "plt.yticks(fontsize=8)\n",
        "plt.xticks(rotation=60, fontsize=8)\n",
        "plt.title('Frequency of 25 Most Common Words for label=1', fontsize=12)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 433
        },
        "id": "5HnS4xJWhFWj",
        "outputId": "7b41108a-3bb0-4e6c-b28c-45b947272d1b"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "words = ta[ta['label']==0]['lemmatized']\n",
        "allwords_0 = []\n",
        "for wordlist in words:\n",
        "    allwords_0 += wordlist\n",
        "print(allwords_0[:100])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fMfMJiw0hUfM",
        "outputId": "1ae26d19-3eda-4f42-f21b-171c7a1232ab"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['myer', 'hold', '75', 'per', 'cent', 'designer', 'label', 'sale', 'wednesday', '22nd', 'department', 'store', 'understood', 'broker', 'deal', 'stock', 'international', 'designer', 'collection', 'time', 'european', 'american', 'retailer', 'move', 'say', 'attempt', 'revive', 'iconic', 'department', 'store', \"'s\", 'australian', 'market', 'bergen-belsen', 'concentration', 'camp', 'germany', 'liberate', 'british', 'canadian', 'troop', '1945', 'become', 'final', 'resting', 'place', '50,000', 'jew', 'gypsy', 'homosexual', 'nazi', 'opponent', 'disable', 'reverend', 'charles', 'martin', 'king', 'parson', 'one', 'handful', 'chaplains', 'helped', 'liberate', 'take', 'image', 'jonas', 'gutierrez', 'trigger', 'contract', 'extension', 'start', 'remain', 'seven', 'match', 'season', 'argentine', 'twice', 'beaten', 'testicular', 'cancer', '31-year-old', 'say', 'never', 'forgive', 'newcastle', 'handle', 'illness', 'one', 'game', 'closer', 'win', 'new', 'contract', 'st', 'james', 'park', 'five', 'american', 'monitor', 'three']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mostcommon_small = nltk.probability.FreqDist(allwords_0).most_common(25)\n",
        "x, y = zip(*mostcommon_small)\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(x, y)\n",
        "plt.xlabel('Words', fontsize=10)\n",
        "plt.ylabel('Frequency of Words', fontsize=10)\n",
        "plt.yticks(fontsize=8)\n",
        "plt.xticks(rotation=60, fontsize=8)\n",
        "plt.title('Frequency of 25 Most Common Words for label=0', fontsize=12)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 433
        },
        "id": "5BskSHAChdKb",
        "outputId": "ac9b5b7e-a164-4661-e1b0-548e6c4546a2"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "counter_1 = Counter(allwords_1)\n",
        "counter_0 = Counter(allwords_0)\n",
        "\n",
        "diff_dict = dict()\n",
        "for word in set(allwords_1 + allwords_0):\n",
        "    diff = (counter_1[word] - counter_0[word])\n",
        "    diff_dict[word] = diff\n",
        "\n",
        "sorted_diff = sorted(diff_dict.items(), key=lambda x: x[1], reverse=True)\n",
        "top = sorted_diff[:25]"
      ],
      "metadata": {
        "id": "JIQ2H8kqjuRS"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x, y = zip(*top)\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(x, y)\n",
        "plt.xlabel('Words', fontsize=10)\n",
        "plt.ylabel('Frequency Difference of Words', fontsize=10)\n",
        "plt.yticks(fontsize=8)\n",
        "plt.xticks(rotation=60, fontsize=8)\n",
        "plt.title('Frequency Difference of 25 Biggest Difference Words between label=1 and label=0', fontsize=12)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429
        },
        "id": "0RP-Qwozku7y",
        "outputId": "423d7b67-39eb-49b5-9a17-ea88f6971147"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}