Information Extraction

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "Name - Aditya Kothari\n",
        "\n",
        "Roll no. - I028\n",
        "\n",
        "Batch - B1"
      ],
      "metadata": {
        "id": "W1XsW6QvCslR"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "P6V8o0_hCk9V"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import nltk\n",
        "import spacy\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.util import bigrams\n",
        "from collections import Counter\n",
        "from nltk.util import bigrams, trigrams, ngrams"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nlp = spacy.load(\"en_core_web_sm\")"
      ],
      "metadata": {
        "id": "SdUY7zUJHEaf"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nltk.download('all')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E-v6n2SwGZe1",
        "outputId": "c3ec4ca0-6269-4e9b-d6af-8840be31be0f"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
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        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 18
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    {
      "cell_type": "code",
      "source": [
        "text = 'Ferrari S.p.A. is an Italian luxury sports car manufacturer based in Maranello, Italy. Founded in 1939 by Enzo Ferrari, the company adopted its current name in 1945 and began producing its line of cars in 1947. Ferrari became a public company in 1960, and from 1963 to 2014 it was a subsidiary of Fiat S.p.A.'"
      ],
      "metadata": {
        "id": "kxWFegmQGX2T"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "NLTK\n"
      ],
      "metadata": {
        "id": "bgdNApOpJqJE"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Tokenisation"
      ],
      "metadata": {
        "id": "4X1VJsOxNWXQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "words = nltk.word_tokenize(text)\n",
        "words"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JU24ZFwrGsS0",
        "outputId": "ec2d9a85-cb30-4c29-fb30-d3da8fc21bd8"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Ferrari',\n",
              " 'S.p.A.',\n",
              " 'is',\n",
              " 'an',\n",
              " 'Italian',\n",
              " 'luxury',\n",
              " 'sports',\n",
              " 'car',\n",
              " 'manufacturer',\n",
              " 'based',\n",
              " 'in',\n",
              " 'Maranello',\n",
              " ',',\n",
              " 'Italy',\n",
              " '.',\n",
              " 'Founded',\n",
              " 'in',\n",
              " '1939',\n",
              " 'by',\n",
              " 'Enzo',\n",
              " 'Ferrari',\n",
              " ',',\n",
              " 'the',\n",
              " 'company',\n",
              " 'adopted',\n",
              " 'its',\n",
              " 'current',\n",
              " 'name',\n",
              " 'in',\n",
              " '1945',\n",
              " 'and',\n",
              " 'began',\n",
              " 'producing',\n",
              " 'its',\n",
              " 'line',\n",
              " 'of',\n",
              " 'cars',\n",
              " 'in',\n",
              " '1947',\n",
              " '.',\n",
              " 'Ferrari',\n",
              " 'became',\n",
              " 'a',\n",
              " 'public',\n",
              " 'company',\n",
              " 'in',\n",
              " '1960',\n",
              " ',',\n",
              " 'and',\n",
              " 'from',\n",
              " '1963',\n",
              " 'to',\n",
              " '2014',\n",
              " 'it',\n",
              " 'was',\n",
              " 'a',\n",
              " 'subsidiary',\n",
              " 'of',\n",
              " 'Fiat',\n",
              " 'S.p.A',\n",
              " '.']"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "PoS Tagging"
      ],
      "metadata": {
        "id": "TMhmTlr9NT8H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pos_tag = nltk.pos_tag(words)\n",
        "pos_tag"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rG_XQywTGyXJ",
        "outputId": "b16efbb3-0d62-4906-b05a-9d5398389513"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('Ferrari', 'NNP'),\n",
              " ('S.p.A.', 'NNP'),\n",
              " ('is', 'VBZ'),\n",
              " ('an', 'DT'),\n",
              " ('Italian', 'JJ'),\n",
              " ('luxury', 'NN'),\n",
              " ('sports', 'NNS'),\n",
              " ('car', 'NN'),\n",
              " ('manufacturer', 'NN'),\n",
              " ('based', 'VBN'),\n",
              " ('in', 'IN'),\n",
              " ('Maranello', 'NNP'),\n",
              " (',', ','),\n",
              " ('Italy', 'NNP'),\n",
              " ('.', '.'),\n",
              " ('Founded', 'VBN'),\n",
              " ('in', 'IN'),\n",
              " ('1939', 'CD'),\n",
              " ('by', 'IN'),\n",
              " ('Enzo', 'NNP'),\n",
              " ('Ferrari', 'NNP'),\n",
              " (',', ','),\n",
              " ('the', 'DT'),\n",
              " ('company', 'NN'),\n",
              " ('adopted', 'VBD'),\n",
              " ('its', 'PRP$'),\n",
              " ('current', 'JJ'),\n",
              " ('name', 'NN'),\n",
              " ('in', 'IN'),\n",
              " ('1945', 'CD'),\n",
              " ('and', 'CC'),\n",
              " ('began', 'VBD'),\n",
              " ('producing', 'VBG'),\n",
              " ('its', 'PRP$'),\n",
              " ('line', 'NN'),\n",
              " ('of', 'IN'),\n",
              " ('cars', 'NNS'),\n",
              " ('in', 'IN'),\n",
              " ('1947', 'CD'),\n",
              " ('.', '.'),\n",
              " ('Ferrari', 'NNP'),\n",
              " ('became', 'VBD'),\n",
              " ('a', 'DT'),\n",
              " ('public', 'JJ'),\n",
              " ('company', 'NN'),\n",
              " ('in', 'IN'),\n",
              " ('1960', 'CD'),\n",
              " (',', ','),\n",
              " ('and', 'CC'),\n",
              " ('from', 'IN'),\n",
              " ('1963', 'CD'),\n",
              " ('to', 'TO'),\n",
              " ('2014', 'CD'),\n",
              " ('it', 'PRP'),\n",
              " ('was', 'VBD'),\n",
              " ('a', 'DT'),\n",
              " ('subsidiary', 'NN'),\n",
              " ('of', 'IN'),\n",
              " ('Fiat', 'NNP'),\n",
              " ('S.p.A', 'NNP'),\n",
              " ('.', '.')]"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "PoS Tagging"
      ],
      "metadata": {
        "id": "kMcQENHyNYwA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "chunks = nltk.ne_chunk(pos_tag)\n",
        "print(chunks)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qXGN-Ma9JmwE",
        "outputId": "42847dc7-163c-44cc-bbc4-e1a373d766e5"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(S\n",
            "  (PERSON Ferrari/NNP)\n",
            "  S.p.A./NNP\n",
            "  is/VBZ\n",
            "  an/DT\n",
            "  (GPE Italian/JJ)\n",
            "  luxury/NN\n",
            "  sports/NNS\n",
            "  car/NN\n",
            "  manufacturer/NN\n",
            "  based/VBN\n",
            "  in/IN\n",
            "  (GPE Maranello/NNP)\n",
            "  ,/,\n",
            "  (GPE Italy/NNP)\n",
            "  ./.\n",
            "  Founded/VBN\n",
            "  in/IN\n",
            "  1939/CD\n",
            "  by/IN\n",
            "  (PERSON Enzo/NNP Ferrari/NNP)\n",
            "  ,/,\n",
            "  the/DT\n",
            "  company/NN\n",
            "  adopted/VBD\n",
            "  its/PRP$\n",
            "  current/JJ\n",
            "  name/NN\n",
            "  in/IN\n",
            "  1945/CD\n",
            "  and/CC\n",
            "  began/VBD\n",
            "  producing/VBG\n",
            "  its/PRP$\n",
            "  line/NN\n",
            "  of/IN\n",
            "  cars/NNS\n",
            "  in/IN\n",
            "  1947/CD\n",
            "  ./.\n",
            "  (PERSON Ferrari/NNP)\n",
            "  became/VBD\n",
            "  a/DT\n",
            "  public/JJ\n",
            "  company/NN\n",
            "  in/IN\n",
            "  1960/CD\n",
            "  ,/,\n",
            "  and/CC\n",
            "  from/IN\n",
            "  1963/CD\n",
            "  to/TO\n",
            "  2014/CD\n",
            "  it/PRP\n",
            "  was/VBD\n",
            "  a/DT\n",
            "  subsidiary/NN\n",
            "  of/IN\n",
            "  (PERSON Fiat/NNP)\n",
            "  S.p.A/NNP\n",
            "  ./.)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Spacy\n"
      ],
      "metadata": {
        "id": "DAT4loERJwLC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "PoS Tagging"
      ],
      "metadata": {
        "id": "R3rTp4eXNPeo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "doc = nlp(text)\n",
        "\n",
        "for token in doc:\n",
        "    print(f\"{token.text:{12}}{token.pos_:{12}}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R52i6thKG2_f",
        "outputId": "fb0155ed-6a16-43c2-e901-62b8fd46c5ca"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Ferrari     PROPN       \n",
            "S.p         PROPN       \n",
            ".           PUNCT       \n",
            "A.          PROPN       \n",
            "is          AUX         \n",
            "an          DET         \n",
            "Italian     ADJ         \n",
            "luxury      NOUN        \n",
            "sports      NOUN        \n",
            "car         NOUN        \n",
            "manufacturerNOUN        \n",
            "based       VERB        \n",
            "in          ADP         \n",
            "Maranello   PROPN       \n",
            ",           PUNCT       \n",
            "Italy       PROPN       \n",
            ".           PUNCT       \n",
            "Founded     VERB        \n",
            "in          ADP         \n",
            "1939        NUM         \n",
            "by          ADP         \n",
            "Enzo        PROPN       \n",
            "Ferrari     PROPN       \n",
            ",           PUNCT       \n",
            "the         DET         \n",
            "company     NOUN        \n",
            "adopted     VERB        \n",
            "its         PRON        \n",
            "current     ADJ         \n",
            "name        NOUN        \n",
            "in          ADP         \n",
            "1945        NUM         \n",
            "and         CCONJ       \n",
            "began       VERB        \n",
            "producing   VERB        \n",
            "its         PRON        \n",
            "line        NOUN        \n",
            "of          ADP         \n",
            "cars        NOUN        \n",
            "in          ADP         \n",
            "1947        NUM         \n",
            ".           PUNCT       \n",
            "Ferrari     PROPN       \n",
            "became      VERB        \n",
            "a           DET         \n",
            "public      ADJ         \n",
            "company     NOUN        \n",
            "in          ADP         \n",
            "1960        NUM         \n",
            ",           PUNCT       \n",
            "and         CCONJ       \n",
            "from        ADP         \n",
            "1963        NUM         \n",
            "to          ADP         \n",
            "2014        NUM         \n",
            "it          PRON        \n",
            "was         AUX         \n",
            "a           DET         \n",
            "subsidiary  NOUN        \n",
            "of          ADP         \n",
            "Fiat        PROPN       \n",
            "S.p         PROPN       \n",
            ".           PUNCT       \n",
            "A.          PROPN       \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "NER"
      ],
      "metadata": {
        "id": "iIWjWwpSNNDH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "doc=nlp(text)\n",
        "for ent in doc.ents:\n",
        "    print(f\"{ent.text} ({ent.label_})\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hpvnxn_XG4KQ",
        "outputId": "727928dc-19db-4ff7-ace1-d90ff5808219"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Ferrari S.p.A. (ORG)\n",
            "Italian (NORP)\n",
            "Maranello (GPE)\n",
            "Italy (GPE)\n",
            "1939 (DATE)\n",
            "Enzo Ferrari (PERSON)\n",
            "1945 (DATE)\n",
            "1947 (DATE)\n",
            "Ferrari (NORP)\n",
            "1960 (DATE)\n",
            "1963 (DATE)\n",
            "2014 (DATE)\n",
            "Fiat S.p.A. (ORG)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Task-2\n"
      ],
      "metadata": {
        "id": "HKJGmuwtNKhP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dataset"
      ],
      "metadata": {
        "id": "nTrHmQHbPBUS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/Womens Clothing E-Commerce Reviews 2.csv')"
      ],
      "metadata": {
        "id": "UzxhG8XmNMB3"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 615
        },
        "id": "HtOsJYWhQGEy",
        "outputId": "01e9fc98-f6b5-44bc-c3b5-0b3228592d4a"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Unnamed: 0  Clothing ID  Age  \\\n",
              "0               0          767   33   \n",
              "1               1         1080   34   \n",
              "2               2         1077   60   \n",
              "3               3         1049   50   \n",
              "4               4          847   47   \n",
              "...           ...          ...  ...   \n",
              "23481       23481         1104   34   \n",
              "23482       23482          862   48   \n",
              "23483       23483         1104   31   \n",
              "23484       23484         1084   28   \n",
              "23485       23485         1104   52   \n",
              "\n",
              "                                                   Title  \\\n",
              "0                                                    NaN   \n",
              "1                                                    NaN   \n",
              "2                                Some major design flaws   \n",
              "3                                       My favorite buy!   \n",
              "4                                       Flattering shirt   \n",
              "...                                                  ...   \n",
              "23481                     Great dress for many occasions   \n",
              "23482                         Wish it was made of cotton   \n",
              "23483                              Cute, but see through   \n",
              "23484  Very cute dress, perfect for summer parties an...   \n",
              "23485                    Please make more like this one!   \n",
              "\n",
              "                                             Review Text  Rating  \\\n",
              "0      Absolutely wonderful - silky and sexy and comf...       4   \n",
              "1      Love this dress!  it's sooo pretty.  i happene...       5   \n",
              "2      I had such high hopes for this dress and reall...       3   \n",
              "3      I love, love, love this jumpsuit. it's fun, fl...       5   \n",
              "4      This shirt is very flattering to all due to th...       5   \n",
              "...                                                  ...     ...   \n",
              "23481  I was very happy to snag this dress at such a ...       5   \n",
              "23482  It reminds me of maternity clothes. soft, stre...       3   \n",
              "23483  This fit well, but the top was very see throug...       3   \n",
              "23484  I bought this dress for a wedding i have this ...       3   \n",
              "23485  This dress in a lovely platinum is feminine an...       5   \n",
              "\n",
              "       Recommended IND  Positive Feedback Count   Division Name  \\\n",
              "0                    1                        0       Initmates   \n",
              "1                    1                        4         General   \n",
              "2                    0                        0         General   \n",
              "3                    1                        0  General Petite   \n",
              "4                    1                        6         General   \n",
              "...                ...                      ...             ...   \n",
              "23481                1                        0  General Petite   \n",
              "23482                1                        0  General Petite   \n",
              "23483                0                        1  General Petite   \n",
              "23484                1                        2         General   \n",
              "23485                1                       22  General Petite   \n",
              "\n",
              "      Department Name Class Name  \n",
              "0            Intimate  Intimates  \n",
              "1             Dresses    Dresses  \n",
              "2             Dresses    Dresses  \n",
              "3             Bottoms      Pants  \n",
              "4                Tops    Blouses  \n",
              "...               ...        ...  \n",
              "23481         Dresses    Dresses  \n",
              "23482            Tops      Knits  \n",
              "23483         Dresses    Dresses  \n",
              "23484         Dresses    Dresses  \n",
              "23485         Dresses    Dresses  \n",
              "\n",
              "[23486 rows x 11 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-344a5f96-e9bf-47fa-a131-542462c1f449\" 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>Unnamed: 0</th>\n",
              "      <th>Clothing ID</th>\n",
              "      <th>Age</th>\n",
              "      <th>Title</th>\n",
              "      <th>Review Text</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Recommended IND</th>\n",
              "      <th>Positive Feedback Count</th>\n",
              "      <th>Division Name</th>\n",
              "      <th>Department Name</th>\n",
              "      <th>Class Name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>767</td>\n",
              "      <td>33</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Absolutely wonderful - silky and sexy and comf...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Initmates</td>\n",
              "      <td>Intimate</td>\n",
              "      <td>Intimates</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1080</td>\n",
              "      <td>34</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Love this dress!  it's sooo pretty.  i happene...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>General</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1077</td>\n",
              "      <td>60</td>\n",
              "      <td>Some major design flaws</td>\n",
              "      <td>I had such high hopes for this dress and reall...</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>General</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1049</td>\n",
              "      <td>50</td>\n",
              "      <td>My favorite buy!</td>\n",
              "      <td>I love, love, love this jumpsuit. it's fun, fl...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Bottoms</td>\n",
              "      <td>Pants</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>847</td>\n",
              "      <td>47</td>\n",
              "      <td>Flattering shirt</td>\n",
              "      <td>This shirt is very flattering to all due to th...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>General</td>\n",
              "      <td>Tops</td>\n",
              "      <td>Blouses</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23481</th>\n",
              "      <td>23481</td>\n",
              "      <td>1104</td>\n",
              "      <td>34</td>\n",
              "      <td>Great dress for many occasions</td>\n",
              "      <td>I was very happy to snag this dress at such a ...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23482</th>\n",
              "      <td>23482</td>\n",
              "      <td>862</td>\n",
              "      <td>48</td>\n",
              "      <td>Wish it was made of cotton</td>\n",
              "      <td>It reminds me of maternity clothes. soft, stre...</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Tops</td>\n",
              "      <td>Knits</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23483</th>\n",
              "      <td>23483</td>\n",
              "      <td>1104</td>\n",
              "      <td>31</td>\n",
              "      <td>Cute, but see through</td>\n",
              "      <td>This fit well, but the top was very see throug...</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23484</th>\n",
              "      <td>23484</td>\n",
              "      <td>1084</td>\n",
              "      <td>28</td>\n",
              "      <td>Very cute dress, perfect for summer parties an...</td>\n",
              "      <td>I bought this dress for a wedding i have this ...</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>General</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23485</th>\n",
              "      <td>23485</td>\n",
              "      <td>1104</td>\n",
              "      <td>52</td>\n",
              "      <td>Please make more like this one!</td>\n",
              "      <td>This dress in a lovely platinum is feminine an...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>22</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23486 rows × 11 columns</p>\n",
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              "  @keyframes spin {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "    </div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dropna(subset=[\"Review Text\", \"Division Name\"], inplace=True)\n",
        "df.drop('Unnamed: 0', axis =1, inplace = True)"
      ],
      "metadata": {
        "id": "gYn6V3QwVAQp"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_word_count(text):\n",
        "    word = text.split()\n",
        "    return len(word)\n",
        "\n",
        "df['Word Count'] = df['Review Text'].apply(get_word_count)"
      ],
      "metadata": {
        "id": "qwXH7FjmVcwU"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_bigrams(text):\n",
        "    wordd = nltk.word_tokenize(text.lower())\n",
        "    bigram_list = list(ngrams(wordd, 2))\n",
        "    return [' '.join(bigram) for bigram in bigram_list]\n",
        "\n",
        "df['Bigrams'] = df['Review Text'].apply(get_bigrams)"
      ],
      "metadata": {
        "id": "h0KitoM6OxQS"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['pos_tag'] = df['Review Text'].apply(lambda x: nltk.pos_tag(nltk.word_tokenize(x)))\n",
        "\n",
        "df['NER'] = df['pos_tag'].apply(lambda x: nltk.ne_chunk(x))"
      ],
      "metadata": {
        "id": "6L434OT6Vv--"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['NER']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ePadQm66jVtr",
        "outputId": "a0bf9f9c-22b1-42b3-dc7b-516a2069bf4b"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        [(Absolutely, RB), (wonderful, JJ), (-, :), (s...\n",
              "1        [(Love, VB), (this, DT), (dress, NN), (!, .), ...\n",
              "2        [(I, PRP), (had, VBD), (such, JJ), (high, JJ),...\n",
              "3        [(I, PRP), (love, VBP), (,, ,), (love, VBP), (...\n",
              "4        [(This, DT), (shirt, NN), (is, VBZ), (very, RB...\n",
              "                               ...                        \n",
              "23481    [(I, PRP), (was, VBD), (very, RB), (happy, JJ)...\n",
              "23482    [(It, PRP), (reminds, VBZ), (me, PRP), (of, IN...\n",
              "23483    [(This, DT), (fit, NN), (well, RB), (,, ,), (b...\n",
              "23484    [(I, PRP), (bought, VBD), (this, DT), (dress, ...\n",
              "23485    [(This, DT), (dress, NN), (in, IN), (a, DT), (...\n",
              "Name: NER, Length: 22628, dtype: object"
            ]
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          "metadata": {},
          "execution_count": 40
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "df.drop('pos_tags',axis=1,inplace=True)"
      ],
      "metadata": {
        "id": "JqAm8qSnm0mg"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "KgLmcT8bTIUT",
        "outputId": "f4143042-d8f1-472a-f51c-9cc7ee21b6b3"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Clothing ID  Age                                              Title  \\\n",
              "0              767   33                                                NaN   \n",
              "1             1080   34                                                NaN   \n",
              "2             1077   60                            Some major design flaws   \n",
              "3             1049   50                                   My favorite buy!   \n",
              "4              847   47                                   Flattering shirt   \n",
              "...            ...  ...                                                ...   \n",
              "23481         1104   34                     Great dress for many occasions   \n",
              "23482          862   48                         Wish it was made of cotton   \n",
              "23483         1104   31                              Cute, but see through   \n",
              "23484         1084   28  Very cute dress, perfect for summer parties an...   \n",
              "23485         1104   52                    Please make more like this one!   \n",
              "\n",
              "                                             Review Text  Rating  \\\n",
              "0      Absolutely wonderful - silky and sexy and comf...       4   \n",
              "1      Love this dress!  it's sooo pretty.  i happene...       5   \n",
              "2      I had such high hopes for this dress and reall...       3   \n",
              "3      I love, love, love this jumpsuit. it's fun, fl...       5   \n",
              "4      This shirt is very flattering to all due to th...       5   \n",
              "...                                                  ...     ...   \n",
              "23481  I was very happy to snag this dress at such a ...       5   \n",
              "23482  It reminds me of maternity clothes. soft, stre...       3   \n",
              "23483  This fit well, but the top was very see throug...       3   \n",
              "23484  I bought this dress for a wedding i have this ...       3   \n",
              "23485  This dress in a lovely platinum is feminine an...       5   \n",
              "\n",
              "       Recommended IND  Positive Feedback Count   Division Name  \\\n",
              "0                    1                        0       Initmates   \n",
              "1                    1                        4         General   \n",
              "2                    0                        0         General   \n",
              "3                    1                        0  General Petite   \n",
              "4                    1                        6         General   \n",
              "...                ...                      ...             ...   \n",
              "23481                1                        0  General Petite   \n",
              "23482                1                        0  General Petite   \n",
              "23483                0                        1  General Petite   \n",
              "23484                1                        2         General   \n",
              "23485                1                       22  General Petite   \n",
              "\n",
              "      Department Name Class Name  Word Count  \\\n",
              "0            Intimate  Intimates           8   \n",
              "1             Dresses    Dresses          62   \n",
              "2             Dresses    Dresses          98   \n",
              "3             Bottoms      Pants          22   \n",
              "4                Tops    Blouses          36   \n",
              "...               ...        ...         ...   \n",
              "23481         Dresses    Dresses          28   \n",
              "23482            Tops      Knits          38   \n",
              "23483         Dresses    Dresses          42   \n",
              "23484         Dresses    Dresses          86   \n",
              "23485         Dresses    Dresses          19   \n",
              "\n",
              "                                                 Bigrams  \\\n",
              "0      [absolutely wonderful, wonderful -, - silky, s...   \n",
              "1      [love this, this dress, dress !, ! it, it 's, ...   \n",
              "2      [i had, had such, such high, high hopes, hopes...   \n",
              "3      [i love, love ,, , love, love ,, , love, love ...   \n",
              "4      [this shirt, shirt is, is very, very flatterin...   \n",
              "...                                                  ...   \n",
              "23481  [i was, was very, very happy, happy to, to sna...   \n",
              "23482  [it reminds, reminds me, me of, of maternity, ...   \n",
              "23483  [this fit, fit well, well ,, , but, but the, t...   \n",
              "23484  [i bought, bought this, this dress, dress for,...   \n",
              "23485  [this dress, dress in, in a, a lovely, lovely ...   \n",
              "\n",
              "                                                 pos_tag  \\\n",
              "0      [(Absolutely, RB), (wonderful, JJ), (-, :), (s...   \n",
              "1      [(Love, VB), (this, DT), (dress, NN), (!, .), ...   \n",
              "2      [(I, PRP), (had, VBD), (such, JJ), (high, JJ),...   \n",
              "3      [(I, PRP), (love, VBP), (,, ,), (love, VBP), (...   \n",
              "4      [(This, DT), (shirt, NN), (is, VBZ), (very, RB...   \n",
              "...                                                  ...   \n",
              "23481  [(I, PRP), (was, VBD), (very, RB), (happy, JJ)...   \n",
              "23482  [(It, PRP), (reminds, VBZ), (me, PRP), (of, IN...   \n",
              "23483  [(This, DT), (fit, NN), (well, RB), (,, ,), (b...   \n",
              "23484  [(I, PRP), (bought, VBD), (this, DT), (dress, ...   \n",
              "23485  [(This, DT), (dress, NN), (in, IN), (a, DT), (...   \n",
              "\n",
              "                                                     NER  \n",
              "0      [(Absolutely, RB), (wonderful, JJ), (-, :), (s...  \n",
              "1      [(Love, VB), (this, DT), (dress, NN), (!, .), ...  \n",
              "2      [(I, PRP), (had, VBD), (such, JJ), (high, JJ),...  \n",
              "3      [(I, PRP), (love, VBP), (,, ,), (love, VBP), (...  \n",
              "4      [(This, DT), (shirt, NN), (is, VBZ), (very, RB...  \n",
              "...                                                  ...  \n",
              "23481  [(I, PRP), (was, VBD), (very, RB), (happy, JJ)...  \n",
              "23482  [(It, PRP), (reminds, VBZ), (me, PRP), (of, IN...  \n",
              "23483  [(This, DT), (fit, NN), (well, RB), (,, ,), (b...  \n",
              "23484  [(I, PRP), (bought, VBD), (this, DT), (dress, ...  \n",
              "23485  [(This, DT), (dress, NN), (in, IN), (a, DT), (...  \n",
              "\n",
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              "      <th>Clothing ID</th>\n",
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              "      <th>Review Text</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Recommended IND</th>\n",
              "      <th>Positive Feedback Count</th>\n",
              "      <th>Division Name</th>\n",
              "      <th>Department Name</th>\n",
              "      <th>Class Name</th>\n",
              "      <th>Word Count</th>\n",
              "      <th>Bigrams</th>\n",
              "      <th>pos_tag</th>\n",
              "      <th>NER</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>767</td>\n",
              "      <td>33</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Absolutely wonderful - silky and sexy and comf...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Initmates</td>\n",
              "      <td>Intimate</td>\n",
              "      <td>Intimates</td>\n",
              "      <td>8</td>\n",
              "      <td>[absolutely wonderful, wonderful -, - silky, s...</td>\n",
              "      <td>[(Absolutely, RB), (wonderful, JJ), (-, :), (s...</td>\n",
              "      <td>[(Absolutely, RB), (wonderful, JJ), (-, :), (s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1080</td>\n",
              "      <td>34</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Love this dress!  it's sooo pretty.  i happene...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>General</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>62</td>\n",
              "      <td>[love this, this dress, dress !, ! it, it 's, ...</td>\n",
              "      <td>[(Love, VB), (this, DT), (dress, NN), (!, .), ...</td>\n",
              "      <td>[(Love, VB), (this, DT), (dress, NN), (!, .), ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1077</td>\n",
              "      <td>60</td>\n",
              "      <td>Some major design flaws</td>\n",
              "      <td>I had such high hopes for this dress and reall...</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>General</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>98</td>\n",
              "      <td>[i had, had such, such high, high hopes, hopes...</td>\n",
              "      <td>[(I, PRP), (had, VBD), (such, JJ), (high, JJ),...</td>\n",
              "      <td>[(I, PRP), (had, VBD), (such, JJ), (high, JJ),...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1049</td>\n",
              "      <td>50</td>\n",
              "      <td>My favorite buy!</td>\n",
              "      <td>I love, love, love this jumpsuit. it's fun, fl...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Bottoms</td>\n",
              "      <td>Pants</td>\n",
              "      <td>22</td>\n",
              "      <td>[i love, love ,, , love, love ,, , love, love ...</td>\n",
              "      <td>[(I, PRP), (love, VBP), (,, ,), (love, VBP), (...</td>\n",
              "      <td>[(I, PRP), (love, VBP), (,, ,), (love, VBP), (...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>847</td>\n",
              "      <td>47</td>\n",
              "      <td>Flattering shirt</td>\n",
              "      <td>This shirt is very flattering to all due to th...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>General</td>\n",
              "      <td>Tops</td>\n",
              "      <td>Blouses</td>\n",
              "      <td>36</td>\n",
              "      <td>[this shirt, shirt is, is very, very flatterin...</td>\n",
              "      <td>[(This, DT), (shirt, NN), (is, VBZ), (very, RB...</td>\n",
              "      <td>[(This, DT), (shirt, NN), (is, VBZ), (very, RB...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23481</th>\n",
              "      <td>1104</td>\n",
              "      <td>34</td>\n",
              "      <td>Great dress for many occasions</td>\n",
              "      <td>I was very happy to snag this dress at such a ...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>28</td>\n",
              "      <td>[i was, was very, very happy, happy to, to sna...</td>\n",
              "      <td>[(I, PRP), (was, VBD), (very, RB), (happy, JJ)...</td>\n",
              "      <td>[(I, PRP), (was, VBD), (very, RB), (happy, JJ)...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23482</th>\n",
              "      <td>862</td>\n",
              "      <td>48</td>\n",
              "      <td>Wish it was made of cotton</td>\n",
              "      <td>It reminds me of maternity clothes. soft, stre...</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Tops</td>\n",
              "      <td>Knits</td>\n",
              "      <td>38</td>\n",
              "      <td>[it reminds, reminds me, me of, of maternity, ...</td>\n",
              "      <td>[(It, PRP), (reminds, VBZ), (me, PRP), (of, IN...</td>\n",
              "      <td>[(It, PRP), (reminds, VBZ), (me, PRP), (of, IN...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23483</th>\n",
              "      <td>1104</td>\n",
              "      <td>31</td>\n",
              "      <td>Cute, but see through</td>\n",
              "      <td>This fit well, but the top was very see throug...</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>42</td>\n",
              "      <td>[this fit, fit well, well ,, , but, but the, t...</td>\n",
              "      <td>[(This, DT), (fit, NN), (well, RB), (,, ,), (b...</td>\n",
              "      <td>[(This, DT), (fit, NN), (well, RB), (,, ,), (b...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23484</th>\n",
              "      <td>1084</td>\n",
              "      <td>28</td>\n",
              "      <td>Very cute dress, perfect for summer parties an...</td>\n",
              "      <td>I bought this dress for a wedding i have this ...</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>General</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>86</td>\n",
              "      <td>[i bought, bought this, this dress, dress for,...</td>\n",
              "      <td>[(I, PRP), (bought, VBD), (this, DT), (dress, ...</td>\n",
              "      <td>[(I, PRP), (bought, VBD), (this, DT), (dress, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23485</th>\n",
              "      <td>1104</td>\n",
              "      <td>52</td>\n",
              "      <td>Please make more like this one!</td>\n",
              "      <td>This dress in a lovely platinum is feminine an...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>22</td>\n",
              "      <td>General Petite</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>Dresses</td>\n",
              "      <td>19</td>\n",
              "      <td>[this dress, dress in, in a, a lovely, lovely ...</td>\n",
              "      <td>[(This, DT), (dress, NN), (in, IN), (a, DT), (...</td>\n",
              "      <td>[(This, DT), (dress, NN), (in, IN), (a, DT), (...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>22628 rows × 14 columns</p>\n",
              "</div>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "        document.querySelector('#df-6d9689fb-fd06-4e8b-aefc-42c6da97cb92 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-6d9689fb-fd06-4e8b-aefc-42c6da97cb92');\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",
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              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-83b3c055-01a2-4520-93df-cec3f14fea65')\"\n",
              "            title=\"Suggest charts.\"\n",
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              "</svg>\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
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              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "\n",
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              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    90% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-83b3c055-01a2-4520-93df-cec3f14fea65 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dataset link - https://www.kaggle.com/datasets/nicapotato/womens-ecommerce-clothing-reviews?resource=download"
      ],
      "metadata": {
        "id": "ZYpDSnc-Uaht"
      }
    }
  ]
}