200968268_L3_Ex2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "90cfc07b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd # importing libraries\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import random\n",
    "import string\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1ceb9e9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Positive Feedback Count</th>\n",
       "      <th>Division Name</th>\n",
       "      <th>Department Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Recommended IND</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>0</td>\n",
       "      <td>Initmates</td>\n",
       "      <td>Intimate</td>\n",
       "      <td>Intimates</td>\n",
       "      <td>1</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>4</td>\n",
       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>1</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>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>General Petite</td>\n",
       "      <td>Bottoms</td>\n",
       "      <td>Pants</td>\n",
       "      <td>1</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>6</td>\n",
       "      <td>General</td>\n",
       "      <td>Tops</td>\n",
       "      <td>Blouses</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Clothing ID  Age                    Title  \\\n",
       "0           0          767   33                      NaN   \n",
       "1           1         1080   34                      NaN   \n",
       "2           2         1077   60  Some major design flaws   \n",
       "3           3         1049   50         My favorite buy!   \n",
       "4           4          847   47         Flattering shirt   \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",
       "   Positive Feedback Count   Division Name Department Name   Category  \\\n",
       "0                        0       Initmates        Intimate  Intimates   \n",
       "1                        4         General         Dresses    Dresses   \n",
       "2                        0         General         Dresses    Dresses   \n",
       "3                        0  General Petite         Bottoms      Pants   \n",
       "4                        6         General            Tops    Blouses   \n",
       "\n",
       "   Recommended IND  \n",
       "0                1  \n",
       "1                1  \n",
       "2                0  \n",
       "3                1  \n",
       "4                1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl=pd.read_csv(\"clothing.csv\")\n",
    "cl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4412fc60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                    0\n",
       "Clothing ID                   0\n",
       "Age                           0\n",
       "Title                      3810\n",
       "Review Text                 845\n",
       "Rating                        0\n",
       "Positive Feedback Count       0\n",
       "Division Name                14\n",
       "Department Name              14\n",
       "Category                     14\n",
       "Recommended IND               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e633ee0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                 0\n",
       "Clothing ID                0\n",
       "Age                        0\n",
       "Title                      0\n",
       "Review Text                0\n",
       "Rating                     0\n",
       "Positive Feedback Count    0\n",
       "Division Name              0\n",
       "Department Name            0\n",
       "Category                   0\n",
       "Recommended IND            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl.dropna(inplace=True)\n",
    "cl.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d235aa1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "cl =cl.drop(columns=['Unnamed: 0', 'Title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3f6e8120",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Clothing ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Review Text</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Positive Feedback Count</th>\n",
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       "      <th>2</th>\n",
       "      <td>1077</td>\n",
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       "      <td>I had such high hopes for this dress and reall...</td>\n",
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       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1049</td>\n",
       "      <td>50</td>\n",
       "      <td>I love, love, love this jumpsuit. it's fun, fl...</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>General Petite</td>\n",
       "      <td>Bottoms</td>\n",
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       "      <th>5</th>\n",
       "      <td>1080</td>\n",
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       "      <td>I love tracy reese dresses, but this one is no...</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>858</td>\n",
       "      <td>39</td>\n",
       "      <td>I aded this in my basket at hte last mintue to...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>General Petite</td>\n",
       "      <td>Tops</td>\n",
       "      <td>Knits</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Clothing ID  Age                                        Review Text  \\\n",
       "2         1077   60  I had such high hopes for this dress and reall...   \n",
       "3         1049   50  I love, love, love this jumpsuit. it's fun, fl...   \n",
       "4          847   47  This shirt is very flattering to all due to th...   \n",
       "5         1080   49  I love tracy reese dresses, but this one is no...   \n",
       "6          858   39  I aded this in my basket at hte last mintue to...   \n",
       "\n",
       "   Rating  Positive Feedback Count   Division Name Department Name Category  \\\n",
       "2       3                        0         General         Dresses  Dresses   \n",
       "3       5                        0  General Petite         Bottoms    Pants   \n",
       "4       5                        6         General            Tops  Blouses   \n",
       "5       2                        4         General         Dresses  Dresses   \n",
       "6       5                        1  General Petite            Tops    Knits   \n",
       "\n",
       "   Recommended IND  \n",
       "2                0  \n",
       "3                1  \n",
       "4                1  \n",
       "5                0  \n",
       "6                1  "
      ]
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e1865a90",
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = cl.groupby(['Clothing ID'], as_index=False).count()\n",
    "below5id = a.loc[a['Age'] < 5]['Clothing ID'].to_numpy()\n",
    "below5id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ddbcefd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0,below5id.size-1):\n",
    "    cl.drop(cl[cl['Clothing ID'] == below5id[i]].index)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "045de631",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Clothing ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Review Text</th>\n",
       "      <th>Rating</th>\n",
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       "      <th>Division Name</th>\n",
       "      <th>Department Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Recommended IND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1077</td>\n",
       "      <td>60</td>\n",
       "      <td>I had such high hopes for this dress and reall...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1049</td>\n",
       "      <td>50</td>\n",
       "      <td>I love, love, love this jumpsuit. it's fun, fl...</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>General Petite</td>\n",
       "      <td>Bottoms</td>\n",
       "      <td>Pants</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>847</td>\n",
       "      <td>47</td>\n",
       "      <td>This shirt is very flattering to all due to th...</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>General</td>\n",
       "      <td>Tops</td>\n",
       "      <td>Blouses</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1080</td>\n",
       "      <td>49</td>\n",
       "      <td>I love tracy reese dresses, but this one is no...</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>858</td>\n",
       "      <td>39</td>\n",
       "      <td>I aded this in my basket at hte last mintue to...</td>\n",
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       "      <td>General Petite</td>\n",
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       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "   Clothing ID  Age                                        Review Text  \\\n",
       "2         1077   60  I had such high hopes for this dress and reall...   \n",
       "3         1049   50  I love, love, love this jumpsuit. it's fun, fl...   \n",
       "4          847   47  This shirt is very flattering to all due to th...   \n",
       "5         1080   49  I love tracy reese dresses, but this one is no...   \n",
       "6          858   39  I aded this in my basket at hte last mintue to...   \n",
       "\n",
       "   Rating  Positive Feedback Count   Division Name Department Name Category  \\\n",
       "2       3                        0         General         Dresses  Dresses   \n",
       "3       5                        0  General Petite         Bottoms    Pants   \n",
       "4       5                        6         General            Tops  Blouses   \n",
       "5       2                        4         General         Dresses  Dresses   \n",
       "6       5                        1  General Petite            Tops    Knits   \n",
       "\n",
       "   Recommended IND  \n",
       "2                0  \n",
       "3                1  \n",
       "4                1  \n",
       "5                0  \n",
       "6                1  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "cl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f48fe4d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "contractions = {\n",
    "\"a'ight\":\"alright\",\n",
    "\"ain't\":\"are not\",\n",
    "\"amn't\":\"am not\",\n",
    "\"aren't\":\"are not\",\n",
    "\"can't\":\"cannot\",\n",
    "\"'cause\": \"because\",\n",
    "\"could've\":\"could have\",\n",
    "\"couldn't\":\"could not\",\n",
    "\"couldn't've\":\"could not have\",\n",
    "\"daren't\":\"dare not\",\n",
    "\"daresn't\":\"dare not\",\n",
    "\"dasn't\":\"dare not\",\n",
    "\"didn't\":\"did not\",\n",
    "\"doesn't\":\"does not\",\n",
    "\"don't\":\"do not\",\n",
    "\"everybody's\":\"everybody is\",\n",
    "\"everyone's\":\"everyone is\",\n",
    "\"giv'n\":\"given\",\n",
    "\"gonna\":\"going to\",\n",
    "\"gon't\":\"go not\", \n",
    "\"gotta\":\"got to\",\n",
    "\"hadn't\":\"had not\",\n",
    "\"had've\":\"had have\",\n",
    "\"hasn't\":\"has not\",\n",
    "\"haven't\":\"have not\",\n",
    "\"he'd\":\"he had\", \n",
    "\"he'll\":\"he will\",\n",
    "\"he's\":\"he is\",\n",
    "\"here's\":\"here is\",\n",
    "\"how'd\":\"how did\",\n",
    "\"how'll\":\"how will\",\n",
    "\"how're\":\"how are\",\n",
    "\"how's\":\"how is\",\n",
    "\"I'd\":\"I had\",\n",
    "\"I'd've\":\"I would have\",\n",
    "\"I'd'nt\":\"I would not\",\n",
    "\"I'd'nt've\":\"I would not have\",\n",
    "\"I'll\":\"I will\",\n",
    "\"I'm\":\"I am\",\n",
    "\"I've\":\"I have\",\n",
    "\"isn't\":\"is not\",\n",
    "\"it'd\":\"it would\",\n",
    "\"it'll\":\"it will\",\n",
    "\"it's\":\"it is\",\n",
    "\"let's\":\"let us\",\n",
    "\"ma'am\":\"madam\",\n",
    "\"mayn't\":\"may not\",\n",
    "\"may've\":\"may have\",\n",
    "\"mightn't\":\"might not\",\n",
    "\"might've\":\"might have\",\n",
    "\"mustn't\":\"must not\",\n",
    "\"mustn't've\":\"must not have\",\n",
    "\"must've\":\"must have\",\n",
    "\"needn't\":\"need not\",\n",
    "\"needn't've\":\"need not have\",\n",
    "\"o'clock\":\"of the clock\",\n",
    "\"oughtn't\":\"ought not\",\n",
    "\"oughtn't've\":\"ought not have\",\n",
    "\"shan't\":\"shall not\",\n",
    "\"she'd\":\"she would\",\n",
    "\"she'll\":\"she will\",\n",
    "\"she's\":\"she is\",\n",
    "\"should've\":\"should have\",\n",
    "\"shouldn't\":\"should not\",\n",
    "\"shouldn't've\":\"should not have\",\n",
    "\"somebody's\":\"somebody is\",\n",
    "\"someone's\":\"someone is\",\n",
    "\"something's\":\"something is\",\n",
    "\"so're\":\"so are\",\n",
    "\"so’s\":\"so is\",\n",
    "\"so’ve\":\"so have\",\n",
    "\"that'll\":\"that will\",\n",
    "\"that're\":\"that are\",\n",
    "\"that's\":\"that is\",\n",
    "\"that'd\":\"that would\",\n",
    "\"there'd\":\"there would\",\n",
    "\"there'll\":\"there will\",\n",
    "\"there're\":\"there are\",\n",
    "\"there's\":\"there is\",\n",
    "\"these're\":\"these are\",\n",
    "\"these've\":\"these have\",\n",
    "\"they'd\":\"they would\",\n",
    "\"they'll\":\"they will\",\n",
    "\"they're\":\"they are\",\n",
    "\"they've\":\"they have\",\n",
    "\"this's\":\"this is\",\n",
    "\"those're\":\"those are\",\n",
    "\"those've\":\"those have\",\n",
    "\"to've\":\"to have\",\n",
    "\"wasn't\":\"was not\",\n",
    "\"we'd\":\"we would\",\n",
    "\"we'd've\":\"we would have\",\n",
    "\"we'll\":\"we will\",\n",
    "\"we're\":\"we are\",\n",
    "\"we've\":\"we have\",\n",
    "\"weren't\":\"were not\",\n",
    "\"what'd\":\"what did\",\n",
    "\"what'll\":\"what will\",\n",
    "\"what're\":\"what are\",\n",
    "\"what's\":\"what is\",\n",
    "\"what've\":\"what have\",\n",
    "\"when's\":\"when is\",\n",
    "\"where'd\":\"where did\",\n",
    "\"where'll\":\"where will\",\n",
    "\"where're\":\"where are\",\n",
    "\"where's\":\"where is\",\n",
    "\"where've\":\"where have\",\n",
    "\"which'd\":\"which would\",\n",
    "\"which'll\":\"which will\",\n",
    "\"which're\":\"which are\",\n",
    "\"which's\":\"which is\",\n",
    "\"which've\":\"which have\",\n",
    "\"who'd\":\"who would\",\n",
    "\"who'd've\":\"who would have\",\n",
    "\"who'll\":\"who will\",\n",
    "\"who're\":\"who are\",\n",
    "\"who's\":\"who is\",\n",
    "\"who've\":\"who have\",\n",
    "\"why'd\":\"why did\",\n",
    "\"why're\":\"why are\",\n",
    "\"why's\":\"why is\",\n",
    "\"won't\":\"will not\",\n",
    "\"would've\":\"would have\",\n",
    "\"wouldn't\":\"would not\",\n",
    "\"wouldn't've\":\"would not have\",\n",
    "\"y'at\":\"you at\",\n",
    "\"yes’m\":\"yes madam\",\n",
    "\"you'd\":\"you would\",\n",
    "\"you'll\":\"you will\",\n",
    "\"you're\":\"you are\",\n",
    "\"you've\":\"you have\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d08485b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cont_to_exp(x):\n",
    "    if type(x) is str:\n",
    "        x = x.replace('\\\\','')\n",
    "        for key in contractions:\n",
    "            value = contractions[key]\n",
    "            x = x.replace(key, value)\n",
    "        return x\n",
    "    else:\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "426bee15",
   "metadata": {},
   "outputs": [
    {
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       "   Clothing ID  Age                                        Review Text  \\\n",
       "2         1077   60  I had such high hopes for this dress and reall...   \n",
       "3         1049   50  I love, love, love this jumpsuit. it's fun, fl...   \n",
       "4          847   47  This shirt is very flattering to all due to th...   \n",
       "5         1080   49  I love tracy reese dresses, but this one is no...   \n",
       "6          858   39  I aded this in my basket at hte last mintue to...   \n",
       "\n",
       "   Rating  Positive Feedback Count   Division Name Department Name Category  \\\n",
       "2       3                        0         General         Dresses  Dresses   \n",
       "3       5                        0  General Petite         Bottoms    Pants   \n",
       "4       5                        6         General            Tops  Blouses   \n",
       "5       2                        4         General         Dresses  Dresses   \n",
       "6       5                        1  General Petite            Tops    Knits   \n",
       "\n",
       "   Recommended IND  \n",
       "2                0  \n",
       "3                1  \n",
       "4                1  \n",
       "5                0  \n",
       "6                1  "
      ]
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     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "cl.head()"
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  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d6e0e609",
   "metadata": {},
   "outputs": [],
   "source": [
    "cl[\"Review Text\"] = cl[\"Review Text\"].apply(lambda x:cont_to_exp(x))\n",
    "cl[\"Review Text\"]= cl[\"Review Text\"].str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a07a25d9",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   Clothing ID  Age                                        Review Text  \\\n",
       "2         1077   60  i had such high hopes for this dress and reall...   \n",
       "3         1049   50  i love, love, love this jumpsuit. it is fun, f...   \n",
       "4          847   47  this shirt is very flattering to all due to th...   \n",
       "5         1080   49  i love tracy reese dresses, but this one is no...   \n",
       "6          858   39  i aded this in my basket at hte last mintue to...   \n",
       "\n",
       "   Rating  Positive Feedback Count   Division Name Department Name Category  \\\n",
       "2       3                        0         General         Dresses  Dresses   \n",
       "3       5                        0  General Petite         Bottoms    Pants   \n",
       "4       5                        6         General            Tops  Blouses   \n",
       "5       2                        4         General         Dresses  Dresses   \n",
       "6       5                        1  General Petite            Tops    Knits   \n",
       "\n",
       "   Recommended IND  \n",
       "2                0  \n",
       "3                1  \n",
       "4                1  \n",
       "5                0  \n",
       "6                1  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl.head()"
   ]
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  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7281a64",
   "metadata": {},
   "outputs": [],
   "source": [
    "cl[\"Review Text\"] = cl[\"Review Text\"].str.translate(str.maketrans('', '', string.punctuation))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c519825b",
   "metadata": {},
   "outputs": [
    {
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       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1049</td>\n",
       "      <td>50</td>\n",
       "      <td>i love love love this jumpsuit it is fun flirt...</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>General Petite</td>\n",
       "      <td>Bottoms</td>\n",
       "      <td>Pants</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>847</td>\n",
       "      <td>47</td>\n",
       "      <td>this shirt is very flattering to all due to th...</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>General</td>\n",
       "      <td>Tops</td>\n",
       "      <td>Blouses</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1080</td>\n",
       "      <td>49</td>\n",
       "      <td>i love tracy reese dresses but this one is not...</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>General</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>Dresses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>858</td>\n",
       "      <td>39</td>\n",
       "      <td>i aded this in my basket at hte last mintue to...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>General Petite</td>\n",
       "      <td>Tops</td>\n",
       "      <td>Knits</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Clothing ID  Age                                        Review Text  \\\n",
       "2         1077   60  i had such high hopes for this dress and reall...   \n",
       "3         1049   50  i love love love this jumpsuit it is fun flirt...   \n",
       "4          847   47  this shirt is very flattering to all due to th...   \n",
       "5         1080   49  i love tracy reese dresses but this one is not...   \n",
       "6          858   39  i aded this in my basket at hte last mintue to...   \n",
       "\n",
       "   Rating  Positive Feedback Count   Division Name Department Name Category  \\\n",
       "2       3                        0         General         Dresses  Dresses   \n",
       "3       5                        0  General Petite         Bottoms    Pants   \n",
       "4       5                        6         General            Tops  Blouses   \n",
       "5       2                        4         General         Dresses  Dresses   \n",
       "6       5                        1  General Petite            Tops    Knits   \n",
       "\n",
       "   Recommended IND  \n",
       "2                0  \n",
       "3                1  \n",
       "4                1  \n",
       "5                0  \n",
       "6                1  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2e7aee0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "cl =cl.drop(columns=['Clothing ID'])\n",
    "#cl =cl.drop(columns=['Clothing ID', 'Age','Rating', 'Positive Feedback Count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "101db88e",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = cl[\"Review Text\"]\n",
    "\n",
    "y = cl['Recommended IND']\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "x_train, x_test, y_train, y_test = train_test_split(x,y,test_size=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a66869f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.feature_extraction.text import TfidfTransformer\n",
    "clf = Pipeline([\n",
    "    ('vectorizer', CountVectorizer()),\n",
    "    ('tfidf', TfidfTransformer()),\n",
    "    ('nb', MultinomialNB())\n",
    "])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "16fef40f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('vectorizer', CountVectorizer()),\n",
       "                ('tfidf', TfidfTransformer()), ('nb', MultinomialNB())])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "30cf40dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8187134502923976"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.score(x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "448684c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   3,  713],\n",
       "       [   0, 3217]], dtype=int64)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = clf.predict(x_test)\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bcaeb3b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "tn = cm[0,0]\n",
    "fp = cm[0,1]\n",
    "fn = cm[1,0]\n",
    "tp = cm[1,1]\n",
    "\n",
    "precision = tp/(tp+fp)\n",
    "recall = tp/(tp+fn)\n",
    "f1  = 2*(precision*recall/(precision+recall))\n",
    "\n",
    "met = ['precision', 'recall', 'F1 score']\n",
    "val = [precision, recall, f1]\n",
    "d = {'Accuracy Metrics': met, 'Values': val}\n",
    "df = pd.DataFrame(data=d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a32dc972",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Accuracy Metrics</th>\n",
       "      <th>Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>precision</td>\n",
       "      <td>0.818575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>recall</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>F1 score</td>\n",
       "      <td>0.900238</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Accuracy Metrics    Values\n",
       "0        precision  0.818575\n",
       "1           recall  1.000000\n",
       "2         F1 score  0.900238"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a520cfae",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45648f72",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "123a82e6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd5704eb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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