Notebooks/2_Flipkart_DATA_ACCESS_AND_EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4a9275ac",
   "metadata": {},
   "source": [
    "# Data Access"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67953c11",
   "metadata": {},
   "source": [
    "#  Import The Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87299fcb",
   "metadata": {},
   "source": [
    "* We Have Stored Our Data In MySQL DataBase.\n",
    "* Connecting DataBase To NoteBook And Doing Other Part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f9280497",
   "metadata": {},
   "outputs": [],
   "source": [
    "import mysql.connector\n",
    "import os\n",
    "import pymysql\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cabd6e9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "db_name = \"webscraping\"             #database name\n",
    "db_host = \"localhost\"               #Host\n",
    "db_username = \"root\"                #Username\n",
    "db_password = \"rajesh@1929\"         #Password"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "05f6ff3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#exception Handling\n",
    "try:\n",
    "    conn = pymysql.connect(host = db_host,\n",
    "                         port = int(3306),\n",
    "                         user = 'root',\n",
    "                         password = db_password,\n",
    "                         db = db_name)\n",
    "except e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0a84845c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sucessfully Connected\n"
     ]
    }
   ],
   "source": [
    "if conn:\n",
    "    print(\"Sucessfully Connected\")\n",
    "else:\n",
    "    print(\"Error\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d58aef7c",
   "metadata": {},
   "source": [
    "* As We Seen Above SQL is Connected Sucessfully"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dda070c1",
   "metadata": {},
   "source": [
    "# DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5ed2a4d",
   "metadata": {},
   "source": [
    "* Reading The Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16e695ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.simplefilter(\"ignore\", UserWarning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fb15007c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_sql_query('SELECT * FROM mobiles_data',conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "56ce43a7",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processor</th>\n",
       "      <th>MyUnknownColumn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ProductName  Stars  Ratings  Reviews  Price         ROM  \\\n",
       "0  APPLE iPhone 11 (White    4.6    95977     7038  43900   64 GB ROM   \n",
       "1  APPLE iPhone 11 (White    4.6    95977     7038  48900  128 GB ROM   \n",
       "2  APPLE iPhone 11 (Black    4.6    95977     7038  48900  128 GB ROM   \n",
       "3  APPLE iPhone 11 (Green    4.6    95977     7038  48900  128 GB ROM   \n",
       "4  APPLE iPhone 11 (Black    4.6    95977     7038  43900   64 GB ROM   \n",
       "\n",
       "                                        Display  \\\n",
       "0  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "1  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "2  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "3  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "4  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "\n",
       "                            Camera                  Processor MyUnknownColumn  \n",
       "0  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor                  \n",
       "1  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor                  \n",
       "2  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor                  \n",
       "3  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor                  \n",
       "4  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor                  "
      ]
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     "execution_count": 7,
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     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dee5bedd",
   "metadata": {},
   "source": [
    "* Cleaning The MyUnknownColumn Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "37cab01d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4                                \n",
       "13                               \n",
       "38     6 Core Processor Processor\n",
       "35                               \n",
       "9      6 Core Processor Processor\n",
       "Name: MyUnknownColumn, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['MyUnknownColumn'].sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8b0d3eb5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#combining Processor and myunknowncolumn into NEW column\n",
    "df['Processorr'] = df['Processor']+df['MyUnknownColumn']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "682ac722",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5                             A13 Bionic Chip Processor\n",
       "39                            A15 Bionic Chip Processor\n",
       "1                             A13 Bionic Chip Processor\n",
       "19                            A15 Bionic Chip Processor\n",
       "35    A13 Bionic Chip with 3rd Gen Neural Engine Pro...\n",
       "Name: Processorr, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Processorr'].sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "13933d3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#droping the column\n",
    "new = df.drop(['Processor','MyUnknownColumn'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0ccd5c79",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
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       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
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      "text/plain": [
       "              ProductName  Stars  Ratings  Reviews  Price         ROM  \\\n",
       "0  APPLE iPhone 11 (White    4.6    95977     7038  43900   64 GB ROM   \n",
       "1  APPLE iPhone 11 (White    4.6    95977     7038  48900  128 GB ROM   \n",
       "2  APPLE iPhone 11 (Black    4.6    95977     7038  48900  128 GB ROM   \n",
       "3  APPLE iPhone 11 (Green    4.6    95977     7038  48900  128 GB ROM   \n",
       "4  APPLE iPhone 11 (Black    4.6    95977     7038  43900   64 GB ROM   \n",
       "\n",
       "                                        Display  \\\n",
       "0  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "1  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "2  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "3  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "4  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "\n",
       "                            Camera                 Processorr  \n",
       "0  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "1  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "2  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "3  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "4  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a91282f1",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ea12e272",
   "metadata": {},
   "outputs": [
    {
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       "      <td>APPLE iPhone 11 (White</td>\n",
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       "      <td>43900</td>\n",
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       "      <td>APPLE iPhone 11 (White</td>\n",
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       "      <td>7038</td>\n",
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       "      <td>A13 Bionic Chip Processor</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
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      "text/plain": [
       "              ProductName  Stars  Ratings  Reviews  Price         ROM  \\\n",
       "0  APPLE iPhone 11 (White    4.6    95977     7038  43900   64 GB ROM   \n",
       "1  APPLE iPhone 11 (White    4.6    95977     7038  48900  128 GB ROM   \n",
       "2  APPLE iPhone 11 (Black    4.6    95977     7038  48900  128 GB ROM   \n",
       "3  APPLE iPhone 11 (Green    4.6    95977     7038  48900  128 GB ROM   \n",
       "4  APPLE iPhone 11 (Black    4.6    95977     7038  43900   64 GB ROM   \n",
       "\n",
       "                                        Display  \\\n",
       "0  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "1  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "2  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "3  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "4  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "\n",
       "                            Camera                 Processorr  \n",
       "0  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "1  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "2  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "3  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "4  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  "
      ]
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     "execution_count": 13,
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    }
   ],
   "source": [
    "new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "69affe07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(48, 9)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe086737",
   "metadata": {},
   "source": [
    "* Hence These Is A SMall Data, There Are 48Rows & 9 Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f88957f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking the null values\n",
    "import missingno as msno\n",
    "msno.matrix(new, color=(0, 0, 0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "938619c6",
   "metadata": {},
   "source": [
    "* There Are No NULL Values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "050d0b41",
   "metadata": {},
   "source": [
    "# Visuvalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1a493150",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8f912c01",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Price', ylabel='Density'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(new['Price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8a0dc510",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new['ProductName'].value_counts().plot(kind='bar',figsize= (10,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "99104127",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9706eb9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.barplot(x=new['ProductName'],y=new['Price'])\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "270fe8ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new['Stars'].value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "82c8ed7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=new['Stars'],y=new['Price'])\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4e1e9fb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "plt.bar(x=new['ProductName'],height = new['Ratings'])\n",
    "plt.title('Highest Rating Mobiles',fontsize=20)\n",
    "plt.xlabel('Mobile')\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f17a8189",
   "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>ProductName</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>43900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>48900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>48900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 (Green</td>\n",
       "      <td>48900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>43900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>APPLE iPhone 11 (Purple</td>\n",
       "      <td>48900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>APPLE iPhone 14 Pro (Silver</td>\n",
       "      <td>139900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>APPLE iPhone SE (Red</td>\n",
       "      <td>30499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>APPLE iPhone 11 (Red</td>\n",
       "      <td>43900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>APPLE iPhone 14 Pro (Space Black</td>\n",
       "      <td>139900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        ProductName   Price\n",
       "0            APPLE iPhone 11 (White   43900\n",
       "1            APPLE iPhone 11 (White   48900\n",
       "2            APPLE iPhone 11 (Black   48900\n",
       "3            APPLE iPhone 11 (Green   48900\n",
       "4            APPLE iPhone 11 (Black   43900\n",
       "5           APPLE iPhone 11 (Purple   48900\n",
       "6       APPLE iPhone 14 Pro (Silver  139900\n",
       "7              APPLE iPhone SE (Red   30499\n",
       "8              APPLE iPhone 11 (Red   43900\n",
       "9  APPLE iPhone 14 Pro (Space Black  139900"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking mobile price\n",
    "small = new[['ProductName','Price']]\n",
    "small.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8da682d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Display', ylabel='Price'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=new['Display'],y=new['Price'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddd8874c",
   "metadata": {},
   "source": [
    "# Skewness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "34bcbd9d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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SSmEPeDm2hgbH915fTINz/P7qIZ5fmamlDc1N4Z6xBfxt4VbeWbgl3OWI+IaX3SQnATOBPmZWZGa3erUsv3th5gZmFu7kx5f2JzctMdzleOL2s3oyPC+FH/5tKVvK94W7HBFf8LIXzTXOuWznXKxzLsc595xXy/KztcWVPDJlJef07cQ3RuaGuxzPxERH8YfxQ2locDzw2iIaGnSWq0hzaRdNBKurb+D+1xaSGBfNI1cOajVnq56obulJ/OSyAcws3MlzM9aHuxyRVk8BH8Ge/HQdi4p288uvD6JT+/BenamlXD0ih3EDsviff6xi+dY94S5HpFVTwEeoJUW7+ePHa7h8aBcuGpQd7nJajJnx6ysG0zExlntfXUD1fp3lKnKiFPARqHp/Pd99bSHpyXH87LKB4S6nxaUlxfG7q4ewekclv/1wVbjLEWm1FPAR6Pf/XMWa4kr+56rWN5BYqJzZO5ObTs1n4hfr+XyNToATOREK+Ajz+ZoSnvl8PdefnMcZvdv2iV8PXdiXXp2SeeD1RZRX1Ya7HJFWRwEfQUora7jv1UUUdErmBxf1D3c5YdcuNprHxg+lbG8t//32El0gROQ4KeAjREOD4/7XFlFRvZ8nrh1GQlzrHkgsVAZ27ch3z+vDB0u28/rconCXI9KqKOAjxMQv1vPZ6hJ+eEl/+nbuEO5yIsptZ/RgTK90fvTOUlZsU9dJkaZSwEeAJUW7+c2HKxk3IIvrT8oLdzkRJzrKeGz8MDokxHLHy/OprKkLd0kirYICPswqa+q4a9J8MpLj+c2Vg31/tuqJymwfzxPXDGPDzr18/y3tjxdpCgV8GB24gMemsioenzCMlMS4cJcU0U7ukc795/fhvUVbeXHmxnCXIxLxFPBhNPGLDby3aCv3n9+H0d3Twl1Oq/CdM3tybr9O/Oz95cxcp6tAiRyNAj5MZhXu5FcfrGDcgCxuP6tnuMtpNaKijD+MH0r3jCTueGU+m8uqwl2SSMRSwIfBtt37uPOV+XRLT+R3Vw/Rfvfj1L5dLE/fMIL99Q3c9tI8qmp10LWlOOeoq2+gqraO7burKa+qpbauIdxlyRHEhLuAtqaqto7bXpzHvtp6Jt92Mu3btc2hCJqrR2YyT1wzjFuen8M9kxfyl+tHEO2zK12Fk3OO0spaNpVVsaV8H2V7ayjbW0t51X7qgmP1/+LvK/71+riYKLqmJNAtPZH89CQGdu3IiG6p5KcnqgETRgr4FlTf4Lhn8kKWbd3NM98cSa9O/rhwdric1acTP7l0AD95dxk/fXcZP7t8gMKkGapq61i9o4KV2ytYW1xJVW1gJM/4mCjSk+Po3DGBftkdSIiNJjY6ijG9MqjeX09VbR17quvYsmsfG3buZc76Mp7/cgMA6UlxnFaQwdh+WZzZO5OOCWrQtCQFfAv69QcrmLp8Bw9fNoCx/bLCXY4v3HhqPlvL9/HU9EKyU9px+1m9wl1Sq1Jb18CKbXtYsHkXa4sraXCQFB9D384dyE9PJDctkcz28UQd5h/ntUc4Z6OhwbG2pJJ5G3cxZ30Zn60u4Z2FW4mJMs7oncmVw3MY268T7WJ1trbXFPAt5IUvN/DsjPXcdGo+N56aH+5yfOW/LujLtt3V/PbDVXRq346rRuSEu6SIV1JRw8zCUhZsKqemroGOCbGcXpBJ/+wOdE1NOGygN1VUlNE7qz29s9pzzeg86hscCzfv4p/LdvDOwq1MWzmfDu1iuHJEDjedmk+39KQQfjJpTAHfAt6cV8RP3l3Guf2y+NElGkQs1KKijP+5ejBle2t58I1FxEYblw/tGu6yIk6Dc6wtruTLdaWs3lFJdJQxuGtHhndLpXtGUrNC/Wiio4wR3dIY0S2NBy/oy5frSnltbhF/nbWR57/cwNi+WdxyWj6n9EjXLrYQU8B7bMqSbXzvjUWM6ZXOn64dpgOBHomPieaZb47k5ue/4r5XFxJlxqVDuoS7rIhQ3+BYVFTOZ6tKKKmsoX18DGP7dWJ0flqLH+SPjjJOL8jk9IJMduzpx19nbeTl2Zv46Jkd9MvuwO1n9eSiQdn6OwkRBbyHPllVzN2TFzAsL5WnbxipfY4eS4iL5rkbR3Hz/5vDva8uxAwuGdx2Q762roE5GwL7wMv21tK5QzuuHpHDoJyOxESFv4d0Vod23H9+H+44uxfvLNzC09MLuWvSAh7/eA13ndOLSwZ3UdA3U/h/yz41Zck2bntxLr2z2jPxplEkxet/aUtIio9h4s2jGJ6Xwl2TFvBCsDdHW1K9v56XZm7g7N99ytsLtpAQG831J3XjznN6MSwvNSLCvbF2sdGMH5XHP+87kz9dO4wog3smL+S8Rz/jrflF1NWrn/2JUup44LW5m3nozcUMy0tl4k2j1DWshSXHx/DSrSdx16QF/OTdZRRXVPPA+X18v3+3en89k77axF8+W8eOPTUMz0vh3H5Z9M5KbhWfPTrKuGRwFy4amM0/lm3n8Y/X8N3XFvHHj9dw5zkFfG1oF2KiI+ufU6RTwIeQc45nPi/kVx+s5PSCDJ66YQSJcVrF4dAuNpo/XzecH72zjP/9ZB1Fu/bx6ysG+fL3sa+2nleCwV5SUcPo7mk8+o2hnNoznUlfbQ53ecctKsq4cFA24wZ05qMVO3j84zU88Poinpi2hjvP7sXXh3VV0DeR/7b2MKmpq+cHby/ljXlFXDwom0fHDyE+RvvcwykmOopffX0gOakJ/O6fq1i1vYI/Xz+C7hn+6JZXVVvHy7M28dT0QkorazilRzpPXDOMk3ukh7u0kIiKMs4f0Jnz+mfx0YpiHvtoNd97YzF/+mStgr6JFPAhUFxRzf99aR7zN5Vzz9gC7hlbQJQODkUEM+OOs3sxsGtH7pm8gMuemMFvrxrMhYOyw13aCdtbU8dLszbyzPRCdu6tZUyvdJ4cO9y3I5KaGef1z+Lcfp34eEUxj32soG8qBXwzfba6hAdeX0RldR1PXjeci1pxcPjZmb0zee/O07jjlfl85+X5XDqkCw9fNoC0pNYzBn9xRTUvfrmRv87eSHnVfk4vyOCesQWMzPdnsB/KzDi3fxZjDwn6J6at5c5zAkEfq6A/iAL+BFXvr+eRKSt5/ssN9M5K5sVbRtMvW9dSjWS5aYm8+Z1T+fOn63hi2hq+XFvKjy/tz6WDu0T0N67VOyp4Znoh7yzcyv6GBs7vn8W3z+zJ8LzUcJcWFocL+gffWMxjU1dz85juTBidq0H8giySLn02cuRIN3fu3HCXcUwz1pTy43eXUliyl1vGdOfBC/r4po/7K7M3eTr/I41f0tJWbt/Dg28sZnHRbobkdOShC/txSs/I2Xddvb+eD5duZ/KcTcwqLKNdbBRXj8jl1tO6k38cxxC8/H1Gyu/SOccnq4p5enohswrLaB8fw4TRudw8pjtdUhLCXZ7nzGyec27k4Z5TC/44bCnfxy/eX86Updvplp7IS7eO5vSCzHCXJSegb+cOvH37GN5esIVH/7mKa56ZxRm9M/nW6d05rVdGWLoVOudYtnUPr8/dzNsLtrCnuo68tES+N64P147OI7UV7U5qSWbGOX2zOKdvFouLynnm8/VM/GIDE7/YwDl9O3Ht6DzO6J3ZJk+aUgu+CbbvruYvn63jla82EWVwx1m9+NYZPXzTam+srbTgG6veX8/zX27g2c/XU1pZQ++sZG44JZ+LBnYmPTne02U3NARCfcrSbUxZup31pXuJi47igoGdmTAql5N7pDdr91FbaMEfTtGuKv46axNvzNtMaWUtXVMSGD8ql6tG5PiuVX+0FrwC/ijWFlfw4syNTJ6zmfoGx5XDu3L32AJyUhPDXZpn2mLAH1BTV8/7i7bx3Iz1LN+2h+go45Qe6Ywb2JlTeqTTMzOp2S37hgZHYele5m/axRdrS5mxppSde2v/tawLB3XmooHZIWutt9WAP6C2roGPVuxg0leb+HxNKQAjuqVy8aBsLh6cTVaHdmGusPkU8MdhX209H63YwcuzNzKrsIzYaOOKYTnccXYv8tL9G+wHtOWAP8A5x4ptFfx9yVbeX7yNjTsD131NT4pjeLdUenVKpkdGEvkZSaQmxpGaGPuvg3oNzlHX4Ni1t5ZdVbWUVtawobSK9aV7WVdSyZKi3VTUBC4xmJEcz+kFGZzWK4Oz+3bypEdPWw/4xjbtrOK9xYHf6YptezCDUd3SOLtvJ04vyKB/doeIPth+JAr4YyivqmXG2lKmLNnOtJXF7NtfT05qAteelMc3RuaS4fHX9EiigD+Yc471pXuZs6GM2evLWLS5nI07q/512bqmat8uhh4ZgUvZDc1NYWhuCj0zkz0PFAX84a0truSDJdv4YMk2Vm6vAP79D/fUnumBIZTTk1pF4OsgayPOOYp27WPplt0sLCpn5rqdLNmyG+cgIzmOK0d05aJB2ZzUPb1NHpSRg5kZPTKT6ZGZzPhRgUCrq29g8659bCqrorwqcJ3Siur9mBlmEG0WaNknxZGeHEe3tETSkuJaxXgwbUWvTsncPbaAu8cWULynmulrSpm+uoTPVpfw9oItAHRMiGVIbgrDclPol92B3lnJ5KUltqqTqjwNeDO7AHgciAaedc494uXyGqupq6co+Ee4uayKjTurWLW9gqVbd1NetR+AmChjeF4q947tzZhe6QzLS1WoyzHFREfRPSPJN0MetHWdOgSuAnbViBwaGhzrSipZsKmcBZt3sWBTOU9MW8OBL2xxMVH0yEiiZ6dkclITyElJoGtqAl1TEsnqEE+HdrER1er3LODNLBr4X+A8oAiYY2bvOueWh3I5zjkefm85pZU1lFbWsLMysN9zVzDED2gXG0XPzGQuGNCZgV07MqhrR/p0bu/LnjAicmKiooyCrPYUZLXnG6NygcDQEGuLK1lTXMmaHRWsKa5k6ZbdTF22g9pDhjKOjgp8e8tIjiMtKXDrmBBLUnwMiXHRJMXFkBgfvI+LJjEuhnaxUSTERTOgS8eQfx4vW/CjgbXOuUIAM5sMXA6ENODNjI9W7CAuOnDl916dkjmpRxqZye3IS08gLy144eDkeH1FFpHjlhQfw5DcFIbkphw0vaHBUVJZQ9GufWwp30dJRQ1le2so21vLzspadu6tZdnWPVRU72dvTT379tcfcRkZyXHM/eF5Ia/dy4DvCjQeq7QIOOnQF5nZbcBtwR8rzWyVhzUBZAClHi+jNfN0/Vzn1YxblrYhjvq71Po5toPW0UbAfnTC8+p2pCe8DPjDNZf/o+uBc+5p4GkP6ziImc090hFn0fppCq2jo9P6ObaWWkdeHg4uAnIb/ZwDbPVweSIi0oiXAT8HKDCz7mYWB0wA3vVweSIi0ohnu2icc3VmdifwDwLdJCc655Z5tbzj0GK7g1oprZ9j0zo6Oq2fY2uRdRRRZ7KKiEjotJ5TskRE5Lgo4EVEfKrVB7yZ/dTMtpjZwuDtokbPfd/M1prZKjMb12j6CDNbEnzujxY8A8rM4s3s1eD02WaW3+g9N5rZmuDtxhb9kC3EzC4Irqu1ZvZQuOvxmpltCG4HC81sbnBamplNDf6ep5pZaqPXh2x7ikRmNtHMis1saaNpLbI+Wsvf1xHWUeRmkHOuVd+AnwIPHGZ6f2AREA90B9YB0cHnvgJOIdBXfwpwYXD67cBfgo8nAK8GH6cBhcH71ODj1HB/9hCvx+jgOuoBxAXXXf9w1+XxZ94AZBwy7bfAQ8HHDwG/CfX2FKk34AxgOLC0JddHa/r7OsI6itgMavUt+KO4HJjsnKtxzq0H1gKjzSwb6OCcm+kCa+5F4GuN3vNC8PEbwNjgf9ZxwFTnXJlzbhcwFbigBT9LS/jX0BLOuVrgwNASbU3jbeAFDt42QrU9RSTn3HSg7JDJLbE+Ws3f1xHW0ZGEfR35JeDvNLPFwa9PB75CHm6ohK7BW9Fhph/0HudcHbAbSD/KvPykLXzGQzngn2Y2zwJDZgBkOee2AQTvOwWnh3J7ak1aYn34YduLyAxqFQFvZh+Z2dLD3C4H/gz0BIYC24DfH3jbYWbljjL9RN/jF23hMx5qjHNuOHAhcIeZnXGU14Zye/ID/X39W8RmUKsIeOfcuc65gYe5veOc2+Gcq3fONQDPENjVAEceKqEo+PjQ6Qe9x8xigI4Evo61hWEX2sJnPIhzbmvwvhh4m8C2syP4FZrgfXHw5aHcnlqTllgfrXrbi+QMahUBfzQHNr6grwMHjm6/C0wIHpXuDhQAXwW/ZlaY2cnBfVvfBN5p9J4DR6evAqYF95H9AzjfzFKDX7/OD07zkzY1tISZJZlZ+wOPCfxOl3LwNnAjB28bodqeWpOWWB+t+u8rojMo3Eelm3sDXgKWAIuDKye70XM/IHDkehXBo9TB6SODv4R1wJ/49xm97YDXCRwM+Qro0eg9twSnrwVuDvfn9mhdXgSsDq6XH4S7Ho8/aw8CPRwWAcsOfF4C+zs/BtYE79O82J4i8QZMIrCLYT+BFuOtLbU+Wsvf1xHWUcRmkIYqEBHxqVa/i0ZERA5PAS8i4lMKeBERn1LAi4j4lAJeRMSnFPDia2ZWHxzhb6mZvWdmKcd4/dBDRgO8zNrAyJriT+omKb5mZpXOueTg4xeA1c65Xx7l9TcBI51zd7ZQiSKeUQte2pKZBAdoMrPRZvalmS0I3vcJnsH7M2B8sNU/3sxuMrM/Bd/zfHDs7i/NrNDMrgpOjzKzJ81smZm9b2YfNHruETNbHhyI6ndh+tzSRnl20W2RSGJm0cBY4LngpJXAGS5wcfhzgV855640sx/TqAUfbNE3lg2cBvQlcNbiG8AVQD4wiMBoiyuAiWaWRuDU9b7OOXes3UMioaaAF79LMLOFBAJ4HoFxtCEwiNMLZlZAYFS+2CbO728uMKjUcjPLCk47DXg9OH27mX0SnL4HqAaeNbO/A+8398OIHA/tohG/2+ecGwp0I3ClqjuC038OfOKcGwhcSmAMkKaoafTYDrk/iAuM5z0aeJPABR0+PJ7CRZpLAS9tgnNuN3A38ICZxRJowW8JPn1To5dWAO2Pc/YzgCuD++KzgLMAzCwZ6Oic+wC4l8B44SItRgEvbYZzbgGB0SMnELjW6K/N7AsC16M94BOg/4GDrE2c9ZsERhZcCjwFzCZwJZ72wPtmthj4DLgvJB9EpInUTVIkBMws2TlXaWbpBIZ5HeOc2x7uuqRt00FWkdB4P9hLJg74ucJdIoFa8CIiPqV98CIiPqWAFxHxKQW8iIhPKeBFRHxKAS8i4lP/HyV1cqM12MKiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: '64 GB ROM'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Input \u001b[1;32mIn [26]\u001b[0m, in \u001b[0;36m<cell line: 5>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      3\u001b[0m     plt\u001b[38;5;241m.\u001b[39mshow()\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(new\u001b[38;5;241m.\u001b[39mcolumns)[\u001b[38;5;241m1\u001b[39m:]:\n\u001b[1;32m----> 6\u001b[0m     \u001b[43mdistplot\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\n",
      "Input \u001b[1;32mIn [26]\u001b[0m, in \u001b[0;36mdistplot\u001b[1;34m(col)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdistplot\u001b[39m(col):\n\u001b[1;32m----> 2\u001b[0m     \u001b[43msns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdistplot\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnew\u001b[49m\u001b[43m[\u001b[49m\u001b[43mcol\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      3\u001b[0m     plt\u001b[38;5;241m.\u001b[39mshow()\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2636\u001b[0m, in \u001b[0;36mdistplot\u001b[1;34m(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax, x)\u001b[0m\n\u001b[0;32m   2633\u001b[0m     a \u001b[38;5;241m=\u001b[39m x\n\u001b[0;32m   2635\u001b[0m \u001b[38;5;66;03m# Make a a 1-d float array\u001b[39;00m\n\u001b[1;32m-> 2636\u001b[0m a \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m   2637\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m a\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m   2638\u001b[0m     a \u001b[38;5;241m=\u001b[39m a\u001b[38;5;241m.\u001b[39msqueeze()\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\series.py:872\u001b[0m, in \u001b[0;36mSeries.__array__\u001b[1;34m(self, dtype)\u001b[0m\n\u001b[0;32m    825\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__array__\u001b[39m(\u001b[38;5;28mself\u001b[39m, dtype: npt\u001b[38;5;241m.\u001b[39mDTypeLike \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m np\u001b[38;5;241m.\u001b[39mndarray:\n\u001b[0;32m    826\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    827\u001b[0m \u001b[38;5;124;03m    Return the values as a NumPy array.\u001b[39;00m\n\u001b[0;32m    828\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    870\u001b[0m \u001b[38;5;124;03m          dtype='datetime64[ns]')\u001b[39;00m\n\u001b[0;32m    871\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 872\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_values\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[1;31mValueError\u001b[0m: could not convert string to float: '64 GB ROM'"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def distplot(col):\n",
    "    sns.distplot(new[col])\n",
    "    plt.show()\n",
    "    \n",
    "for i in list(new.columns)[1:]:\n",
    "    distplot(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8de04dbf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ProductName', ylabel='Price'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "sns.barplot(x = 'ProductName',y = 'Price', data = new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ad2a8115",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='ProductName', ylabel='Ratings'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "sns.barplot(x = 'ProductName',y = 'Ratings', data = new)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bab486e9",
   "metadata": {},
   "source": [
    "# Distribution Of Plots\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2b49710f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# find the distribution of plots\n",
    "def boxplot(col):\n",
    "    sns.boxplot(new[col])\n",
    "    plt.show()\n",
    "    \n",
    "for i in list(new.select_dtypes(exclude=['object']).columns)[1:]:\n",
    "    boxplot(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5f3e74b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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r/a6g7yQOAAAAgE4SBwAAANDFHAcSBwAAAEA3iQMAAADoInEgcQAAAAB0kzgAAACALk3iQOIAAAAA6CRxAAAAAF3McSBxAAAAAHSTOAAAAIAurfW7gr6TOAAAAAA6SRwAAABAF3McSBwAAAAA3SQOAAAAoIvEgcQBAAAA0E3jAAAAAOjkVgUAAADo0tyqIHEAAAAAdJI4AAAAgA5toPW7hL6TOAAAAAA6SRwAAABAF8sxShwAAAAA3SQOAAAAoItVFSQOAAAAgG4SBwAAANDFqgoSBwAAAEA3iQMAAADoYlUFiQMAAACgm8QBAAAAdJE4kDgAAAAAukkcAAAAQJdmVQWJAwAAAKCTxgEAAADQya0KAAAA0MXkiBIHAAAAQDeJAwAAAOgyYHJEiQMAAACgk8QBAAAAdGnmOJA4AAAAADpJHAAAAEAXcxxIHAAAAADdRj1xMGf340b7FMByzLj8lH6XAABja5t9+l0BsAZqA+Y4kDgAAAAAOpnjAAAAALqY40DiAAAAAFYXVXVAVV1bVTdU1QkdY55fVZdX1VVV9cOVPafEAQAAAHRp42eOg6paJ8knk+ybZF6Si6vqjNba1UPGbJTkU0kOaK39pqo2X9nzShwAAADA6uFpSW5ord3YWnswyVeTHLLUmL9N8s3W2m+SpLV2+8qeVOMAAAAAugy0MXtU1cyqumTIY+ZS1UxPcvOQ7Xm9fUM9IcnGVXVBVV1aVa9c2b8CtyoAAADAONBam51k9jBDankvW2p73SRPTbJPkvWS/HdVXdRau+7PrUvjAAAAAFYP85JsPWR7qyS3LGfMHa21e5PcW1U/SjIjyZ/dOHCrAgAAAHQZGBi7x4pdnGTHqtquqiYlOTzJGUuN+XaS51bVulW1fpKnJ7lmZf4KJA4AAABgNdBaW1RVxyY5J8k6ST7XWruqqmb1jp/WWrumqs5OMjfJQJLPtNauXJnzahwAAABAl4GlpxDor9bamUnOXGrfaUttfyjJh1bVOd2qAAAAAHSSOAAAAIAubURzD6zRJA4AAACAThIHAAAA0GWczXHQDxIHAAAAQCeJAwAAAOjQBsxxIHEAAAAAdJI4AAAAgC7mOJA4AAAAALpJHAAAAEAXiQOJAwAAAKCbxAEAAAB0aVZVkDgAAAAAOmkcAAAAAJ3cqgAAAABdTI4ocQAAAAB0kzgAAACADk3iQOIAAAAA6CZxAAAAAF0kDiQOAAAAgG4SBwAAANBlYKDfFfSdxAEAAADQSeIAAAAAupjjQOIAAAAA6CZxAAAAAF0kDiQOAAAAgG4SBwAAANChNYkDiQMAAACgk8QBAAAAdDHHgcQBAAAA0E3jAAAAAOjkVgUAAADo4lYFiQMAAACgm8QBAAAAdGgSBxIHAAAAQDeJAwAAAOgicSBxAAAAAHSTOAAAAIAuA/0uoP8kDgAAAIBOEgcAAADQwaoKEgcAAADAMEbUOKiqD1bV5KqaWFXnVdUdVXXEaBcHAAAAfTXQxu4xTo00cbBfa+2eJC9OMi/JE5IcP2pVAQAAAOPCSOc4mNj786AkX2mt/a6qRqkkAAAAGCesqjDixsF3quqXSe5PcnRVPTbJA6NXFgAAADAejKhx0Fo7oar+b5J7WmsPVdV9SQ4Z3dIAAACgv6yqMMLGQVW9dMjzh5/eXVUDrbXbR6MwAAAAoP9GeqvCa5M8M8n5ve3nJ7koyROq6t2ttS+OQm0AAABAn420cTCQ5EmttduSpKq2SHJqkqcn+VESjQMAAADWPCZHHPFyjNs+3DTouT3JE1prv0uycNWXBQAAAIwHI00c/Liqvpvk673tlyX5UVU9Jsldo1EYAAAA9JvJEUfeODgmg82CZyepJF9I8o3WWkuy9yjVBgAAAPTZiG5VaIP+s7X2D621N/eea7usxiY//8nZ9YefzK4Xnpotj3npMsc3+cu9svO5H8vO534sO33r5Kz3pG2XHDBhQnY++5Ts8Pl3jE3BsJZ45/tPyV4vOjyHHjGr36XAWsW1B6PrQx8+KXOuOD8X/eyszNh9l2HHfvgj78qtt1+5eHujjSbnK189LRf97Kxc8KNvZeednzDa5cKSBsbwMU6NqHFQVS+tquur6u6quqeqFlTVPaNdHKNkwoRs89435Loj352r9n5jNjnkuXn0jlstMeSPv7kt1x72jly975tzyz//Rx73waOXOL7Fa1+c+2+YN5ZVw1rh0IP2zWmnvLffZcBax7UHo2e//Z+f7XfYNjN22ztvPPbEfOyfu6+1Jz9lt0yZMnmJfW89/pjMnXt1nvH0AzPzdcflgx/6x9EuGVjKSCdH/GCSl7TWprTWJrfWNmytTV7hqxiXHrP7jvnjr+bnwd/clrZwUX737Quz0X5PX2LMvZdem4fuvnfw+WXXZtLUTRcfmzh100zZZ4/c8e/njmndsDbYY/fdMmXyhv0uA9Y6rj0YPS9+8b75ype/mSS5+OLLM2XK5Gyx5WOXGTdhwoS8730n5p3v/MAS+3d60g654PyfJkmuu+7GbPO4rbL55puNfuHQ0wbG7jFejbRxcFtr7ZpRrYQxM2nqJnlw/h2Ltx+89c5MmrpJ5/jNDn9h7j7/ssXbW7/rtZn3vtMTd6sAALACU6dtkXnz5i/evuW38zNt2pbLjJs165X53vd+kNtu/d8l9l9xxTV5ySH7J0meuseMbLPN9EybvuzrgdEz0sbBJVX1tar6m95tCy+tqmVvjO+pqplVdUlVXfLNe3+1aiplFapl9nT1ADZ81q7Z7PAXZt77vpAkmbLPHll0x92574r/Gc0CAQBYQ1Qt72fPJX/43HLq5jn0pQfltFNPX2bsKR8+LRttPCU/veh7mTXrVZkz56osWvTQqNULyzDHwYhXVZic5L4k+w3Z15J8c3mDW2uzk8xOkku2OtTX0uPMg/PvzKSpf4p3Tdpy0yy89XfLjFvvSY/L4z54bK4/8t156K4FSZIN9twpG+23Z6a84KmZ8KiJmbDh+tnu42/OTW/62FiVDwDAODfzDUfm1a85PEly6aVzs9VWUxcfmzZ9aubPv22J8TNm7JLtt982c6+8IEmy/vrrZc4V52fGbntnwYI/5Kg3vG3x2Kuu+XF+/aubR/9DAIuNqHHQWnvNaBfC2Ll3zvV59HZTM2nrzbPw1t9lk0OekxuPPWWJMZOmbZbt//WE3PT3H80fb7pl8f7fnvyl/PbkLyVJNnzmrtniDYdoGgAAsITZn/5iZn/6i0mS/Q/YO2+Y9cp8/evfyZ577p577lmwzO0I55x9frbf7mmLt2+9/crM2G1w1fcpUzbMffc9kIULF+bVrzk8P7nw51mw4A9j92FY643nuQfGyrCNg6p6W2vtg1X1LxlMGCyhtfamUauM0fPQQH7zf/41T/jyScmEdXLn136QB667OY89YvDesf/90jmZ+g8vz7obbZjHvX9wWaq26KFc86K39rNqWCscf9LJufgXc3PXXfdkn0OPyNGvPTIvO3j/fpcFazzXHoyec84+P/vvv3fmXnlB7r/v/sya9af0wDf+3+dyzNEn5Nb5t3e+/olP3CGzP/ORDDw0kF/+8vocfdTbx6JsYIha+v6iJQ5WHdxa+05VvWp5x1try96EtBS3KkB/zLj8lBUPAoA1yMbb7NPvEmCt9If7blp2Ios1yB37P2/Mfqfd7Jwfjsu/y2ETB6217/Se3tda+/rQY1X1V6NWFQAAADAujHRVhRNHuA8AAADWGG1g7B4jUVUHVNW1VXVDVZ0wzLg9q+qhqjpsZf8OVjTHwYFJDkoyvao+PuTQ5CSLVvbkAAAAwMhU1TpJPplk3yTzklxcVWe01q5ezrj/m+ScVXHeFSUObklySZIHklw65HFGEjMGAQAAwNh5WpIbWms3ttYeTPLVJIcsZ9wbk3wjSffMo4/AiuY4mJNkTlX9e2tt4ao4IQAAAKwuxnI5xqqamWTmkF2zW2uzh2xPT3LzkO15SZ6+1HtMT/KXSV6QZM9VUdewjYMhtq2qDyTZOcmjH97ZWnv8qigCAAAA1na9JsHsYYYsb9WFpVd9+FiSt7fWHqpaNYs0jLRx8G9JTkry0SR7J3lNll8wAAAArDHGMnEwAvOSbD1ke6sMTjEw1B5JvtprGmyW5KCqWtRa+9afe9KRrqqwXmvtvCTVWvt1a+1dGYw9AAAAAGPj4iQ7VtV2VTUpyeEZnINwsdbadq21bVtr2yb5zyRHr0zTIBl54uCBqpqQ5PqqOjbJb5NsvjInBgAAgHGvjZ+wfWttUe938nOSrJPkc621q6pqVu/4aaNx3pE2Dt6cZP0kb0ryngymDV45GgUBAAAAy9daOzPJmUvtW27DoLX26lVxzhE1DlprF/ee/iHJa6pq3SQvT/KzVVEEAAAAjEfjbI6Dvhh2joOqmlxVJ1bVJ6pqvxp0bJIbkvz12JQIAAAA9MuKEgdfTPL7JP+d5HVJjk8yKcmhrbXLR7c0AAAA6K82MH7mOOiXFTUOHt9a2y1JquozSe5Isk1rbcGoVwYAAAD03YoaBwsfftJae6iqbtI0AAAAYG1hjoMVNw5mVNU9veeVZL3ediVprbXJo1odAAAA0FfDNg5aa+uMVSEAAAAw3rRmjoNhV1UAAAAA1m4rulUBAAAA1lrmOJA4AAAAAIahcQAAAAB0cqsCAAAAdGgDJkeUOAAAAAA6SRwAAABAh9b6XUH/SRwAAAAAnSQOAAAAoIM5DiQOAAAAgGFIHAAAAEAHiQOJAwAAAGAYEgcAAADQwaoKEgcAAADAMCQOAAAAoIM5DiQOAAAAgGFIHAAAAECH1iQOJA4AAACAThIHAAAA0KEN9LuC/pM4AAAAADppHAAAAACd3KoAAAAAHQZMjihxAAAAAHSTOAAAAIAOlmOUOAAAAACGIXEAAAAAHdqAxIHEAQAAANBJ4gAAAAA6tNbvCvpP4gAAAADoJHEAAAAAHcxxIHEAAAAADEPiAAAAADoMNIkDiQMAAACgk8QBAAAAdGgSBxIHAAAAQDeJAwAAAOjQWr8r6D+JAwAAAKCTxgEAAADQya0KAAAA0MFyjBIHAAAAwDAkDgAAAKCD5RglDgAAAIBhSBwAAABAB8sxShwAAAAAw5A4AAAAgA5WVZA4AAAAAIYx6omDR018aLRPAQAAeWDRg/0uAVgDWVVB4gAAAAAYhjkOAAAAoIM5DiQOAAAAgGFIHAAAAECH1u8CxgGJAwAAAKCTxAEAAAB0MMeBxAEAAAAwDIkDAAAA6NAkDiQOAAAAYHVRVQdU1bVVdUNVnbCc46+oqrm9x0+rasbKnlPjAAAAAFYDVbVOkk8mOTDJzkn+pqp2XmrYTUme11r7iyTvSTJ7Zc/rVgUAAADoMNDvApb0tCQ3tNZuTJKq+mqSQ5Jc/fCA1tpPh4y/KMlWK3tSiQMAAAAYB6pqZlVdMuQxc6kh05PcPGR7Xm9fl9cmOWtl65I4AAAAgA4tYzc5Ymttdoa/tWB5xbTlDqzaO4ONg+esbF0aBwAAALB6mJdk6yHbWyW5ZelBVfUXST6T5MDW2p0re1KNAwAAAOgwsNzv8/vm4iQ7VtV2SX6b5PAkfzt0QFVtk+SbSY5srV23Kk6qcQAAAACrgdbaoqo6Nsk5SdZJ8rnW2lVVNat3/LQk/5hk0ySfqqokWdRa22NlzqtxAAAAAB0GxnCOg5ForZ2Z5Myl9p025PnrkrxuVZ7TqgoAAABAJ4kDAAAA6DCWqyqMVxIHAAAAQCeJAwAAAOgw0O8CxgGJAwAAAKCTxAEAAAB0MMeBxAEAAAAwDIkDAAAA6GCOA4kDAAAAYBgaBwAAAEAntyoAAABAB7cqSBwAAAAAw5A4AAAAgA6WY5Q4AAAAAIYhcQAAAAAdBgQOJA4AAACAbhIHAAAA0GHAHAcSBwAAAEA3iQMAAADo0PpdwDggcQAAAAB0kjgAAACADgP9LmAckDgAAAAAOkkcAAAAQIeBsqqCxAEAAADQSeIAAAAAOlhVQeIAAAAAGIbGAQAAANDJrQoAAADQwXKMEgcAAADAMCQOAAAAoMOA1RglDgAAAIBuEgcAAADQYSAiB484cVBVG1fVX4xGMQAAAMD4MqLGQVVdUFWTq2qTJHOS/FtVnTK6pQEAAEB/tTF8jFcjTRxMaa3dk+SlSf6ttfbUJC8cvbIAAACA8WCkcxysW1VTk/x1kneMYj0AAAAwblhVYeSJg3cnOSfJDa21i6vq8UmuH72yAAAAgPFgpImD77TWvv7wRmvtxiQvG52SAAAAYHwY6HcB48BIGwdXVtVtSX6c5EdJftJau3v0ygIAAADGgxHdqtBa2yHJ3yS5IsmLk8ypqstHsS4AAADoO6sqjDBxUFVbJXl2kucmmZHkqiQXjmJdAAAAwDgw0lsVfpPk4iTvb63NGsV6AAAAYNywqsLIV1V4cpIvJPnbqvrvqvpCVb12FOsCAAAAxoERJQ5aa3Oq6n+S/E8Gb1c4IsleST47irUBAAAAfTbSOQ4uSfKoJD/N4NwGe7XWfj2ahQEAAEC/WY5x5HMcHNha+99RrQQAAAAYd0Y6x8GEqvpsVZ2VJFW1szkOVm8b7PWUPOG8U/OE8z+dx846bJnjGx3yvOxw1sezw1kfz+P/84N59JO2XXxswoaPyTafOiE7/uDU7Hjup7L+k584hpXDmu2d7z8le73o8Bx6hHloYSy59mB0ffSUd+eXV1+Yyy49N0/efdfljvnsZz6a66/971xy8fdzycXfz4wZuyRJDj54v1x26bm55OLv56L/PjPPftaeY1k6ZGAMH+PVSBsHn09yTpJpve3rkrx5FOphLEyYkGnvnpWbXv2uXL/fMZnykr3yqB22XmLIgzfflhtffmJuOPBNuf1fvpbp7z928bFpJ70+C354Wa5/4VG54aA35YEb5o31J4A11qEH7ZvTTnlvv8uAtY5rD0bPgQe8IDvusF122vk5Oeqot+eTn/hA59i3n/je7LHnftljz/0yZ85VSZL/+q8L85Sn7ps99twvr5/5lnz60x8eq9KBnpE2DjZrrf1Hek2Q1tqiJA+NWlWMqvVn7JgHfz0/C2++LW3hotz9nR9l8r5PX2LMfZf9MgP33Dv4/Be/zMQtN0uSTNhgvTzmabvm91/7fpKkLVyUgQX3ju0HgDXYHrvvlimTN+x3GbDWce3B6Dn44P3zxS//Z5LkZz+/LFM2mpItt9x8xK+/9977Fj9/zPrrp7W2ymuE4bQau8d4NdLGwb1VtWmSliRV9Ywkd49aVYyqdbfcNAvn37F4e+Gtd2bilpt2jt/k5ftlwQ8vTZJM2nrLLPrd3dnqQ2/ODt/9WKaf/MbUeo8a9ZoBAFg9TZ+2ZebdfMvi7d/Om5/p07Zc7tj3vPvtuezSc/ORD70rkyZNWrz/kEMOyJVX/DBnfPv0vP71bxn1moEljbRxcFySM5JsX1U/SfKFJG/sGlxVM6vqkqq65D8XWHxh3KllW1ldndvHPGO3bPzX++bWkz8/+NJ118l6u2yfO798Zm548ZszcN8D2fyoZedIAACAJKkR/uz5jnd+ILvsulee8cwXZeNNNsrbjj968bFvf/vs7Lrb8/Kyw16bf3rX8aNaLyzNHAcjbBy01i5L8rwkz0ryhiS7tNbmDjN+dmttj9baHodt+LhVUymrzKL5d2Ti1M0Wb0/cctMsuu13y4x79E7bZvrJb8yvZ743D921IEmycP4dWXjrHbn/8uuSJHef9ZM8epftx6ZwAABWC0fNetXiSQ5vmX9rttp62uJj07eamlvm37bMa2699fYkyYMPPpjTT/9a9tzjycuM+fGFP8vjH/+4bLrpxqNXPLCMYRsHVfWC3p8vTfKSJE9M8oQkB/f2sRq6b+71edS20zJxqy1SE9fNlIP3yj0/+PkSYyZOe2y2OfXEzDvulDx405+iZYvuuCsL59+RSY+fniTZ4Fkz8scbbh7T+gEAGN9OPe30xZMcnnHGOTnyFYMJ1ac/7Sm55+57FjcJhho678FLXnJArrr6l0mS7bffdvH+J+++ayZNmpg77/z96H4AGELiIFl3Bcefl+S/khy8nGMtyTdXeUWMvocGcstJp2W7L/xTMmFCfv/1H+SP1/8mm/ztAUmS3/372dn8TYdn3Y0nZ9p7jkqStEUP5X8OOS5JcstJn87WH31LatK6efA3t2Xe8R/r1yeBNc7xJ52ci38xN3fddU/2OfSIHP3aI/Oyg/fvd1mwxnPtweg586zzcsABL8i11/wk991/f173uuMWH/vOt7+QmbOOz/z5t+WLp38imz12k1RV5sy5Kkcfc0KS5KV/eVCOOOKwLFy4KA/c/0D+9hVH9eujwFqrRjIraVWt01r7s1ZRuGK7g017Cn2w08X/3O8SAGBMrTftuf0uAdZKix787TheD2Dl/cvWR4zZ77RvvPlL4/LvcqSTI95UVbOrap9a3uwmAAAAwBpppI2DJyb5QZJjMthE+ERVPWf0ygIAAID+G6ixe4xXI11V4f7W2n+01l6a5MlJJif54ahWBgAAAPTdiiZHXKyqnpfk5UkOTHJxkr8eraIAAABgPBjPqx2MlRE1DqrqpiSXJ/mPJMe31u4dzaIAAACA8WGkiYMZrbV7RrUSAAAAYNwZ6eSIW1bVeVV1ZZJU1V9U1TtHsS4AAADou4ExfIxXI20c/GuSE5MsTJLW2twkh49WUQAAAMCyquqAqrq2qm6oqhOWc7yq6uO943Or6ikre86RNg7Wb639fKl9i1b25AAAADCetTF8rEhVrZPkkxlctGDnJH9TVTsvNezAJDv2HjOTnPrIP/WSRto4uKOqtk/vs1TVYUnmr+zJAQAAgBF7WpIbWms3ttYeTPLVJIcsNeaQJF9ogy5KslFVTV2Zk450csRjksxOslNV/TbJTUlesTInBgAAgPFuoMbuXFU1M4MpgYfNbq3NHrI9PcnNQ7bnJXn6Um+zvDHTsxJf/o+ocdBauzHJC6vqMRlMKdyf5OVJfv3nnhgAAAD4k16TYPYwQ5bXxlj6LoeRjHlEhr1VoaomV9WJVfWJqto3yX1JXpXkhiR/vTInBgAAgPFunK2qMC/J1kO2t0pyy58x5hFZ0RwHX0zyxCRXJHl9ku8n+askh7bWlr6PAgAAABg9FyfZsaq2q6pJGVzt8IylxpyR5JW91RWekeTu1tpKzVG4olsVHt9a2y1JquozSe5Isk1rbcHKnBQAAABWByuV8V/FWmuLqurYJOckWSfJ51prV1XVrN7x05KcmeSgDN4pcF+S16zseVfUOFg4pMCHquomTQMAAADoj9bamRlsDgzdd9qQ5y2DCxysMitqHMyoqnt6zyvJer3t6tUzeVUWAwAAAOPJwLjKHPTHsI2D1to6Y1UIAAAAMP6MaDlGAAAAWBuNcLWDNdqKVlUAAAAA1mISBwAAANDBDAcSBwAAAMAwNA4AAACATm5VAAAAgA4mR5Q4AAAAAIYhcQAAAAAdBqrfFfSfxAEAAADQSeIAAAAAOgxYkFHiAAAAAOgmcQAAAAAd5A0kDgAAAIBhSBwAAABAh4F+FzAOSBwAAAAAnSQOAAAAoINVFSQOAAAAgGFIHAAAAEAHeQOJAwAAAGAYEgcAAADQwaoKEgcAAADAMDQOAAAAgE5uVQAAAIAOlmOUOAAAAACGIXEAAAAAHeQNJA4AAACAYUgcAAAAQAfLMUocAAAAAMOQOAAAAIAOzSwHEgcAAABAN4kDAAAA6GCOA4kDAAAAYBgSBwAAANBhwBwHEgcAAABAN4kDAAAA6CBvIHEAAAAADEPiAAAAADqY40DiAAAAABiGxgEAAADQya0KAAAA0GGg3wWMAxIHAAAAQCeJAwAAAOjQTI4ocQAAAAB0kzgAAACADuY4kDgAAAAAhjHqiYNn3nblaJ8CWJ5t9ul3BbDWemDRg/0uAdZK99/y436XAKyBzHEgcQAAAAAMwxwHAAAA0MEcBxIHAAAAwDAkDgAAAKDDQDPHgcQBAAAA0EniAAAAADrIG0gcAAAAAMOQOAAAAIAOAzIHEgcAAABAN40DAAAAoJNbFQAAAKBDc6uCxAEAAADQTeIAAAAAOgz0u4BxQOIAAAAA6KRxAAAAAB0G0sbssTKqapOqOreqru/9ufFyxmxdVedX1TVVdVVV/f1I3lvjAAAAAFZ/JyQ5r7W2Y5LzettLW5TkLa21JyV5RpJjqmrnFb2xxgEAAAB0aGP4z0o6JMnpveenJzl0mc/S2vzW2mW95wuSXJNk+oreWOMAAAAAxoGqmllVlwx5zHwEL9+itTY/GWwQJNl8BefaNsmTk/xsRW9sVQUAAADoMJarKrTWZieZ3XW8qn6QZMvlHHrHIzlPVW2Q5BtJ3txau2dF4zUOAAAAYDXQWnth17Gquq2qprbW5lfV1CS3d4ybmMGmwZdba98cyXndqgAAAAAdWmtj9lhJZyR5Ve/5q5J8e+kBVVVJPpvkmtbaKSN9Y40DAAAAWP2dnGTfqro+yb697VTVtKo6szfm2UmOTPKCqrq89zhoRW/sVgUAAADoMLDyqx2MidbanUn2Wc7+W5Ic1Ht+YZJ6pO8tcQAAAAB0kjgAAACADmO5qsJ4JXEAAAAAdNI4AAAAADq5VQEAAAA6tNVkcsTRJHEAAAAAdJI4AAAAgA6ry3KMo0niAAAAAOgkcQAAAAAdWpM4kDgAAAAAOkkcAAAAQIeBfhcwDkgcAAAAAJ0kDgAAAKBDs6qCxAEAAADQTeIAAAAAOgxIHEgcAAAAAN0kDgAAAKBDaxIHEgcAAABAJ4kDAAAA6GCOA4kDAAAAYBgSBwAAANChSRxIHAAAAADdNA4AAACATm5VAAAAgA4DlmOUOAAAAAC6SRwAAABAB3kDiQMAAABgGBIHAAAA0GFA5kDiAAAAAOgmcQAAAAAdJA4kDgAAAIBhSBwAAABAh9YkDiQOAAAAgE4SBwAAANDBHAcSBwAAAMAwRtQ4qKonVNV5VXVlb/svquqdo1saAAAA9Fcbw3/Gq5EmDv41yYlJFiZJa21uksNHqygAAABgfBjpHAfrt9Z+XlVD9y0ahXoAAABg3LCqwsgTB3dU1fbJYHaiqg5LMn/UqgIAAADGhZEmDo5JMjvJTlX12yQ3JTli1KoCAAAAxoURJQ5aaze21l6Y5LFJdmqtPae19qtRrYxR96EPn5Q5V5yfi352VmbsvsuwYz/8kXfl1tuvXLy90UaT85WvnpaLfnZWLvjRt7Lzzk8Y7XJhjeHag/756Cnvzi+vvjCXXXpunrz7rssd89nPfDTXX/vfueTi7+eSi7+fGTMGr9ODD94vl116bi65+Pu56L/PzLOftedYlg5rpHe+/5Ts9aLDc+gRs/pdCnQaSBuzx3g10lUV3l9VG7XW7m2tLaiqjavqvaNdHKNnv/2fn+132DYzdts7bzz2xHzsn7v/dT75KbtlypTJS+x76/HHZO7cq/OMpx+Yma87Lh/80D+OdsmwRnDtQf8ceMALsuMO22WnnZ+To456ez75iQ90jn37ie/NHnvulz323C9z5lyVJPmv/7owT3nqvtljz/3y+plvyac//eGxKh3WWIcetG9OO8WvFTDejXSOgwNba3c9vNFa+32Sg0alIsbEi1+8b77y5W8mSS6++PJMmTI5W2z52GXGTZgwIe9734l55zuX/OFqpyftkAvO/2mS5Lrrbsw2j9sqm2++2egXDqs51x70z8EH758vfvk/kyQ/+/llmbLRlGy55eYjfv299963+Plj1l/fZFmwCuyx+26ZMnnDfpcBw2qtjdljvBpp42CdqnrUwxtVtV6SRw0znnFu6rQtMm/en+a3vOW38zNt2pbLjJs165X53vd+kNtu/d8l9l9xxTV5ySH7J0meuseMbLPN9EybvuzrgSW59qB/pk/bMvNuvmXx9m/nzc/05Vx/SfKed789l116bj7yoXdl0qRJi/cfcsgBufKKH+aMb5+e17/+LaNeMwCMByNtHHwpyXlV9dqq+rsk5yY5vWtwVc2sqkuq6pKFixasijpZxZZaWjPJssuMbDl18xz60oNy2qnL/qs+5cOnZaONp+SnF30vs2a9KnPmXJVFix4atXphTeHag/4ZyfWXJO945weyy6575RnPfFE23mSjvO34oxcf+/a3z86uuz0vLzvstfmndx0/qvUCMD6Y42CEqyq01j5YVVck2SdJJXlPa+2cYcbPzuAqDNlg/e3G76dfy8x8w5F59WsOT5JceuncbLXV1MXHpk2fmvnzb1ti/IwZu2T77bfN3CsvSJKsv/56mXPF+Zmx295ZsOAPOeoNb1s89qprfpxf/+rm0f8QsBpy7UH/HDXrVXnta1+RJLnkksuz1dbTFh+bvtXU3LLU9Zckt956e5LkwQcfzOmnfy3H/cOyk7b9+MKf5fGPf1w23XTj3Hnn70epegAYH0aaOEhr7azW2ltba28ZrmnA+DX701/Ms57xojzrGS/Kd7/z/fzNK16aJNlzz91zzz0LlolEn3P2+dl+u6dllyc9N7s86bm57777M2O3vZMkU6ZsmIkTJyZJXv2aw/OTC3+eBQv+MLYfCFYTrj3on1NPO33xJIdnnHFOjnzFYUmSpz/tKbnn7nsWNwmGGjrvwUteckCuuvqXSZLtt9928f4n775rJk2aqGkAsBZoY/jPeDVs4qCqLmytPaeqFiRLfIpK0lprkzteyjh3ztnnZ//9987cKy/I/ffdn1mz/vQN5jf+3+dyzNEn5Nb5y/4w9bAnPnGHzP7MRzLw0EB++cvrc/RRbx+LsmG159qD/jnzrPNywAEvyLXX/CT33X9/Xve64xYf+863v5CZs47P/Pm35YunfyKbPXaTVFXmzLkqRx9zQpLkpX95UI444rAsXLgoD9z/QP72FUf166PAGuP4k07Oxb+Ym7vuuif7HHpEjn7tkXnZwfv3uyxgKTXaMze6VQGAtc0Dix7sdwmwVrr/lh/3uwRYK03c7PHLTiKzBtl1i2eM2e+0V9520bj8u1zhrQpVNaGqrhyLYgAAAIDxZYWTI7bWBqpqTlVt01r7zVgUBQAAAOPBeJ57YKyMaFWFJFOTXFVVP09y78M7W2svGZWqAAAAgHFhpI2DfxrVKgAAAGAcGhjleQFXBytaVeHRSWYl2SHJFUk+21pbNBaFAQAAAP23osTB6UkWJvlxkgOT7Jzk70e7KAAAABgPzHGw4sbBzq213ZKkqj6b5OejXxIAAAAwXqxoOcaFDz9xiwIAAACsfVaUOJhRVff0nleS9XrblaS11iaPanUAAADQRyZHXEHjoLW2zlgVAgAAAIw/I12OEQAAANY6Jkdc8RwHAAAAwFpM4gAAAAA6mONA4gAAAABWe1W1SVWdW1XX9/7ceJix61TVL6rquyN5b40DAAAA6NDG8J+VdEKS81prOyY5r7fd5e+TXDPSN9Y4AAAAgNXfIUlO7z0/PcmhyxtUVVsleVGSz4z0jc1xAAAAAB1aGxizc1XVzCQzh+ya3VqbPcKXb9Fam58krbX5VbV5x7iPJXlbkg1HWpfGAQAAAIwDvSZBZ6Ogqn6QZMvlHHrHSN6/ql6c5PbW2qVV9fyR1qVxAAAAAB0GVn7ugVWmtfbCrmNVdVtVTe2lDaYmuX05w56d5CVVdVCSRyeZXFVfaq0dMdx5zXEAAAAAq78zkryq9/xVSb699IDW2omtta1aa9smOTzJf62oaZBoHAAAAECn1tqYPVbSyUn2rarrk+zb205VTauqM1fmjd2qAAAAAKu51tqdSfZZzv5bkhy0nP0XJLlgJO+tcQAAAAAdxtMcB/3iVgUAAACgk8YBAAAA0MmtCgAAANBhFUxauNqTOAAAAAA6SRwAAABAhwGJA4kDAAAAoJvEAQAAAHRolmOUOAAAAAC6SRwAAABAB6sqSBwAAAAAw5A4AAAAgA4D5jiQOAAAAAC6SRwAAABAB3McSBwAAAAAw5A4AAAAgA4DEgcSBwAAAEA3iQMAAADoYI4DiQMAAABgGBoHAAAAQCe3KgAAAECHgbhVQeIAAAAA6CRxAAAAAB1MjihxAAAAAAxD4gAAAAA6DEgcSBwAAAAA3SQOAAAAoEOzqoLEAQAAANBN4gAAAAA6mONA4gAAAAAYhsQBAAAAdGgSBxIHAAAAQDeJAwAAAOhgVQWJAwAAAGAYEgcAAADQwRwHEgcAAADAMDQOAAAAgE5uVQAAAIAOblWQOAAAAACGIXEAAAAAHeQNJA4AAACAYZT7NRhOVc1src3udx2wtnHtQX+49qA/XHswvkkcsCIz+10ArKVce9Afrj3oD9cejGMaBwAAAEAnjQMAAACgk8YBK+JeM+gP1x70h2sP+sO1B+OYyREBAACAThIHAAAAQCeNAwAAAKCTxsFaqKreUVVXVdXcqrq8qp5eVW+uqvX7XRus7qrqod51dWVVfaeqNlrB+N2r6qAh2y+pqhNGvVBYgzzS626Y93l3Vb1wFZcHa62lrs2vd/2sWVU/HevagEfGHAdrmap6ZpJTkjy/tfbHqtosyaQkP02yR2vtjkfwXuu01h4apVJhtVRVf2itbdB7fnqS61pr7xtm/KszeO0dO0YlwhrnkV53wNhY6tr8cpJLW2unDDnuZ0lYTUgcrH2mJrmjtfbHJOk1Cg5LMi3J+VV1fpJU1alVdUkvmfBPD7+4qn5VVf9YVRcm+auqelNVXd1LL3y1D58HxrP/TjI9SarqaVX106r6Re/PJ1bVpCTvTvLy3jcyL6+qV1fVJ3qv+XxVfbw3/saqOqy3f0JVfap3fX63qs4ccuzkIdfkh/v0uaGfhl5321fV2VV1aVX9uKp2qqopvf+WTeiNWb+qbq6qib1r7uFr6alV9cPea8+pqqlVtXlVXdo7PqOqWlVt09v+n957/VXv29U5VfWjPv0dwHj04yQ7VNXzq+r8qvr3JFckgw2GhwdV1duq6oreNXRyb98y13J/PgKsvdbtdwGMue8n+cequi7JD5J8rbX28ao6LsneQxIH72it/a6q1klyXlX9RWttbu/YA6215yRJVd2SZLteemGjMf4sMG71rp19kny2t+uXSfZqrS3qRaHf31p7WVX9Y4YkDnoJhKGmJnlOkp2SnJHkP5O8NMm2SXZLsnmSa5J8rqo2SfKXSXZqrTXXJGub5Vx3s5PMaq1dX1VPT/Kp1toLqmpOkuclOT/JwUnOaa0trKqH32dikn9Jckhr7X+r6uVJ3tda+7uqenRVTU7y3CSXJHlur5l+e2vtvt41vX9r7beuQRhUVesmOTDJ2b1dT0uya2vtpqXGHZjk0CRP711Pm/QOLXMtJ3nBmBQPJNE4WOu01v5QVU/N4A88eyf5Wi3/fuq/rqqZGfzfyNQkOyd5uHHwtSHj5ib5clV9K8m3RqtuWI2sV1WXZ/AX+0uTnNvbPyXJ6VW1Y5KWZOII3+9brbWBJFdX1Ra9fc9J8vXe/lsfTgoluSfJA0k+U1XfS/Ldlf0wsJpY5rqrqg2SPCvJ1x9uCCR5VO/PryV5eQYbB4dn8JeQoZ6YZNfe+yTJOknm9479NMmzk+yV5P1JDkhSGfw2NUl+kuTzVfUfSb65qj4grKYevjaTwWvksxm8Ln++dNOg54VJ/q21dl+S9L7EGu5aBsaIxsFaqHcv2QVJLqiqK5K8aujxqtouyVuT7Nla+31VfT7Jo4cMuXfI8xdl8IenlyT5P1W1S2tt0SiWD+Pd/a213atqSgZ/cT8myceTvCfJ+a21v6yqbTN4DY7EH4c8r6X+XEIvzfC0DH7jeniSY+MbGdYOy7vuPp/krtba7ssZf0aSD/S+zXxqkv9a6ngluaq19szlvPbHGWy+Py7Jt5O8PYPNwO8mSWttVu8b0Rclubyqdm+t3bmSnw9WV/cvfQ32fvm/d7mjB6+9pSdgm5DuaxkYI+Y4WMv07qvecciu3ZP8OsmCJBv29k3O4P+h3937hvPAjveakGTr1tr5Sd6WZKMkG4xO5bB6aa3dneRNSd7aiz1PSfLb3uFXDxk69NobqQuTvKw318EWSZ6fJL1vZaa01s5M8uYMXt+w1hh63SW5P8lNVfVXSVKDZvTG/SHJz5P8c5LvLmdytmuTPLYGJxROb/6DXXrHfpTkiCTX91I/v0tyUAaTBqmq7VtrP2ut/WOSO5JsPWofGNY830/yd9VbfaGqNmmt3ZOOaxkYOxIHa58NkvxL777LRUluSDIzyd8kOauq5rfW9q6qXyS5KsmN6f0wtBzrJPlS7xueSvLR1tpdo1w/rDZaa7/o3Ut9eJIPZvBWheOy5Leb5yc5oRfl/MAI3/obGUwVXJnkuiQ/S3J3BhsQ366qR2fwmvyHVfE5YHWy1HX3iiSnVtU7M3h70FeTzOkN/VqSr6fXeFvqPR6swUkSP977b9y6ST6WwRTCr3rfmD488eGFSbZqrf2+t/2hXoO+kpw35HzACrTWzq6q3ZNcUlUPJjkzyf+X4a9lYAxYjhFgNVRVG/TmLNk0g9+cPru1dmu/6wIAYM0jcQCwevpuLzk0Kcl7NA0AABgtEgcAAABAJ5MjAgAAAJ00DgAAAIBOGgcAAABAJ40DAAAAoJPGAQAAANDp/wecWU1Q/8Hd2QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "sns.heatmap(new.corr(),annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "82bcfef1",
   "metadata": {},
   "outputs": [],
   "source": [
    "corr_matrix = new.corr()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bbe2b500",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ratings    1.000000\n",
       "Reviews    0.996262\n",
       "Stars      0.237663\n",
       "Price     -0.485087\n",
       "Name: Ratings, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " corr_matrix[\"Ratings\"].sort_values(ascending=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d178eef5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x202a6639c70>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5733e8a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x202a6c39a90>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 614.25x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(new,hue='Price')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaa54f65",
   "metadata": {},
   "source": [
    "# Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9a4e7de",
   "metadata": {},
   "source": [
    "# Display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "79401c7e",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>APPLE iPhone 11 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ProductName  Stars  Ratings  Reviews  Price         ROM  \\\n",
       "0  APPLE iPhone 11 (White    4.6    95977     7038  43900   64 GB ROM   \n",
       "1  APPLE iPhone 11 (White    4.6    95977     7038  48900  128 GB ROM   \n",
       "2  APPLE iPhone 11 (Black    4.6    95977     7038  48900  128 GB ROM   \n",
       "3  APPLE iPhone 11 (Green    4.6    95977     7038  48900  128 GB ROM   \n",
       "4  APPLE iPhone 11 (Black    4.6    95977     7038  43900   64 GB ROM   \n",
       "\n",
       "                                        Display  \\\n",
       "0  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "1  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "2  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "3  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "4  15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "\n",
       "                            Camera                 Processorr  \n",
       "0  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "1  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "2  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "3  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  \n",
       "4  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "4a6ce42a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# clean the Display column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "65d13301",
   "metadata": {},
   "outputs": [],
   "source": [
    "new['Liquid_Retina_HD'] = new['Display'].apply(lambda x:1 if 'Liquid Retina HD Display' in x else 0)\n",
    "new['Super_Retina_XDR'] = new['Display'].apply(lambda x:1 if 'Super Retina XDR Display' in x else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1c900396",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
       "      <th>Liquid_Retina_HD</th>\n",
       "      <th>Super_Retina_XDR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>APPLE iPhone 11 (Red</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Liquid Retina HD Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>APPLE iPhone SE (White</td>\n",
       "      <td>4.5</td>\n",
       "      <td>152</td>\n",
       "      <td>596</td>\n",
       "      <td>35499</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>11.94 cm (4.7 inch) Retina HD Display</td>\n",
       "      <td>12MP Rear Camera | 7MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip with 3rd Gen Neural Engine Pro...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>APPLE iPhone 14 (Purple</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>79900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Super Retina XDR Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>APPLE iPhone 14 Pro (Silver</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>129900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Super Retina XDR Display</td>\n",
       "      <td>48MP + 12MP + 12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A16 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>APPLE iPhone 12 (Purple</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>59900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>15.49 cm (6.1 inch) Super Retina XDR Display</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A14 Bionic Chip with Next Generation Neural En...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    ProductName  Stars  Ratings  Reviews   Price         ROM  \\\n",
       "8          APPLE iPhone 11 (Red    4.6    95977     7038   43900   64 GB ROM   \n",
       "11       APPLE iPhone SE (White    4.5      152      596   35499  128 GB ROM   \n",
       "20      APPLE iPhone 14 (Purple    5.0        3        0   79900  128 GB ROM   \n",
       "10  APPLE iPhone 14 Pro (Silver    5.0        4        1  129900  128 GB ROM   \n",
       "45      APPLE iPhone 12 (Purple    4.6      181      662   59900   64 GB ROM   \n",
       "\n",
       "                                         Display  \\\n",
       "8   15.49 cm (6.1 inch) Liquid Retina HD Display   \n",
       "11         11.94 cm (4.7 inch) Retina HD Display   \n",
       "20  15.49 cm (6.1 inch) Super Retina XDR Display   \n",
       "10  15.49 cm (6.1 inch) Super Retina XDR Display   \n",
       "45  15.49 cm (6.1 inch) Super Retina XDR Display   \n",
       "\n",
       "                                           Camera  \\\n",
       "8                 12MP + 12MP | 12MP Front Camera   \n",
       "11            12MP Rear Camera | 7MP Front Camera   \n",
       "20                12MP + 12MP | 12MP Front Camera   \n",
       "10  48MP + 12MP + 12MP + 12MP | 12MP Front Camera   \n",
       "45                12MP + 12MP | 12MP Front Camera   \n",
       "\n",
       "                                           Processorr  Liquid_Retina_HD  \\\n",
       "8                           A13 Bionic Chip Processor                 1   \n",
       "11  A13 Bionic Chip with 3rd Gen Neural Engine Pro...                 0   \n",
       "20         A15 Bionic Chip 6 Core Processor Processor                 0   \n",
       "10         A16 Bionic Chip 6 Core Processor Processor                 0   \n",
       "45  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "\n",
       "    Super_Retina_XDR  \n",
       "8                  0  \n",
       "11                 0  \n",
       "20                 1  \n",
       "10                 1  \n",
       "45                 1  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "609a2784",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.49 cm (6.1 inch) Super Retina XDR Display    19\n",
       "15.49 cm (6.1 inch) Liquid Retina HD Display    12\n",
       "13.72 cm (5.4 inch) Super Retina XDR Display     7\n",
       "17.02 cm (6.7 inch) Super Retina XDR Display     6\n",
       "11.94 cm (4.7 inch) Retina HD Display            4\n",
       "Name: Display, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new['Display'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "64179774",
   "metadata": {},
   "outputs": [],
   "source": [
    "final = new.drop('Display',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "204a7d93",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
       "      <th>Liquid_Retina_HD</th>\n",
       "      <th>Super_Retina_XDR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>APPLE iPhone 14 (Purple</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>89900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>APPLE iPhone 13 Mini (Starlight</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2188</td>\n",
       "      <td>197</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>APPLE iPhone 12 (Purple</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A14 Bionic Chip with Next Generation Neural En...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>APPLE iPhone 12 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A14 Bionic Chip with Next Generation Neural En...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 (Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        ProductName  Stars  Ratings  Reviews  Price  \\\n",
       "32          APPLE iPhone 14 (Purple    5.0        3        0  89900   \n",
       "43  APPLE iPhone 13 Mini (Starlight    4.5     2188      197  64900   \n",
       "26          APPLE iPhone 12 (Purple    4.6      181      662  64900   \n",
       "30           APPLE iPhone 12 (Green    4.6      181      662  64900   \n",
       "4            APPLE iPhone 11 (Black    4.6    95977     7038  43900   \n",
       "\n",
       "           ROM                           Camera  \\\n",
       "32  256 GB ROM  12MP + 12MP | 12MP Front Camera   \n",
       "43  128 GB ROM  12MP + 12MP | 12MP Front Camera   \n",
       "26  128 GB ROM  12MP + 12MP | 12MP Front Camera   \n",
       "30  128 GB ROM  12MP + 12MP | 12MP Front Camera   \n",
       "4    64 GB ROM  12MP + 12MP | 12MP Front Camera   \n",
       "\n",
       "                                           Processorr  Liquid_Retina_HD  \\\n",
       "32         A15 Bionic Chip 6 Core Processor Processor                 0   \n",
       "43                          A15 Bionic Chip Processor                 0   \n",
       "26  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "30  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "4                           A13 Bionic Chip Processor                 1   \n",
       "\n",
       "    Super_Retina_XDR  \n",
       "32                 1  \n",
       "43                 1  \n",
       "26                 1  \n",
       "30                 1  \n",
       "4                  0  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "781388e2",
   "metadata": {},
   "source": [
    "# ProductName"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3735dd79",
   "metadata": {},
   "outputs": [],
   "source": [
    "final['ProductName'] = final['ProductName'].str.replace('$', '', regex=True).replace('\\,', '.', regex=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "55b01e48",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\AppData\\Local\\Temp\\ipykernel_18340\\2242520711.py:1: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  final['ProductName'] = final['ProductName'].str.replace(\")\",'')\n"
     ]
    }
   ],
   "source": [
    "final['ProductName'] = final['ProductName'].str.replace(\")\",'')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "71cd850d",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
       "      <th>Liquid_Retina_HD</th>\n",
       "      <th>Super_Retina_XDR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>APPLE iPhone 12 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A14 Bionic Chip with Next Generation Neural En...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>APPLE iPhone 13 Mini (Blue</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2188</td>\n",
       "      <td>197</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>APPLE iPhone 14 (Purple</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>89900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Apple iPhone 11 (Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95955</td>\n",
       "      <td>7038</td>\n",
       "      <td>49900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>APPLE iPhone 14 ((PRODUCTRED</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>89900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>APPLE iPhone SE (Black</td>\n",
       "      <td>4.5</td>\n",
       "      <td>152</td>\n",
       "      <td>589</td>\n",
       "      <td>35499</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP Rear Camera | 7MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip with 3rd Gen Neural Engine Pro...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>APPLE iPhone 11 (Yellow</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95955</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>APPLE iPhone 12 (White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A14 Bionic Chip with Next Generation Neural En...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>APPLE iPhone 14 Pro Max (Space Black</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>149900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>48MP + 12MP + 12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A16 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>APPLE iPhone 13 Mini ((PRODUCTRED</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2188</td>\n",
       "      <td>197</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             ProductName  Stars  Ratings  Reviews   Price  \\\n",
       "30                APPLE iPhone 12 (Green    4.6      181      662   64900   \n",
       "31            APPLE iPhone 13 Mini (Blue    4.5     2188      197   64900   \n",
       "32               APPLE iPhone 14 (Purple    5.0        3        0   89900   \n",
       "33                Apple iPhone 11 (Green    4.6    95955     7038   49900   \n",
       "34          APPLE iPhone 14 ((PRODUCTRED    5.0        3        0   89900   \n",
       "35                APPLE iPhone SE (Black    4.5      152      589   35499   \n",
       "36               APPLE iPhone 11 (Yellow    4.6    95955     7038   48900   \n",
       "37                APPLE iPhone 12 (White    4.6      181      662   64900   \n",
       "38  APPLE iPhone 14 Pro Max (Space Black    0.0        0        0  149900   \n",
       "39     APPLE iPhone 13 Mini ((PRODUCTRED    4.5     2188      197   64900   \n",
       "\n",
       "           ROM                                         Camera  \\\n",
       "30  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "31  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "32  256 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "33   64 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "34  256 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "35  128 GB ROM            12MP Rear Camera | 7MP Front Camera   \n",
       "36  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "37  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "38  256 GB ROM  48MP + 12MP + 12MP + 12MP | 12MP Front Camera   \n",
       "39  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "\n",
       "                                           Processorr  Liquid_Retina_HD  \\\n",
       "30  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "31                          A15 Bionic Chip Processor                 0   \n",
       "32         A15 Bionic Chip 6 Core Processor Processor                 0   \n",
       "33                          A13 Bionic Chip Processor                 1   \n",
       "34         A15 Bionic Chip 6 Core Processor Processor                 0   \n",
       "35  A13 Bionic Chip with 3rd Gen Neural Engine Pro...                 0   \n",
       "36                          A13 Bionic Chip Processor                 1   \n",
       "37  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "38         A16 Bionic Chip 6 Core Processor Processor                 0   \n",
       "39                          A15 Bionic Chip Processor                 0   \n",
       "\n",
       "    Super_Retina_XDR  \n",
       "30                 1  \n",
       "31                 1  \n",
       "32                 1  \n",
       "33                 0  \n",
       "34                 1  \n",
       "35                 0  \n",
       "36                 0  \n",
       "37                 1  \n",
       "38                 1  \n",
       "39                 1  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final[30:40]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "66ec63fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\AppData\\Local\\Temp\\ipykernel_18340\\3343722985.py:1: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  final['ProductName'] = final['ProductName'].str.replace(\"(\",'')\n"
     ]
    }
   ],
   "source": [
    "final['ProductName'] = final['ProductName'].str.replace(\"(\",'')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "105b198b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ProductName</th>\n",
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       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>APPLE iPhone 12 Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
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       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>APPLE iPhone 13 Mini Blue</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2188</td>\n",
       "      <td>197</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>APPLE iPhone 14 Purple</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>89900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Apple iPhone 11 Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95955</td>\n",
       "      <td>7038</td>\n",
       "      <td>49900</td>\n",
       "      <td>64 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>APPLE iPhone 14 PRODUCTRED</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>89900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>APPLE iPhone SE Black</td>\n",
       "      <td>4.5</td>\n",
       "      <td>152</td>\n",
       "      <td>589</td>\n",
       "      <td>35499</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP Rear Camera | 7MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip with 3rd Gen Neural Engine Pro...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>APPLE iPhone 11 Yellow</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95955</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>APPLE iPhone 12 White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>181</td>\n",
       "      <td>662</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A14 Bionic Chip with Next Generation Neural En...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>APPLE iPhone 14 Pro Max Space Black</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>149900</td>\n",
       "      <td>256 GB ROM</td>\n",
       "      <td>48MP + 12MP + 12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A16 Bionic Chip 6 Core Processor Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>APPLE iPhone 13 Mini PRODUCTRED</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2188</td>\n",
       "      <td>197</td>\n",
       "      <td>64900</td>\n",
       "      <td>128 GB ROM</td>\n",
       "      <td>12MP + 12MP | 12MP Front Camera</td>\n",
       "      <td>A15 Bionic Chip Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "                            ProductName  Stars  Ratings  Reviews   Price  \\\n",
       "30                APPLE iPhone 12 Green    4.6      181      662   64900   \n",
       "31            APPLE iPhone 13 Mini Blue    4.5     2188      197   64900   \n",
       "32               APPLE iPhone 14 Purple    5.0        3        0   89900   \n",
       "33                Apple iPhone 11 Green    4.6    95955     7038   49900   \n",
       "34           APPLE iPhone 14 PRODUCTRED    5.0        3        0   89900   \n",
       "35                APPLE iPhone SE Black    4.5      152      589   35499   \n",
       "36               APPLE iPhone 11 Yellow    4.6    95955     7038   48900   \n",
       "37                APPLE iPhone 12 White    4.6      181      662   64900   \n",
       "38  APPLE iPhone 14 Pro Max Space Black    0.0        0        0  149900   \n",
       "39      APPLE iPhone 13 Mini PRODUCTRED    4.5     2188      197   64900   \n",
       "\n",
       "           ROM                                         Camera  \\\n",
       "30  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "31  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "32  256 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "33   64 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "34  256 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "35  128 GB ROM            12MP Rear Camera | 7MP Front Camera   \n",
       "36  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "37  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "38  256 GB ROM  48MP + 12MP + 12MP + 12MP | 12MP Front Camera   \n",
       "39  128 GB ROM                12MP + 12MP | 12MP Front Camera   \n",
       "\n",
       "                                           Processorr  Liquid_Retina_HD  \\\n",
       "30  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "31                          A15 Bionic Chip Processor                 0   \n",
       "32         A15 Bionic Chip 6 Core Processor Processor                 0   \n",
       "33                          A13 Bionic Chip Processor                 1   \n",
       "34         A15 Bionic Chip 6 Core Processor Processor                 0   \n",
       "35  A13 Bionic Chip with 3rd Gen Neural Engine Pro...                 0   \n",
       "36                          A13 Bionic Chip Processor                 1   \n",
       "37  A14 Bionic Chip with Next Generation Neural En...                 0   \n",
       "38         A16 Bionic Chip 6 Core Processor Processor                 0   \n",
       "39                          A15 Bionic Chip Processor                 0   \n",
       "\n",
       "    Super_Retina_XDR  \n",
       "30                 1  \n",
       "31                 1  \n",
       "32                 1  \n",
       "33                 0  \n",
       "34                 1  \n",
       "35                 0  \n",
       "36                 0  \n",
       "37                 1  \n",
       "38                 1  \n",
       "39                 1  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "final[30:40]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cc85649",
   "metadata": {},
   "source": [
    "# Rom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "62fcefe6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#removing gb in rom column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "5cdb3acb",
   "metadata": {},
   "outputs": [],
   "source": [
    "final['ROM'] = final['ROM'].str.replace('GB ROM','')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "5bbab407",
   "metadata": {},
   "outputs": [],
   "source": [
    "final['ROM'] = final['ROM'].astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "ce51461f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "             ProductName  Stars  Ratings  Reviews  Price  ROM  \\\n",
       "0  APPLE iPhone 11 White    4.6    95977     7038  43900   64   \n",
       "1  APPLE iPhone 11 White    4.6    95977     7038  48900  128   \n",
       "\n",
       "                            Camera                 Processorr  \\\n",
       "0  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor   \n",
       "1  12MP + 12MP | 12MP Front Camera  A13 Bionic Chip Processor   \n",
       "\n",
       "   Liquid_Retina_HD  Super_Retina_XDR  \n",
       "0                 1                 0  \n",
       "1                 1                 0  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "final.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e623372",
   "metadata": {},
   "source": [
    "# Camera"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "a1e9c78a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rajesh\\AppData\\Local\\Temp\\ipykernel_18340\\2628332049.py:1: FutureWarning: The default value of regex will change from True to False in a future version.\n",
      "  final['Camera'] = final['Camera'].str.replace('12MP + 12MP | 12MP Front Camera','12MP')\n",
      "C:\\Users\\rajesh\\AppData\\Local\\Temp\\ipykernel_18340\\2628332049.py:4: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  final['Camera'] = final['Camera'].str.replace('|','')\n"
     ]
    }
   ],
   "source": [
    "final['Camera'] = final['Camera'].str.replace('12MP + 12MP | 12MP Front Camera','12MP')\n",
    "final['Camera'] = final['Camera'].str.replace('Rear Camera','')\n",
    "final['Camera'] = final['Camera'].str.replace('Front Camera','')\n",
    "final['Camera'] = final['Camera'].str.replace('|','')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "0f81cc92",
   "metadata": {},
   "outputs": [
    {
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       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>APPLE iPhone 11 Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>7038</td>\n",
       "      <td>43900</td>\n",
       "      <td>64</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ProductName  Stars  Ratings  Reviews  Price  ROM  \\\n",
       "0  APPLE iPhone 11 White    4.6    95977     7038  43900   64   \n",
       "1  APPLE iPhone 11 White    4.6    95977     7038  48900  128   \n",
       "2  APPLE iPhone 11 Black    4.6    95977     7038  48900  128   \n",
       "3  APPLE iPhone 11 Green    4.6    95977     7038  48900  128   \n",
       "4  APPLE iPhone 11 Black    4.6    95977     7038  43900   64   \n",
       "\n",
       "             Camera                 Processorr  Liquid_Retina_HD  \\\n",
       "0  12MP + 12MP 12MP  A13 Bionic Chip Processor                 1   \n",
       "1  12MP + 12MP 12MP  A13 Bionic Chip Processor                 1   \n",
       "2  12MP + 12MP 12MP  A13 Bionic Chip Processor                 1   \n",
       "3  12MP + 12MP 12MP  A13 Bionic Chip Processor                 1   \n",
       "4  12MP + 12MP 12MP  A13 Bionic Chip Processor                 1   \n",
       "\n",
       "   Super_Retina_XDR  \n",
       "0                 0  \n",
       "1                 0  \n",
       "2                 0  \n",
       "3                 0  \n",
       "4                 0  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "28330c6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#removing Reviews colum\n",
    "df_final = final.drop('Reviews',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "196f2c8c",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
       "      <th>Liquid_Retina_HD</th>\n",
       "      <th>Super_Retina_XDR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>APPLE iPhone 11 White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>43900</td>\n",
       "      <td>64</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>APPLE iPhone 11 White</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>APPLE iPhone 11 Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APPLE iPhone 11 Green</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>APPLE iPhone 11 Black</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>43900</td>\n",
       "      <td>64</td>\n",
       "      <td>12MP + 12MP 12MP</td>\n",
       "      <td>A13 Bionic Chip Processor</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ProductName  Stars  Ratings  Price  ROM            Camera  \\\n",
       "0  APPLE iPhone 11 White    4.6    95977  43900   64  12MP + 12MP 12MP   \n",
       "1  APPLE iPhone 11 White    4.6    95977  48900  128  12MP + 12MP 12MP   \n",
       "2  APPLE iPhone 11 Black    4.6    95977  48900  128  12MP + 12MP 12MP   \n",
       "3  APPLE iPhone 11 Green    4.6    95977  48900  128  12MP + 12MP 12MP   \n",
       "4  APPLE iPhone 11 Black    4.6    95977  43900   64  12MP + 12MP 12MP   \n",
       "\n",
       "                  Processorr  Liquid_Retina_HD  Super_Retina_XDR  \n",
       "0  A13 Bionic Chip Processor                 1                 0  \n",
       "1  A13 Bionic Chip Processor                 1                 0  \n",
       "2  A13 Bionic Chip Processor                 1                 0  \n",
       "3  A13 Bionic Chip Processor                 1                 0  \n",
       "4  A13 Bionic Chip Processor                 1                 0  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b46e726",
   "metadata": {},
   "source": [
    "# Label Encoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "97283070",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "f480603f",
   "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>ProductName</th>\n",
       "      <th>Stars</th>\n",
       "      <th>Ratings</th>\n",
       "      <th>Price</th>\n",
       "      <th>ROM</th>\n",
       "      <th>Camera</th>\n",
       "      <th>Processorr</th>\n",
       "      <th>Liquid_Retina_HD</th>\n",
       "      <th>Super_Retina_XDR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>43900</td>\n",
       "      <td>64</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>48900</td>\n",
       "      <td>128</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>95977</td>\n",
       "      <td>43900</td>\n",
       "      <td>64</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ProductName  Stars  Ratings  Price  ROM  Camera  Processorr  \\\n",
       "0            4    4.6    95977  43900   64       1           0   \n",
       "1            4    4.6    95977  48900  128       1           0   \n",
       "2            0    4.6    95977  48900  128       1           0   \n",
       "3            1    4.6    95977  48900  128       1           0   \n",
       "4            0    4.6    95977  43900   64       1           0   \n",
       "\n",
       "   Liquid_Retina_HD  Super_Retina_XDR  \n",
       "0                 1                 0  \n",
       "1                 1                 0  \n",
       "2                 1                 0  \n",
       "3                 1                 0  \n",
       "4                 1                 0  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1=['ProductName','Camera','Processorr']\n",
    "for i in list1:\n",
    "    df_final[i]=le.fit_transform(df_final[i])\n",
    "    \n",
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "5d5ded11",
   "metadata": {},
   "outputs": [],
   "source": [
    "#saving file to csv\n",
    "df_final.to_csv('Iphone_df.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "0ed885b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# saving file to csv and doing next process"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
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