task3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0664cc7b",
   "metadata": {},
   "source": [
    "<b>The Sparks Foundation: Data Science and Business Analysis Internship</b>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e4d39c1",
   "metadata": {},
   "source": [
    "<b>Task 3: Exploratory Data Analysis - Retail</b>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14fc1286",
   "metadata": {},
   "source": [
    "Perform 'Exploratory Data Analysis' on Dataset 'SampleStore'.<br> \n",
    "As a business manager, try to find out the weak areas where you can work to make profit.<br>\n",
    "What all business problems can you derive by exploring the data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93b90994",
   "metadata": {},
   "source": [
    "<b>Author: Chaitrali S. Mirashi</b>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c538ef2",
   "metadata": {},
   "source": [
    "<b>Importing required libraries</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8e3ced67",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf37f81",
   "metadata": {},
   "source": [
    "<b>Importing and describing the dataset</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cad32bac",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('SampleSuperstore.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2fe4baec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Second Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420</td>\n",
       "      <td>South</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Bookcases</td>\n",
       "      <td>261.9600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.9136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Second Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>42420</td>\n",
       "      <td>South</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>731.9400</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>219.5820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Second Class</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Labels</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.8714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Standard Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311</td>\n",
       "      <td>South</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>957.5775</td>\n",
       "      <td>5</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-383.0310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Standard Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Lauderdale</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33311</td>\n",
       "      <td>South</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>22.3680</td>\n",
       "      <td>2</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2.5164</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ship Mode    Segment        Country             City       State  \\\n",
       "0    Second Class   Consumer  United States        Henderson    Kentucky   \n",
       "1    Second Class   Consumer  United States        Henderson    Kentucky   \n",
       "2    Second Class  Corporate  United States      Los Angeles  California   \n",
       "3  Standard Class   Consumer  United States  Fort Lauderdale     Florida   \n",
       "4  Standard Class   Consumer  United States  Fort Lauderdale     Florida   \n",
       "\n",
       "   Postal Code Region         Category Sub-Category     Sales  Quantity  \\\n",
       "0        42420  South        Furniture    Bookcases  261.9600         2   \n",
       "1        42420  South        Furniture       Chairs  731.9400         3   \n",
       "2        90036   West  Office Supplies       Labels   14.6200         2   \n",
       "3        33311  South        Furniture       Tables  957.5775         5   \n",
       "4        33311  South  Office Supplies      Storage   22.3680         2   \n",
       "\n",
       "   Discount    Profit  \n",
       "0      0.00   41.9136  \n",
       "1      0.00  219.5820  \n",
       "2      0.00    6.8714  \n",
       "3      0.45 -383.0310  \n",
       "4      0.20    2.5164  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e69612ec",
   "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>Ship Mode</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9989</th>\n",
       "      <td>Second Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>33180</td>\n",
       "      <td>South</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>25.248</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.1028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9990</th>\n",
       "      <td>Standard Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Costa Mesa</td>\n",
       "      <td>California</td>\n",
       "      <td>92627</td>\n",
       "      <td>West</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>91.960</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.6332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9991</th>\n",
       "      <td>Standard Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Costa Mesa</td>\n",
       "      <td>California</td>\n",
       "      <td>92627</td>\n",
       "      <td>West</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>258.576</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.3932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9992</th>\n",
       "      <td>Standard Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Costa Mesa</td>\n",
       "      <td>California</td>\n",
       "      <td>92627</td>\n",
       "      <td>West</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>29.600</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.3200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9993</th>\n",
       "      <td>Second Class</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Westminster</td>\n",
       "      <td>California</td>\n",
       "      <td>92683</td>\n",
       "      <td>West</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Appliances</td>\n",
       "      <td>243.160</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.9480</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Ship Mode   Segment        Country         City       State  \\\n",
       "9989    Second Class  Consumer  United States        Miami     Florida   \n",
       "9990  Standard Class  Consumer  United States   Costa Mesa  California   \n",
       "9991  Standard Class  Consumer  United States   Costa Mesa  California   \n",
       "9992  Standard Class  Consumer  United States   Costa Mesa  California   \n",
       "9993    Second Class  Consumer  United States  Westminster  California   \n",
       "\n",
       "      Postal Code Region         Category Sub-Category    Sales  Quantity  \\\n",
       "9989        33180  South        Furniture  Furnishings   25.248         3   \n",
       "9990        92627   West        Furniture  Furnishings   91.960         2   \n",
       "9991        92627   West       Technology       Phones  258.576         2   \n",
       "9992        92627   West  Office Supplies        Paper   29.600         4   \n",
       "9993        92683   West  Office Supplies   Appliances  243.160         2   \n",
       "\n",
       "      Discount   Profit  \n",
       "9989       0.2   4.1028  \n",
       "9990       0.0  15.6332  \n",
       "9991       0.2  19.3932  \n",
       "9992       0.0  13.3200  \n",
       "9993       0.0  72.9480  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "65f1eef5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9994, 13)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c328d9ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9994 entries, 0 to 9993\n",
      "Data columns (total 13 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Ship Mode     9994 non-null   object \n",
      " 1   Segment       9994 non-null   object \n",
      " 2   Country       9994 non-null   object \n",
      " 3   City          9994 non-null   object \n",
      " 4   State         9994 non-null   object \n",
      " 5   Postal Code   9994 non-null   int64  \n",
      " 6   Region        9994 non-null   object \n",
      " 7   Category      9994 non-null   object \n",
      " 8   Sub-Category  9994 non-null   object \n",
      " 9   Sales         9994 non-null   float64\n",
      " 10  Quantity      9994 non-null   int64  \n",
      " 11  Discount      9994 non-null   float64\n",
      " 12  Profit        9994 non-null   float64\n",
      "dtypes: float64(3), int64(2), object(8)\n",
      "memory usage: 1015.1+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "201c8fa2",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9994.000000</td>\n",
       "      <td>9994.000000</td>\n",
       "      <td>9994.000000</td>\n",
       "      <td>9994.000000</td>\n",
       "      <td>9994.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>55190.379428</td>\n",
       "      <td>229.858001</td>\n",
       "      <td>3.789574</td>\n",
       "      <td>0.156203</td>\n",
       "      <td>28.656896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>32063.693350</td>\n",
       "      <td>623.245101</td>\n",
       "      <td>2.225110</td>\n",
       "      <td>0.206452</td>\n",
       "      <td>234.260108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1040.000000</td>\n",
       "      <td>0.444000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-6599.978000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>23223.000000</td>\n",
       "      <td>17.280000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.728750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>56430.500000</td>\n",
       "      <td>54.490000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>8.666500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>90008.000000</td>\n",
       "      <td>209.940000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>29.364000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>99301.000000</td>\n",
       "      <td>22638.480000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>8399.976000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Postal Code         Sales     Quantity     Discount       Profit\n",
       "count   9994.000000   9994.000000  9994.000000  9994.000000  9994.000000\n",
       "mean   55190.379428    229.858001     3.789574     0.156203    28.656896\n",
       "std    32063.693350    623.245101     2.225110     0.206452   234.260108\n",
       "min     1040.000000      0.444000     1.000000     0.000000 -6599.978000\n",
       "25%    23223.000000     17.280000     2.000000     0.000000     1.728750\n",
       "50%    56430.500000     54.490000     3.000000     0.200000     8.666500\n",
       "75%    90008.000000    209.940000     5.000000     0.200000    29.364000\n",
       "max    99301.000000  22638.480000    14.000000     0.800000  8399.976000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c7132804",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ship Mode       0\n",
       "Segment         0\n",
       "Country         0\n",
       "City            0\n",
       "State           0\n",
       "Postal Code     0\n",
       "Region          0\n",
       "Category        0\n",
       "Sub-Category    0\n",
       "Sales           0\n",
       "Quantity        0\n",
       "Discount        0\n",
       "Profit          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "414ab208",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Postal Code</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.023854</td>\n",
       "      <td>0.012761</td>\n",
       "      <td>0.058443</td>\n",
       "      <td>-0.029961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sales</th>\n",
       "      <td>-0.023854</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.200795</td>\n",
       "      <td>-0.028190</td>\n",
       "      <td>0.479064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quantity</th>\n",
       "      <td>0.012761</td>\n",
       "      <td>0.200795</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.008623</td>\n",
       "      <td>0.066253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Discount</th>\n",
       "      <td>0.058443</td>\n",
       "      <td>-0.028190</td>\n",
       "      <td>0.008623</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.219487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Profit</th>\n",
       "      <td>-0.029961</td>\n",
       "      <td>0.479064</td>\n",
       "      <td>0.066253</td>\n",
       "      <td>-0.219487</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Postal Code     Sales  Quantity  Discount    Profit\n",
       "Postal Code     1.000000 -0.023854  0.012761  0.058443 -0.029961\n",
       "Sales          -0.023854  1.000000  0.200795 -0.028190  0.479064\n",
       "Quantity        0.012761  0.200795  1.000000  0.008623  0.066253\n",
       "Discount        0.058443 -0.028190  0.008623  1.000000 -0.219487\n",
       "Profit         -0.029961  0.479064  0.066253 -0.219487  1.000000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c113081",
   "metadata": {},
   "source": [
    " <b>Data Visualization</b>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cba46cb",
   "metadata": {},
   "source": [
    "1) Category versus Sub-Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f006d859",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "plt.bar('Sub-Category','Category', data=data)\n",
    "plt.xlabel('Sub-Category')\n",
    "plt.ylabel('Category')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89c8569c",
   "metadata": {},
   "source": [
    "2) Segment visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e1227bf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 22,
     "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": [
    "(data['Segment'].value_counts() / len(data['Segment']*100)).plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f0eef2f",
   "metadata": {},
   "source": [
    "Visualization results:-<br>\n",
    "50% Consumers (approx)<br>\n",
    "30% Corporates (approx)<br>\n",
    "20% Home Office (approx)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1474cd83",
   "metadata": {},
   "source": [
    "3) Region Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "86b4c96d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Region'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(data['Region'].value_counts() / len(data['Region']*100)).plot(kind='pie')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68997a91",
   "metadata": {},
   "source": [
    "Visualization results:-<br>\n",
    "The order of most reached regions of the sales was:-<br>\n",
    "<b>West > East > Central > South </b>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a935999",
   "metadata": {},
   "source": [
    "4) Region-wise Profit and Sales relation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7db9e122",
   "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": [
    "fig, rw = plt.subplots()\n",
    "colors = {'West':'blue', 'East':'yellow', 'Central':'green', 'South':'red'}\n",
    "rw.scatter(data['Sales'], data['Profit'], c=data['Region'].apply(lambda x:colors[x]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "913bd83d",
   "metadata": {},
   "source": [
    "Visualization results:-<br>\n",
    "The super store has faced loss mostly in Central Region.<br>\n",
    "And the most profit was made from East and West region of the country."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c3464b9",
   "metadata": {},
   "source": [
    "5) Segment wise Discount and Profit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "98464e3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAD4CAYAAAD7CAEUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAATrElEQVR4nO3de7Bd5X3e8e9jEbBxU3NTKZFoJBKNU+q4rXqCmXHjuibhmlikxS6eJJYxjZoUp0lpJxZ2pjDteAanTRzcSdwoQAKOa8DOBTXGJQKbeDpTLgI7GHAIJ1yMZC4nBkMaHAj2r3/sV3gj67JfnbP3Pkfn+5nZs9f6rbXXet+js8+jdU9VIUnSqF4x7QZIkpYWg0OS1MXgkCR1MTgkSV0MDklSl0Om3YBxOOaYY2rNmjXTboYkLSl33nnnX1TVyv3Nd1AGx5o1a9i+ffu0myFJS0qSR0aZz11VkqQuBockqYvBIUnqYnBIkroYHJKkLgaHJKmLwSFJ6mJwSJK6GBySpC4H5ZXj0v6s2fypfU5/+NKzJtQSaelxi0OS1MXgkCR1MTgkSV0MDklSl7EFR5IrkzyZ5J6h2n9N8qdJ7k7y+0mOGJp2UZLZJPcnOW2ofnqrzSbZPK72SpJGM84tjt8GTt+ttg14XVW9Hvgz4CKAJCcC5wL/oH3m15OsSLIC+DXgDOBE4B1tXknSlIwtOKrqc8BTu9X+qKpebKO3Aqvb8Abgmqp6vqoeAmaBk9prtqoerKoXgGvavJKkKZnmMY53A59uw6uAR4em7Wi1vdW/TZJNSbYn2T43NzeG5kqSYErBkeT9wIvAxxZqmVW1papmqmpm5cr9PjJXknSAJn7leJJ3AT8CnFJV1co7geOHZlvdauyjLkmagolucSQ5HfgF4K1V9dzQpK3AuUkOS7IWWAfcDtwBrEuyNsmhDA6gb51kmyVJLze2LY4kHwfeDByTZAdwMYOzqA4DtiUBuLWqfrqq7k1yHXAfg11YF1TVN9py3gPcCKwArqyqe8fVZknS/o0tOKrqHXsoX7GP+T8AfGAP9RuAGxawaZKkefDKcUlSF4NDktTF4JAkdTE4JEldDA5JUheDQ5LUxeCQJHUxOCRJXQwOSVIXg0OS1MXgkCR1MTgkSV0MDklSF4NDktTF4JAkdTE4JEldDA5JUheDQ5LUxeCQJHUxOCRJXQwOSVIXg0OS1MXgkCR1MTgkSV3GFhxJrkzyZJJ7hmpHJdmW5IH2fmSrJ8mHk8wmuTvJ+qHPbGzzP5Bk47jaK0kazTi3OH4bOH232mbg5qpaB9zcxgHOANa11ybgIzAIGuBi4A3AScDFu8JGkjQdYwuOqvoc8NRu5Q3AVW34KuDsofrVNXArcESS44DTgG1V9VRVPQ1s49vDSJI0QZM+xnFsVT3Whh8Hjm3Dq4BHh+bb0Wp7q3+bJJuSbE+yfW5ubmFbLUl6ydQOjldVAbWAy9tSVTNVNbNy5cqFWqwkaTeTDo4n2i4o2vuTrb4TOH5ovtWttre6JGlKJh0cW4FdZ0ZtBK4fqr+znV11MvBM26V1I3BqkiPbQfFTW02SNCWHjGvBST4OvBk4JskOBmdHXQpcl+R84BHg7W32G4AzgVngOeA8gKp6Ksl/Ae5o8/3nqtr9gLskaYLGFhxV9Y69TDplD/MWcMFelnMlcOUCNk2SNA9eOS5J6mJwSJK6GBySpC4GhySpi8EhSepicEiSuhgckqQuBockqYvBIUnqYnBIkroYHJKkLgaHJKmLwSFJ6mJwSJK6GBySpC4GhySpi8EhSepicEiSuhgckqQuBockqYvBIUnqYnBIkroYHJKkLgaHJKnLVIIjyb9Pcm+Se5J8PMkrk6xNcluS2STXJjm0zXtYG59t09dMo82SpIGJB0eSVcC/A2aq6nXACuBc4IPAh6rqe4GngfPbR84Hnm71D7X5JElTMq1dVYcAr0pyCHA48BjwFuCTbfpVwNlteEMbp00/JUkm11RJ0rCJB0dV7QT+G/BlBoHxDHAn8LWqerHNtgNY1YZXAY+2z77Y5j969+Um2ZRke5Ltc3Nz4+2EJC1jIwVHku9fqBUmOZLBVsRa4LuAVwOnz3e5VbWlqmaqamblypXzXZwkaS9G3eL49SS3J/m3SV4zz3X+EPBQVc1V1d8Avwe8ETii7boCWA3sbMM7geMB2vTXAF+dZxskSQdopOCoqh8EfpzBH/A7k/zPJD98gOv8MnByksPbsYpTgPuAzwLntHk2Ate34a1tnDb9M1VVB7huSdI8jXyMo6oeAH4ReC/wz4APJ/nTJP+iZ4VVdRuDg9x3AV9sbdjSlnthklkGxzCuaB+5Aji61S8ENvesT5K0sA7Z/yyQ5PXAecBZwDbgR6vqriTfBfxfBrubRlZVFwMX71Z+EDhpD/P+NfC2nuVLksZnpOAA/jtwOfC+qvr6rmJVfSXJL46lZZKkRWnU4DgL+HpVfQMgySuAV1bVc1X10bG1TpK06Ix6jOMm4FVD44e3miRpmRk1OF5ZVf9v10gbPnw8TZIkLWajBsdfJVm/ayTJPwG+vo/5JUkHqVGPcfw88IkkXwEC/F3gX42rUZKkxWuk4KiqO5J8H/DaVrq/XfUtSVpmRt3iAPgBYE37zPokVNXVY2mVJGnRGvUCwI8C3wN8AfhGKxdgcEjSMjPqFscMcKL3iJIkjXpW1T0MDohLkpa5Ubc4jgHuS3I78PyuYlW9dSytkiQtWqMGxyXjbIQkaekY9XTcP07y3cC6qropyeHAivE2TZK0GI366NifYvAMjd9opVXAH4ypTZKkRWzUg+MXMHi867Pw0kOd/s64GiVJWrxGDY7nq+qFXSPt2d+emitJy9CowfHHSd4HvKo9a/wTwP8aX7MkSYvVqMGxGZhj8IzwfwPcwOD545KkZWbUs6q+Cfxme0mSlrFR71X1EHs4plFVJyx4iyRJi1rPvap2eSXwNuCohW+OJGmxG+kYR1V9dei1s6p+FThrvE2TJC1Go+6qWj80+goGWyA9z/KQJB0kRv3j/8tDwy8CDwNvP9CVJjkCuBx4HYNjJ+8G7geuZfCwqIeBt1fV00kCXAacCTwHvKuq7jrQdUuS5mfUs6r++QKv9zLgf1fVOUkOBQ4H3gfcXFWXJtnM4BTg9wJnAOva6w3AR9q7JGkKRt1VdeG+plfVr4y6wiSvAd4EvKt99gXghSQbgDe32a4CbmEQHBuAq9tDpG5NckSS46rqsVHXKUlaOKNeADgD/AyDmxuuAn4aWA98Z3v1WMvgYsLfSvL5JJcneTVw7FAYPA4c24ZXAY8OfX5Hq71Mkk1JtifZPjc319kkSdKoRj3GsRpYX1V/CZDkEuBTVfUTB7jO9cDPVtVtSS5jsFvqJVVVSbruhVVVW4AtADMzM95HS5LGZNQtjmOBF4bGX+BbWwS9dgA7quq2Nv5JBkHyRJLjANr7k236TuD4oc+vbjVJ0hSMGhxXA7cnuaRtbdzG4DhEt6p6HHg0yWtb6RTgPmArsLHVNgLXt+GtwDszcDLwjMc3JGl6Rj2r6gNJPg38YCudV1Wfn8d6fxb4WDuj6kHgPAYhdl2S84FH+NbpvjcwOBV3lsHpuOfNY72SpHnquYjvcODZqvqtJCuTrK2qhw5kpVX1BV5+G5NdTtnDvMXgQVKSpEVg1EfHXszg1NiLWuk7gN8ZV6MkSYvXqMc4fgx4K/BXAFX1FfpPw5UkHQRGDY4X2i6jAmjXXUiSlqFRg+O6JL8BHJHkp4Cb8KFOkrQs7ffgeLvJ4LXA9wHPAq8F/lNVbRtz2yRJi9B+g6NdxX1DVX0/YFhI0jI36q6qu5L8wFhbIklaEka9juMNwE8keZjBmVVhsDHy+nE1TJK0OO0zOJL8var6MnDahNojSVrk9rfF8QcM7or7SJLfrap/OYE2SZIWsf0d48jQ8AnjbIgkaWnYX3DUXoYlScvU/nZV/cMkzzLY8nhVG4ZvHRz/22NtnSRp0dlncFTVikk1RJK0NIx6HYckSYDBIUnqZHBIkrr0PAFQWjbWbP7UPqc/fOlZE2qJtPi4xSFJ6mJwSJK6GBySpC4GhySpi8EhSepicEiSukwtOJKsSPL5JH/YxtcmuS3JbJJrkxza6oe18dk2fc202ixJmu4Wx88BXxoa/yDwoar6XuBp4PxWPx94utU/1OaTJE3JVIIjyWrgLODyNh7gLcAn2yxXAWe34Q1tnDb9lDa/JGkKprXF8avALwDfbONHA1+rqhfb+A5gVRteBTwK0KY/0+aXJE3BxIMjyY8AT1bVnQu83E1JtifZPjc3t5CLliQNmcYWxxuBtyZ5GLiGwS6qy4Ajkuy6d9ZqYGcb3gkcD9Cmvwb46u4LraotVTVTVTMrV64cbw8kaRmbeHBU1UVVtbqq1gDnAp+pqh8HPguc02bbCFzfhre2cdr0z1SVj7GVpClZTNdxvBe4MMksg2MYV7T6FcDRrX4hsHlK7ZMkMeXbqlfVLcAtbfhB4KQ9zPPXwNsm2jBJ0l4tpi0OSdISYHBIkroYHJKkLgaHJKmLwSFJ6mJwSJK6GBySpC4GhySpi8EhSepicEiSuhgckqQuBockqYvBIUnqYnBIkroYHJKkLgaHJKmLwSFJ6mJwSJK6GBySpC4GhySpi8EhSepicEiSuhgckqQuBockqYvBIUnqMvHgSHJ8ks8muS/JvUl+rtWPSrItyQPt/chWT5IPJ5lNcneS9ZNusyTpW6axxfEi8B+q6kTgZOCCJCcCm4Gbq2odcHMbBzgDWNdem4CPTL7JkqRdJh4cVfVYVd3Vhv8S+BKwCtgAXNVmuwo4uw1vAK6ugVuBI5IcN9lWS5J2meoxjiRrgH8M3AYcW1WPtUmPA8e24VXAo0Mf29Fquy9rU5LtSbbPzc2Nr9GStMxNLTiS/C3gd4Gfr6pnh6dVVQHVs7yq2lJVM1U1s3LlygVsqSRp2FSCI8l3MAiNj1XV77XyE7t2QbX3J1t9J3D80MdXt5okaQqmcVZVgCuAL1XVrwxN2gpsbMMbgeuH6u9sZ1edDDwztEtLkjRhh0xhnW8EfhL4YpIvtNr7gEuB65KcDzwCvL1NuwE4E5gFngPOm2hrJUkvM/HgqKr/A2Qvk0/Zw/wFXDDWRkmSRuaV45KkLgaHJKmLwSFJ6mJwSJK6GBySpC4GhySpi8EhSepicEiSuhgckqQuBockqYvBIUnqYnBIkroYHJKkLtO4rbq05K3Z/Km9Tnv40rMm2BJp8tzikCR1MTgkSV0MDklSF4NDktTF4JAkdTE4JEldDA5JUhev49BBa1/XWkg6cG5xSJK6GBySpC5LZldVktOBy4AVwOVVdemUmyTt0f52kXlLEi11SyI4kqwAfg34YWAHcEeSrVV133Rbpmlaqscw5nOfK0NJi8GSCA7gJGC2qh4ESHINsAEwOBY5/9D1mW8Yzufz8w2t+Sx7Przh5OSlqqbdhv1Kcg5welX96zb+k8Abquo9Q/NsAja10dcC94+hKccAfzGG5S5Wy62/YJ+XC/u8Z99dVSv3t6ClssWxX1W1BdgyznUk2V5VM+Ncx2Ky3PoL9nm5sM/zs1TOqtoJHD80vrrVJEkTtlSC4w5gXZK1SQ4FzgW2TrlNkrQsLYldVVX1YpL3ADcyOB33yqq6dwpNGeuusEVoufUX7PNyYZ/nYUkcHJckLR5LZVeVJGmRMDgkSV0MjibJ25Lcm+SbSWZ2m3ZRktkk9yc5bah+eqvNJtk8VF+b5LZWv7Yd0F/UklySZGeSL7TXmUPTuvq/VB1s/dklycNJvtj+Xbe32lFJtiV5oL0f2epJ8uH2M7g7yfrptn40Sa5M8mSSe4Zq3X1MsrHN/0CSjdPoy6j20ufJfI+rytfgOM/fZ3Dh4C3AzFD9ROBPgMOAtcCfMzhAv6INnwAc2uY5sX3mOuDcNvw/gJ+Zdv9G6P8lwH/cQ727/0vxdbD1Z7e+PQwcs1vtl4DNbXgz8ME2fCbwaSDAycBt027/iH18E7AeuOdA+wgcBTzY3o9sw0dOu2+dfZ7I99gtjqaqvlRVe7rafANwTVU9X1UPAbMMboHy0m1QquoF4BpgQ5IAbwE+2T5/FXD22DswPl39n2I75+tg68/+bGDwuwkv/x3dAFxdA7cCRyQ5bgrt61JVnwOe2q3c28fTgG1V9VRVPQ1sA04fe+MP0F76vDcL+j02OPZvFfDo0PiOVttb/Wjga1X14m71peA9bdP9yl2b9fT3f6k62PozrIA/SnJnuzUPwLFV9Vgbfhw4tg0fTD+H3j4eLH0f+/d4WQVHkpuS3LOH18H8P8uX7Kf/HwG+B/hHwGPAL0+zrVpQ/7Sq1gNnABckedPwxBrsyzioz8tfDn1sJvI9XhIXAC6UqvqhA/jYvm53sqf6Vxls+h7StjoWze1RRu1/kt8E/rCN9vZ/qTpob2tTVTvb+5NJfp/B7oknkhxXVY+13TRPttkPpp9Dbx93Am/erX7LBNq5YKrqiV3D4/weL6stjgO0FTg3yWFJ1gLrgNvZy21Q2v9sPguc0z6/Ebh+Cu3ustt+7B8Ddp2p0dX/SbZ5gR1s/QEgyauTfOeuYeBUBv+2Wxn8bsLLf0e3Au9sZx6dDDwztLtnqent443AqUmObLt4Tm21JWNi3+NpnxmwWF7th7wDeB54ArhxaNr7GZx5cD9wxlD9TODP2rT3D9VPaP8os8AngMOm3b8R+v9R4IvA3e0X57gD7f9SfR1s/Wl9OoHBmTJ/Aty7q18MjsXdDDwA3AQc1eph8NC0P2+/DzPTantnPz/OYNfM37Tv8fkH0kfg3e17OwucN+1+HUCfJ/I99pYjkqQu7qqSJHUxOCRJXQwOSVIXg0OS1MXgkCR1MTgkSV0MDklSl/8P46Q3R0+qd8cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp_data = data.loc[(data['Segment']=='Consumer') & (data['Discount']==0.2)]\n",
    "temp_data['Profit'].plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d64f5906",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 43,
     "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": [
    "temp_data = data.loc[(data['Segment']=='Consumer') & (data['Discount']==0.8)]\n",
    "temp_data['Profit'].plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "778a3eb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 44,
     "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": [
    "temp_data = data.loc[(data['Segment']=='Corporate') & (data['Discount']==0.2)]\n",
    "temp_data['Profit'].plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "21b6dac7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 45,
     "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": [
    "temp_data = data.loc[(data['Segment']=='Corporate') & (data['Discount']==0.8)]\n",
    "temp_data['Profit'].plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "de6251c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 46,
     "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": [
    "temp_data = data.loc[(data['Segment']=='Home Office') & (data['Discount']==0.2)]\n",
    "temp_data['Profit'].plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "26ac74e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 47,
     "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": [
    "temp_data = data.loc[(data['Segment']=='Home Office') & (data['Discount']==0.8)]\n",
    "temp_data['Profit'].plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4762b673",
   "metadata": {},
   "source": [
    "Visualization results:-<br>\n",
    "Whenever the discounts are more than 20% the Superstore faces a loss."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f2d9e30",
   "metadata": {},
   "source": [
    "6) State wise Profit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "fb822bbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "pro=data.groupby(['State'])['Profit'].sum()\n",
    "s=pro[pro>3000]\n",
    "s.sort_values(ascending=False)\n",
    "s.plot.bar()\n",
    "plt.ylabel('Profit')\n",
    "plt.xticks(rotation=70)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4dce4e1",
   "metadata": {},
   "source": [
    "Visualization results:-<br>\n",
    "The states of Califoria and New York have greater profits.<br>\n",
    "The states of Mississippi, Nevada and Connecticut have lesser profits."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}