Customer_Segmentation.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CUSTOMER SEGMENTATION"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing Required Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('Mall_Customers.csv')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Viewing the first 5 values of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>CustomerID</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Male</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Female</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Female</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CustomerID   Genre  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0           1    Male   19                  15                      39\n",
       "1           2    Male   21                  15                      81\n",
       "2           3  Female   20                  16                       6\n",
       "3           4  Female   23                  16                      77\n",
       "4           5  Female   31                  17                      40"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Viewing the last 5 values of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>Female</td>\n",
       "      <td>35</td>\n",
       "      <td>120</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>Female</td>\n",
       "      <td>45</td>\n",
       "      <td>126</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>Male</td>\n",
       "      <td>32</td>\n",
       "      <td>126</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>Male</td>\n",
       "      <td>32</td>\n",
       "      <td>137</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>Male</td>\n",
       "      <td>30</td>\n",
       "      <td>137</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "     CustomerID   Genre  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "195         196  Female   35                 120                      79\n",
       "196         197  Female   45                 126                      28\n",
       "197         198    Male   32                 126                      74\n",
       "198         199    Male   32                 137                      18\n",
       "199         200    Male   30                 137                      83"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Male</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Female</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Female</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "   CustomerID  Gender  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0           1    Male   19                  15                      39\n",
       "1           2    Male   21                  15                      81\n",
       "2           3  Female   20                  16                       6\n",
       "3           4  Female   23                  16                      77\n",
       "4           5  Female   31                  17                      40"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(columns={'Genre': 'Gender'}, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking the shape of our dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 5)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Getting to know our dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>CustomerID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>200.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>100.500000</td>\n",
       "      <td>38.850000</td>\n",
       "      <td>60.560000</td>\n",
       "      <td>50.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>57.879185</td>\n",
       "      <td>13.969007</td>\n",
       "      <td>26.264721</td>\n",
       "      <td>25.823522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>50.750000</td>\n",
       "      <td>28.750000</td>\n",
       "      <td>41.500000</td>\n",
       "      <td>34.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>100.500000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>61.500000</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>150.250000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>78.000000</td>\n",
       "      <td>73.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>137.000000</td>\n",
       "      <td>99.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       CustomerID         Age  Annual Income (k$)  Spending Score (1-100)\n",
       "count  200.000000  200.000000          200.000000              200.000000\n",
       "mean   100.500000   38.850000           60.560000               50.200000\n",
       "std     57.879185   13.969007           26.264721               25.823522\n",
       "min      1.000000   18.000000           15.000000                1.000000\n",
       "25%     50.750000   28.750000           41.500000               34.750000\n",
       "50%    100.500000   36.000000           61.500000               50.000000\n",
       "75%    150.250000   49.000000           78.000000               73.000000\n",
       "max    200.000000   70.000000          137.000000               99.000000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 200 entries, 0 to 199\n",
      "Data columns (total 5 columns):\n",
      " #   Column                  Non-Null Count  Dtype \n",
      "---  ------                  --------------  ----- \n",
      " 0   CustomerID              200 non-null    int64 \n",
      " 1   Gender                  200 non-null    object\n",
      " 2   Age                     200 non-null    int64 \n",
      " 3   Annual Income (k$)      200 non-null    int64 \n",
      " 4   Spending Score (1-100)  200 non-null    int64 \n",
      "dtypes: int64(4), object(1)\n",
      "memory usage: 7.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking if the dataset has any null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
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       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     CustomerID  Gender    Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0         False   False  False               False                   False\n",
       "1         False   False  False               False                   False\n",
       "2         False   False  False               False                   False\n",
       "3         False   False  False               False                   False\n",
       "4         False   False  False               False                   False\n",
       "..          ...     ...    ...                 ...                     ...\n",
       "195       False   False  False               False                   False\n",
       "196       False   False  False               False                   False\n",
       "197       False   False  False               False                   False\n",
       "198       False   False  False               False                   False\n",
       "199       False   False  False               False                   False\n",
       "\n",
       "[200 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CustomerID                0\n",
       "Gender                    0\n",
       "Age                       0\n",
       "Annual Income (k$)        0\n",
       "Spending Score (1-100)    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We don't need customer ID for analysing and understanding our data, so we can drop the column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0    Male   19                  15                      39\n",
       "1    Male   21                  15                      81\n",
       "2  Female   20                  16                       6\n",
       "3  Female   23                  16                      77\n",
       "4  Female   31                  17                      40"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop([\"CustomerID\"], axis = 1, inplace = True)\n",
    "df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysis and Visualization of data\n",
    "\n",
    "Creating a distribution plot for age, annual income and spending score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\swapn\\AppData\\Local\\Temp\\ipykernel_15816\\3252386055.py:7: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(df[x], bins = 20)\n",
      "C:\\Users\\swapn\\AppData\\Local\\Temp\\ipykernel_15816\\3252386055.py:7: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(df[x], bins = 20)\n",
      "C:\\Users\\swapn\\AppData\\Local\\Temp\\ipykernel_15816\\3252386055.py:7: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(df[x], bins = 20)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1, figsize = (15,6))\n",
    "n = 0\n",
    "for x in ['Age', 'Annual Income (k$)', 'Spending Score (1-100)']:\n",
    "    n+=1\n",
    "    plt.subplot(1, 3, n)\n",
    "    plt.subplots_adjust(hspace=0.5, wspace= 0.5)\n",
    "    sns.distplot(df[x], bins = 20)\n",
    "    plt.title('Distplot of {}'. format(x))\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking the count of males and females in our dataset using countplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uXFiz36RJk7Lrrrumbdu26dChQ/bdd9/MnDnzK+ebPn169tprr7Ru3TqVlZU59NBD88EHH6y29wMAAAAA6i3W/fznP8/555+fLl265N133820adMyduzY3Hzzzbn22mvz/PPPZ8SIEfnRj36UKVOm1Nr33HPPzZVXXpm//OUvefPNN3PwwQdn/PjxufXWW3PPPffk3nvvzRVXXFGz/YIFCzJy5Mg8/vjjuf/++9OoUaMccMABqa6u/tLZ5s6dm29/+9vp169fHn/88UyaNCnvvfdeDj744OW+nkWLFqWqqqrWDwAAAACsjHr7GGxFRUXatGmTxo0bZ4MNNsiiRYsyZsyY/PnPf87OO++cJNl4443z8MMP57rrrsvAgQNr9h09enQGDBiQJDnyyCNz5plnZubMmdl4442TJN///vczefLknH766UmSgw46qNZz/+IXv0jHjh3zwgsvZOutt15mtiuvvDL9+vXLmDFjau3TtWvXvPLKK9lss82W2Wfs2LE577zzvua7AgAAAEBDVq93g/1HM2bMyMKFC7P77rundevWNT8333zzMh9Z3WabbWp+r6ysTMuWLWtC3dJlc+bMqXn86quv5pBDDsnGG2+c8vLy9OjRI0kya9asL53lmWeeyeTJk2vNscUWWyTJcj8+e+aZZ2bevHk1P2+++Wad3gcAAAAAGq56vcHEP5o/f36S5J577slGG21Ua12zZs1qPV5vvfVqfi8rK6v1eOmyf/yI63777Zfu3bvnhhtuSOfOnVNdXZ2tt946n3322XJn2W+//TJu3Lhl1m244YZfuk+zZs2WmRMAAAAAVkZhYt2WW26ZZs2aZdasWbU+8vp1ffjhh3n55Zdzww03ZLfddkuSPPzww1+5z3bbbZff/va36dGjR5o0KcxbBAAAAMA6rjAfg23Tpk1OOeWUjBgxIhMmTMjMmTPz5JNP5oorrsiECRPqfNx27dqlQ4cOuf766zNjxow88MADGTly5FfuM2zYsHz00Uc55JBDMm3atMycOTN/+tOfcvjhh2fJkiV1ngUAAAAAvkqhLhu74IIL0rFjx4wdOzavvfZa2rZtm+222y5nnXVWnY/ZqFGj3HbbbTnxxBOz9dZbZ/PNN8/ll1+eQYMGLXefzp07Z+rUqTn99NOzxx57ZNGiRenevXu++93vplGjwvRNAAAAANYxZaVSqVTfQ6yLqqqqUlFRkXk3JOUt63saAAAAgLXAD9fdTFXTiubNS3l5+XK3c5kYAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABdFkZXcolUp5880306lTpzRv3nx1zLRuOXheUl5e31MAAAAAsBZY6SvrSqVSNt1007z55purYx4AAAAAaLBWOtY1atQovXr1yocffrg65gEAAACABqtO31l30UUX5dRTT8306dNX9TwAAAAA0GCVlUql0sru1K5duyxcuDCLFy9O06ZN06JFi1rrP/roo1U24NqqqqoqFRUVmTdvXsp9Zx0AAABAg7airWilbzCRJOPHj6/rXAAAAADActQp1h122GGreg4AAAAAaPDq9J11STJz5sz89Kc/zSGHHJI5c+YkSSZOnJjnn39+lQ0HAAAAAA1JnWLdlClT0qdPnzz66KO58847M3/+/CTJM888k1GjRq3SAQEAAACgoahTrDvjjDMyevTo3HfffWnatGnN8m9/+9v561//usqGAwAAAICGpE6x7rnnnssBBxywzPJOnTrlgw8++NpDAQAAAEBDVKdY17Zt27z77rvLLH/qqaey0UYbfe2hAAAAAKAhqlOs+8EPfpDTTz89s2fPTllZWaqrqzN16tSccsop+c///M9VPSMAAAAANAh1inVjxozJFltska5du2b+/PnZcsst881vfjO77LJLfvrTn67qGQEAAACgQSgrlUqluu48a9asTJ8+PfPnz0+/fv3Sq1evVTnbWq2qqioVFRWZN29eysvL63scAAAAAOrRiraiJl/nSbp165Zu3bp9nUMAAAAAAP/PCse6kSNHrvBBL7vssjoNAwAAAAAN2QrHuqeeeqrW4yeffDKLFy/O5ptvniR55ZVX0rhx42y//fardkIAAAAAaCBWONZNnjy55vfLLrssbdq0yYQJE9KuXbskyccff5zDDz88u+2226qfEgAAAAAagDrdYGKjjTbKvffem6222qrW8unTp2ePPfbIO++8s8oGXFu5wQQAAAAAS61oK2pU14O///77yyx///3388knn9TlkAAAAADQ4NUp1h1wwAE5/PDDc+edd+att97KW2+9ld/+9rc58sgjc+CBB67qGQEAAACgQVjh76z7R9dee21OOeWU/PCHP8znn3/+xYGaNMmRRx6ZSy65ZJUOCAAAAAANRZ2+s26pBQsWZObMmUmSTTbZJK1atVplg63tfGcdAAAAAEutaCuq05V1S7Vq1SrbbLPN1zkEAAAAAPD/1CnWLViwIBdddFHuv//+zJkzJ9XV1bXWv/baa6tkOAAAAABoSOoU63784x9nypQpOfTQQ7PhhhumrKxsVc8FAAAAAA1OnWLdxIkTc88992TAgAGreh4AAAAAaLAa1WWndu3apX379qt6FgAAAABo0OoU6y644IKcc845Wbhw4aqeBwAAAAAarDp9DPbSSy/NzJkzU1lZmR49emS99dartf7JJ59cJcMBAAAAQENSp1i3//77r+IxAAAAAICyUqlUqu8h1kVVVVWpqKjIvHnzUl5eXt/jAAAAAFCPVrQV1ek765Jk7ty5ufHGG3PmmWfmo48+SvLFx1/ffvvtuh4SAAAAABq0On0M9tlnn83gwYNTUVGRN954Iz/5yU/Svn373HnnnZk1a1ZuvvnmVT0nAAAAAKzz6nRl3ciRIzN06NC8+uqrad68ec3yvffeOw899NAqGw4AAAAAGpI6xbpp06bl6KOPXmb5RhttlNmzZ3/toQAAAACgIapTrGvWrFmqqqqWWf7KK6+kY8eOX3soAAAAAGiI6hTr/u3f/i3nn39+Pv/88yRJWVlZZs2aldNPPz0HHXTQKh0QAAAAABqKOsW6Sy+9NPPnz0+nTp3y6aefZuDAgdl0003TunXrXHjhhat6RgAAAABoEOp0N9iKiorcd999mTp1ap555pnMnz8/2223XQYPHryq5wMAAACABmOlrqz79NNPc/fdd9c8vvvuuzNjxozMnj07f/zjH3Paaafl73//+yofEgAAAAAagpW6sm7ChAm55557su+++yZJrrzyymy11VZp0aJFkuSll17KhhtumBEjRqz6SQEAAABgHbdSV9bdcsstOeqoo2otu/XWWzN58uRMnjw5l1xySW6//fZVOiAAAAAANBQrFetmzJiRPn361Dxu3rx5GjX6/w+xww475IUXXlh10wEAAABAA7JSH4OdO3duFi1aVPP4/fffr7W+urq61noAAAAAYMWt1JV1Xbp0yfTp05e7/tlnn02XLl2+9lAAAAAA0BCt1JV1e++9d84555zss88+ad68ea11n376ac4777zss88+q3TAtd3YirFpnub/ekMAAABWuVGlUfU9AsBKWalYd9ZZZ+X222/P5ptvnuOPPz6bbbZZkuTll1/OlVdemcWLF+ess85aLYMCAAAAwLpupWJdZWVl/vKXv+TYY4/NGWeckVKplCQpKyvL7rvvnquvvjqVlZWrZVAAAAAAWNetVKxLkp49e2bSpEn56KOPMmPGjCTJpptumvbt26/y4QAAAACgIVnpWLdU+/bts8MOO6zKWQAAAACgQVupu8ECAAAAAKuPWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwAAAAAFIdYBAAAAQEGIdUmGDh2a/fffv77HAAAAAKCBE+sAAAAAoCDEOgAAAAAoiLUu1g0aNCgnnHBChg8fnnbt2qWysjI33HBDFixYkMMPPzxt2rTJpptumokTJyZJlixZkiOPPDI9e/ZMixYtsvnmm+fnP//5Vz5HdXV1xo4dW7NP375985vf/GZNvDwAAAAAGrC1LtYlyYQJE7L++uvnscceywknnJBjjz02//7v/55ddtklTz75ZPbYY48ceuihWbhwYaqrq9OlS5fccccdeeGFF3LOOefkrLPOyu23377c448dOzY333xzrr322jz//PMZMWJEfvSjH2XKlCnL3WfRokWpqqqq9QMAAAAAK6OsVCqV6nuIlTFo0KAsWbIk//u//5vkiyvnKioqcuCBB+bmm29OksyePTsbbrhhHnnkkey0007LHOP444/P7Nmza66WGzp0aObOnZvf//73WbRoUdq3b58///nP2XnnnWv2+fGPf5yFCxfm1ltv/dK5zj333Jx33nnLLD8jZ6R5mn/t1w0AAMDKG1UaVd8jACRJqqqqUlFRkXnz5qW8vHy52zVZgzOtMttss03N740bN06HDh3Sp0+fmmWVlZVJkjlz5iRJrrrqqvziF7/IrFmz8umnn+azzz7Ltttu+6XHnjFjRhYuXJjdd9+91vLPPvss/fr1W+5MZ555ZkaOHFnzuKqqKl27dl3p1wYAAABAw7VWxrr11luv1uOysrJay8rKypJ88d1zt912W0455ZRceuml2XnnndOmTZtccsklefTRR7/02PPnz0+S3HPPPdloo41qrWvWrNlyZ2rWrNlXrgcAAACAf2WtjHUrY+rUqdlll11y3HHH1SybOXPmcrffcsst06xZs8yaNSsDBw5cEyMCAAAAQJIGEOt69eqVm2++OX/605/Ss2fP/J//838ybdq09OzZ80u3b9OmTU455ZSMGDEi1dXV2XXXXTNv3rxMnTo15eXlOeyww9bwKwAAAACgoVjnY93RRx+dp556Kv/xH/+RsrKyHHLIITnuuOMyceLE5e5zwQUXpGPHjhk7dmxee+21tG3bNtttt13OOuusNTg5AAAAAA3NWnc32LXF0jt8uBssAABA/XE3WKAoVvRusI3W4EwAAAAAwFcQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACiIJvU9wLruzHlnpry8vL7HAAAAAGAt4Mo6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAghDrAAAAAKAgxDoAAAAAKAixDgAAAAAKQqwDAAAAgIIQ6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOsAAAAAoCDEOgAAAAAoCLEOAAAAAApCrAMAAACAgmhS3wOsq0qlUpKkqqqqnicBAAAAoL4tbURLm9HyiHWryYcffpgk6dq1az1PAgAAAEBRfPLJJ6moqFjuerFuNWnfvn2SZNasWV/5BwANSVVVVbp27Zo333wz5eXl9T0OFILzAmpzTsCynBewLOcFa6NSqZRPPvkknTt3/srtxLrVpFGjL74OsKKiwn844J+Ul5c7L+CfOC+gNucELMt5ActyXrC2WZELutxgAgAAAAAKQqwDAAAAgIIQ61aTZs2aZdSoUWnWrFl9jwKF4byAZTkvoDbnBCzLeQHLcl6wLisr/av7xQIAAAAAa4Qr6wAAAACgIMQ6AAAAACgIsQ4AAAAACkKsAwAAAICCEOtWk6uuuio9evRI8+bNs+OOO+axxx6r75FgjRg7dmy+8Y1vpE2bNunUqVP233//vPzyy7W2+fvf/55hw4alQ4cOad26dQ466KC899579TQxrHkXXXRRysrKMnz48Jplzgsaorfffjs/+tGP0qFDh7Ro0SJ9+vTJ448/XrO+VCrlnHPOyYYbbpgWLVpk8ODBefXVV+txYlh9lixZkrPPPjs9e/ZMixYtsskmm+SCCy7IP94P0DnBuu6hhx7Kfvvtl86dO6esrCy///3va61fkXPgo48+ypAhQ1JeXp62bdvmyCOPzPz589fgq4CvT6xbDX79619n5MiRGTVqVJ588sn07ds3e+65Z+bMmVPfo8FqN2XKlAwbNix//etfc9999+Xzzz/PHnvskQULFtRsM2LEiPzhD3/IHXfckSlTpuSdd97JgQceWI9Tw5ozbdq0XHfdddlmm21qLXde0NB8/PHHGTBgQNZbb71MnDgxL7zwQi699NK0a9euZpuLL744l19+ea699to8+uijadWqVfbcc8/8/e9/r8fJYfUYN25crrnmmlx55ZV58cUXM27cuFx88cW54oorarZxTrCuW7BgQfr27ZurrrrqS9evyDkwZMiQPP/887nvvvty991356GHHspRRx21pl4CrBolVrkddtihNGzYsJrHS5YsKXXu3Lk0duzYepwK6secOXNKSUpTpkwplUql0ty5c0vrrbde6Y477qjZ5sUXXywlKT3yyCP1NSasEZ988kmpV69epfvuu680cODA0kknnVQqlZwXNEynn356adddd13u+urq6tIGG2xQuuSSS2qWzZ07t9SsWbPSr371qzUxIqxR++yzT+mII46otezAAw8sDRkypFQqOSdoeJKUfve739U8XpFz4IUXXiglKU2bNq1mm4kTJ5bKyspKb7/99hqbHb4uV9atYp999lmeeOKJDB48uGZZo0aNMnjw4DzyyCP1OBnUj3nz5iVJ2rdvnyR54okn8vnnn9c6R7bYYot069bNOcI6b9iwYdlnn31q/f1PnBc0THfddVf69++ff//3f0+nTp3Sr1+/3HDDDTXrX3/99cyePbvWeVFRUZEdd9zRecE6aZdddsn999+fV155JUnyzDPP5OGHH85ee+2VxDkBK3IOPPLII2nbtm369+9fs83gwYPTqFGjPProo2t8ZqirJvU9wLrmgw8+yJIlS1JZWVlreWVlZV566aV6mgrqR3V1dYYPH54BAwZk6623TpLMnj07TZs2Tdu2bWttW1lZmdmzZ9fDlLBm3HbbbXnyySczbdq0ZdY5L2iIXnvttVxzzTUZOXJkzjrrrEybNi0nnnhimjZtmsMOO6zm7/6X/ZvKecG66IwzzkhVVVW22GKLNG7cOEuWLMmFF16YIUOGJIlzggZvRc6B2bNnp1OnTrXWN2nSJO3bt3eesFYR64DVZtiwYZk+fXoefvjh+h4F6tWbb76Zk046Kffdd1+aN29e3+NAIVRXV6d///4ZM2ZMkqRfv36ZPn16rr322hx22GH1PB2sebfffntuueWW3Hrrrdlqq63y9NNPZ/jw4encubNzAqCB8THYVWz99ddP48aNl7mD33vvvZcNNtignqaCNe/444/P3XffncmTJ6dLly41yzfYYIN89tlnmTt3bq3tnSOsy5544onMmTMn2223XZo0aZImTZpkypQpufzyy9OkSZNUVlY6L2hwNtxww2y55Za1lvXu3TuzZs1Kkpq/+/5NRUNx6qmn5owzzsgPfvCD9OnTJ4ceemhGjBiRsWPHJnFOwIqcAxtssMEyN3ZcvHhxPvroI+cJaxWxbhVr2rRptt9++9x///01y6qrq3P//fdn5513rsfJYM0olUo5/vjj87vf/S4PPPBAevbsWWv99ttvn/XWW6/WOfLyyy9n1qxZzhHWWd/5znfy3HPP5emnn6756d+/f4YMGVLzu/OChmbAgAF5+eWXay175ZVX0r179yRJz549s8EGG9Q6L6qqqvLoo486L1gnLVy4MI0a1f7fs8aNG6e6ujqJcwJW5BzYeeedM3fu3DzxxBM12zzwwAOprq7OjjvuuMZnhrryMdjVYOTIkTnssMPSv3//7LDDDhk/fnwWLFiQww8/vL5Hg9Vu2LBhufXWW/N//+//TZs2bWq+G6KioiItWrRIRUVFjjzyyIwcOTLt27dPeXl5TjjhhOy8887Zaaed6nl6WD3atGlT872NS7Vq1SodOnSoWe68oKEZMWJEdtlll4wZMyYHH3xwHnvssVx//fW5/vrrkyRlZWUZPnx4Ro8enV69eqVnz545++yz07lz5+y///71OzysBvvtt18uvPDCdOvWLVtttVWeeuqpXHbZZTniiCOSOCdoGObPn58ZM2bUPH799dfz9NNPp3379unWrdu/PAd69+6d7373u/nJT36Sa6+9Np9//nmOP/74/OAHP0jnzp3r6VVBHdT37WjXVVdccUWpW7dupaZNm5Z22GGH0l//+tf6HgnWiCRf+nPTTTfVbPPpp5+WjjvuuFK7du1KLVu2LB1wwAGld999t/6GhnowcODA0kknnVTz2HlBQ/SHP/yhtPXWW5eaNWtW2mKLLUrXX399rfXV1dWls88+u1RZWVlq1qxZ6Tvf+U7p5ZdfrqdpYfWqqqoqnXTSSaVu3bqVmjdvXtp4441L//Vf/1VatGhRzTbOCdZ1kydP/tL/lzjssMNKpdKKnQMffvhh6ZBDDim1bt26VF5eXjr88MNLn3zyST28Gqi7slKpVKqnTggAAAAA/APfWQcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQYh0AAAAAFIRYBwCwFnrjjTdSVlaWp59+ur5HqfHSSy9lp512SvPmzbPtttvW9zgAAGslsQ4AoA6GDh2asrKyXHTRRbWW//73v09ZWVk9TVW/Ro0alVatWuXll1/O/fffv9ztZs+enRNOOCEbb7xxmjVrlq5du2a//fb7yn1WRhFDJgDAihLrAADqqHnz5hk3blw+/vjj+h5llfnss8/qvO/MmTOz6667pnv37unQocOXbvPGG29k++23zwMPPJBLLrkkzz33XCZNmpRvfetbGTZsWJ2fe23z+eef1/cIAEBBiXUAAHU0ePDgbLDBBhk7duxytzn33HOX+Ujo+PHj06NHj5rHQ4cOzf77758xY8aksrIybdu2zfnnn5/Fixfn1FNPTfv27dOlS5fcdNNNyxz/pZdeyi677JLmzZtn6623zpQpU2qtnz59evbaa6+0bt06lZWVOfTQQ/PBBx/UrB80aFCOP/74DB8+POuvv3723HPPL30d1dXVOf/889OlS5c0a9Ys2267bSZNmlSzvqysLE888UTOP//8lJWV5dxzz/3S4xx33HEpKyvLY489loMOOiibbbZZttpqq4wcOTJ//etfk3z5lXFz585NWVlZHnzwwSTJxx9/nCFDhqRjx45p0aJFevXqVfP+9OzZM0nSr1+/lJWVZdCgQSv0GpY+7+23357ddtstLVq0yDe+8Y288sormTZtWvr375/WrVtnr732yvvvv1/rdd14443p3bt3mjdvni222CJXX331Msf99a9/nYEDB6Z58+a55ZZb8re//S377bdf2rVrl1atWmWrrbbKH//4xy993wCAhkOsAwCoo8aNG2fMmDG54oor8tZbb32tYz3wwAN555138tBDD+Wyyy7LqFGjsu+++6Zdu3Z59NFHc8wxx+Too49e5nlOPfXUnHzyyXnqqaey8847Z7/99suHH36Y5IvA9e1vfzv9+vXL448/nkmTJuW9997LwQcfXOsYEyZMSNOmTTN16tRce+21Xzrfz3/+81x66aX57//+7zz77LPZc88982//9m959dVXkyTvvvtuttpqq5x88sl59913c8oppyxzjI8++iiTJk3KsGHD0qpVq2XWt23bdoXfr7PPPjsvvPBCJk6cmBdffDHXXHNN1l9//STJY489liT585//nHfffTd33nnnCr2GpUaNGpWf/vSnefLJJ9OkSZP88Ic/zGmnnZaf//zn+d///d/MmDEj55xzTs32t9xyS84555xceOGFefHFFzNmzJicffbZmTBhQq3jnnHGGTnppJPy4osvZs8998ywYcOyaNGiPPTQQ3nuuecybty4tG7deoXfAwBgHVUCAGClHXbYYaXvfe97pVKpVNppp51KRxxxRKlUKpV+97vflf7xn1ijRo0q9e3bt9a+P/vZz0rdu3evdazu3buXlixZUrNs8803L+222241jxcvXlxq1apV6Ve/+lWpVCqVXn/99VKS0kUXXVSzzeeff17q0qVLady4caVSqVS64IILSnvssUet537zzTdLSUovv/xyqVQqlQYOHFjq16/fv3y9nTt3Ll144YW1ln3jG98oHXfccTWP+/btWxo1atRyj/Hoo4+WkpTuvPPOr3yupa/tqaeeqln28ccfl5KUJk+eXCqVSqX99tuvdPjhh6/w/ivyGpbud+ONN9as/9WvflVKUrr//vtrlo0dO7a0+eab1zzeZJNNSrfeemut415wwQWlnXfeudZxx48fX2ubPn36lM4999yveCcAgIbIlXUAAF/TuHHjMmHChLz44ot1PsZWW22VRo3+/3+aVVZWpk+fPjWPGzdunA4dOmTOnDm19tt5551rfm/SpEn69+9fM8czzzyTyZMnp3Xr1jU/W2yxRZIvvl9uqe233/4rZ6uqqso777yTAQMG1Fo+YMCAlXrNpVJphbf9V4499tjcdttt2XbbbXPaaaflL3/5y1duvzKvYZtttqn5vbKyMklq/VlUVlbW/DksWLAgM2fOzJFHHlnrfR49enSt9zhJ+vfvX+vxiSeemNGjR2fAgAEZNWpUnn322RV89QDAukysAwD4mr75zW9mzz33zJlnnrnMukaNGi0Tqb7s5gLrrbdercdlZWVfuqy6unqF55o/f37222+/PP3007V+Xn311Xzzm9+s2e7LPpK6OvTq1StlZWV56aWXvnK7pdHyH9+3f37P9tprr/ztb3/LiBEj8s477+Q73/nOl370ti7+8X1femfff1629M9h/vz5SZIbbrih1ns8ffr0mu/gW+qf3+cf//jHee2113LooYfmueeeS//+/XPFFVesktcAAKy9xDoAgFXgoosuyh/+8Ic88sgjtZZ37Ngxs2fPrhWe/vHGCV/XPwahxYsX54knnkjv3r2TJNttt12ef/759OjRI5tuummtn5UJdOXl5encuXOmTp1aa/nUqVOz5ZZbrvBx2rdvnz333DNXXXVVFixYsMz6uXPnJvniPUu++B68pb7sPevYsWMOO+yw/M///E/Gjx+f66+/PknStGnTJMmSJUtW+Wv4Z5WVlencuXNee+21Zd7jpTe6+Cpdu3bNMccckzvvvDMnn3xybrjhhjrPAgCsG5rU9wAAAOuCPn36ZMiQIbn88strLR80aFDef//9XHzxxfn+97+fSZMmZeLEiSkvL18lz3vVVVelV69e6d27d372s5/l448/zhFHHJEkGTZsWG644YYccsghOe2009K+ffvMmDEjt912W2688cY0btx4hZ/n1FNPzahRo7LJJptk2223zU033ZSnn346t9xyy0rPO2DAgOywww45//zzs80222Tx4sW57777cs011+TFF19MixYtstNOO+Wiiy5Kz549M2fOnPz0pz+tdZxzzjkn22+/fbbaaqssWrQod999d02k7NSpU1q0aJFJkyalS5cuad68eSoqKlbZa/hn5513Xk488cRUVFTku9/9bhYtWpTHH388H3/8cUaOHLnc/YYPH5699torm222WT7++ONMnjy55jUAAA2XK+sAAFaR888/f5mPqfbu3TtXX311rrrqqvTt2zePPfbYKvu4ZvLFFX0XXXRR+vbtm4cffjh33XVXzV1Rl15JtmTJkuyxxx7p06dPhg8fnrZt29b6frwVceKJJ2bkyJE5+eST06dPn0yaNCl33XVXevXqtVLH2XjjjfPkk0/mW9/6Vk4++eRsvfXW2X333XP//ffnmmuuqdnuF7/4RRYvXpztt98+w4cPz+jRo2sdp2nTpjnzzDOzzTbb5Jvf/GYaN26c2267LckX3913+eWX57rrrkvnzp3zve99b5W+hn/24x//ODfeeGNuuumm9OnTJwMHDswvf/nLf3ll3ZIlSzJs2LD07t073/3ud7PZZpvl6quv/lqzAABrv7LSqvymXwAAAACgzlxZBwAAAAAFIdYBAAAAQEGIdQAAAABQEGIdAAAAABSEWAcAAAAABSHWAQAAAEBBiHUAAAAAUBBiHQAAAAAUhFgHAAAAAAUh1gEAAABAQYh1AAAAAFAQ/x+Qz5p8eaJT9wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "male = df.Gender[(df.Gender == 'Male')]\n",
    "female = df.Gender[(df.Gender == 'Female')]\n",
    "\n",
    "x = [\"male\", \"female\"]\n",
    "y = [len(male.values), len(female.values)]\n",
    "\n",
    "plt.figure(figsize=(15,6))\n",
    "plt.barh(x, y, color=['purple', 'orange'])\n",
    "\n",
    "plt.title(\"Gender Plot\")\n",
    "plt.xlabel(\"Number of Customers\")\n",
    "plt.ylabel(\"Gender\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking which age range has the highest number of customers using barplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age_18_25 = df.Age[(df.Age >= 18) & (df.Age <= 25)]\n",
    "age_26_35 = df.Age[(df.Age >= 26) & (df.Age <= 35)]\n",
    "age_36_45 = df.Age[(df.Age >= 36) & (df.Age <= 45)]\n",
    "age_46_55 = df.Age[(df.Age >= 46) & (df.Age <= 55)]\n",
    "age_55above = df.Age[df.Age >= 56]\n",
    "\n",
    "agex = [\"18-25\", \"26-35\", \"36-45\", \"46-55\", \"55+\"]\n",
    "agey = [len(age_18_25.values), len(age_26_35.values), len(age_36_45.values), len(age_46_55.values), len(age_55above.values)]\n",
    "\n",
    "plt.figure(figsize=(15,6))\n",
    "sns.barplot(x = agex, y = agey, palette=\"mako\")\n",
    "\n",
    "plt.title(\"Number of Customer and Ages\")\n",
    "plt.xlabel(\"Age\")\n",
    "plt.ylabel(\"Number of Customer\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Relationship between annual income and spending score using scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x= \"Annual Income (k$)\", y= \"Spending Score (1-100)\", data= df)\n",
    "plt.title(\"Relationship between annual income and spending score\")\n",
    "plt.xlabel(\"Annual Income (k$)\")\n",
    "plt.ylabel(\"Spending Score (1-100)\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Relationship between number of customers and spending score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uuuv+xzmrfGnWokWLJF/8YbRs2bKO0wAAAABQVyoqKtKhQ4fKvug/WeVLsy9vyWzZsqXSDAAAAIBqPcLLiwAAAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKKM0AAAAAoEiDug4AAHw73b3lQXUdAWrdHs/8ua4jAADLyZVmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAARZRmAAAAAFBEaQYAAAAAReq0NFtvvfVSVla21GfgwIFJkvnz52fgwIFZY4010rx58/Tt2zczZ86sy8gAAAAAfAvUaWn21FNP5b333qv83H///UmSn/70p0mSwYMH54477sjNN9+ciRMn5t13381+++1Xl5EBAAAA+BZoUJcHX2uttaosjxw5Ml26dMmOO+6YOXPm5JprrskNN9yQnXfeOUkyduzYbLzxxnnyySez7bbb1kVkAAAAAL4FVppnmi1cuDB/+tOf0r9//5SVlWXKlClZtGhRdtlll8o5Xbt2TceOHTNp0qSv3M+CBQtSUVFR5QMAAAAApVhpSrPbb789s2fPzmGHHZYkmTFjRho1apRWrVpVmde2bdvMmDHjK/czYsSIlJeXV346dOhQi6kBAAAAWBWtNKXZNddck9133z3t27f/WvsZNmxY5syZU/l55513aighAAAAAN8WdfpMsy+9/fbbeeCBB3LrrbdWjrVr1y4LFy7M7Nmzq1xtNnPmzLRr1+4r99W4ceM0bty4NuMCAAAAsIpbKa40Gzt2bNq0aZM999yzcqxnz55p2LBhJkyYUDn26quvZvr06enVq1ddxAQAAADgW6LOrzRbsmRJxo4dm0MPPTQNGvz/OOXl5RkwYECGDBmS1q1bp2XLljnuuOPSq1cvb84EAAAAoFbVeWn2wAMPZPr06enfv/9S6y6++OLUq1cvffv2zYIFC9KnT59cccUVdZASAAAAgG+TskKhUKjrELWpoqIi5eXlmTNnTlq2bFnXcQCA/+fuLQ+q6whQ6/Z45s91HQEA+Del9EQrxTPNAAAAAGBlojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCJKMwAAAAAoojQDAAAAgCLLXZotXLgwr776aj7//POazAMAAAAAda7k0mzevHkZMGBAmjVrlm7dumX69OlJkuOOOy4jR46s8YAAAAAAsKKVXJoNGzYszz33XB5++OE0adKkcnyXXXbJX/7ylxoNBwAAAAB1oUGpG9x+++35y1/+km233TZlZWWV4926dcubb75Zo+EAAAAAoC6UfKXZBx98kDZt2iw1Pnfu3ColGgAAAAB8U5Vcmm211Va56667Kpe/LMp+//vfp1evXjWXDAAAAADqSMm3Z5577rnZfffd8/LLL+fzzz/PJZdckpdffjlPPPFEJk6cWBsZAQAAAGCFKvlKs+233z7PPfdcPv/883Tv3j333Xdf2rRpk0mTJqVnz561kREAAAAAVqiSSrNFixalf//+KSsry9VXX53Jkyfn5Zdfzp/+9Kd07959uQL861//yiGHHJI11lgjTZs2Tffu3fP0009Xri8UCjn99NOz9tprp2nTptlll13y+uuvL9exAAAAAKA6SirNGjZsmFtuuaXGDj5r1qz07t07DRs2zD333JOXX345F154YVZfffXKOeeff34uvfTSXHXVVfnHP/6R1VZbLX369Mn8+fNrLAcAAAAA/LuSn2m2zz775Pbbb8/gwYO/9sHPO++8dOjQIWPHjq0c69y5c+XPhUIho0aNymmnnZa99947SXLdddelbdu2uf3223PggQd+7QwAAAAAUKzk0myDDTbIWWedlccffzw9e/bMaqutVmX9oEGDqr2vv//97+nTp09++tOfZuLEiVlnnXXyy1/+MkceeWSSZNq0aZkxY0Z22WWXym3Ky8uzzTbbZNKkScsszRYsWJAFCxZULldUVJT6FQEAAAD4liu5NLvmmmvSqlWrTJkyJVOmTKmyrqysrKTS7K233sqVV16ZIUOG5JRTTslTTz2VQYMGpVGjRjn00EMzY8aMJEnbtm2rbNe2bdvKdcVGjBiRM888s8RvBQAAAAD/X8ml2bRp02rs4EuWLMlWW22Vc889N0myxRZb5MUXX8xVV12VQw89dLn2OWzYsAwZMqRyuaKiIh06dKiRvAAAAAB8O5T0IoBihUIhhUJhubdfe+21s8kmm1QZ23jjjTN9+vQkSbt27ZIkM2fOrDJn5syZleuKNW7cOC1btqzyAQAAAIBSLFdpdt1116V79+5p2rRpmjZtmh49euSPf/xjyfvp3bt3Xn311Spjr732Wjp16pTki5cCtGvXLhMmTKhcX1FRkX/84x/p1avX8kQHAAAAgP+q5NszL7roogwfPjzHHntsevfunSR57LHHcswxx+TDDz8s6a2agwcPznbbbZdzzz03+++/fyZPnpwxY8ZkzJgxSb54RtoJJ5yQ3/72t9lggw3SuXPnDB8+PO3bt88+++xTanQAAAAAqJaSS7PLLrssV155ZX7+859Xjv34xz9Ot27d8pvf/Kak0mzrrbfObbfdlmHDhuWss85K586dM2rUqPTr169yzkknnZS5c+fmqKOOyuzZs7P99ttn/PjxadKkSanRAQAAAKBaygolPpSsSZMmefHFF7P++utXGX/99dfTvXv3zJ8/v0YDfl0VFRUpLy/PnDlzPN8MAFYid295UF1HgFq3xzN/rusIAMC/KaUnKvmZZuuvv35uuummpcb/8pe/ZIMNNih1dwAAAACw0in59swzzzwzBxxwQB555JHKZ5o9/vjjmTBhwjLLNAAAAAD4pin5SrO+ffvmH//4R9Zcc83cfvvtuf3227Pmmmtm8uTJ2XfffWsjIwAAAACsUCVfaZYkPXv2zJ/+9KeazgIAAAAAK4WSrzS7++67c++99y41fu+99+aee+6pkVAAAAAAUJdKLs2GDh2axYsXLzVeKBQydOjQGgkFAAAAAHWp5NLs9ddfzyabbLLUeNeuXfPGG2/USCgAAAAAqEsll2bl5eV56623lhp/4403stpqq9VIKAAAAACoSyWXZnvvvXdOOOGEvPnmm5Vjb7zxRk488cT8+Mc/rtFwAAAAAFAXSi7Nzj///Ky22mrp2rVrOnfunM6dO2fjjTfOGmuskQsuuKA2MgIAAADACtWg1A3Ky8vzxBNP5P77789zzz2Xpk2bpkePHvne975XG/kAAAAAYIUruTRLkrKysuy2227ZbbfdajoPAAAAANS5at+eOWnSpNx5551Vxq677rp07tw5bdq0yVFHHZUFCxbUeEAAAAAAWNGqXZqdddZZeemllyqXX3jhhQwYMCC77LJLhg4dmjvuuCMjRoyolZAAAAAAsCJVuzSbOnVqfvCDH1Qu33jjjdlmm21y9dVXZ8iQIbn00ktz00031UpIAAAAAFiRql2azZo1K23btq1cnjhxYnbffffK5a233jrvvPNOzaYDAAAAgDpQ7dKsbdu2mTZtWpJk4cKFeeaZZ7LttttWrv/kk0/SsGHDmk8IAAAAACtYtUuzPfbYI0OHDs2jjz6aYcOGpVmzZtlhhx0q1z///PPp0qVLrYQEAAAAgBWpQXUnnn322dlvv/2y4447pnnz5rn22mvTqFGjyvV/+MMfsttuu9VKSAAAAABYkapdmq255pp55JFHMmfOnDRv3jz169evsv7mm29O8+bNazwgAAAAAKxo1S7NvlReXr7M8datW3/tMAAAAACwMqj2M80AAAAA4NtCaQYAAAAARZRmAAAAAFBEaQYAAAAARZarNPvjH/+Y3r17p3379nn77beTJKNGjcrf/va3Gg0HAAAAAHWh5NLsyiuvzJAhQ7LHHntk9uzZWbx4cZKkVatWGTVqVE3nAwAAAIAVruTS7LLLLsvVV1+dU089NfXr168c32qrrfLCCy/UaDgAAAAAqAsll2bTpk3LFltssdR448aNM3fu3BoJBQAAAAB1qeTSrHPnzpk6depS4+PHj8/GG29cE5kAAAAAoE41KHWDIUOGZODAgZk/f34KhUImT56cP//5zxkxYkR+//vf10ZGAAAAAFihSi7NjjjiiDRt2jSnnXZa5s2bl4MPPjjt27fPJZdckgMPPLA2MgIAAADAClVyaZYk/fr1S79+/TJv3rx8+umnadOmTU3nAgAAAIA6s1yl2ZeaNWuWZs2a1VQWAAAAAFgplPwigJkzZ+ZnP/tZ2rdvnwYNGqR+/fpVPgAAAADwTVfylWaHHXZYpk+fnuHDh2fttddOWVlZbeQCAAAAgDpTcmn22GOP5dFHH83mm29eC3EAAAAAoO6VfHtmhw4dUigUaiMLAAAAAKwUSi7NRo0alaFDh+af//xnLcQBAAAAgLpXrdszV1999SrPLps7d266dOmSZs2apWHDhlXmfvzxxzWbEAAAAABWsGqVZqNGjarlGAAAAACw8qhWaXbooYfWdg4AAAAAWGmU/Eyz+vXr5/33319q/KOPPkr9+vVrJBQAAAAA1KWSS7OvenPmggUL0qhRo68dCAAAAADqWrVuz0ySSy+9NElSVlaW3//+92nevHnlusWLF+eRRx5J165daz4hAAAAAKxg1S7NLr744iRfXGl21VVXVbkVs1GjRllvvfVy1VVX1XxCAAAAAFjBql2aTZs2LUmy00475dZbb83qq69ea6EAAAAAoC6V/Eyzhx56qMYKs9/85jcpKyur8vn3Wzznz5+fgQMHZo011kjz5s3Tt2/fzJw5s0aODQAAAABfpeTSrKZ169Yt7733XuXnscceq1w3ePDg3HHHHbn55pszceLEvPvuu9lvv/3qMC0AAAAA3wbVvj2z1gI0aJB27dotNT5nzpxcc801ueGGG7LzzjsnScaOHZuNN944Tz75ZLbddtsVHRUAAACAb4k6v9Ls9ddfT/v27fOd73wn/fr1y/Tp05MkU6ZMyaJFi7LLLrtUzu3atWs6duyYSZMmfeX+FixYkIqKiiofAAAAAChFnZZm22yzTcaNG5fx48fnyiuvzLRp07LDDjvkk08+yYwZM9KoUaO0atWqyjZt27bNjBkzvnKfI0aMSHl5eeWnQ4cOtfwtAAAAAFjVlHx75vPPP7/M8bKysjRp0iQdO3ZM48aNq7Wv3XffvfLnHj16ZJtttkmnTp1y0003pWnTpqVGS5IMGzYsQ4YMqVyuqKhQnAEAAABQkpJLs8033zxlZWVfub5hw4Y54IAD8rvf/S5NmjQpad+tWrXKhhtumDfeeCO77rprFi5cmNmzZ1e52mzmzJnLfAbalxo3blzt0g4AAAAAlqXk2zNvu+22bLDBBhkzZkymTp2aqVOnZsyYMdloo41yww035JprrsmDDz6Y0047reQwn376ad58882svfba6dmzZxo2bJgJEyZUrn/11Vczffr09OrVq+R9AwAAAEB1lXyl2TnnnJNLLrkkffr0qRzr3r171l133QwfPjyTJ0/OaqutlhNPPDEXXHDBf9zXr371q+y1117p1KlT3n333ZxxxhmpX79+DjrooJSXl2fAgAEZMmRIWrdunZYtW+a4445Lr169vDkTAAAAgFpVcmn2wgsvpFOnTkuNd+rUKS+88EKSL27hfO+99/7rvv7P//k/Oeigg/LRRx9lrbXWyvbbb58nn3wya621VpLk4osvTr169dK3b98sWLAgffr0yRVXXFFqZAAAAAAoScmlWdeuXTNy5MiMGTMmjRo1SpIsWrQoI0eOTNeuXZMk//rXv9K2bdv/uq8bb7zxP65v0qRJRo8endGjR5caEwAAAACWW8ml2ejRo/PjH/846667bnr06JHki6vPFi9enDvvvDNJ8tZbb+WXv/xlzSYFAAAAgBWk5NJsu+22y7Rp03L99dfntddeS5L89Kc/zcEHH5wWLVokSX72s5/VbEoAAAAAWIFKLs2SpEWLFjnmmGNqOgsAAAAArBSWqzR7/fXX89BDD+X999/PkiVLqqw7/fTTayQYAAAAANSVkkuzq6++Or/4xS+y5pprpl27dikrK6tcV1ZWpjQDAAAA4Buv5NLst7/9bc4555ycfPLJtZEHAAAAAOpcvVI3mDVrVn7605/WRhYAAAAAWCmUXJr99Kc/zX333VcbWQAAAABgpVDy7Znrr79+hg8fnieffDLdu3dPw4YNq6wfNGhQjYUDAAAAgLpQVigUCqVs0Llz56/eWVlZ3nrrra8dqiZVVFSkvLw8c+bMScuWLes6DgDw/9y95UF1HQFq3R7P/LmuIwAA/6aUnqjkK82mTZu23MEAAAAA4Jug5GeaAQAAAMCqrlpXmg0ZMiRnn312VltttQwZMuQ/zr3oootqJBgAAAAA1JVqlWbPPvtsFi1aVPnzVykrK6uZVAAAAABQh6pVmj300EPL/BkAAAAAVkUlP9PsT3/6U+bNm1cbWQAAAABgpVByaTZ48OC0adMmBx98cO6+++4sXry4NnIBAAAAQJ0puTR77733cuONN6asrCz7779/1l577QwcODBPPPFEbeQDAAAAgBWu5NKsQYMG+dGPfpTrr78+77//fi6++OL885//zE477ZQuXbrURkYAAAAAWKGq9SKAr9KsWbP06dMns2bNyttvv51XXnmlpnIBAAAAQJ0p+UqzJJk3b16uv/767LHHHllnnXUyatSo7LvvvnnppZdqOh8AAAAArHAlX2l24IEH5s4770yzZs2y//77Z/jw4enVq1dtZAMAAACAOlFyaVa/fv3cdNNN6dOnT+rXr18bmQAAAACgTpVcml1//fW1kQMAAAAAVhrL9SKAuXPnZuLEiZk+fXoWLlxYZd2gQYNqJBgAAAAA1JWSS7Nnn302e+yxR+bNm5e5c+emdevW+fDDD9OsWbO0adNGaQYAAADAN17Jb88cPHhw9tprr8yaNStNmzbNk08+mbfffjs9e/bMBRdcUBsZAQAAAGCFKrk0mzp1ak488cTUq1cv9evXz4IFC9KhQ4ecf/75OeWUU2ojIwAAAACsUCWXZg0bNky9el9s1qZNm0yfPj1JUl5ennfeeadm0wEAAABAHSj5mWZbbLFFnnrqqWywwQbZcccdc/rpp+fDDz/MH//4x2y66aa1kREAAAAAVqiSrzQ799xzs/baaydJzjnnnKy++ur5xS9+kQ8++CBjxoyp8YAAAAAAsKKVfKXZVlttVflzmzZtMn78+BoNBAAAAAB1reQrzQAAAABgVVftK8222GKLlJWV/dd5zzzzzNcKBAAAAAB1rdql2T777FP5c6FQyIgRI3LMMcekdevWtZELAAAAAOpMWaFQKCzPhi1atMhzzz2X73znOzWdqUZVVFSkvLw8c+bMScuWLes6DgDw/9y95UF1HQFq3R7P/LmuIwAA/6aUnsgzzQAAAACgiNIMAAAAAIoozQAAAACgSLVfBHDppZdWWf78888zbty4rLnmmlXGBw0aVDPJAAAAAKCOVPtFAJ07d/7vOysry1tvvfW1Q9UkLwIAgJWTFwHwbeBFAACwcimlJ6r2lWbTpk372sEAAAAA4JvAM80AAAAAoIjSDAAAAACKKM0AAAAAoIjSDAAAAACKlFSaff7557nuuusyc+bM2soDAAAAAHWupNKsQYMGOeaYYzJ//vzaygMAAAAAda7k2zO/+93vZurUqTUeZOTIkSkrK8sJJ5xQOTZ//vwMHDgwa6yxRpo3b56+ffu6yg0AAACAWteg1A1++ctfZsiQIXnnnXfSs2fPrLbaalXW9+jRo+QQTz31VH73u98tte3gwYNz11135eabb055eXmOPfbY7Lfffnn88cdLPgYAAAAAVFfJpdmBBx6YJBk0aFDlWFlZWQqFQsrKyrJ48eKS9vfpp5+mX79+ufrqq/Pb3/62cnzOnDm55pprcsMNN2TnnXdOkowdOzYbb7xxnnzyyWy77balRgcAAACAaim5NJs2bVqNBhg4cGD23HPP7LLLLlVKsylTpmTRokXZZZddKse6du2ajh07ZtKkSV9Zmi1YsCALFiyoXK6oqKjRvAAAAACs+kouzTp16lRjB7/xxhvzzDPP5Kmnnlpq3YwZM9KoUaO0atWqynjbtm0zY8aMr9zniBEjcuaZZ9ZYRgAAAAC+fUp+EUCS/PGPf0zv3r3Tvn37vP3220mSUaNG5W9/+1u19/HOO+/k+OOPz/XXX58mTZosT4xlGjZsWObMmVP5eeedd2ps3wAAAAB8O5Rcml155ZUZMmRI9thjj8yePbvyGWatWrXKqFGjqr2fKVOm5P3338+WW26ZBg0apEGDBpk4cWIuvfTSNGjQIG3bts3ChQsze/bsKtvNnDkz7dq1+8r9Nm7cOC1btqzyAQAAAIBSlFyaXXbZZbn66qtz6qmnpn79+pXjW221VV544YVq7+cHP/hBXnjhhUydOrXys9VWW6Vfv36VPzds2DATJkyo3ObVV1/N9OnT06tXr1JjAwAAAEC1LdeLALbYYoulxhs3bpy5c+dWez8tWrTIpptuWmVstdVWyxprrFE5PmDAgAwZMiStW7dOy5Ytc9xxx6VXr17enAkAAABArSq5NOvcuXOmTp261AsBxo8fn4033rjGgiXJxRdfnHr16qVv375ZsGBB+vTpkyuuuKJGjwEAAAAAxUouzYYMGZKBAwdm/vz5KRQKmTx5cv785z9nxIgR+f3vf/+1wjz88MNVlps0aZLRo0dn9OjRX2u/AAAAAFCKkkuzI444Ik2bNs1pp52WefPm5eCDD0779u1zySWX5MADD6yNjAAAAACwQpVcmiVJv3790q9fv8ybNy+ffvpp2rRpU9O5AAAAAKDOLFdp9qVmzZqlWbNmNZUFAAAAAFYKJZdmH330UU4//fQ89NBDef/997NkyZIq6z/++OMaCwcAAAAAdaHk0uxnP/tZ3njjjQwYMCBt27ZNWVlZbeQCAAAAgDpTcmn26KOP5rHHHstmm21WG3kAAAAAoM7VK3WDrl275rPPPquNLAAAAACwUii5NLviiity6qmnZuLEifnoo49SUVFR5QMAAAAA33Ql357ZqlWrVFRUZOedd64yXigUUlZWlsWLF9dYOAAAAACoCyWXZv369UvDhg1zww03eBEAAAAAAKukkkuzF198Mc8++2w22mij2sgDAAAAAHWu5GeabbXVVnnnnXdqIwsAAAAArBRKvtLsuOOOy/HHH59f//rX6d69exo2bFhlfY8ePWosHAAAAADUhZJLswMOOCBJ0r9//8qxsrIyLwIAAAAAYJVRcmk2bdq02sgBAAAAACuNkkuzTp061UYOAAAAAFhplFyaJcmbb76ZUaNG5ZVXXkmSbLLJJjn++OPTpUuXGg0HAAAAAHWh5NLs3nvvzY9//ONsvvnm6d27d5Lk8ccfT7du3XLHHXdk1113rfGQK7PtO+9Y1xGg1j02bWJdRwAAAIAVquTSbOjQoRk8eHBGjhy51PjJJ5/8rSvNAAAAAFj11Ct1g1deeSUDBgxYarx///55+eWXayQUAAAAANSlkkuztdZaK1OnTl1qfOrUqWnTpk1NZAIAAACAOlXy7ZlHHnlkjjrqqLz11lvZbrvtknzxTLPzzjsvQ4YMqfGAAAAAALCilVyaDR8+PC1atMiFF16YYcOGJUnat2+f3/zmNxk0aFCNBwQAAACAFa3k0qysrCyDBw/O4MGD88knnyRJWrRoUePBAAAAAKCulPxMs5133jmzZ89O8kVZ9mVhVlFRkZ133rlGwwEAAABAXSi5NHv44YezcOHCpcbnz5+fRx99tEZCAQAAAEBdqvbtmc8//3zlzy+//HJmzJhRubx48eKMHz8+66yzTs2mAwAAAIA6UO3SbPPNN09ZWVnKysqWeRtm06ZNc9lll9VoOAAAAACoC9UuzaZNm5ZCoZDvfOc7mTx5ctZaa63KdY0aNUqbNm1Sv379WgkJAAAAACtStUuzTp06JUmWLFlSa2EAAAAAYGVQ8osArr322tx1112VyyeddFJatWqV7bbbLm+//XaNhgMAAACAulByaXbuueemadOmSZJJkybl8ssvz/nnn58111wzgwcPrvGAAAAAALCiVfv2zC+98847WX/99ZMkt99+e37yk5/kqKOOSu/evfP973+/pvMBAAAAwApX8pVmzZs3z0cffZQkue+++7LrrrsmSZo0aZLPPvusZtMBAAAAQB0o+UqzXXfdNUcccUS22GKLvPbaa9ljjz2SJC+99FLWW2+9ms4HAAAAACtcyVeajR49Or169coHH3yQW265JWussUaSZMqUKTnooINqPCAAAAAArGglX2nWqlWrXH755UuNn3nmmTUSCAAAAADqWsml2SOPPPIf13/ve99b7jAAAAAAsDIouTRb1hsyy8rKKn9evHjx1woEAAAAAHWt5GeazZo1q8rn/fffz/jx47P11lvnvvvuq42MAAAAALBClXylWXl5+VJju+66axo1apQhQ4ZkypQpNRIMAACoO28cf3BdR4Bat/4lN9R1BGAlVvKVZl+lbdu2efXVV2tqdwAAAABQZ0q+0uz555+vslwoFPLee+9l5MiR2XzzzWsqFwAAAADUmZJLs8033zxlZWUpFApVxrfddtv84Q9/qLFgAAAAAFBXSi7Npk2bVmW5Xr16WWuttdKkSZMaCwUAAAAAdank0qxTp061kQMAAAAAVhrVfhHAgw8+mE022SQVFRVLrZszZ066deuWRx99tEbDAQAAAEBdqHZpNmrUqBx55JFp2bLlUuvKy8tz9NFH56KLLqrRcAAAAABQF6pdmj333HP54Q9/+JXrd9ttt0yZMqWkg1955ZXp0aNHWrZsmZYtW6ZXr1655557KtfPnz8/AwcOzBprrJHmzZunb9++mTlzZknHAAAAAIBSVbs0mzlzZho2bPiV6xs0aJAPPvigpIOvu+66GTlyZKZMmZKnn346O++8c/bee++89NJLSZLBgwfnjjvuyM0335yJEyfm3XffzX777VfSMQAAAACgVNV+EcA666yTF198Meuvv/4y1z///PNZe+21Szr4XnvtVWX5nHPOyZVXXpknn3wy6667bq655prccMMN2XnnnZMkY8eOzcYbb5wnn3wy2267bUnHAgAAAIDqqvaVZnvssUeGDx+e+fPnL7Xus88+yxlnnJEf/ehHyx1k8eLFufHGGzN37tz06tUrU6ZMyaJFi7LLLrtUzunatWs6duyYSZMmfeV+FixYkIqKiiofAAAAAChFta80O+2003Lrrbdmww03zLHHHpuNNtooSfK///u/GT16dBYvXpxTTz215AAvvPBCevXqlfnz56d58+a57bbbsskmm2Tq1Klp1KhRWrVqVWV+27ZtM2PGjK/c34gRI3LmmWeWnAMAAAC+CWbeflldR4Ba13af4+o6QvVLs7Zt2+aJJ57IL37xiwwbNiyFQiFJUlZWlj59+mT06NFp27ZtyQE22mijTJ06NXPmzMlf//rXHHrooZk4cWLJ+/nSsGHDMmTIkMrlioqKdOjQYbn3BwAAAMC3T7VLsyTp1KlT7r777syaNStvvPFGCoVCNthgg6y++urLHaBRo0aVz0nr2bNnnnrqqVxyySU54IADsnDhwsyePbvK1WYzZ85Mu3btvnJ/jRs3TuPGjZc7DwAAAABU+5lm/2711VfP1ltvne9+97tfqzBbliVLlmTBggXp2bNnGjZsmAkTJlSue/XVVzN9+vT06tWrRo8JAAAAAP+upCvNatqwYcOy++67p2PHjvnkk09yww035OGHH869996b8vLyDBgwIEOGDEnr1q3TsmXLHHfccenVq5c3ZwIAAABQq+q0NHv//ffz85//PO+9917Ky8vTo0eP3Hvvvdl1112TJBdffHHq1auXvn37ZsGCBenTp0+uuOKKuowMAAAAwLdAnZZm11xzzX9c36RJk4wePTqjR49eQYkAAAAAoJrPNNtyyy0za9asJMlZZ52VefPm1WooAAAAAKhL1SrNXnnllcydOzdJcuaZZ+bTTz+t1VAAAAAAUJeqdXvm5ptvnsMPPzzbb799CoVCLrjggjRv3nyZc08//fQaDQgAAAAAK1q1SrNx48bljDPOyJ133pmysrLcc889adBg6U3LysqUZgAAAAB841WrNNtoo41y4403Jknq1auXCRMmpE2bNrUaDAAAAADqSslvz1yyZElt5AAAAACAlUbJpVmSvPnmmxk1alReeeWVJMkmm2yS448/Pl26dKnRcAAAAABQF6r19sx/d++992aTTTbJ5MmT06NHj/To0SP/+Mc/0q1bt9x///21kREAAAAAVqiSrzQbOnRoBg8enJEjRy41fvLJJ2fXXXetsXAAAAAAUBdKvtLslVdeyYABA5Ya79+/f15++eUaCQUAAAAAdankK83WWmutTJ06NRtssEGV8alTp3qjJrDSGbrpQXUdAWrdyBf/XNcRAABglVNyaXbkkUfmqKOOyltvvZXtttsuSfL444/nvPPOy5AhQ2o8IAAAAACsaCWXZsOHD0+LFi1y4YUXZtiwYUmS9u3b5ze/+U0GDRpU4wEBAAAAYEUruTQrKyvL4MGDM3jw4HzyySdJkhYtWtR4MAAAAACoKyWXZv9OWQYAAADAqqjkt2cCAAAAwKpOaQYAAAAARZRmAAAAAFCkpNJs0aJF+cEPfpDXX3+9tvIAAAAAQJ0rqTRr2LBhnn/++drKAgAAAAArhZJvzzzkkENyzTXX1EYWAAAAAFgpNCh1g88//zx/+MMf8sADD6Rnz55ZbbXVqqy/6KKLaiwcAAAAANSFkkuzF198MVtuuWWS5LXXXquyrqysrGZSAQAAAEAdKrk0e+ihh2ojBwAAAACsNEp+ptmX3njjjdx777357LPPkiSFQqHGQgEAAABAXSq5NPvoo4/ygx/8IBtuuGH22GOPvPfee0mSAQMG5MQTT6zxgAAAAACwopVcmg0ePDgNGzbM9OnT06xZs8rxAw44IOPHj6/RcAAAAABQF0p+ptl9992Xe++9N+uuu26V8Q022CBvv/12jQUDAAAAgLpS8pVmc+fOrXKF2Zc+/vjjNG7cuEZCAQAAAEBdKrk022GHHXLddddVLpeVlWXJkiU5//zzs9NOO9VoOAAAAACoCyXfnnn++efnBz/4QZ5++uksXLgwJ510Ul566aV8/PHHefzxx2sjIwAAAACsUCVfabbpppvmtddey/bbb5+99947c+fOzX777Zdnn302Xbp0qY2MAAAAALBClXylWZKUl5fn1FNPreksAAAAALBSWK7SbNasWbnmmmvyyiuvJEk22WSTHH744WndunWNhgMAAACAulDy7ZmPPPJI1ltvvVx66aWZNWtWZs2alUsvvTSdO3fOI488UhsZAQAAAGCFKvlKs4EDB+aAAw7IlVdemfr16ydJFi9enF/+8pcZOHBgXnjhhRoPCQAAAAArUslXmr3xxhs58cQTKwuzJKlfv36GDBmSN954o0bDAQAAAEBdKLk023LLLSufZfbvXnnllWy22WY1EgoAAAAA6lK1bs98/vnnK38eNGhQjj/++LzxxhvZdtttkyRPPvlkRo8enZEjR9ZOSgAAAABYgapVmm2++eYpKytLoVCoHDvppJOWmnfwwQfngAMOqLl0AAAAAFAHqlWaTZs2rbZzAAAAAMBKo1qlWadOnWo7BwAAAACsNKpVmhV7991389hjj+X999/PkiVLqqwbNGhQjQQDAAAAgLpScmk2bty4HH300WnUqFHWWGONlJWVVa4rKytTmgEAAADwjVdyaTZ8+PCcfvrpGTZsWOrVq1cbmQAAAACgTpXces2bNy8HHnigwgwAAACAVVbJzdeAAQNy880310YWAAAAAFgplHx75ogRI/KjH/0o48ePT/fu3dOwYcMq6y+66KKS9nXrrbfmf//3f9O0adNst912Oe+887LRRhtVzpk/f35OPPHE3HjjjVmwYEH69OmTK664Im3bti01OgAAAABUy3KVZvfee29lsVX8IoBSTJw4MQMHDszWW2+dzz//PKecckp22223vPzyy1lttdWSJIMHD85dd92Vm2++OeXl5Tn22GOz33775fHHHy81OgAAAABUS8ml2YUXXpg//OEPOeyww772wcePH19ledy4cWnTpk2mTJmS733ve5kzZ06uueaa3HDDDdl5552TJGPHjs3GG2+cJ598Mttuu+3XzgAAAAAAxUp+plnjxo3Tu3fv2siSOXPmJElat26dJJkyZUoWLVqUXXbZpXJO165d07Fjx0yaNGmZ+1iwYEEqKiqqfAAAAACgFCWXZscff3wuu+yyGg+yZMmSnHDCCendu3c23XTTJMmMGTPSqFGjtGrVqsrctm3bZsaMGcvcz4gRI1JeXl756dChQ41nBQAAAGDVVvLtmZMnT86DDz6YO++8M926dVvqRQC33nrrcgUZOHBgXnzxxTz22GPLtf2Xhg0bliFDhlQuV1RUKM4AAAAAKEnJpVmrVq2y33771WiIY489NnfeeWceeeSRrLvuupXj7dq1y8KFCzN79uwqV5vNnDkz7dq1W+a+GjdunMaNG9doPgAAAAC+XUouzcaOHVtjBy8UCjnuuONy22235eGHH07nzp2rrO/Zs2caNmyYCRMmpG/fvkmSV199NdOnT0+vXr1qLAcAAAAA/LuSS7OaNHDgwNxwww3529/+lhYtWlQ+p6y8vDxNmzZNeXl5BgwYkCFDhqR169Zp2bJljjvuuPTq1cubMwEAAACoNSWXZp07d05ZWdlXrn/rrbeqva8rr7wySfL973+/yvjYsWNz2GGHJUkuvvji1KtXL3379s2CBQvSp0+fXHHFFaXGBgAAAIBqK7k0O+GEE6osL1q0KM8++2zGjx+fX//61yXtq1Ao/Nc5TZo0yejRozN69OiS9g0AAAAAy6vk0uz4449f5vjo0aPz9NNPf+1AAAAAAFDX6tXUjnbffffccsstNbU7AAAAAKgzNVaa/fWvf03r1q1rancAAAAAUGdKvj1ziy22qPIigEKhkBkzZuSDDz7wgH4AAAAAVgkll2b77LNPleV69eplrbXWyve///107dq1pnIBAAAAQJ0puTQ744wzaiMHAAAAAKw0auyZZgAAAACwqqj2lWb16tWr8iyzZSkrK8vnn3/+tUMBAAAAQF2qdml22223feW6SZMm5dJLL82SJUtqJBQAAAAA1KVql2Z77733UmOvvvpqhg4dmjvuuCP9+vXLWWedVaPhAAAAAKAuLNczzd59990ceeSR6d69ez7//PNMnTo11157bTp16lTT+QAAAABghSupNJszZ05OPvnkrL/++nnppZcyYcKE3HHHHdl0001rKx8AAAAArHDVvj3z/PPPz3nnnZd27drlz3/+8zJv1wQAAACAVUG1S7OhQ4emadOmWX/99XPttdfm2muvXea8W2+9tcbCAQAAAEBdqHZp9vOf/zxlZWW1mQUAAAAAVgrVLs3GjRtXizEAAAAAYOWxXG/PBAAAAIBVmdIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIoozQAAAACgiNIMAAAAAIrUaWn2yCOPZK+99kr79u1TVlaW22+/vcr6QqGQ008/PWuvvXaaNm2aXXbZJa+//nrdhAUAAADgW6NOS7O5c+dms802y+jRo5e5/vzzz8+ll16aq666Kv/4xz+y2mqrpU+fPpk/f/4KTgoAAADAt0mDujz47rvvnt13332Z6wqFQkaNGpXTTjste++9d5LkuuuuS9u2bXP77bfnwAMPXJFRAQAAAPgWWWmfaTZt2rTMmDEju+yyS+VYeXl5ttlmm0yaNOkrt1uwYEEqKiqqfAAAAACgFCttaTZjxowkSdu2bauMt23btnLdsowYMSLl5eWVnw4dOtRqTgAAAABWPSttaba8hg0bljlz5lR+3nnnnbqOBAAAAMA3zEpbmrVr1y5JMnPmzCrjM2fOrFy3LI0bN07Lli2rfAAAAACgFCttada5c+e0a9cuEyZMqByrqKjIP/7xj/Tq1asOkwEAAACwqqvTt2d++umneeONNyqXp02blqlTp6Z169bp2LFjTjjhhPz2t7/NBhtskM6dO2f48OFp37599tlnn7oLDQAAAMAqr05Ls6effjo77bRT5fKQIUOSJIceemjGjRuXk046KXPnzs1RRx2V2bNnZ/vtt8/48ePTpEmTuooMAAAAwLdAnZZm3//+91MoFL5yfVlZWc4666ycddZZKzAVAAAAAN92K+0zzQAAAACgrijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKCI0gwAAAAAiijNAAAAAKDIN6I0Gz16dNZbb700adIk22yzTSZPnlzXkQAAAABYha30pdlf/vKXDBkyJGeccUaeeeaZbLbZZunTp0/ef//9uo4GAAAAwCpqpS/NLrroohx55JE5/PDDs8kmm+Sqq65Ks2bN8oc//KGuowEAAACwimpQ1wH+k4ULF2bKlCkZNmxY5Vi9evWyyy67ZNKkScvcZsGCBVmwYEHl8pw5c5IkFRUVtZLx8yWf18p+YWVSW+fPirBg8aK6jgC17pt6js5zfvIt8E09P5PkkwXOUVZ939Rz9JN5n9V1BKh1TWvp/PzyvC8UCv917kpdmn344YdZvHhx2rZtW2W8bdu2+d///d9lbjNixIiceeaZS4136NChVjLCt0F5eXldRwD+g1Hlt9R1BOCrOD9h5fa7v9Z1AuArnVyre//kk0/+6//XXalLs+UxbNiwDBkypHJ5yZIl+fjjj7PGGmukrKysDpNREyoqKtKhQ4e88847admyZV3HAYo4R2Hl5fyElZtzFFZezs9VS6FQyCeffJL27dv/17krdWm25pprpn79+pk5c2aV8ZkzZ6Zdu3bL3KZx48Zp3LhxlbFWrVrVVkTqSMuWLf2XFazEnKOw8nJ+wsrNOQorL+fnqqO6d1Ot1C8CaNSoUXr27JkJEyZUji1ZsiQTJkxIr1696jAZAAAAAKuylfpKsyQZMmRIDj300Gy11Vb57ne/m1GjRmXu3Lk5/PDD6zoaAAAAAKuolb40O+CAA/LBBx/k9NNPz4wZM7L55ptn/PjxS70cgG+Hxo0b54wzzljqFlxg5eAchZWX8xNWbs5RWHk5P7+9ygrVeccmAAAAAHyLrNTPNAMAAACAuqA0AwAAAIAiSjMAAAAAKKI0AwAAAIAiSjPqzCOPPJK99tor7du3T1lZWW6//fb/OP/jjz/Occcdl4022ihNmzZNx44dM2jQoMyZM6fKvOnTp2fPPfdMs2bN0qZNm/z617/O559/XovfBL75RowYka233jotWrRImzZtss8+++TVV1+tMmfMmDH5/ve/n5YtW6asrCyzZ88u6RgfffRR1l133WVu+/DDD2fLLbdM48aNs/7662fcuHFf7wvBKmzkyJEpKyvLCSecUDn2dc7PcePGpUePHmnSpEnatGmTgQMHVln//PPPZ4cddkiTJk3SoUOHnH/++TX0TWDV8a9//SuHHHJI1lhjjTRt2jTdu3fP008/Xbn+1ltvzW677ZY11lgjZWVlmTp1arX2+9prr2XvvffOmmuumZYtW2b77bfPQw89VGWO333h/1u8eHGGDx+ezp07p2nTpunSpUvOPvvs/Pv7D5f3fDznnHOy3XbbpVmzZmnVqtUy51TnfPR77zeL0ow6M3fu3Gy22WYZPXp0tea/++67effdd3PBBRfkxRdfzLhx4zJ+/PgMGDCgcs7ixYuz5557ZuHChXniiSdy7bXXZty4cTn99NNr62vAKmHixIkZOHBgnnzyydx///1ZtGhRdtttt8ydO7dyzrx58/LDH/4wp5xyynIdY8CAAenRo8dS49OmTcuee+6ZnXbaKVOnTs0JJ5yQI444Ivfee+9yfx9YVT311FP53e9+t9S5tLzn50UXXZRTTz01Q4cOzUsvvZQHHnggffr0qVxfUVGR3XbbLZ06dcqUKVPyP//zP/nNb36TMWPG1Mj3gVXBrFmz0rt37zRs2DD33HNPXn755Vx44YVZffXVK+fMnTs322+/fc4777yS9v2jH/0on3/+eR588MFMmTIlm222WX70ox9lxowZSfzuC8XOO++8XHnllbn88svzyiuv5Lzzzsv555+fyy67rHLO8p6PCxcuzE9/+tP84he/WOb66pyPfu/9BirASiBJ4bbbbit5u5tuuqnQqFGjwqJFiwqFQqFw9913F+rVq1eYMWNG5Zwrr7yy0LJly8KCBQtqKi6s8t5///1CksLEiROXWvfQQw8VkhRmzZpV7f1dccUVhR133LEwYcKEpbY96aSTCt26dasy/4ADDij06dNneePDKumTTz4pbLDBBoX777+/sOOOOxaOP/74peaUcn5+/PHHhaZNmxYeeOCBr5xzxRVXFFZfffUq/xt68sknFzbaaKPl+QqwSjr55JML22+/fbXmTps2rZCk8Oyzz/7XuR988EEhSeGRRx6pHKuoqCgkKdx///2FQsHvvlBszz33LPTv37/K2H777Vfo16/fUnNLOR//3dixYwvl5eVLjVfnfPR77zePK834RpszZ05atmyZBg0aJEkmTZqU7t27p23btpVz+vTpk4qKirz00kt1FRO+cb687bl169Zfe18vv/xyzjrrrFx33XWpV2/p/9mZNGlSdtlllypjffr0yaRJk772sWFVMnDgwOy5555LnS/L6/7778+SJUvyr3/9KxtvvHHWXXfd7L///nnnnXcq50yaNCnf+9730qhRo8qxPn365NVXX82sWbNqJAd80/3973/PVlttlZ/+9Kdp06ZNtthii1x99dVfe79rrLFGNtpoo1x33XWZO3duPv/88/zud79LmzZt0rNnzyR+94Vi2223XSZMmJDXXnstSfLcc8/lsccey+67717rx67O+ej33m+eBnUdAJbXhx9+mLPPPjtHHXVU5diMGTOq/JdUksrlLy9jB/6zJUuW5IQTTkjv3r2z6aabfq19LViwIAcddFD+53/+Jx07dsxbb7211JyvOm8rKiry2WefpWnTpl8rA6wKbrzxxjzzzDN56qmnamyfb731VpYsWZJzzz03l1xyScrLy3Paaadl1113zfPPP59GjRplxowZ6dy5c5Xt/v1/V//99jP4tnrrrbdy5ZVXZsiQITnllFPy1FNPZdCgQWnUqFEOPfTQ5d5vWVlZHnjggeyzzz5p0aJF6tWrlzZt2mT8+PGV557ffaGqoUOHpqKiIl27dk39+vWzePHinHPOOenXr1+tH7s656Pfe795XGnGSuncc89N8+bNKz/Tp0+vsr6ioiJ77rlnNtlkk/zmN7+pm5Cwiho4cGBefPHF3HjjjSVtt/vuu1ees926dUuSDBs2LBtvvHEOOeSQ2ogK3wrvvPNOjj/++Fx//fVp0qTJcu1jWefnkiVLsmjRolx66aXp06dPtt122/z5z3/O66+/vtSDxoGvtmTJkmy55ZY599xzs8UWW+Soo47KkUcemauuuqra+zjmmGOq/O6bJIVCIQMHDkybNm3y6KOPZvLkydlnn32y11575b333qutrwPfaDfddFOuv/763HDDDXnmmWdy7bXX5oILLsi1115b7X0s63zk28uVZqyUjjnmmOy///6Vy+3bt6/8+ZNPPskPf/jDtGjRIrfddlsaNmxYua5du3aZPHlylX3NnDmzch3wnx177LG5884788gjj2Tdddctadvf//73+eyzz5Kk8rx88MEH88ILL+Svf/1rklS+uWjNNdfMqaeemjPPPDPt2rWrPE+/NHPmzLRs2dK/tkGSKVOm5P3338+WW25ZObZ48eI88sgjufzyy7NgwYLUr1//P+5jWefn2muvnSTZZJNNKuettdZaWXPNNSv/seqrzs8v1wFfnEv/fh4lycYbb5xbbrml2vs466yz8qtf/arK2IMPPpg777wzs2bNSsuWLZMkV1xxRe6///5ce+21GTp0qN99ocivf/3rDB06NAceeGCSpHv37nn77bczYsSIal/5uazzsTqqcz76vfebR2nGSql169bLfJZSRUVF+vTpk8aNG+fvf//7Uv/i3qtXr5xzzjl5//3306ZNmyRfPLOlZcuWS/0yA/x/hUIhxx13XG677bY8/PDDS92OVR3rrLPOUmO33HJL5f9RT75481///v3z6KOPpkuXLkm+OG/vvvvuKtvdf//96dWrV8kZYFX0gx/8IC+88EKVscMPPzxdu3bNySef/F8Ls2TZ52fv3r2TJK+++mplSf7xxx/nww8/TKdOnZJ8cX6eeuqpWbRoUWXZdv/992ejjTZyayb8P717986rr75aZey1116rPI+qo02bNpW/u35p3rx5SbLU80Dr1auXJUuWJPG7LxSbN2/eUudM/fr1K8+Z6ljW+Vgd1Tkf/d77zaM0o858+umneeONNyqXp02blqlTp6Z169bp2LHjUvO/fO39vHnz8qc//SkVFRWpqKhI8sW/jNevXz+77bZbNtlkk/zsZz/L+eefnxkzZuS0007LwIED07hx4xX23eCbZuDAgbnhhhvyt7/9LS1atKh87kJ5eXnlv3rNmDEjM2bMqDxvX3jhhbRo0SIdO3b8yhcGfFmMfenDDz9M8sW/wLdq1SrJF1eWXn755TnppJPSv3//PPjgg7npppty11131cZXhW+cFi1aLPV8wdVWWy1rrLFG5fjynJ8bbrhh9t577xx//PEZM2ZMWrZsmWHDhqVr167ZaaedkiQHH3xwzjzzzAwYMCAnn3xyXnzxxVxyySW5+OKLa/EbwzfL4MGDs9122+Xcc8/N/vvvn8mTJ2fMmDEZM2ZM5ZyPP/4406dPz7vvvpsklSVbu3btvvKKsF69emX11VfPoYcemtNPPz1NmzbN1VdfnWnTpmXPPfdMEr/7QpG99tor55xzTjp27Jhu3brl2WefzUUXXZT+/ftXzlme8zFJpk+fXrnt4sWLM3Xq1CTJ+uuvn+bNm1frfPR77zdQHb+9k2+xhx56qJBkqc+hhx5a0vwkhWnTplXO++c//1nYfffdC02bNi2sueaahRNPPLGwaNGiFfOl4Bvqq86tsWPHVs4544wz/uuc/+bL83jWrFlLjW+++eaFRo0aFb7zne+UtE/4Ntpxxx0Lxx9/fOXy8p6fc+bMKfTv37/QqlWrQuvWrQv77rtvYfr06VXmPPfcc4Xtt9++0Lhx48I666xTGDlyZC18I/hmu+OOOwqbbrppoXHjxoWuXbsWxowZU2X92LFjl3mOnnHGGf9xv0899VRht912K7Ru3brQokWLwrbbblu4++67q8zxuy/8fxUVFYXjjz++0LFjx0KTJk0K3/nOdwqnnnpqYcGCBZVzlvd8PPTQQ5e53UMPPVQ5pzrno997v1nKCoX/94AZAAAAACCJt2cCAAAAwFKUZgAAAABQRGkGAAAAAEWUZgAAAABQRGkGAAAAAEWUZgAAAABQRGkGAAAAAEWUZgAAAABQRGkGAAAAAEWUZgAA3wAffPBBfvGLX6Rjx45p3Lhx2rVrlz59+uTxxx+v62gAAKukBnUdAACA/65v375ZuHBhrr322nznO9/JzJkzM2HChHz00Ue1cryFCxemUaNGtbJvAIBvAleaAQCs5GbPnp1HH3005513Xnbaaad06tQp3/3udzNs2LD8+Mc/rpxz9NFHp23btmnSpEk23XTT3HnnnZX7uOWWW9KtW7c0btw46623Xi688MIqx1hvvfVy9tln5+c//3latmyZo446Kkny2GOPZYcddkjTpk3ToUOHDBo0KHPnzl1xXx4AoI4ozQAAVnLNmzdP8+bNc/vtt2fBggVLrV+yZEl23333PP744/nTn/6Ul19+OSNHjkz9+vWTJFOmTMn++++fAw88MC+88EJ+85vfZPjw4Rk3blyV/VxwwQXZbLPN8uyzz2b48OF5880388Mf/jB9+/bN888/n7/85S957LHHcuyxx66Irw0AUKfKCoVCoa5DAADwn91yyy058sgj89lnn2XLLbfMjjvumAMPPDA9evTIfffdl9133z2vvPJKNtxww6W27devXz744IPcd999lWMnnXRS7rrrrrz00ktJvrjSbIsttshtt91WOeeII45I/fr187vf/a5y7LHHHsuOO+6YuXPnpkmTJrX4jQEA6pYrzQAAvgH69u2bd999N3//+9/zwx/+MA8//HC23HLLjBs3LlOnTs266667zMIsSV555ZX07t27yljv3r3z+uuvZ/HixZVjW221VZU5zz33XMaNG1d5pVvz5s3Tp0+fLFmyJNOmTav5LwkAsBLxIgAAgG+IJk2aZNddd82uu+6a4cOH54gjjsgZZ5yRX/3qVzWy/9VWW63K8qeffpqjjz46gwYNWmpux44da+SYAAArK6UZAMA31CabbJLbb789PXr0yP/5P/8nr7322jKvNtt4443z+OOPVxl7/PHHs+GGG1Y+92xZttxyy7z88stZf/31azw7AMDKzu2ZAAAruY8++ig777xz/vSnP+X555/PtGnTcvPNN+f888/P3nvvnR133DHf+9730rdv39x///2ZNm1a7rnnnowfPz5JcuKJJ2bChAk5++yz89prr+Xaa6/N5Zdf/l+vUDv55JPzxBNP5Nhjj83UqVPz+uuv529/+5sXAQAA3wquNAMAWMk1b94822yzTS6++OK8+eabWbRoUTp06JAjjzwyp5xySpIvXhTwq1/9KgcddFDmzp2b9ddfPyNHjkzyxRVjN910U04//fScffbZWXvttXPWWWflsMMO+4/H7dGjRyZOnJhTTz01O+ywQwqFQrp06ZIDDjigtr8yAECd8/ZMAAAAACji9kwAAAAAKKI0AwAAAIAiSjMAAAAAKKI0AwAAAIAiSjMAAAAAKKI0AwAAAIAiSjMAAAAAKKI0AwAAAIAiSjMAAAAAKKI0AwAAAIAiSjMAAAAAKPJ/AQvFT9eAdXb/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ss_1_20 = df[\"Spending Score (1-100)\"][(df[\"Spending Score (1-100)\"] >= 1) & (df[\"Spending Score (1-100)\"] <= 20)]\n",
    "ss_21_40 = df[\"Spending Score (1-100)\"][(df[\"Spending Score (1-100)\"] >= 21) & (df[\"Spending Score (1-100)\"] <= 40)]\n",
    "ss_41_60 = df[\"Spending Score (1-100)\"][(df[\"Spending Score (1-100)\"] >= 41) & (df[\"Spending Score (1-100)\"] <= 60)]\n",
    "ss_61_80 = df[\"Spending Score (1-100)\"][(df[\"Spending Score (1-100)\"] >= 61) & (df[\"Spending Score (1-100)\"] <= 80)]\n",
    "ss_81_100 = df[\"Spending Score (1-100)\"][(df[\"Spending Score (1-100)\"] >= 81) & (df[\"Spending Score (1-100)\"] <= 100)]\n",
    "\n",
    "ssx = [\"1-20\", \"21-40\", \"41-60\", \"61-80\", \"81-100\"]\n",
    "ssy = [len(ss_1_20.values), len(ss_21_40.values), len(ss_41_60.values), len(ss_61_80.values), len(ss_81_100.values)]\n",
    "\n",
    "plt.figure(figsize=(15, 6))\n",
    "sns.barplot(x=ssx, y=ssy, palette= \"rocket\")\n",
    "plt.title(\"Spending Scores\")\n",
    "plt.xlabel(\"Score\")\n",
    "plt.ylabel(\"Number of Customer Having the Score\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Relationship between number of customers and annual income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ai0_30 = df[\"Annual Income (k$)\"][(df[\"Annual Income (k$)\"] >= 0) & (df[\"Annual Income (k$)\"] <= 30)]\n",
    "ai31_60 = df[\"Annual Income (k$)\"][(df[\"Annual Income (k$)\"] >= 31) & (df[\"Annual Income (k$)\"] <= 60)]\n",
    "ai61_90 = df[\"Annual Income (k$)\"][(df[\"Annual Income (k$)\"] >= 61) & (df[\"Annual Income (k$)\"] <= 90)]\n",
    "ai91_120 = df[\"Annual Income (k$)\"][(df[\"Annual Income (k$)\"] >= 91) & (df[\"Annual Income (k$)\"] <= 120)]\n",
    "ai121_150 = df[\"Annual Income (k$)\"][(df[\"Annual Income (k$)\"] >= 121) & (df[\"Annual Income (k$)\"] <= 150)]\n",
    "\n",
    "aix = [\"$ 0 - 30,000\", \"$ 30,001 - 60,000\", \"$ 60,001 - 90,000\", \"$ 90,001 - 120,000\", \"$ 120,001 - 150,000\"]\n",
    "aiy = [len(ai0_30.values), len(ai31_60.values), len(ai61_90.values), len(ai91_120.values), len(ai121_150.values)]\n",
    "\n",
    "plt.figure(figsize=(15,6))\n",
    "sns.barplot(x=aix, y=aiy, palette=\"Spectral\")\n",
    "plt.title(\"Annual Incomes\")\n",
    "plt.xlabel(\"Income\")\n",
    "plt.ylabel(\"Number of Customer\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's consider the relationship between age and spending score and cluster the data\n",
    "\n",
    "Finding the optimal number of clusters that we need to create using Elbow method or Within Cluster Sum of Square (WCSS) method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0    Male   19                  15                      39\n",
       "1    Male   21                  15                      81\n",
       "2  Female   20                  16                       6\n",
       "3  Female   23                  16                      77\n",
       "4  Female   31                  17                      40"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[19, 39],\n",
       "       [21, 81],\n",
       "       [20,  6],\n",
       "       [23, 77],\n",
       "       [31, 40],\n",
       "       [22, 76],\n",
       "       [35,  6],\n",
       "       [23, 94],\n",
       "       [64,  3],\n",
       "       [30, 72],\n",
       "       [67, 14],\n",
       "       [35, 99],\n",
       "       [58, 15],\n",
       "       [24, 77],\n",
       "       [37, 13],\n",
       "       [22, 79],\n",
       "       [35, 35],\n",
       "       [20, 66],\n",
       "       [52, 29],\n",
       "       [35, 98],\n",
       "       [35, 35],\n",
       "       [25, 73],\n",
       "       [46,  5],\n",
       "       [31, 73],\n",
       "       [54, 14],\n",
       "       [29, 82],\n",
       "       [45, 32],\n",
       "       [35, 61],\n",
       "       [40, 31],\n",
       "       [23, 87],\n",
       "       [60,  4],\n",
       "       [21, 73],\n",
       "       [53,  4],\n",
       "       [18, 92],\n",
       "       [49, 14],\n",
       "       [21, 81],\n",
       "       [42, 17],\n",
       "       [30, 73],\n",
       "       [36, 26],\n",
       "       [20, 75],\n",
       "       [65, 35],\n",
       "       [24, 92],\n",
       "       [48, 36],\n",
       "       [31, 61],\n",
       "       [49, 28],\n",
       "       [24, 65],\n",
       "       [50, 55],\n",
       "       [27, 47],\n",
       "       [29, 42],\n",
       "       [31, 42],\n",
       "       [49, 52],\n",
       "       [33, 60],\n",
       "       [31, 54],\n",
       "       [59, 60],\n",
       "       [50, 45],\n",
       "       [47, 41],\n",
       "       [51, 50],\n",
       "       [69, 46],\n",
       "       [27, 51],\n",
       "       [53, 46],\n",
       "       [70, 56],\n",
       "       [19, 55],\n",
       "       [67, 52],\n",
       "       [54, 59],\n",
       "       [63, 51],\n",
       "       [18, 59],\n",
       "       [43, 50],\n",
       "       [68, 48],\n",
       "       [19, 59],\n",
       "       [32, 47],\n",
       "       [70, 55],\n",
       "       [47, 42],\n",
       "       [60, 49],\n",
       "       [60, 56],\n",
       "       [59, 47],\n",
       "       [26, 54],\n",
       "       [45, 53],\n",
       "       [40, 48],\n",
       "       [23, 52],\n",
       "       [49, 42],\n",
       "       [57, 51],\n",
       "       [38, 55],\n",
       "       [67, 41],\n",
       "       [46, 44],\n",
       "       [21, 57],\n",
       "       [48, 46],\n",
       "       [55, 58],\n",
       "       [22, 55],\n",
       "       [34, 60],\n",
       "       [50, 46],\n",
       "       [68, 55],\n",
       "       [18, 41],\n",
       "       [48, 49],\n",
       "       [40, 40],\n",
       "       [32, 42],\n",
       "       [24, 52],\n",
       "       [47, 47],\n",
       "       [27, 50],\n",
       "       [48, 42],\n",
       "       [20, 49],\n",
       "       [23, 41],\n",
       "       [49, 48],\n",
       "       [67, 59],\n",
       "       [26, 55],\n",
       "       [49, 56],\n",
       "       [21, 42],\n",
       "       [66, 50],\n",
       "       [54, 46],\n",
       "       [68, 43],\n",
       "       [66, 48],\n",
       "       [65, 52],\n",
       "       [19, 54],\n",
       "       [38, 42],\n",
       "       [19, 46],\n",
       "       [18, 48],\n",
       "       [19, 50],\n",
       "       [63, 43],\n",
       "       [49, 59],\n",
       "       [51, 43],\n",
       "       [50, 57],\n",
       "       [27, 56],\n",
       "       [38, 40],\n",
       "       [40, 58],\n",
       "       [39, 91],\n",
       "       [23, 29],\n",
       "       [31, 77],\n",
       "       [43, 35],\n",
       "       [40, 95],\n",
       "       [59, 11],\n",
       "       [38, 75],\n",
       "       [47,  9],\n",
       "       [39, 75],\n",
       "       [25, 34],\n",
       "       [31, 71],\n",
       "       [20,  5],\n",
       "       [29, 88],\n",
       "       [44,  7],\n",
       "       [32, 73],\n",
       "       [19, 10],\n",
       "       [35, 72],\n",
       "       [57,  5],\n",
       "       [32, 93],\n",
       "       [28, 40],\n",
       "       [32, 87],\n",
       "       [25, 12],\n",
       "       [28, 97],\n",
       "       [48, 36],\n",
       "       [32, 74],\n",
       "       [34, 22],\n",
       "       [34, 90],\n",
       "       [43, 17],\n",
       "       [39, 88],\n",
       "       [44, 20],\n",
       "       [38, 76],\n",
       "       [47, 16],\n",
       "       [27, 89],\n",
       "       [37,  1],\n",
       "       [30, 78],\n",
       "       [34,  1],\n",
       "       [30, 73],\n",
       "       [56, 35],\n",
       "       [29, 83],\n",
       "       [19,  5],\n",
       "       [31, 93],\n",
       "       [50, 26],\n",
       "       [36, 75],\n",
       "       [42, 20],\n",
       "       [33, 95],\n",
       "       [36, 27],\n",
       "       [32, 63],\n",
       "       [40, 13],\n",
       "       [28, 75],\n",
       "       [36, 10],\n",
       "       [36, 92],\n",
       "       [52, 13],\n",
       "       [30, 86],\n",
       "       [58, 15],\n",
       "       [27, 69],\n",
       "       [59, 14],\n",
       "       [35, 90],\n",
       "       [37, 32],\n",
       "       [32, 86],\n",
       "       [46, 15],\n",
       "       [29, 88],\n",
       "       [41, 39],\n",
       "       [30, 97],\n",
       "       [54, 24],\n",
       "       [28, 68],\n",
       "       [41, 17],\n",
       "       [36, 85],\n",
       "       [34, 23],\n",
       "       [32, 69],\n",
       "       [33,  8],\n",
       "       [38, 91],\n",
       "       [47, 16],\n",
       "       [35, 79],\n",
       "       [45, 28],\n",
       "       [32, 74],\n",
       "       [32, 18],\n",
       "       [30, 83]], dtype=int64)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x1 = df.loc[:, [\"Age\", \"Spending Score (1-100)\"]].values\n",
    "#x1 = df.iloc[:, [1,3]].values\n",
    "x1"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For each value of k we calculate WCSS which is the Within Cluster Sum of Squared distance between each point and the centroid in a cluster.\n",
    "\n",
    "Plotting WCSS with key value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# creating a blank list wcss\n",
    "wcss = []\n",
    "\n",
    "for k in range(1, 11):\n",
    "    kmeans = KMeans(n_clusters=k, init=\"k-means++\")\n",
    "    kmeans.fit(x1)\n",
    "    wcss.append(kmeans.inertia_)\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.grid()\n",
    "plt.plot(range(1,11), wcss, color=\"red\", marker = \"o\")\n",
    "plt.xlabel(\"K Value (Number of clusters)\")\n",
    "plt.ylabel(\"WCSS Values\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Forming Cluster\n",
    "\n",
    "Let's divide our data into 4 clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3 1 0 1 3 1 0 1 0 1 0 1 0 1 0 1 3 3 0 1 3 1 0 1 0 1 0 3 0 1 0 1 0 1 0 1 0\n",
      " 1 0 1 2 1 2 3 0 3 2 3 3 3 2 3 3 2 2 2 2 2 3 2 2 3 2 2 2 3 2 2 3 3 2 2 2 2\n",
      " 2 3 2 3 3 2 2 3 2 2 3 2 2 3 3 2 2 3 2 3 3 3 2 3 2 3 3 2 2 3 2 3 2 2 2 2 2\n",
      " 3 3 3 3 3 2 2 2 2 3 3 3 1 3 1 2 1 0 1 0 1 3 1 0 1 0 1 0 1 0 1 3 1 0 1 2 1\n",
      " 0 1 0 1 0 1 0 1 0 1 0 1 2 1 0 1 0 1 0 1 0 3 0 1 0 1 0 1 0 1 0 1 0 1 0 1 3\n",
      " 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1]\n"
     ]
    }
   ],
   "source": [
    "#Initialize the class object\n",
    "kmeans = KMeans(n_clusters=4)\n",
    "\n",
    "#predict the labels of clusters.\n",
    "label = kmeans.fit_predict(x1)\n",
    "\n",
    "print(label)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking the centroids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[43.29166667 15.02083333]\n",
      " [30.1754386  82.35087719]\n",
      " [55.70833333 48.22916667]\n",
      " [27.61702128 49.14893617]]\n"
     ]
    }
   ],
   "source": [
    "print(kmeans.cluster_centers_)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing clusters on a scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x1[:,0], x1[:,1], c=kmeans.labels_, cmap='rainbow')\n",
    "\n",
    "#Plotting cluster center\n",
    "plt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:,1], color='black')\n",
    "\n",
    "plt.title('Cluster of Customers')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Spending Score (1-100)')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly lets form clusters based on annual income and spending score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 15,  39],\n",
       "       [ 15,  81],\n",
       "       [ 16,   6],\n",
       "       [ 16,  77],\n",
       "       [ 17,  40],\n",
       "       [ 17,  76],\n",
       "       [ 18,   6],\n",
       "       [ 18,  94],\n",
       "       [ 19,   3],\n",
       "       [ 19,  72],\n",
       "       [ 19,  14],\n",
       "       [ 19,  99],\n",
       "       [ 20,  15],\n",
       "       [ 20,  77],\n",
       "       [ 20,  13],\n",
       "       [ 20,  79],\n",
       "       [ 21,  35],\n",
       "       [ 21,  66],\n",
       "       [ 23,  29],\n",
       "       [ 23,  98],\n",
       "       [ 24,  35],\n",
       "       [ 24,  73],\n",
       "       [ 25,   5],\n",
       "       [ 25,  73],\n",
       "       [ 28,  14],\n",
       "       [ 28,  82],\n",
       "       [ 28,  32],\n",
       "       [ 28,  61],\n",
       "       [ 29,  31],\n",
       "       [ 29,  87],\n",
       "       [ 30,   4],\n",
       "       [ 30,  73],\n",
       "       [ 33,   4],\n",
       "       [ 33,  92],\n",
       "       [ 33,  14],\n",
       "       [ 33,  81],\n",
       "       [ 34,  17],\n",
       "       [ 34,  73],\n",
       "       [ 37,  26],\n",
       "       [ 37,  75],\n",
       "       [ 38,  35],\n",
       "       [ 38,  92],\n",
       "       [ 39,  36],\n",
       "       [ 39,  61],\n",
       "       [ 39,  28],\n",
       "       [ 39,  65],\n",
       "       [ 40,  55],\n",
       "       [ 40,  47],\n",
       "       [ 40,  42],\n",
       "       [ 40,  42],\n",
       "       [ 42,  52],\n",
       "       [ 42,  60],\n",
       "       [ 43,  54],\n",
       "       [ 43,  60],\n",
       "       [ 43,  45],\n",
       "       [ 43,  41],\n",
       "       [ 44,  50],\n",
       "       [ 44,  46],\n",
       "       [ 46,  51],\n",
       "       [ 46,  46],\n",
       "       [ 46,  56],\n",
       "       [ 46,  55],\n",
       "       [ 47,  52],\n",
       "       [ 47,  59],\n",
       "       [ 48,  51],\n",
       "       [ 48,  59],\n",
       "       [ 48,  50],\n",
       "       [ 48,  48],\n",
       "       [ 48,  59],\n",
       "       [ 48,  47],\n",
       "       [ 49,  55],\n",
       "       [ 49,  42],\n",
       "       [ 50,  49],\n",
       "       [ 50,  56],\n",
       "       [ 54,  47],\n",
       "       [ 54,  54],\n",
       "       [ 54,  53],\n",
       "       [ 54,  48],\n",
       "       [ 54,  52],\n",
       "       [ 54,  42],\n",
       "       [ 54,  51],\n",
       "       [ 54,  55],\n",
       "       [ 54,  41],\n",
       "       [ 54,  44],\n",
       "       [ 54,  57],\n",
       "       [ 54,  46],\n",
       "       [ 57,  58],\n",
       "       [ 57,  55],\n",
       "       [ 58,  60],\n",
       "       [ 58,  46],\n",
       "       [ 59,  55],\n",
       "       [ 59,  41],\n",
       "       [ 60,  49],\n",
       "       [ 60,  40],\n",
       "       [ 60,  42],\n",
       "       [ 60,  52],\n",
       "       [ 60,  47],\n",
       "       [ 60,  50],\n",
       "       [ 61,  42],\n",
       "       [ 61,  49],\n",
       "       [ 62,  41],\n",
       "       [ 62,  48],\n",
       "       [ 62,  59],\n",
       "       [ 62,  55],\n",
       "       [ 62,  56],\n",
       "       [ 62,  42],\n",
       "       [ 63,  50],\n",
       "       [ 63,  46],\n",
       "       [ 63,  43],\n",
       "       [ 63,  48],\n",
       "       [ 63,  52],\n",
       "       [ 63,  54],\n",
       "       [ 64,  42],\n",
       "       [ 64,  46],\n",
       "       [ 65,  48],\n",
       "       [ 65,  50],\n",
       "       [ 65,  43],\n",
       "       [ 65,  59],\n",
       "       [ 67,  43],\n",
       "       [ 67,  57],\n",
       "       [ 67,  56],\n",
       "       [ 67,  40],\n",
       "       [ 69,  58],\n",
       "       [ 69,  91],\n",
       "       [ 70,  29],\n",
       "       [ 70,  77],\n",
       "       [ 71,  35],\n",
       "       [ 71,  95],\n",
       "       [ 71,  11],\n",
       "       [ 71,  75],\n",
       "       [ 71,   9],\n",
       "       [ 71,  75],\n",
       "       [ 72,  34],\n",
       "       [ 72,  71],\n",
       "       [ 73,   5],\n",
       "       [ 73,  88],\n",
       "       [ 73,   7],\n",
       "       [ 73,  73],\n",
       "       [ 74,  10],\n",
       "       [ 74,  72],\n",
       "       [ 75,   5],\n",
       "       [ 75,  93],\n",
       "       [ 76,  40],\n",
       "       [ 76,  87],\n",
       "       [ 77,  12],\n",
       "       [ 77,  97],\n",
       "       [ 77,  36],\n",
       "       [ 77,  74],\n",
       "       [ 78,  22],\n",
       "       [ 78,  90],\n",
       "       [ 78,  17],\n",
       "       [ 78,  88],\n",
       "       [ 78,  20],\n",
       "       [ 78,  76],\n",
       "       [ 78,  16],\n",
       "       [ 78,  89],\n",
       "       [ 78,   1],\n",
       "       [ 78,  78],\n",
       "       [ 78,   1],\n",
       "       [ 78,  73],\n",
       "       [ 79,  35],\n",
       "       [ 79,  83],\n",
       "       [ 81,   5],\n",
       "       [ 81,  93],\n",
       "       [ 85,  26],\n",
       "       [ 85,  75],\n",
       "       [ 86,  20],\n",
       "       [ 86,  95],\n",
       "       [ 87,  27],\n",
       "       [ 87,  63],\n",
       "       [ 87,  13],\n",
       "       [ 87,  75],\n",
       "       [ 87,  10],\n",
       "       [ 87,  92],\n",
       "       [ 88,  13],\n",
       "       [ 88,  86],\n",
       "       [ 88,  15],\n",
       "       [ 88,  69],\n",
       "       [ 93,  14],\n",
       "       [ 93,  90],\n",
       "       [ 97,  32],\n",
       "       [ 97,  86],\n",
       "       [ 98,  15],\n",
       "       [ 98,  88],\n",
       "       [ 99,  39],\n",
       "       [ 99,  97],\n",
       "       [101,  24],\n",
       "       [101,  68],\n",
       "       [103,  17],\n",
       "       [103,  85],\n",
       "       [103,  23],\n",
       "       [103,  69],\n",
       "       [113,   8],\n",
       "       [113,  91],\n",
       "       [120,  16],\n",
       "       [120,  79],\n",
       "       [126,  28],\n",
       "       [126,  74],\n",
       "       [137,  18],\n",
       "       [137,  83]], dtype=int64)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x2 = df.loc[:, [\"Annual Income (k$)\", \"Spending Score (1-100)\"]].values\n",
    "#x1 = df.iloc[:, [2,3]].values\n",
    "x2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "wcss = []\n",
    "for k in range(1, 11):\n",
    "    kmeans = KMeans(n_clusters=k, init=\"k-means++\")\n",
    "    kmeans.fit(x2)\n",
    "    wcss.append(kmeans.inertia_)\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.grid()\n",
    "plt.plot(range(1,11), wcss,  color=\"red\", marker = \"o\")\n",
    "plt.xlabel(\"K Value\")\n",
    "plt.ylabel(\"WCSS\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Forming Cluster\n",
    "\n",
    "Dividing data into 5 clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4 2 4\n",
      " 2 4 2 4 2 4 1 4 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 3 0 3 1 3 0 3 0 3 1 3 0 3 0 3 0 3 0 3 1 3 0 3 0 3\n",
      " 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0\n",
      " 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3]\n"
     ]
    }
   ],
   "source": [
    "kmeans = KMeans(n_clusters=5)\n",
    "\n",
    "label = kmeans.fit_predict(x2)\n",
    "\n",
    "print(label)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking the centroids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[88.2        17.11428571]\n",
      " [55.2962963  49.51851852]\n",
      " [25.72727273 79.36363636]\n",
      " [86.53846154 82.12820513]\n",
      " [26.30434783 20.91304348]]\n"
     ]
    }
   ],
   "source": [
    "print(kmeans.cluster_centers_)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing clusters using scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x2[:,0], x2[:,1], c=kmeans.labels_, cmap='rainbow')\n",
    "plt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:,1], color='black')\n",
    "\n",
    "plt.title('Cluster of Customers')\n",
    "plt.xlabel('Annual Income (k$)')\n",
    "plt.ylabel('Spending Score (1-100)')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets consider all of the 3 together i.e., annual income, age and spending score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 19,  15,  39],\n",
       "       [ 21,  15,  81],\n",
       "       [ 20,  16,   6],\n",
       "       [ 23,  16,  77],\n",
       "       [ 31,  17,  40],\n",
       "       [ 22,  17,  76],\n",
       "       [ 35,  18,   6],\n",
       "       [ 23,  18,  94],\n",
       "       [ 64,  19,   3],\n",
       "       [ 30,  19,  72],\n",
       "       [ 67,  19,  14],\n",
       "       [ 35,  19,  99],\n",
       "       [ 58,  20,  15],\n",
       "       [ 24,  20,  77],\n",
       "       [ 37,  20,  13],\n",
       "       [ 22,  20,  79],\n",
       "       [ 35,  21,  35],\n",
       "       [ 20,  21,  66],\n",
       "       [ 52,  23,  29],\n",
       "       [ 35,  23,  98],\n",
       "       [ 35,  24,  35],\n",
       "       [ 25,  24,  73],\n",
       "       [ 46,  25,   5],\n",
       "       [ 31,  25,  73],\n",
       "       [ 54,  28,  14],\n",
       "       [ 29,  28,  82],\n",
       "       [ 45,  28,  32],\n",
       "       [ 35,  28,  61],\n",
       "       [ 40,  29,  31],\n",
       "       [ 23,  29,  87],\n",
       "       [ 60,  30,   4],\n",
       "       [ 21,  30,  73],\n",
       "       [ 53,  33,   4],\n",
       "       [ 18,  33,  92],\n",
       "       [ 49,  33,  14],\n",
       "       [ 21,  33,  81],\n",
       "       [ 42,  34,  17],\n",
       "       [ 30,  34,  73],\n",
       "       [ 36,  37,  26],\n",
       "       [ 20,  37,  75],\n",
       "       [ 65,  38,  35],\n",
       "       [ 24,  38,  92],\n",
       "       [ 48,  39,  36],\n",
       "       [ 31,  39,  61],\n",
       "       [ 49,  39,  28],\n",
       "       [ 24,  39,  65],\n",
       "       [ 50,  40,  55],\n",
       "       [ 27,  40,  47],\n",
       "       [ 29,  40,  42],\n",
       "       [ 31,  40,  42],\n",
       "       [ 49,  42,  52],\n",
       "       [ 33,  42,  60],\n",
       "       [ 31,  43,  54],\n",
       "       [ 59,  43,  60],\n",
       "       [ 50,  43,  45],\n",
       "       [ 47,  43,  41],\n",
       "       [ 51,  44,  50],\n",
       "       [ 69,  44,  46],\n",
       "       [ 27,  46,  51],\n",
       "       [ 53,  46,  46],\n",
       "       [ 70,  46,  56],\n",
       "       [ 19,  46,  55],\n",
       "       [ 67,  47,  52],\n",
       "       [ 54,  47,  59],\n",
       "       [ 63,  48,  51],\n",
       "       [ 18,  48,  59],\n",
       "       [ 43,  48,  50],\n",
       "       [ 68,  48,  48],\n",
       "       [ 19,  48,  59],\n",
       "       [ 32,  48,  47],\n",
       "       [ 70,  49,  55],\n",
       "       [ 47,  49,  42],\n",
       "       [ 60,  50,  49],\n",
       "       [ 60,  50,  56],\n",
       "       [ 59,  54,  47],\n",
       "       [ 26,  54,  54],\n",
       "       [ 45,  54,  53],\n",
       "       [ 40,  54,  48],\n",
       "       [ 23,  54,  52],\n",
       "       [ 49,  54,  42],\n",
       "       [ 57,  54,  51],\n",
       "       [ 38,  54,  55],\n",
       "       [ 67,  54,  41],\n",
       "       [ 46,  54,  44],\n",
       "       [ 21,  54,  57],\n",
       "       [ 48,  54,  46],\n",
       "       [ 55,  57,  58],\n",
       "       [ 22,  57,  55],\n",
       "       [ 34,  58,  60],\n",
       "       [ 50,  58,  46],\n",
       "       [ 68,  59,  55],\n",
       "       [ 18,  59,  41],\n",
       "       [ 48,  60,  49],\n",
       "       [ 40,  60,  40],\n",
       "       [ 32,  60,  42],\n",
       "       [ 24,  60,  52],\n",
       "       [ 47,  60,  47],\n",
       "       [ 27,  60,  50],\n",
       "       [ 48,  61,  42],\n",
       "       [ 20,  61,  49],\n",
       "       [ 23,  62,  41],\n",
       "       [ 49,  62,  48],\n",
       "       [ 67,  62,  59],\n",
       "       [ 26,  62,  55],\n",
       "       [ 49,  62,  56],\n",
       "       [ 21,  62,  42],\n",
       "       [ 66,  63,  50],\n",
       "       [ 54,  63,  46],\n",
       "       [ 68,  63,  43],\n",
       "       [ 66,  63,  48],\n",
       "       [ 65,  63,  52],\n",
       "       [ 19,  63,  54],\n",
       "       [ 38,  64,  42],\n",
       "       [ 19,  64,  46],\n",
       "       [ 18,  65,  48],\n",
       "       [ 19,  65,  50],\n",
       "       [ 63,  65,  43],\n",
       "       [ 49,  65,  59],\n",
       "       [ 51,  67,  43],\n",
       "       [ 50,  67,  57],\n",
       "       [ 27,  67,  56],\n",
       "       [ 38,  67,  40],\n",
       "       [ 40,  69,  58],\n",
       "       [ 39,  69,  91],\n",
       "       [ 23,  70,  29],\n",
       "       [ 31,  70,  77],\n",
       "       [ 43,  71,  35],\n",
       "       [ 40,  71,  95],\n",
       "       [ 59,  71,  11],\n",
       "       [ 38,  71,  75],\n",
       "       [ 47,  71,   9],\n",
       "       [ 39,  71,  75],\n",
       "       [ 25,  72,  34],\n",
       "       [ 31,  72,  71],\n",
       "       [ 20,  73,   5],\n",
       "       [ 29,  73,  88],\n",
       "       [ 44,  73,   7],\n",
       "       [ 32,  73,  73],\n",
       "       [ 19,  74,  10],\n",
       "       [ 35,  74,  72],\n",
       "       [ 57,  75,   5],\n",
       "       [ 32,  75,  93],\n",
       "       [ 28,  76,  40],\n",
       "       [ 32,  76,  87],\n",
       "       [ 25,  77,  12],\n",
       "       [ 28,  77,  97],\n",
       "       [ 48,  77,  36],\n",
       "       [ 32,  77,  74],\n",
       "       [ 34,  78,  22],\n",
       "       [ 34,  78,  90],\n",
       "       [ 43,  78,  17],\n",
       "       [ 39,  78,  88],\n",
       "       [ 44,  78,  20],\n",
       "       [ 38,  78,  76],\n",
       "       [ 47,  78,  16],\n",
       "       [ 27,  78,  89],\n",
       "       [ 37,  78,   1],\n",
       "       [ 30,  78,  78],\n",
       "       [ 34,  78,   1],\n",
       "       [ 30,  78,  73],\n",
       "       [ 56,  79,  35],\n",
       "       [ 29,  79,  83],\n",
       "       [ 19,  81,   5],\n",
       "       [ 31,  81,  93],\n",
       "       [ 50,  85,  26],\n",
       "       [ 36,  85,  75],\n",
       "       [ 42,  86,  20],\n",
       "       [ 33,  86,  95],\n",
       "       [ 36,  87,  27],\n",
       "       [ 32,  87,  63],\n",
       "       [ 40,  87,  13],\n",
       "       [ 28,  87,  75],\n",
       "       [ 36,  87,  10],\n",
       "       [ 36,  87,  92],\n",
       "       [ 52,  88,  13],\n",
       "       [ 30,  88,  86],\n",
       "       [ 58,  88,  15],\n",
       "       [ 27,  88,  69],\n",
       "       [ 59,  93,  14],\n",
       "       [ 35,  93,  90],\n",
       "       [ 37,  97,  32],\n",
       "       [ 32,  97,  86],\n",
       "       [ 46,  98,  15],\n",
       "       [ 29,  98,  88],\n",
       "       [ 41,  99,  39],\n",
       "       [ 30,  99,  97],\n",
       "       [ 54, 101,  24],\n",
       "       [ 28, 101,  68],\n",
       "       [ 41, 103,  17],\n",
       "       [ 36, 103,  85],\n",
       "       [ 34, 103,  23],\n",
       "       [ 32, 103,  69],\n",
       "       [ 33, 113,   8],\n",
       "       [ 38, 113,  91],\n",
       "       [ 47, 120,  16],\n",
       "       [ 35, 120,  79],\n",
       "       [ 45, 126,  28],\n",
       "       [ 32, 126,  74],\n",
       "       [ 32, 137,  18],\n",
       "       [ 30, 137,  83]], dtype=int64)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x3 = df.loc[:, [\"Age\", \"Annual Income (k$)\", \"Spending Score (1-100)\"]].values\n",
    "#x3=df.iloc[:, 1:]\n",
    "x3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "wcss = []\n",
    "for k in range(1, 11):\n",
    "    kmeans = KMeans(n_clusters=k, init=\"k-means++\")\n",
    "    kmeans.fit(x3)\n",
    "    wcss.append(kmeans.inertia_)\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.grid()\n",
    "plt.plot(range(1,11), wcss, color=\"red\", marker = \"o\")\n",
    "plt.xlabel(\"K Value\")\n",
    "plt.ylabel(\"WCSS\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let optimal number of clusters is 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3 0 3\n",
      " 0 3 0 3 0 3 0 3 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 4 1 4 2 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 2 4 1 4 1 4\n",
      " 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1\n",
      " 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4]\n"
     ]
    }
   ],
   "source": [
    "kmeans = KMeans(n_clusters=5)\n",
    "\n",
    "label = kmeans.fit_predict(x3)\n",
    "\n",
    "print(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[25.52173913 26.30434783 78.56521739]\n",
      " [40.66666667 87.75       17.58333333]\n",
      " [43.08860759 55.29113924 49.56962025]\n",
      " [45.2173913  26.30434783 20.91304348]\n",
      " [32.69230769 86.53846154 82.12820513]]\n"
     ]
    }
   ],
   "source": [
    "print(kmeans.cluster_centers_)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 3 used variables here, and we have 3 axis so we need to plot a 3D graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure(figsize=(20, 10))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "ax.scatter(x3[:,0], x3[:,1], x3[:,2], c=kmeans.labels_, cmap='rainbow')\n",
    "ax.scatter(kmeans.cluster_centers_[:,0], kmeans.cluster_centers_[:,1], kmeans.cluster_centers_[:,2], s = 80, color = 'black', label = 'Centroid')\n",
    "ax.view_init(30, 185)\n",
    "\n",
    "plt.title('Cluster of Customers')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Annual Income (k$)')\n",
    "ax.set_zlabel('Spending Score (1-100)')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some of the customers have less salary but more spending\n",
    "\n",
    "Target audience should be the one maximum customers are included with decent salary and spending is also well\n",
    "\n",
    "So, the company will promote their products more with the customers included in this cluster than the customers included in any other clusters\n",
    "\n",
    "This is the most important intuitions which is extracted by a lot of companies to target their customers based on the available data"
   ]
  }
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