Digital Transformation [Banking].ipynb

{
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   "cell_type": "markdown",
   "id": "cbfb4fa5",
   "metadata": {},
   "source": [
    "# Digital Transformation [Banking]\n",
    "\n",
    "\n",
    "## Business Objective\n",
    "\n",
    "Bank XYZ has a growing customer base where the majority of them are liability customers (depositors) vs. borrowers (asset customers). The bank is interested in expanding the borrower’s base rapidly to bring in more business via loan interests.\n",
    "A campaign that the bank ran in the last quarter showed an average single-digit conversion rate. In the last town hall, the marketing head mentioned that digital transformation is the core strength of the business strategy, how to devise effective campaigns with better target marketing to increase the conversion ratio to double-digit with the same budget as per the last campaign.\n",
    "As a data scientist, you are asked to develop a machine learning model to identify potential borrowers to support focused marketing."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53d34ffa",
   "metadata": {},
   "source": [
    "## Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3d4409fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd #data manipulation\n",
    "import numpy as np #mathematical operations\n",
    "import matplotlib.pyplot as plt #visualisation\n",
    "%matplotlib inline\n",
    "import seaborn as sns #visualisation\n",
    "pd.set_option('display.max_rows',None) #display max rows\n",
    "pd.set_option('display.max_columns',None) #display max columns\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6078d82f",
   "metadata": {},
   "source": [
    "## Load the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8c9c1f88",
   "metadata": {},
   "outputs": [],
   "source": [
    "data1=pd.read_csv('Data1.csv') #read data1\n",
    "data2=pd.read_csv('Data2.csv') #read data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ce963140",
   "metadata": {},
   "outputs": [
    {
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       "      <th>CustomerSince</th>\n",
       "      <th>HighestSpend</th>\n",
       "      <th>ZipCode</th>\n",
       "      <th>HiddenScore</th>\n",
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      "text/plain": [
       "   ID  Age  CustomerSince  HighestSpend  ZipCode  HiddenScore  \\\n",
       "0   1   25              1            49    91107            4   \n",
       "1   2   45             19            34    90089            3   \n",
       "2   3   39             15            11    94720            1   \n",
       "3   4   35              9           100    94112            1   \n",
       "4   5   35              8            45    91330            4   \n",
       "\n",
       "   MonthlyAverageSpend  Level  \n",
       "0                  1.6      1  \n",
       "1                  1.5      1  \n",
       "2                  1.0      1  \n",
       "3                  2.7      2  \n",
       "4                  1.0      2  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.head() #top 5 values of data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e51d7a51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000, 8)"
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "data1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0efcd16e",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "   ID  Mortgage  Security  FixedDepositAccount  InternetBanking  CreditCard  \\\n",
       "0   1         0         1                    0                0           0   \n",
       "1   2         0         1                    0                0           0   \n",
       "2   3         0         0                    0                0           0   \n",
       "3   4         0         0                    0                0           0   \n",
       "4   5         0         0                    0                0           1   \n",
       "\n",
       "   LoanOnCard  \n",
       "0         NaN  \n",
       "1         NaN  \n",
       "2         NaN  \n",
       "3         NaN  \n",
       "4         NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.head()  #top 5 values of data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e4122d3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data2.merge(data1,how='left',on='ID') #Merging data2 and data1 on common column 'ID'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "612bd94a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000, 7)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.shape #Rows and Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2f031c39",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "   ID  Mortgage  Security  FixedDepositAccount  InternetBanking  CreditCard  \\\n",
       "0   1         0         1                    0                0           0   \n",
       "1   2         0         1                    0                0           0   \n",
       "2   3         0         0                    0                0           0   \n",
       "3   4         0         0                    0                0           0   \n",
       "4   5         0         0                    0                0           1   \n",
       "\n",
       "   LoanOnCard  Age  CustomerSince  HighestSpend  ZipCode  HiddenScore  \\\n",
       "0         NaN   25              1            49    91107            4   \n",
       "1         NaN   45             19            34    90089            3   \n",
       "2         NaN   39             15            11    94720            1   \n",
       "3         NaN   35              9           100    94112            1   \n",
       "4         NaN   35              8            45    91330            4   \n",
       "\n",
       "   MonthlyAverageSpend  Level  \n",
       "0                  1.6      1  \n",
       "1                  1.5      1  \n",
       "2                  1.0      1  \n",
       "3                  2.7      2  \n",
       "4                  1.0      2  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head() #top 5 values after merging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "db872476",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 5000 entries, 0 to 4999\n",
      "Data columns (total 14 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   ID                   5000 non-null   int64  \n",
      " 1   Mortgage             5000 non-null   int64  \n",
      " 2   Security             5000 non-null   int64  \n",
      " 3   FixedDepositAccount  5000 non-null   int64  \n",
      " 4   InternetBanking      5000 non-null   int64  \n",
      " 5   CreditCard           5000 non-null   int64  \n",
      " 6   LoanOnCard           4980 non-null   float64\n",
      " 7   Age                  5000 non-null   int64  \n",
      " 8   CustomerSince        5000 non-null   int64  \n",
      " 9   HighestSpend         5000 non-null   int64  \n",
      " 10  ZipCode              5000 non-null   int64  \n",
      " 11  HiddenScore          5000 non-null   int64  \n",
      " 12  MonthlyAverageSpend  5000 non-null   float64\n",
      " 13  Level                5000 non-null   int64  \n",
      "dtypes: float64(2), int64(12)\n",
      "memory usage: 585.9 KB\n"
     ]
    }
   ],
   "source": [
    "data.info() #checking type of data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e20e13c",
   "metadata": {},
   "outputs": [
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       "      <th>count</th>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.00000</td>\n",
       "      <td>5000.000000</td>\n",
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       "      <td>4980.000000</td>\n",
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       "      <td>5000.000000</td>\n",
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       "      <td>2500.500000</td>\n",
       "      <td>56.498800</td>\n",
       "      <td>0.104400</td>\n",
       "      <td>0.06040</td>\n",
       "      <td>0.596800</td>\n",
       "      <td>0.294000</td>\n",
       "      <td>0.096386</td>\n",
       "      <td>45.338400</td>\n",
       "      <td>20.104600</td>\n",
       "      <td>73.774200</td>\n",
       "      <td>93152.503000</td>\n",
       "      <td>2.396400</td>\n",
       "      <td>1.937938</td>\n",
       "      <td>1.881000</td>\n",
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       "      <th>std</th>\n",
       "      <td>1443.520003</td>\n",
       "      <td>101.713802</td>\n",
       "      <td>0.305809</td>\n",
       "      <td>0.23825</td>\n",
       "      <td>0.490589</td>\n",
       "      <td>0.455637</td>\n",
       "      <td>0.295149</td>\n",
       "      <td>11.463166</td>\n",
       "      <td>11.467954</td>\n",
       "      <td>46.033729</td>\n",
       "      <td>2121.852197</td>\n",
       "      <td>1.147663</td>\n",
       "      <td>1.747659</td>\n",
       "      <td>0.839869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>9307.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1250.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>91911.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2500.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>93437.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3750.250000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>94608.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5000.000000</td>\n",
       "      <td>635.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>224.000000</td>\n",
       "      <td>96651.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                ID     Mortgage     Security  FixedDepositAccount  \\\n",
       "count  5000.000000  5000.000000  5000.000000           5000.00000   \n",
       "mean   2500.500000    56.498800     0.104400              0.06040   \n",
       "std    1443.520003   101.713802     0.305809              0.23825   \n",
       "min       1.000000     0.000000     0.000000              0.00000   \n",
       "25%    1250.750000     0.000000     0.000000              0.00000   \n",
       "50%    2500.500000     0.000000     0.000000              0.00000   \n",
       "75%    3750.250000   101.000000     0.000000              0.00000   \n",
       "max    5000.000000   635.000000     1.000000              1.00000   \n",
       "\n",
       "       InternetBanking   CreditCard   LoanOnCard          Age  CustomerSince  \\\n",
       "count      5000.000000  5000.000000  4980.000000  5000.000000    5000.000000   \n",
       "mean          0.596800     0.294000     0.096386    45.338400      20.104600   \n",
       "std           0.490589     0.455637     0.295149    11.463166      11.467954   \n",
       "min           0.000000     0.000000     0.000000    23.000000      -3.000000   \n",
       "25%           0.000000     0.000000     0.000000    35.000000      10.000000   \n",
       "50%           1.000000     0.000000     0.000000    45.000000      20.000000   \n",
       "75%           1.000000     1.000000     0.000000    55.000000      30.000000   \n",
       "max           1.000000     1.000000     1.000000    67.000000      43.000000   \n",
       "\n",
       "       HighestSpend       ZipCode  HiddenScore  MonthlyAverageSpend  \\\n",
       "count   5000.000000   5000.000000  5000.000000          5000.000000   \n",
       "mean      73.774200  93152.503000     2.396400             1.937938   \n",
       "std       46.033729   2121.852197     1.147663             1.747659   \n",
       "min        8.000000   9307.000000     1.000000             0.000000   \n",
       "25%       39.000000  91911.000000     1.000000             0.700000   \n",
       "50%       64.000000  93437.000000     2.000000             1.500000   \n",
       "75%       98.000000  94608.000000     3.000000             2.500000   \n",
       "max      224.000000  96651.000000     4.000000            10.000000   \n",
       "\n",
       "             Level  \n",
       "count  5000.000000  \n",
       "mean      1.881000  \n",
       "std       0.839869  \n",
       "min       1.000000  \n",
       "25%       1.000000  \n",
       "50%       2.000000  \n",
       "75%       3.000000  \n",
       "max       3.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe() #calculating all aggrigate operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "538d1f19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000, 14)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape #checking shpe of dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8edd86d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                      0\n",
       "Mortgage                0\n",
       "Security                0\n",
       "FixedDepositAccount     0\n",
       "InternetBanking         0\n",
       "CreditCard              0\n",
       "LoanOnCard             20\n",
       "Age                     0\n",
       "CustomerSince           0\n",
       "HighestSpend            0\n",
       "ZipCode                 0\n",
       "HiddenScore             0\n",
       "MonthlyAverageSpend     0\n",
       "Level                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum() #checking null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "46b1bc77",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['LoanOnCard'].fillna(data['LoanOnCard'].median(),inplace=True) #imuting null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8fd80083",
   "metadata": {
    "scrolled": true
   },
   "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>ID</th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Security</th>\n",
       "      <th>FixedDepositAccount</th>\n",
       "      <th>InternetBanking</th>\n",
       "      <th>CreditCard</th>\n",
       "      <th>LoanOnCard</th>\n",
       "      <th>Age</th>\n",
       "      <th>CustomerSince</th>\n",
       "      <th>HighestSpend</th>\n",
       "      <th>ZipCode</th>\n",
       "      <th>HiddenScore</th>\n",
       "      <th>MonthlyAverageSpend</th>\n",
       "      <th>Level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>49</td>\n",
       "      <td>91107</td>\n",
       "      <td>4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45</td>\n",
       "      <td>19</td>\n",
       "      <td>34</td>\n",
       "      <td>90089</td>\n",
       "      <td>3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>94720</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35</td>\n",
       "      <td>9</td>\n",
       "      <td>100</td>\n",
       "      <td>94112</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>91330</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  Mortgage  Security  FixedDepositAccount  InternetBanking  CreditCard  \\\n",
       "0   1         0         1                    0                0           0   \n",
       "1   2         0         1                    0                0           0   \n",
       "2   3         0         0                    0                0           0   \n",
       "3   4         0         0                    0                0           0   \n",
       "4   5         0         0                    0                0           1   \n",
       "\n",
       "   LoanOnCard  Age  CustomerSince  HighestSpend  ZipCode  HiddenScore  \\\n",
       "0         0.0   25              1            49    91107            4   \n",
       "1         0.0   45             19            34    90089            3   \n",
       "2         0.0   39             15            11    94720            1   \n",
       "3         0.0   35              9           100    94112            1   \n",
       "4         0.0   35              8            45    91330            4   \n",
       "\n",
       "   MonthlyAverageSpend  Level  \n",
       "0                  1.6      1  \n",
       "1                  1.5      1  \n",
       "2                  1.0      1  \n",
       "3                  2.7      2  \n",
       "4                  1.0      2  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head() #top 5 values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0cb031a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                     0\n",
       "Mortgage               0\n",
       "Security               0\n",
       "FixedDepositAccount    0\n",
       "InternetBanking        0\n",
       "CreditCard             0\n",
       "LoanOnCard             0\n",
       "Age                    0\n",
       "CustomerSince          0\n",
       "HighestSpend           0\n",
       "ZipCode                0\n",
       "HiddenScore            0\n",
       "MonthlyAverageSpend    0\n",
       "Level                  0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum() #checking null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "018f76d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().sum() #checking for duplicated values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "65666522",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['ID','ZipCode','Age','InternetBanking','FixedDepositAccount'],axis=1,inplace=True) #dropping unnecessary features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c36a589",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9417da8d",
   "metadata": {},
   "source": [
    "### Heat Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d93bd330",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x2000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "sns.heatmap(data.corr(),annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d253a174",
   "metadata": {},
   "source": [
    "We observe from heat map that,\n",
    "\n",
    "1.HighestSpend is moderatly corelated with LoanOnCard and MonthlyAverageSpend."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d926350b",
   "metadata": {},
   "source": [
    "### Count Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8b9061b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in data.columns:\n",
    "    plt.figure(figsize=(10,10))\n",
    "    sns.countplot(x=i, data=data)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc07fdae",
   "metadata": {},
   "source": [
    "From the above visualisation we observe that,\n",
    "\n",
    "1.Majority of people don't have security(i.e 4000+).\n",
    "\n",
    "2.3500 people don,t have Creditcard.\n",
    "\n",
    "4.4000+ people don't have Loanoncard.\n",
    "\n",
    "5.Hidden Score count for each category,\n",
    "\n",
    "a)1 count is 1400+ \n",
    "\n",
    "b)2 count is 1200+\n",
    "\n",
    "c)3 count is 1000 \n",
    "\n",
    "d)4 is 1200\n",
    "\n",
    "6)Level count for each category,\n",
    "\n",
    "a)1 count is 2000+.\n",
    "\n",
    "b)2 count is 1250+.\n",
    "\n",
    "c)3 xount is 1500."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b097ff2a",
   "metadata": {},
   "source": [
    "### Box Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fa394527",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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PjiVLlsTRRx9drdEHlb78Th933HGxZs2a+Ne//tX92DPPPBN1dXXR2trar/MOVn1Z53Xr1kVdXc9dyZAhQyLiv//C5X9Xk31hv53+uBWbvkJz0003laVLl5YLLrigDBs2rKxataqUUsrFF19cvvKVr3Rvv+mrHd/97nfL0qVLy0033eRrjtuht+t82223lfr6+jJjxozywgsvdN9ee+21Wv0Ig0Zv1/rtfIth+/R2nTs6Okpra2s5/fTTy9NPP10efvjhctBBB5Wzzz67Vj/CoNDbdZ41a1apr68vM2fOLM8++2x55JFHyrhx48r48eNr9SMMCh0dHWXx4sVl8eLFJSLKtGnTyuLFi7u/TjoQ9oVVD4RSSpkxY0YZOXJkaWhoKEcddVR5+OGHu58788wzywknnNBj+4ceeqh8+MMfLg0NDWX//fcvP/3pT6s88eDUm3U+4YQTSkSk25lnnln9wQeh3v5Ob04gbL/ernN7e3uZOHFiaW5uLq2treXCCy8s69atq/LUg09v13n69OllzJgxpbm5uYwYMaJ86UtfKs8//3yVpx5cHnzwwW3+P3cg7Atd7hkASFyLAQBIBAIAkAgEACARCABAIhAAgEQgAACJQAAAEoEAACQCAd6jKpVK3H333RERsWrVqqhUKrFkyZKazrQl+++/f/z4xz+u9RjwniMQYAB58cUX4zvf+U6MGjUqGhsbo62tLU499dT43e9+16/v29bWFi+88EIcfvjhERHx0EMPRaVSiddee23AzAhUV1Uv9wxs3apVq+K4446LXXbZJa655po44ogjYsOGDTF//vw499xz469//Wt6zYYNG96VK7kNGTIk9t57736ZcXts3LgxKpVKuiogUDv+NsIAMWnSpKhUKvHkk0/G6aefHqNHj47DDjssLrzwwnj88ccj4q2PBW644Yb41Kc+FcOGDYsrr7wyIiJ++9vfxtixY6OpqSlGjRoVU6ZMic7Ozu4/e/ny5fHRj340mpqaYsyYMemysZt/xLBq1ar42Mc+FhERu+66a1QqlTjrrLO2e8aIiGnTpsUHP/jBGDZsWLS1tcWkSZN6XHb55ptvjl122SXuueeeGDNmTDQ2NsZzzz0XL730Upx66qnR3NwcBxxwQMyePbtf1hp4Z44gwADw6quvxrx58+Kqq66KYcOGped32WWX7v+ePHlyTJ06Na677roYMmRIzJ8/P7785S/H9OnT4/jjj49nn302vvnNb3Zv29XVFZ/97Gdjjz32iMcffzzWrl0bF1xwwVZnaWtrizlz5sTnPve5WLZsWbS0tERzc3OvZqyrq4vp06fH/vvvHytXroxJkybFRRddFDNnzuzeZt26dTF16tT4+c9/Hrvvvnvsueee8fnPfz5Wr14dv//976OhoSHOO++8eOmll3q/oMD/rl+vFQlslyeeeKJERLnrrru2uV1ElAsuuKDHY8cff3y5+uqrezx26623lhEjRpRSSpk/f34ZMmRIWb16dffz9913X4mIMnfu3FJKKStXriwRURYvXlxK+e+laP/5z3/2esYt+dWvflV233337vuzZs0qEVGWLFnS/diyZctKRJTHH3+8+7H29vYSEeW6667r9XsC/xtHEGAAKP9/1fVKpfKO244bN67H/UWLFsWf/vSnuOqqq7of27hxY7z55puxbt26aG9vj/322y9aW1u7nz/22GP7dcYHH3wwrr766li6dGmsXbs2Ojs7480334w33nij++hDQ0NDHHHEEd2vaW9vj/r6+h4/3yGHHNLjyARQPc5BgAHgoIMOikqlEu3t7e+47dsP73d1dcWUKVNiyZIl3bennnoqli9fHk1NTd079s1tz06+rzM+99xzcfLJJ8fhhx8ec+bMiUWLFsWMGTMi4q2TKjdpbm7uMUdvAgTofwIBBoDddtstTjrppJgxY0a88cYb6fktfd1wk6OOOiqWLVsWH/jAB9Ktrq4uxowZE3/7299izZo13a957LHHtjlPQ0NDRLx1JKK3My5cuDA6Ozvj2muvjWOOOSZGjx7d47235tBDD43Ozs5YuHBh92PLli3b5s8O9B+BAAPEzJkzY+PGjTF+/PiYM2dOLF++PNrb22P69Onb/Ejg8ssvj1tuuSWuuOKKePrpp6O9vT3uuOOOuOyyyyIiYuLEiXHwwQfHV7/61fjLX/4SCxYsiEsvvXSbs4wcOTIqlUrcc8898Y9//KP7GwjbM+OBBx4YnZ2dcf3118eKFSvi1ltvjRtuuOEdf/6DDz44PvnJT8Y3vvGNeOKJJ2LRokVx9tlnR3Nz8/YuIfBuqu0pEMDm1qxZU84999wycuTI0tDQUPbdd99y2mmnlQcffLCUUnqcWLi5efPmlQkTJpTm5ubS0tJSxo8fX372s591P79s2bLykY98pDQ0NJTRo0eXefPmbfMkxVJK+cEPflD23nvvUqlUyplnnrndM5ZSyrRp08qIESNKc3NzOemkk8ott9zS46THWbNmleHDh6ef44UXXiinnHJKaWxsLPvtt1+55ZZbysiRI52kCDVQKWULH1ACAO9pPmIAABKBAAAkAgEASAQCAJAIBAAgEQgAQCIQAIBEIAAAiUAAABKBAAAkAgEASP4PhxZsnC/ipNYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting boxplot for each feature\n",
    "for i in data.columns:\n",
    "    sns.boxplot(data[i])\n",
    "    plt.xlabel(i)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41426f84",
   "metadata": {},
   "source": [
    "From the above visualisation we observe that,\n",
    "\n",
    "1.Mortgage,HighestSpend,MonthlyAverageSpend has outliers.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e2a835c",
   "metadata": {},
   "source": [
    "### Capping for outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dd3a7ab4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the columns with outliers\n",
    "columns_with_outliers=['Mortgage','HighestSpend','MonthlyAverageSpend']\n",
    "# Loop through each column and cap the outliers\n",
    "for column_name in columns_with_outliers:\n",
    "    Q1 = data[column_name].quantile(0.25)\n",
    "    Q3 = data[column_name].quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    lower_bound = Q1 - 1.5*IQR\n",
    "    upper_bound = Q3 + 1.5*IQR\n",
    "    data[column_name] = data[column_name].clip(lower_bound, upper_bound)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "970efa31",
   "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>Mortgage</th>\n",
       "      <th>Security</th>\n",
       "      <th>CreditCard</th>\n",
       "      <th>LoanOnCard</th>\n",
       "      <th>CustomerSince</th>\n",
       "      <th>HighestSpend</th>\n",
       "      <th>HiddenScore</th>\n",
       "      <th>MonthlyAverageSpend</th>\n",
       "      <th>Level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19</td>\n",
       "      <td>34.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>45.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mortgage  Security  CreditCard  LoanOnCard  CustomerSince  HighestSpend  \\\n",
       "0       0.0         1           0         0.0              1          49.0   \n",
       "1       0.0         1           0         0.0             19          34.0   \n",
       "2       0.0         0           0         0.0             15          11.0   \n",
       "3       0.0         0           0         0.0              9         100.0   \n",
       "4       0.0         0           1         0.0              8          45.0   \n",
       "\n",
       "   HiddenScore  MonthlyAverageSpend  Level  \n",
       "0            4                  1.6      1  \n",
       "1            3                  1.5      1  \n",
       "2            1                  1.0      1  \n",
       "3            1                  2.7      2  \n",
       "4            4                  1.0      2  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6246b5c8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting boxplot for each feature\n",
    "for i in data.columns:\n",
    "    sns.boxplot(data[i])\n",
    "    plt.xlabel(i)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a101bec",
   "metadata": {},
   "source": [
    "we observe that,There are no outliers after capping."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3350b9b",
   "metadata": {},
   "source": [
    "### Hist Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f3ca5fe3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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WRCgVAgSh6y6niy2X0FpfBmU3u6X6giAISInWISVah6dnJuHLszV4MysfXxU3wgA1DpyuxsGzNUgM90NKtA6ROq8rvmYiT+U2Y3bsdjv++c9/oqmpCePGjUNRUREqKiowY8YM1zlarRYZGRnIycnBggULkJubC5vN1uGcqKgopKSkICcnp8uwY7FYYLH80BRuNBp774URUZdEUcRXZ2uxOacY+05Woq1RBUE+atyZGonbkyMxZmAw1H24towgCFAp5feBr1IqMDkpHLqmILz/9D2YtWIrLlp9UNtkRWFFIworGhHso0FydACGRQbAm609JCOSh538/HyMGzcOLS0t8PPzw44dOzB8+HDk5OQAAPT6jr+J6fV6XLhwAQBQUVEBjUaDoKCgy86pqKjo8muuXr0aK1eu7OFXQkTXShRFHDhdjdf2nsHRkgbX8VsSgvHgmDjMTI6AFz9se42jxYTB/g5kDI5DhbEFBZeMOF3ZiLpmK748U4Ocs7UYFO6LlLZB1WztIU8nedhJSkpCXl4eGhoa8MEHH2Du3LnIzs52Pf7Tf2SiKF71H97Vzlm2bBmWLFnium80GhEbG9vNV0BE10oURew7WYXX9p7B9xcNAACtSoH/MzoWD4+Lx+Bwf4kr7F8EQUCkzhuROm9MHBKKUxWNKCgzorrRgtOVJpyuNEHnrUZKlLO1x1cr+UcGUbdI/pOr0WhcA5TT09Nx+PBhvPrqq3j22WcBOFtvIiMjXedXVVW5WnsiIiJgtVpRX1/foXWnqqoK48eP7/JrarVaaLXa3ng5RNSFvNIGvPjpCRwurgcAeKuVeGhsHB6ZOBDh/l4SV0dalRKpMYFIjQlEpbEFBWUGnK4wwWC24atzzmntCaG+SInWIS7YBwq29pAHkTzs/JQoirBYLEhISEBERASysrIwatQoAIDVakV2djb+9Kc/AQDS0tKgVquRlZWFOXPmAADKy8tRUFCAl19+WbLXQEQ/uFjfjD/vOoV/55UBcK72O3f8ADwyYSBC/fhLhzvSB3hBH+CFCYPDcLqqEccvGVFhbMG56iacq26Cv5cKyVEBSI7Uwc/L7T5GiC4j6U/pc889h8zMTMTGxqKxsRHbt2/HgQMHsHPnTgiCgMWLF2PVqlVITExEYmIiVq1aBR8fHzzwwAMAAJ1Oh/nz52Pp0qUICQlBcHAwnnrqKYwYMcI1O4uIpGG22vH6/jN488siWFsdEATg/ptj8NSMJETo2JLjCTQqBVKidEiJ0qHGZEHBJQNOVjSisaUVh87X4ZvzdYgL8cGgUD9or317L6I+J2nYqaysxMMPP4zy8nLodDqkpqZi586dmD59OgDgmWeegdlsxmOPPeZaVHD37t2uNXYA4JVXXoFKpcKcOXNciwpu3ryZa+wQSSjrRCVWfHwclxrMAIBxA0Ow/M5hSInWSVwZdVeonxaTksJx2+BQnK0yIb/MgLKGFlyobW7bHkODyHmvYlt+I5r9a5Aaq0PAVbbAIOorkoadTZs2XfFxQRCwYsUKrFixostzvLy8sG7dOqxbt66HqyOi61Va14yVn5zAnsJKAEB0oDf+cNdwzBiu54wemVApFRgaGYChkQGob7LibLUJRTVNKDeYodEPwr8KTfhX4TcQBGBQmB9GxgRiRHQAYoJ8EB3kjegg7+sKQQ6HiEZLK4xm52aojS02GNv/bDtmbLHB0uqAQnBu9eHnpUKAlxoROi/EBHkjIdT3qnuPkbyxs5WIbpi11YE3vzyPdfvOoMXmgEoh4JGJA7FoymD4aPjfjFwF+Wow2jcYowcE49zJ49j8t3W497HlKDYJKK0z42yVCWerTPjgu47P828LI15qBbzUSmhVCqiUClhsdlhaHWix2dFic6DJ0opGy433jwkCkBDqi5tiA5ExJAwZQ8IQ6NM323mQe+D/QkR0Q3LO1eD3HxXgXHUTAGDswGD81+wUJOo5jbw/0SqBpuP78R9j/xs333wzakwWfF/agLzSBpyubMSlBjMu1ZtR39zeQnN9IUarUsDfS40Ab+d2HQFtgan9vpdKAYcI2OwONFpaYWi2odxgRmm9GdWNFpyvbsL56iZ8+N0lKBUCJieFIT3YBgh9t2AlSYdhh/odURThEOHWy/x7gqrGFqz6tBAftc2yCvXT4Hd3Dsfsm6LYZUUI9dNi6jA9pg7ruDBsk6UV5QYzTBZ7WwuOsxWn1eGAl0rpbOlRK+ClUsJXq0SAtxr+XipoVd0fh1ljsiD/kgHfnK/D/pNVOFXZiD2FVdgDIOqRv6LYpECUQ+z2jvTk/hh2SHYqDC3Iv2TAiTIjLtQ1obSuGdWNFtQ329BkaXVt9KhUCNCqFAj0ViPYT4OIAG/EBfsgIdQHw6MCMDSCi6h1xu4Qse2bC3h51yk0trRCEICHx8Zj6Ywk6Lw5LoKuzFer6vPFI0P9tJicFI7JSeH4z8yhOFtlwj+PlOK9b4phDIpCbh1w7psLmJIUjthgnz6tjfoG/ycnj2d3iCg3Cwie8Rge+6wKFabya35es9WOZqsdZQbnkvk/JgjAsIgAjBkYjAmJoRg/KLTfb2FQcMmA5TvyXasfp8bo8MI9KUiNCZS2MKLrMDjcD8vuGIaM0Cbc/vgqRE77NRqabfjw6CUMjfDHpCFh3AleZhh2yGPVN1vxfWkDTleaYLap4T/qDlSY7FAIQGK4P5KjAzAozA+xwT6ICPBCkI8afl4qqJUKKAUBNrsDZpsd9c021DVZcKmhBSW1TThbZcKJciMqjRacKDfiRLkRb39VDC+1AhMTw3DfzTGYMjQcGlX/6etvbLFhTdZpbMkphkME/LUqPHN7Eh4YE8/uQPJYXioFGg/vwLz/+zAuIAzfX3SuI1TWYMYdIyKhD+B6UHLBsEMep8ZkwaHzta4BsQCgVYioOfIpVj/xMB6Yfgv8rqP7KT6k8+OVxhYcLq7D1+dqsf9kFcoMLdh9ohK7T1QiyEeN2TdF42dpMUiOCpDtGBVRFPF5QQVWfnIclUYLAODukVH43Z3DEM4PApIJtQKYlBiOpAh/7CyogLGlFf9zpBRThoYjOYprQ8kBww55jGarc9XWgksGiG3HBoT4YGRsIBS1xVi7+q9If+mR6wo6V6IP8MKs1CjMSo2CKIooLG/Ev7+/hB3fXUJVowWbc4qxOacYo+ICsWDiQEwfHiGrVo6S2mb8/t8FyD5dDcD5vf6ve1IwITFM4sqIekekzhsP3BKHrMJKnKtuwp7CKphaWnFLQrBsf6HpLxh2yCOcqzZhb2EVzDY7AGBwmB/GDgxGSNveShfrevfrC4KA4VEBGB4VgKdnJOHg2Rr8K/cidh+vxNGSBjy69TsMCPHB/AkD8fO0GI8e29Nis+PNL87j9f1nYWl1QKNU4LeTBuG3kwZ59OsiuhZatRJ3jojE1+drcbi4HoeK6tBstWNSUhgDjwdj2CG31upwIPtUNQrKnIOHQ3w1mJwUjuggb8lqUikVmJQUjklJ4ahutGBLTjHeOXQBxbXN+P1HBVibdRqPTByIh8fGe9RsLlEUset4JV787ARK65zbPNw6OAT/NTsFA8P8JK6OqO8IgoDxg0Lhp1Vh/6lqHLtkgEIhYGJiKAOPh/Kc/4mp32m2tuJ/j5Wj3NACAEiLC8LYQcFQKdxnYHCYvxZPzUzCbycNwj+PlOLvB4twsd6Mlz4/ib9ln8NvJgzE3PEDeqxrrbecrDDij5+cQM65WgCAPkCL5+4YhrtHcs0c6r9SYwKhUiiQVViJvNIGqBQCbh0cKnVZ1A3u/T8w9Vv1zVbsOHoJjS2t0KgUuCMlAvEhvlKX1SVfrQrzbk3Ag2Pj8dHRS1i//yyKa5vx512n8OaX5zH/1gTMvXWA222MWNZgxmt7z+B/jpTCITp3uV4wcSAezRjkUa1SRL1leFQAWh0O7D9VjSMX6uHvpeJSCx6I/5uR26lvsuKD7y6iyWqHzluNu0dGIdjXM/axUSsV+Hl6LO4dFY1PjpVh3b6zOF/dhL9kncabX57Hr29LwK9uTZB88b0akwVv7D+HrYcuwGp3AADuGBGBZZnDuKga0U+kxgSixebA1+drceB0NXTearf+5Ysux7BDbqW++YegE+KrwX03R3vkRpIqpQL3jorB3SOj8b9toedslQlr95zBpi+L8KtbByDN39HndbWPMXr7qyI0WZ2DvW9JCMYzM5OQPiC4z+sh8hSjBwShvtmKkxWN+KygAv9ndCyCuJmox/C8TxGSrWZrKz46eskZdPw0uG+UZwadH1MqBMy+KRqzUqPweUE51u09i1OVjXht31l4qwQETvy/MN/4ps5XdbzMgLcOFuOT78tcLTkjonV4emYSJnDQpVsqKSlBTU1Nj1+3sLCwx6/ZHwiCgKnDwmEw21BuaMFn+eX4RXosVEr3GUNIXfPsTxKSjVa7A598Xw5jSyt03mpZBJ0fUyoEzEqNwh0pkdh1vAKv7j2DkxWN0I2bg8/LRJxuLUdyVADignx6bDNCS6uIj78vw7ZvLuDQ+R/m5revCzQzOYIhpwf0RngoLy/Hz37+c7SYzT1+7XYmk6nXri1XKoUCd4yIxLZvSlBjsuLLMzWYPDRc6rLoGsjn04Q8liiKyDpRiQpjC7QqBWaPjJJV0PkxhUJA5ohIzEyOwN8+/Rortx+EV2wyzlaZcLbKBG+1EoPD/TAgxAexwT5QX+dvjc3WVpQ0KRB619P41ceVaGmtAOAMW3eMiMSvbh2Am+OCeuOl9TvGOudiiw899FCvfY17n/gjEpJSevSahd9m4/Mtr6KlpaVHr9tf+GlVmJmsx0d5ZTh2yYCYYG8k9vHGpnT95PmJQh7l2CUDTleZoBCAWamRCPKQwcg3QqEQMCbaC5XbnsX8V3agShWKM5UmmG125F8yIP+SAQoBCPHVIjxAi0BvNQK81dCqFM5mcxGw2h1osdlhMNtQ32xFpdECg9kGQAXf4RloaRURG+yNe26Kxi9viUNUoHRrE10LT+u2MZucaz/duWA5klLTevTa7YHEPyQCMYnJPXrtypJzPXq9/ig+xBfp8UE4cqEe+09WIzrQW7a/oMkF3x2SVFVjC7487fyAu3VwKGKC+t9MIJ1GRHJiOCYmhqG0rhlFNU0orm2CsaUV1SYLqk2W67ue2oGS7H/ijd89hv8zfYxHdFWVlJRg6LBhMDc399rX6K1um5CoeAaSPtAbYfhGgvDYgSEorm1CjcmKA6eqcceIyB6sjHoaww5JxmZ34LP8CthFEQNDfTEqNlDqkiSlVAgYEOqLAaG+EEURJksrKowtqGm0wthig7HFBmurA612ERAAjVIBrUqBAG81dN5qhPtroQ/wQk3xSaz58h0khS72iKADADU1NTA3N+PBZ/8MfdygHr02u208X2+H4e4EYaVCwPThemw/XIozVSacqWxEop7dWe6KYYckk3OuFgazDX5aFaYP13vMB3NfEAQB/l5q+HupkdiPxj/q4waxlYQu01th+EaDcLi/F0bHB+Pb4jrsP1WNuGAfaLl/nFti2CFJlDWYkVfaAACYNiycG0wS0VX1dBjuiSB8S0IwzlQ1or7ZhkPn65CRFNYDlVFP4wIB1OfsDiCrsBIAMDwygCuREpHHUioETEpyNr9+f7EB1Y3XN8aO+gbDDvW5U40KNDTb4KtRYkIiN9UjIs8WF+yDxHA/iAD2n6qCKIpSl0Q/wW4s6lPKgDCcMjq7rCYOCfOI7itPmxJNRH1vQmIoimqaUG5oca6ZJXVB1AHDDvWpoMm/hkMUEB3ojcRwP6nLuSpPnhJNRH3H30uNtPggfFNUh6/O1WIKG63dCsMO9ZnjVRb4Dp0AQETGkDCPmH3FKdFEdK1ujgtC/iUDDGYbzps4SsSdMOxQnxBFEZu/bwQADPRzIMxfK3FF14dToonoajQqBcYkBGP/qWoUGpQQNOzMcheMntQndh2vxLl6GxxWM4bp7FKXQ0TUK5KjdAjyUcPqEBAw+l6py6E2DDvU6+wOEX/ZfQoAYDzyb3i5/5hkIqJuUSoEjBsYAgAISL8bTVaHxBURwLBDfeDj7y/hTJUJfhoBxm93SF0OEVGvGhzuhwC1AwovP3xyuknqcggMO9TLWu0OrN1zBgBwT5IfRAv/4RORvAmC4Oqu/98zTTA02ySuiBh2qFd9ml+OC7XNCPbV4I7E/rejORH1T9HeIqzVxWi2idj0VZHU5fR7DDvUa0RRxIYDzhlHvxo/AF4q/rgRUf8gCIDhq/cAAFtyitFkaZW4ov6Nnz7Ua/adrMLJikb4aVX4v+MGSF0OEVGfaj79NSL9lDCYbXjv2xKpy+nXJA07q1evxujRo+Hv74/w8HDcc889OHXqVIdz5s2bB0EQOtzGjh3b4RyLxYJFixYhNDQUvr6+uPvuu3Hx4sW+fCn0E6IoYv3+swCAB8fGQeejlrgiIqI+JjowO8m5Uvymg0WwtnJmllQkXVQwOzsbCxcuxOjRo9Ha2orly5djxowZOHHiBHx9f9gJ+/bbb8fbb7/tuq/RaDpcZ/Hixfjkk0+wfft2hISEYOnSpZg1axZyc3OhVHKesxRyL9Tju5IGaFQKzL8tQepyqAf1xl5h3CeM5GrSAG/861QLyg0t+Pj7MvwsLUbqkvolScPOzp07O9x/++23ER4ejtzcXEycONF1XKvVIiIiotNrGAwGbNq0Ce+88w6mTZsGANi6dStiY2OxZ88ezJw587LnWCwWWCwW132j0dgTL4d+5K22AXn3jYpGuL+XxNVQT+ntvcK4TxjJjUYp4Ne3DcDLO09h4xfncP/N0R6xVY7cuNV2EQaDAQAQHBzc4fiBAwcQHh6OwMBAZGRk4MUXX0R4eDgAIDc3FzabDTNmzHCdHxUVhZSUFOTk5HQadlavXo2VK1f24ivp3y7WN2NnQQUAYN6tA6QthnpUb+0Vxn3CSM4eGhuP9fvO4nSlCQfP1mBCYpjUJfU7bhN2RFHEkiVLcNtttyElJcV1PDMzEz//+c8RHx+PoqIi/P73v8eUKVOQm5sLrVaLiooKaDQaBAUFdbieXq9HRUVFp19r2bJlWLJkieu+0WhEbGxs77ywfuidry/AIQK3Dg7B0IgAqcuhXtDTe4VxnzCSswAvNX6WFoMtX1/A218VM+xIwG3CzuOPP45jx47h4MGDHY7/4he/cP09JSUF6enpiI+Px6effor77ruvy+uJothlU6FWq4VW61kbUXqKZmura9bBr8ZzrA4REQDMHT8AW76+gH0nq1BU04SEUN+rP4l6jFuEnUWLFuHjjz/GF198gZiYKw/eioyMRHx8PM6cca7KGxERAavVivr6+g6tO1VVVRg/fnyv1k2X23H0EowtrYgP8cGUoeFSl9Ov9cagXw4kJuqegWF+mJwUhv2nqrElpxgr7u65llG6OknDjiiKWLRoEXbs2IEDBw4gIeHqLQG1tbUoLS1FZGQkACAtLQ1qtRpZWVmYM2cOAKC8vBwFBQV4+eWXe7V+6kgURbx7yNmq8/DYeCgUHIQnBWNdNQDgoYce6rWvwYHERNfvV7cmYP+pavzzSCmWzBiCAC8uydFXJA07CxcuxLZt2/Dvf/8b/v7+rjE2Op0O3t7eMJlMWLFiBe6//35ERkaiuLgYzz33HEJDQ3Hvvfe6zp0/fz6WLl2KkJAQBAcH46mnnsKIESNcs7Oob3x/0YAT5UZoVApOr5SQ2eScXXjnguVISk3r0WtzIDFR901IDMXgcD+crTLho6OXuNhqH5I07GzYsAEAMGnSpA7H3377bcybNw9KpRL5+fn4xz/+gYaGBkRGRmLy5Ml4//334e/v7zr/lVdegUqlwpw5c2A2mzF16lRs3ryZa+z0sW3fXAAA3DkiEoE+mqucTb0tJCq+RwcRAxxITHQjBEHAQ2PisOKTE3j3UAkeHhvPaeh9RPJurCvx9vbGrl27rnodLy8vrFu3DuvWreup0ug6GVts+OT7cgDAA2PiJK6GiMg93XtzDF7aeRKnKhuRe6Ee6QOCr/4kumFuMUCZPN9HRy/BbLMjMdwP6fFBV39CL+npAbQckEtEPUnnrcbdI6PwP0cu4t1vShh2+gjDDvWI9w+XAnC26kjRLNvbg3I5IJeIesqDY+LxP0cu4tP8cvxh1nAE+bLbv7cx7NANO1FmxPEyIzRKBe65KVqSGnprUC4H5BJRT0uN0SElOgAFl4z44LuL+M2EgVKXJHsMO3TDPvjOucP8tOHhkv+G0tODcjkgl4h6miAI+OUtcVi+owDvHy7F/NsSOFC5lymkLoA8m83uwEdHLwEAp5sTEV2ju0ZGQatS4EyVCd9fNEhdjuwx7NAN2X+yCrVNVoT6aTGR+70QEV2TAC817hjhXBy3fcwj9R6GHboh/8p1dmHdd3M0VEr+OBERXas56c4NqD/5vgxmq13iauSNn07UbfVNVuw/VQUAuP9mdmEREV2PMQnBiAv2gcnSis8LyqUuR9YYdqjbPs0vh80uYnhkAJIi/K/+BCIiclEoBPy8bazj/xxhV1ZvYtihbvs4rwwAcM+oKIkrISLyTPe1hZ1viupQbjBLXI18ceo5dcvF+mZ8W1wHQXDOKiAiAnpn1XE5r2QeHeiNWwYE49viOnycV4YFGYOkLkmWGHaoW9r3wRqTEIxInbfE1RCR1Hp7FXNAviuZzx4VhW+L6/ARw06vYdihbvl3nnNtHalWTCYi99Jbq5gD8l/J/M4RkVjx8XEUlhtxurIRQ/QcA9nTGHboup2qaMTJikZolApkpkRKXQ4RuZGeXsUckP9K5oE+GmQMCceewkp8dPQSnrl9qNQlyQ4HKNN1+yzf2YU1cUgodD5qiashIvJ87RM9/p1XBodDlLga+WHYoevWvh5E++qfRER0Y6YN08NPq8KlBjNyS+qlLkd2GHboupytasTpShPUSgFTh+mlLoeISBa81ErMTI4AANd+g9RzuhV2Bg4ciNra2suONzQ0YOBAblUvZ5/nVwAAbhscCp03u7CIiHpKe1fWp/nlsLY6JK5GXroVdoqLi2G3X76Ph8ViwaVLTKRy9lmBM+xksguLiKhHjR8UijB/LRqabfjidLXU5cjKdc3G+vjjj11/37VrF3Q6neu+3W7H3r17MWDAgB4rjtxLUU0TCsuNUCkEzBjOLiwiop6kVAi4KzUKb31VhI/yLmEa/5/tMdcVdu655x4AgCAImDt3bofH1Go1BgwYgL/85S89Vhy5l/aByeMGhSDQRyNxNURE8nPPKGfY2VNYCZOlFX5arhDTE67ru+hwOPsQExIScPjwYYSGhvZKUeSe2sfrcBYWEVHvGBGtw8AwX5yvbsKeE5W4ZxQXbu0J3RqzU1RUxKDTz5TWNSP/kgEKAezCIiLqJYIg4M62XyjbW9PpxnW7fWzv3r3Yu3cvqqqqXC0+7d56660bLozcS/s/urEDQxDip5W4GiIi+cpMicS6fWdx4FQ1miyt8GVX1g3r1ndw5cqV+OMf/4j09HRERkZCEISeroskVlJSgpqaGtf9fx5y/j1FZ8N3333XrWvKeediIqKeMizSHwNCfFBc24wDp6pxZyqHDtyoboWdv/71r9i8eTMefvjhnq6H3EBJSQmGDhsGc3MzAEDpH4aYx96GKDrw+1/fjeVNDTd0fbnuXExE1BMEQcDtKZH4a/Y5fFZQzrDTA7oVdqxWK8aPH9/TtZCbqKmpgbm5GQ8++2fo4wbhjFGBYw1AmBfws5e730Up952LiYh6yh0jIvDX7HPYf7IKLTY7vNRKqUvyaN0KO7/5zW+wbds2/P73v+/pesiN6OMGISYxGV8fKQXQguR4PWJiA7t9PbnvXExE1FNGROsQHeiNSw1mZJ+udm0lQd3TrbDT0tKCjRs3Ys+ePUhNTYVa3XHbgDVr1vRIcSS9Zmsryg3OlphBYb4SV0NE1D8IgoDMlAj8/WARPs8vZ9i5Qd0KO8eOHcNNN90EACgoKOjwGAcry0txbTNEAGH+Wvh7cS8sIqK+kjkiEn8/WIS9hVWwtNqhVbErq7u6FXb279/f03WQmzpf7RxMnBDKVh0ior40KjYQ+gAtKo0WfHW2BlOGco2z7urWooLUP9hFoKTOOSNrIMMOEVGfUigEZKY4Z2J91raCPXVPt1p2Jk+efMXuqn379nW7IHIf1S0CbHYRvlolwv25kCARUV+7PSUCm3OKkXWiEja7A2ol2yi6o1thp328TjubzYa8vDwUFBRctkEoea5ys/MfVUKoL8diERF1w40upqp0iNBpFTCYbXhn1ze4KUKL0NBQxMXF9VCF/UO3ws4rr7zS6fEVK1Zc14Jxq1evxocffoiTJ0/C29sb48ePx5/+9CckJSW5zhFFEStXrsTGjRtRX1+PMWPGYP369UhOTnadY7FY8NRTT+G9996D2WzG1KlT8cYbbyAmJqY7L4/atIedgaF+EldCRORZjHXVAICHHnrohq8VPOMx+I+6A0+/tg11u16Ht48PThYWMvBchx7dcOOhhx7CLbfcgv/+7/++pvOzs7OxcOFCjB49Gq2trVi+fDlmzJiBEydOwNfXOUbk5Zdfxpo1a7B582YMGTIEL7zwAqZPn45Tp07B398fALB48WJ88skn2L59O0JCQrB06VLMmjULubm5UCo5er071OEDYbYLUCkExAZ5S10OEZFHMZuMAIA7FyxHUmraDV2rskXAwSog9OaZuP2meGz709Ooqalh2LkOPRp2vv76a3h5eV3z+Tt37uxw/+2330Z4eDhyc3MxceJEiKKItWvXYvny5bjvvvsAAFu2bIFer8e2bduwYMECGAwGbNq0Ce+88w6mTZsGANi6dStiY2OxZ88ezJw5s+deYD/ikzgGABAf4gMV+4iJiLolJCoeMYnJVz/xCiIdIr6tOw9LqwNq/eAeqqx/6VbYaQ8e7URRRHl5OY4cOXJDqyobDAYAQHBwMACgqKgIFRUVmDFjhuscrVaLjIwM5OTkYMGCBcjNzYXNZutwTlRUFFJSUpCTk9Np2LFYLLBYLK77RqOx2zXLlfdgZ9jhlHMiImkpFQIGhPjgdKXJNbyArk+3wo5Op+twX6FQICkpCX/84x87hI7rIYoilixZgttuuw0pKSkAgIoK51Q7vb7j2gJ6vR4XLlxwnaPRaBAUFHTZOe3P/6nVq1dj5cqV3aqzP6hptkMbMRiAyLBDROQGBob64XSlCWVmThbpjm6Fnbfffrun68Djjz+OY8eO4eDBg5c99tOZQKIoXnV20JXOWbZsGZYsWeK6bzQaERsb242q5Sm3zLk9RLBGhI+mR3s6iYioGwaE+EAhAI02BVSB3AX9et3QJ1lubi4KCwshCAKGDx+OUaNGdes6ixYtwscff4wvvviiwwyqiAjnXiAVFRWIjPzhza2qqnK19kRERMBqtaK+vr5D605VVVWXO7NrtVpotVw3piuHy5xdfFHeDokrISIiANCqlYgO9EZpvRneg2+RuhyP063Ov6qqKkyZMgWjR4/GE088gccffxxpaWmYOnUqqqurr/k6oiji8ccfx4cffoh9+/YhISGhw+MJCQmIiIhAVlaW65jVakV2drYryKSlpUGtVnc4p7y8HAUFBV2GHepak6UVx6qcYSfSh2GHiMhdDAxzLgPikzhW4ko8T7fCzqJFi2A0GnH8+HHU1dWhvr4eBQUFMBqNeOKJJ675OgsXLsTWrVuxbds2+Pv7o6KiAhUVFTCbzQCc3VeLFy/GqlWrsGPHDhQUFGDevHnw8fHBAw88AMA5fmj+/PlYunQp9u7di6NHj+Khhx7CiBEjXLOz6NodPFuDVgdgqy+HP3uwiIjcRvsYSm3McDRa+Mvo9ejWx9nOnTuxZ88eDBs2zHVs+PDhWL9+/XUNUN6wYQMAYNKkSR2Ov/3225g3bx4A4JlnnoHZbMZjjz3mWlRw9+7drjV2AOcihyqVCnPmzHEtKrh582ausdMNB05VAQDM5w5DGHm7xNUQEVE7nbcaAWoHjDYlvqtoQYbUBXmQboUdh8MBtVp92XG1Wg2H49rTpiiKVz1HEASsWLECK1as6PIcLy8vrFu3DuvWrbvmr02XE0UR+086uyHN548AYNghInInUd4ijDbg8CXL1U8ml251Y02ZMgVPPvkkysrKXMcuXbqE//iP/8DUqVN7rDjqW6cqG1FhbIFGCVhKC6Quh4iIfiKybeLI0QoLLK12iavxHN0KO6+//joaGxsxYMAADBo0CIMHD0ZCQgIaGxvZuuLB2lt1UsK1EFutEldDREQ/FaQR0dpYC3OriEPn66Qux2N0qxsrNjYW3333HbKysnDy5EmIoojhw4dzQLCH2982XictQosdEtdCRESXEwTAfO5b+N+UiT0nKpExJEzqkjzCdbXs7Nu3D8OHD3dtrzB9+nQsWrQITzzxBEaPHo3k5GR8+eWXvVIo9S5jiw25F+oBAKMiuQYREZG7Mp/5BgCwp7Dymsa+0nWGnbVr1+KRRx5BQEDAZY/pdDosWLAAa9as6bHiqO8cPFMDu0PEwDBfRPhxzjkRkbsyX/geWqWAckMLjpdxb8drcV1h5/vvv8ftt3c9Q2fGjBnIzc294aKo7+0/6ezCmpwULnElRER0RXYbRkZoAAD72v7vpiu7rrBTWVnZ6ZTzdiqV6rpWUCb3IIoiDpx2vm+Tktj/S0Tk7tIivQD8MNaSruy6wk50dDTy8/O7fPzYsWMd9rAiz3C8zIjqRgu81UrckhAsdTlERHQVN0c4x1bmlTagromzZ6/musLOHXfcgT/84Q9oaWm57DGz2Yznn38es2bN6rHiqG9kt7Xq3Do4BFoVV50mInJ3IT5KDIsMgCgC2afZunM11zUS9Xe/+x0+/PBDDBkyBI8//jiSkpIgCAIKCwuxfv162O12LF++vLdqpV7SPl5nEsfrEBF5jClDw1BYbsT+k9W4d1SM1OW4tesKO3q9Hjk5Ofjtb3+LZcuWuaa8CYKAmTNn4o033oBer++VQql3NDRb8V2Jc8o5x+sQEXmOyUnhWL//HLJPV8PuEKFUCFKX5Laue45xfHw8PvvsM9TX1+Ps2bMQRRGJiYkICgrqjfqol315pgYOEUgM90NMkI/U5RAR0TW6KTYQOm81DGYbjpbUI30Ax1x2pVvbRQBAUFAQRo8ejVtuuYVBx4O1j+SfPJRdWEREnkSlVGBi2wrKnJV1Zd0OO+T5HA4RX5yuAQBM4pLjREQeZ8rQtrBzksu+XAnDTj9WWGFEjck55TxtAFvniIg8zcTEMAgCcKLciArD5TOlyYlhpx9rb9UZN4hTzomIPFGInxYjYwIBAAfYldUlhp1+7MszzmbPiYmhEldCRETd1b7ND8ftdI1hp59qtrbiSLFzyvkEjtchIvJYU9ommBw8UwNrq0PiatwTw04/deh8Lax2B6IDvTEw1FfqcoiIqJuSowIQ6qdFk9WOI8V1Upfjlhh2+qn28ToTh4RBELgQFRGRp1IoBNeisNwFvXMMO/3UF23jdTKGcLwOEZGn47idK2PY6Ycu1jfjfHUTlAoB4wYx7BARebrbEkOhVAg4V92Ei/XNUpfjdhh2+qH2Lqz2pcaJiMiz6bzVGBUbCOCH/+PpBww7/dAXp9unnHMWFhGRXLRvHdH+fzz9gGGnn2m1O/DVufbByezCIiKSi/aw89XZGtjsnIL+Yww7/cz3FxvQ2NIKnbcaqW2rbhIRkecbEa1DkI8ajZZW5JU2SF2OW2HY6Wey2/pybxvsHMxGRETyoFQIuC2RXVmdYdjpZ1xbRLALi4hIdtq3/8lm2OmAYacfMTTb8H1b0+YEDk4mIpKdjLZxO/mXDKg1WSSuxn0w7PQjB8/WwCECg8P9EBXoLXU5RETUw8IDvDA0wh+i6Pw/n5wYdvoRTjknIpK/jLatI9iV9QOGnX5CFEWO1yEi6gcyXIOUa+BwiBJX4x4YdvqJc9UmlBlaoFEpMCYhROpyiIiol6QNCIK3WokakwWFFUapy3ELDDv9RPuU81sGBMNbo5S4GiIi6i1alRLjBzl/qeXWEU4MO/2Ea7wOu7CIiGSvfTXl7NPcBR2QOOx88cUXuOuuuxAVFQVBEPDRRx91eHzevHkQBKHDbezYsR3OsVgsWLRoEUJDQ+Hr64u7774bFy9e7MNX4f5abHZ8U1QL4Id/AEREJF/tU9BzL9SjydIqcTXSkzTsNDU1YeTIkXj99de7POf2229HeXm56/bZZ591eHzx4sXYsWMHtm/fjoMHD8JkMmHWrFmw2+29Xb7HOFJcjxabA+H+WiTp/aUuh4iIetmAUF/EBfvAZhfx9blaqcuRnErKL56ZmYnMzMwrnqPVahEREdHpYwaDAZs2bcI777yDadOmAQC2bt2K2NhY7NmzBzNnzuz0eRaLBRbLD4stGY3yHsD1RdssrAmJYRAEbhFBRNQfTBwSiq2HSpB9uhrThuulLkdSbj9m58CBAwgPD8eQIUPwyCOPoKrqh/7H3Nxc2Gw2zJgxw3UsKioKKSkpyMnJ6fKaq1evhk6nc91iY2N79TVIjeN1iIj6n4wh4QB++IW3P3PrsJOZmYl3330X+/btw1/+8hccPnwYU6ZMcbXKVFRUQKPRICgoqMPz9Ho9KioqurzusmXLYDAYXLfS0tJefR1SqjK24GRFIwSBW0QQEfUn4waFQKUQcKG2GcU1TVKXIylJu7Gu5he/+IXr7ykpKUhPT0d8fDw+/fRT3HfffV0+TxTFK3bXaLVaaLXaHq3VXX1xxjntcES0DsG+GomrISKivuKnVSEtPgjfFNXhizPVGBDqK3VJknHrlp2fioyMRHx8PM6cOQMAiIiIgNVqRX19fYfzqqqqoNf37/7Jdu1dWBMS2YVFRNTftG8d8UU/3zrCo8JObW0tSktLERkZCQBIS0uDWq1GVlaW65zy8nIUFBRg/PjxUpXpNhwO0bURHPfDIiLqf9r/7885Vwtrq0PiaqQjaTeWyWTC2bNnXfeLioqQl5eH4OBgBAcHY8WKFbj//vsRGRmJ4uJiPPfccwgNDcW9994LANDpdJg/fz6WLl2KkJAQBAcH46mnnsKIESNcs7P6s+NlRtQ1WeGnVeHm+KCrP4GIiGRleGQAQv20qDFZcORCHcYP6p+t/JK27Bw5cgSjRo3CqFGjAABLlizBqFGj8Ic//AFKpRL5+fmYPXs2hgwZgrlz52LIkCH4+uuv4e//w1oxr7zyCu655x7MmTMHt956K3x8fPDJJ59AqeSWCO0j8McNCoFa6VGNeERE1AMUCgET24Yx9Odd0CVt2Zk0aRJEsesdWXft2nXVa3h5eWHdunVYt25dT5YmC+0/2BM5XoeISFYKCwuv+dxYjRkAsOv7EszUm694bmhoKOLi4m6oNnfk1rOx6MpKSkpQU9P5Jm/NNgdyi+sAACG2Knz3Xd01X/d6/hEREVHfMdY5f4l96KGHrvk5Ch8dYhe9i+KGVoyeOBWOpoYuz/X28cHJwkLZBR6GHQ9VUlKCocOGwdzc3Onj3oPHIPz+38NWX4Y7M2Z162uYTKYbKZGIiHqY2eRc8f/OBcuRlJp2zc/bW+5Ag02Be/+wGfF+nQ9Uriw5h3f/9DRqamoYdsg91NTUwNzcjAef/TP0cYMue/xonRLnTUBSrB7/Z/2H13Xtwm+z8fmWV9HS0tJT5RIRUQ8KiYpHTGLyNZ8/WKjBkQv1aFQHISax8y2Y5Ixhx8Pp4wZ1+gO/J6cYgA3JA2MQE+Z3XdesLDnXM8UREZFbiA/xwZEL9Sipa77qwrtyxCk6MtTQbIXBbINCAGKCfKQuh4iIJBap84ZaKcBss6O60XL1J8gMw44MXah1juOJ1HlDo+JbTETU3ykVAmLbfvm9UNf5WE854yehDLX/IMeHsFWHiIic4to+E9p/Ie5PGHZkxu4QcbG+LewEM+wQEZFT+2dCucHc77aOYNiRmXKDGTa7CG+1EmH+/WNndyIiurpAHw103mo4RLh+Ke4vGHZkpr15Mj7Ep9+Nticioitrb93pb11ZDDsy4xqvwy4sIiL6ifaxnP1tkDLDjow0WVpdUwrjODiZiIh+IibIBwoBMJhtaGi2Sl1On2HYkZHStqQe5q+Fj4brRRIRUUcalQKROm8A/at1h2FHRtiFRUREV9Pe8l/Sj8btMOzIhCiKHQYnExERdab9F+LS+mbYHaLE1fQNhh2ZqDZZYLbZoVYKriZKIiKinwr318JbrYTNLqLcYJa6nD7BsCMT7a06MUE+UCo45ZyIiDonCALi+tkUdIYdmWjve+V4HSIiupr24Q4l/WSQMsOODFhbHShra4rkeB0iIrqa9padqkYLmq2tElfT+xh2ZOBifTMcIqDzViPQRyN1OURE5OZ8tSqE+jk/L/pD6w7Djgy097nGsQuLiIiuUXyIL4D+MQWdYUcGXOvrsAuLiIiukWufrLpmiKK8p6Az7Hg4k8257LdCAGKCOOWciIiuTWSgF1QKAc1WO2pM8t46gmHHw1W2ON/CSJ03tCqlxNUQEZGnUCkUrl+SL9Q1SVxN72LY8XDtYYcbfxIR0fVqH7cj9/V2GHY8mVKFqhbnAoIJbT+wRERE16p9rGd5QwtaHRIX04sYdjyYV2wK7KIAX43SNYWQiIjoWgV6qxHgpYJdFFFtke/q+ww7Hsx7YDoAYECoLwRBvj+kRETUOwRBcA2DqDTLNxLI95X1A66wwy4sIiLqpvhg52dI+xhQOZLvK5O58sZWqENiIEBEbDCnnBMRUffEBntDEABTqwBlQLjU5fQKhh0P9V2FBQAQqhU55ZyIiLpNq1IiMsALAOCdcLPE1fQOhh0P9V25M+xEeMt4+DwREfWJ9inoDDvkNsxWO45XM+wQEVHPaJ+C7jXgJtjs8ts6gmHHAx06XwurHWg1VMFfJXU1RETk6cL9tdAqRCi0PjhZI7+tIyQNO1988QXuuusuREVFQRAEfPTRRx0eF0URK1asQFRUFLy9vTFp0iQcP368wzkWiwWLFi1CaGgofH19cffdd+PixYt9+Cr63v5TVQAA8/kj4IxzIiK6UYIguHoKctuGSciJpGGnqakJI0eOxOuvv97p4y+//DLWrFmD119/HYcPH0ZERASmT5+OxsZG1zmLFy/Gjh07sH37dhw8eBAmkwmzZs2C3W7vq5fRp0RRxL6TbWHn3BGJqyEiIrloDzvtE2DkRNJOkMzMTGRmZnb6mCiKWLt2LZYvX4777rsPALBlyxbo9Xps27YNCxYsgMFgwKZNm/DOO+9g2rRpAICtW7ciNjYWe/bswcyZM/vstfSVc9VNuFhvhkoBtJR8L3U5REQkE+FeIkSHHReNQGldM2KD5bPnotuO2SkqKkJFRQVmzJjhOqbVapGRkYGcnBwAQG5uLmw2W4dzoqKikJKS4jqnMxaLBUajscPNUxxo68JKCdNAtMkvfRMRkTQ0CsBy8QSAH4ZLyIXbhp2KigoAgF6v73Bcr9e7HquoqIBGo0FQUFCX53Rm9erV0Ol0rltsbGwPV9972n8Ab470krgSIiKSm/bhEftPMuz0qZ/u+SSK4lX3gbraOcuWLYPBYHDdSktLe6TW3maytOLbojoAwM2RWomrISIiuTGfd4adnHO1aLHJZ+yr24adiIgIALishaaqqsrV2hMREQGr1Yr6+vouz+mMVqtFQEBAh5sn+PJ0NWx2EQNCfBDFOedERNTDbDUXEOqjgKXVga/P10pdTo9x27CTkJCAiIgIZGVluY5ZrVZkZ2dj/PjxAIC0tDSo1eoO55SXl6OgoMB1jpxkFVYCAKYN6zrIERER3Yi0tmEScurKkjTsmEwm5OXlIS8vD4BzUHJeXh5KSkogCAIWL16MVatWYceOHSgoKMC8efPg4+ODBx54AACg0+kwf/58LF26FHv37sXRo0fx0EMPYcSIEa7ZWXLRane4fvCmDWfYISKi3tE+TGLfySqIojxWU5a0L+TIkSOYPHmy6/6SJUsAAHPnzsXmzZvxzDPPwGw247HHHkN9fT3GjBmD3bt3w9/f3/WcV155BSqVCnPmzIHZbMbUqVOxefNmKJXy2hwz90I96pttCPRRIz0+CMcaLkhdEhERydCIcA00KgUu1ptxrroJg8P9pC7phkkadiZNmnTF1CgIAlasWIEVK1Z0eY6XlxfWrVuHdevW9UKF7mNPWxfWlKRwqJRu2/tIREQezkulwNiBIfjidDUOnKqSRdjhp6YHEEURWSecYWc6u7CIiKiXTU4KAwDXiv2ejmHHA5yrNqG4thkapQIThoRJXQ4REcnc5KRwAMDh4jo0ttgkrubGMex4gKwTzmQ9blAI/LScck5ERL1rQKgvEkJ9YbOLOHimRupybhjDjgfIOuFca4hdWERE1FemDXO27rQPo/BkDDturrrRgqOlDQCAqW0/eERERL1t+nDn4r57T1ah1e6QuJobw7Dj5vafrIIoAiOidYjUeUtdDhER9RNp8UEI9tXAYLbh2+I6qcu5IQw7bm43Z2EREZEElAoBU4bKoyuLYceNma12HDxbDYBbRBARUd+b0faLdtaJSo9eTZlhx419dbYGLTYHogO9MSzS/+pPICIi6kETEsPgpXaupnyyolHqcrqNYceN/XghQUEQJK6GiIj6G2+NErcNdq7v5sldWQw7bqrV7nDtcs7xOkREJJX2rqzdbcugeCKGHTd16Hwd6pqsCPbVYExCsNTlEBFRPzVlWDgEASi4ZERZg1nqcrqFYcdNfZpfBgCYmRzBjT+JiEgyoX5apMUFAfhhU2pPw09RN9Rqd2DXcecP1J0jIiWuhoiI+rvpP5qV5YkYdtzQj7uwxg5kFxYREUlrRrJzNeWvz9XCYPa8jUEZdtzQp/nlAICZyXp2YRERkeQSQn0xONwPrQ4RB05VSV3OdeMnqZtxdmE5R7zfwS4sIiJyE57clcWw42a+KXJ2YQX5qDFuYIjU5RAREQH4YQr6/pNVaLHZJa7m+jDsuJkfurA4C4uIiNzHTbGBiNJ5oclqR/bpaqnLuS78NHUjrXYHdhWwC4uIiNyPIAjIbPts+rztF3NPwbDjRr4tqkNtkxWBPmqMG8QuLCIici/tv4jvKfSsriyGHTfi6sIaHgE1u7CIiMjNjIoNRESAF0yWVnx5pkbqcq4ZP1HdhN0h/jALK5VdWERE5H4UCgGZI5xr7nzmQV1ZDDtu4pvztagxObuwxrMLi4iI3FT7yv57TlTC0uoZXVkMO27io7xLAIDMFHZhERGR+7o5LggRAV5otLTiwCnPmJXFT1U30GKz4/N8ZxfWvaNiJK6GiIioawqFgFltwy0+/r5M4mquDcOOG9hbWIVGSyuiA72RHh8kdTlERERXNPumaADA3sJKmCytEldzdQw7bmDHUWcX1j2joqBQCBJXQ0REdGUp0QFICPVFi82BrBMVUpdzVQw7Eqtrsro2VbunLSkTERG5M0EQcNfIKADAx3nu35XFsCOxT4+VodUhIiU6AIl6f6nLISIiuiZ3t4WdL8/UoK7JKnE1V8awI7F/5V4EwFYdIiLyLIPD/ZAcFYBWh4hPj7l36w7DjoROVhjx/UUDVAoB945i2CEiIs/S/tn1r+8uSVzJlTHsSOifR5ytOtOG6RHip5W4GiIiousz+6ZoKBUCvi9twNkqk9TldIlhRyLWVgc+apuF9fN0rq1DRESeJ8xfi0lDwgAAH3x3UeJquqaSuoD+at/JKtQ2WRHmr0VG2w8KERGR1AoLC6/r/FFBVuwF8P43RZgS2gRlJ0uohIaGIi4urocqvH5uHXZWrFiBlStXdjim1+tRUeGc0y+KIlauXImNGzeivr4eY8aMwfr165GcnCxFuZ0qKSlBTc3lO8O++WUdAOC2aBWOfZ933de93h9GIiKiKzHWObd+eOihh67viUoVYha+gzr4Y+LPf4OW4rzLTvH28cHJwkLJAo9bhx0ASE5Oxp49e1z3lUql6+8vv/wy1qxZg82bN2PIkCF44YUXMH36dJw6dQr+/tJP4y4pKcHQYcNgbm7ucFwZEIboRzdBEBR4felDWFvX/YFdJpP79pESEZHnMJuMAIA7FyxHUmradT33aJ0S501A2q9WYkxox81BK0vO4d0/PY2amhqGna6oVCpERERcdlwURaxduxbLly/HfffdBwDYsmUL9Ho9tm3bhgULFnR5TYvFAovF4rpvNBp7vnAANTU1MDc348Fn/wx93CDX8eMNSpw0KhCmdeD+/1rXrWsXfpuNz7e8ipaWlp4ql4iICCFR8YhJvL4eEo2xBecPl6LcrEJIfCK8NcqrP6kPuX3YOXPmDKKioqDVajFmzBisWrUKAwcORFFRESoqKjBjxgzXuVqtFhkZGcjJybli2Fm9evVl3WO9SR83yPWDY3eI+PyrIgB2jE6MQkw3FxKsLDnXgxUSERF1X3iAF8L9tahqtKCw3Iib3WyfR7eejTVmzBj84x//wK5du/Dmm2+ioqIC48ePR21trWvcjl6v7/CcH4/p6cqyZctgMBhct9LS0l57DT91rtqEZqsdPholBob59dnXJSIi6k0p0ToAQH6ZAaIoSlxNR27dspOZmen6+4gRIzBu3DgMGjQIW7ZswdixYwE49+f4MVEULzv2U1qtFlqtNOva5F8yAABSonSdjlgnIiLyREl6f3x5phoNzTZcajAjJshH6pJc3Lpl56d8fX0xYsQInDlzxjWO56etOFVVVZe19riLGpMFF+vNEAAkRwdIXQ4REVGP0agUSGobmtH+i7278KiwY7FYUFhYiMjISCQkJCAiIgJZWVmux61WK7KzszF+/HgJq+xaXmkDAGBQmB8CvNTSFkNERNTD2ruyzlaZ0GRplbiaH7h12HnqqaeQnZ2NoqIifPPNN/jZz34Go9GIuXPnQhAELF68GKtWrcKOHTtQUFCAefPmwcfHBw888IDUpV+m2dqKkxWNAICb4gKlLYaIiKgX6AO8EKnzgkN0r9Ydtx6zc/HiRfzyl79ETU0NwsLCMHbsWBw6dAjx8fEAgGeeeQZmsxmPPfaYa1HB3bt3u8UaOz+Vf8kAu0NEuL8WUTovqcshIiLqFSNjAlFuqED+JQPSB7jHrCy3Djvbt2+/4uOCIGDFihVYsWJF3xTUTXYROHbRmXBHxQVedQA1ERGRpxoc7gffs0o0Wew4W2mCO8w7dutuLLkobVKg2WqHn1aFxHD3a3UiIiLqKUqFgNToQADA0dIGuMMsdIad3iYocMroXEnypthATjcnIiLZS4kOgFIhoKrRghqL9J97DDu9zCfpVphaBXipFBjRNkqdiIhIznw0KgyLdPZktP/CLyWGnV4kiiJ04+YAcLbqaFT8dhMRUf+QFhcEAUBliwLqsARJa+Gnby86Um6BJjwBKkHEyNhAqcshIiLqM4E+GiTqncOTdWN/JmktDDu96ONTTQCAgX4OeKmlb8YjIiLqS+nxwQAAn6G3ocIk3SKDDDu9aMnYQBgO/ROJAXapSyEiIupzYf5a6L0cEBRKfH62WbI6GHZ6UZC3Eg3ZW+DFRh0iIuqnhuvsqN35Oh4cId3SKww7RERE1GuCtSJM3++ERindFHSGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI12YSdN954AwkJCfDy8kJaWhq+/PJLqUsiIiIiNyCLsPP+++9j8eLFWL58OY4ePYoJEyYgMzMTJSUlUpdGREREEpNF2FmzZg3mz5+P3/zmNxg2bBjWrl2L2NhYbNiwQerSiIiISGIqqQu4UVarFbm5ufjP//zPDsdnzJiBnJycTp9jsVhgsVhc9w0GAwDAaDT2aG0mkwkAcPHMcVjMzT167cqScwCAiuLTOOfr4xHXZs19c23W3DfX9sSae/ParLlvru2JNVdfLALg/Ezs6c/Z9uuJonjlE0UPd+nSJRGA+NVXX3U4/uKLL4pDhgzp9DnPP/+8CIA33njjjTfeeJPBrbS09IpZweNbdtoJgtDhviiKlx1rt2zZMixZssR13+FwoK6uDiEhIV0+x5MYjUbExsaitLQUAQEBUpfTb/F9cA98H9wD3wf3ILf3QRRFNDY2Iioq6orneXzYCQ0NhVKpREVFRYfjVVVV0Ov1nT5Hq9VCq9V2OBYYGNhbJUomICBAFj/Mno7vg3vg++Ae+D64Bzm9Dzqd7qrnePwAZY1Gg7S0NGRlZXU4npWVhfHjx0tUFREREbkLj2/ZAYAlS5bg4YcfRnp6OsaNG4eNGzeipKQEjz76qNSlERERkcRkEXZ+8YtfoLa2Fn/84x9RXl6OlJQUfPbZZ4iPj5e6NElotVo8//zzl3XVUd/i++Ae+D64B74P7qG/vg+CKF5tvhYRERGR5/L4MTtEREREV8KwQ0RERLLGsENERESyxrBDREREssawIzNvvPEGEhIS4OXlhbS0NHz55ZdSlyR7X3zxBe666y5ERUVBEAR89NFHHR4XRRErVqxAVFQUvL29MWnSJBw/flyaYmVq9erVGD16NPz9/REeHo577rkHp06d6nAO34fet2HDBqSmproWrBs3bhw+//xz1+N8D6SxevVqCIKAxYsXu471t/eCYUdG3n//fSxevBjLly/H0aNHMWHCBGRmZqKkpETq0mStqakJI0eOxOuvv97p4y+//DLWrFmD119/HYcPH0ZERASmT5+OxsbGPq5UvrKzs7Fw4UIcOnQIWVlZaG1txYwZM9DU1OQ6h+9D74uJicFLL72EI0eO4MiRI5gyZQpmz57t+hDle9D3Dh8+jI0bNyI1NbXD8X73XtzwTpzkNm655Rbx0Ucf7XBs6NCh4n/+539KVFH/A0DcsWOH677D4RAjIiLEl156yXWspaVF1Ol04l//+lcJKuwfqqqqRABidna2KIp8H6QUFBQk/v3vf+d7IIHGxkYxMTFRzMrKEjMyMsQnn3xSFMX++e+BLTsyYbVakZubixkzZnQ4PmPGDOTk5EhUFRUVFaGioqLD+6LVapGRkcH3pRcZDAYAQHBwMAC+D1Kw2+3Yvn07mpqaMG7cOL4HEli4cCHuvPNOTJs2rcPx/vheyGIFZQJqampgt9sv2/xUr9dftkkq9Z32731n78uFCxekKEn2RFHEkiVLcNtttyElJQUA34e+lJ+fj3HjxqGlpQV+fn7YsWMHhg8f7voQ5XvQN7Zv347c3FwcOXLkssf6478Hhh2ZEQShw31RFC87Rn2P70vfefzxx3Hs2DEcPHjwssf4PvS+pKQk5OXloaGhAR988AHmzp2L7Oxs1+N8D3pfaWkpnnzySezevRteXl5dntef3gt2Y8lEaGgolErlZa04VVVVl6V36jsREREAwPeljyxatAgff/wx9u/fj5iYGNdxvg99R6PRYPDgwUhPT8fq1asxcuRIvPrqq3wP+lBubi6qqqqQlpYGlUoFlUqF7OxsvPbaa1CpVK7vd396Lxh2ZEKj0SAtLQ1ZWVkdjmdlZWH8+PESVUUJCQmIiIjo8L5YrVZkZ2fzfelBoiji8ccfx4cffoh9+/YhISGhw+N8H6QjiiIsFgvfgz40depU5OfnIy8vz3VLT0/Hgw8+iLy8PAwcOLDfvRfsxpKRJUuW4OGHH0Z6ejrGjRuHjRs3oqSkBI8++qjUpcmayWTC2bNnXfeLioqQl5eH4OBgxMXFYfHixVi1ahUSExORmJiIVatWwcfHBw888ICEVcvLwoULsW3bNvz73/+Gv7+/6zdWnU4Hb29v1xojfB9613PPPYfMzEzExsaisbER27dvx4EDB7Bz506+B33I39/fNV6tna+vL0JCQlzH+917Id1EMOoN69evF+Pj40WNRiPefPPNrqm31Hv2798vArjsNnfuXFEUndM8n3/+eTEiIkLUarXixIkTxfz8fGmLlpnOvv8AxLffftt1Dt+H3vfrX//a9f9PWFiYOHXqVHH37t2ux/keSOfHU89Fsf+9F4IoiqJEOYuIiIio13HMDhEREckaww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOEdENmjdvHu655x6pyyCiLjDsEFGXKioqsGjRIgwcOBBarRaxsbG46667sHfv3hu+dnFxMQRBQF5e3o0X2sv+9re/YeTIkfD19UVgYCBGjRqFP/3pT67HX331VWzevFm6AonoirgRKBF1qri4GLfeeisCAwPx8ssvIzU1FTabDbt27cLChQtx8uRJqUvsdTabDf/4xz+wZMkSvPbaa8jIyIDFYsGxY8dw4sQJ13k6nU7CKonoqqTenIuI3FNmZqYYHR0tmkymyx6rr68Xi4qKRADi0aNHOxwHIO7fv18URVGsq6sTH3jgATE0NFT08vISBw8eLL711luiKF6+eWdGRoYoiqJot9vFlStXitHR0aJGoxFHjhwpfv75566v0f5133//ffG2224Tvby8xPT0dPHUqVPit99+K6alpYm+vr7izJkzxaqqqg51v/XWW+LQoUNFrVYrJiUlievXr+/0uhkZGaJWqxXfeustcfbs2eK8efOu+L2aO3euOHv2bNf9jIwMcdGiReLTTz8tBgUFiXq9Xnz++ecv+x4+8sgjYnh4uKjVasXk5GTxk08+cT3+1VdfiRMmTBC9vLzEmJgYcdGiRZ2+F0R0dQw7RHSZ2tpaURAEcdWqVV2ecy1hZ+HCheJNN90kHj58WCwqKhKzsrLEjz/+WBRFUfz2229FAOKePXvE8vJysba2VhRFUVyzZo0YEBAgvvfee+LJkyfFZ555RlSr1eLp06c7fN2hQ4eKO3fuFE+cOCGOHTtWvPnmm8VJkyaJBw8eFL/77jtx8ODB4qOPPuqqbePGjWJkZKT4wQcfiOfPnxc/+OADMTg4WNy8eXOH6w4YMMB1zqVLl8QFCxaIQ4cOFYuLi7v8XnQWdgICAsQVK1aIp0+fFrds2SIKguDaAdxut4tjx44Vk5OTxd27d4vnzp0TP/nkE/Gzzz4TRVEUjx07Jvr5+YmvvPKKePr0afGrr74SR40addXQRUSdY9ghost88803IgDxww8/7PKcawk7d911l/irX/3qmp8viqIYFRUlvvjiix2OjR49Wnzsscc6PO/vf/+76/H33ntPBCDu3bvXdWz16tViUlKS635sbKy4bdu2Dtf9r//6L3HcuHEdrrt27doO55SVlYljx44VAYhDhgwR586dK77//vui3W53ndNZ2Lntttsuew3PPvusKIqiuGvXLlGhUIinTp3q9Hvz8MMPi//v//2/Dse+/PJLUaFQiGazudPnEFHXOECZiC4jiiIAQBCEG7rOb3/7W2zfvh033XQTnnnmGeTk5FzxfKPRiLKyMtx6660djt96660oLCzscCw1NdX1d71eDwAYMWJEh2NVVVUAgOrqapSWlmL+/Pnw8/Nz3V544QWcO3euw3XT09M73I+MjMTXX3+N/Px8PPHEE7DZbJg7dy5uv/12OByOLl/Lj+trv057PXl5eYiJicGQIUM6fW5ubi42b97codaZM2fC4XCgqKioy69JRJ3jAGUiukxiYiIEQUBhYWGXU6oVCufvSu3BCHAO6P2xzMxMXLhwAZ9++in27NmDqVOnYuHChfjv//7vK379n4YsURQvO6ZWqy87/6fH2sNI+59vvvkmxowZ0+E6SqWyw31fX99Oa0pJSUFKSgoWLlyIgwcPYsKECcjOzsbkyZM7Pf/Htfy0Hm9v706f087hcGDBggV44oknLnssLi7uis8losuxZYeILhMcHIyZM2di/fr1aGpquuzxhoYGhIWFAQDKy8tdxzubRh4WFoZ58+Zh69atWLt2LTZu3AgA0Gg0AAC73e46NyAgAFFRUTh48GCHa+Tk5GDYsGHdfj16vR7R0dE4f/48Bg8e3OGWkJBw3dcbPnw4AHT6vbkWqampuHjxIk6fPt3p4zfffDOOHz9+Wa2DBw92fd+I6NqxZYeIOvXGG29g/PjxuOWWW/DHP/4RqampaG1tRVZWFjZs2IDCwkKMHTsWL730EgYMGICamhr87ne/63CNP/zhD0hLS0NycjIsFgv+93//1xVawsPD4e3tjZ07dyImJgZeXl7Q6XR4+umn8fzzz2PQoEG46aab8PbbbyMvLw/vvvvuDb2eFStW4IknnkBAQAAyMzNhsVhw5MgR1NfXY8mSJV0+77e//S2ioqIwZcoUxMTEoLy8HC+88ALCwsIwbty4btWSkZGBiRMn4v7778eaNWswePBgnDx5EoIg4Pbbb8ezzz6LsWPHYuHChXjkkUfg6+uLwsJCZGVlYd26dd39FhD1W2zZIaJOJSQk4LvvvsPkyZOxdOlSpKSkYPr06di7dy82bNgAAHjrrbdgs9mQnp6OJ598Ei+88EKHa2g0GixbtgypqamYOHEilEoltm/fDgBQqVR47bXX8Le//Q1RUVGYPXs2AOCJJ57A0qVLsXTpUowYMQI7d+7Exx9/jMTExBt6Pb/5zW/w97//HZs3b8aIESOQkZGBzZs3X7VlZ9q0aTh06BB+/vOfY8iQIbj//vvh5eWFvXv3IiQkpNv1fPDBBxg9ejR++ctfYvjw4XjmmWdcrVypqanIzs7GmTNnMGHCBIwaNQq///3vERkZ2e2vR9SfCeKPO9yJiIiIZIYtO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQka/8fmsZVtUI51koAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting histplot for each feature\n",
    "for i in data.columns:\n",
    "    sns.histplot(data[i],kde=True)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b94deb50",
   "metadata": {},
   "source": [
    "from above hist plot we observe that\n",
    "1.Customersince is normally distrubuted.\n",
    "2.HighestSpend,MonthlyAverageSpend is right skewed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "dae93aeb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Mortgage\n",
      "[  0.  155.  104.  134.  111.  252.5 163.  159.   97.  122.  193.  198.\n",
      " 153.  211.  207.  240.  112.  132.  118.  174.  126.  236.  166.  136.\n",
      " 103.  101.  251.  161.  149.  188.  116.  135.  244.  164.   81.  140.\n",
      "  95.   89.   90.  105.  100.  209.  249.   91.   98.  145.  150.  169.\n",
      "  99.   78.  113.  117.  121.  138.   77.  158.  109.  131.   88.  129.\n",
      " 196.  123.  167.  190.  248.   82.  185.  148.  175.  147.  220.  133.\n",
      " 182.  125.  124.  224.  141.  119.  139.  115.  172.  156.  221.  108.\n",
      " 179.  176.   76.   87.  203.  180.  230.  137.  152.  144.   94.  208.\n",
      "  83.  218.  205.  227.  239.   85.  160.   75.  107.   92.  187.  106.\n",
      " 214.  127.  252.  170.  177.   79.  232.  212.  250.   84.  130.  204.\n",
      " 157.  231.  247.  229.   86.  142.  184.  233.  215.  197.  228.  128.\n",
      " 241.  178.  162.  234.  219.  181.  120.  200.  222.  154.  171.  146.\n",
      " 110.  201.  237.  102.   93.  195.  194.  238.  226.  114.  245.  151.\n",
      " 199.   80.  186.  246.  242.  143.  223.  192.  217.  168.  165.  183.\n",
      " 216.  191.  213.  235.  206.  189.  202.   96.  210.  225.  243.  173. ]\n",
      "\n",
      "\n",
      "Security\n",
      "[1 0]\n",
      "\n",
      "\n",
      "CreditCard\n",
      "[0 1]\n",
      "\n",
      "\n",
      "LoanOnCard\n",
      "[0. 1.]\n",
      "\n",
      "\n",
      "CustomerSince\n",
      "[ 1 19 15  9  8 13 27 24 10 39  5 23 32 41 30 14 18 21 28 31 11 16 20 35\n",
      "  6 25  7 12 26 37 17  2 36 29  3 22 -1 34  0 38 40 33  4 -2 42 -3 43]\n",
      "\n",
      "\n",
      "HighestSpend\n",
      "[ 49.   34.   11.  100.   45.   29.   72.   22.   81.  180.  105.  114.\n",
      "  40.  112.  130.  186.5  21.   25.   63.   62.   43.  152.   83.  158.\n",
      "  48.  119.   35.   41.   18.   50.  121.   71.  141.   80.   84.   60.\n",
      " 132.  104.   52.    8.  131.   44.  139.   93.   39.  125.   32.   20.\n",
      " 115.   69.   85.  135.   12.  133.   19.   82.  109.   42.   78.   51.\n",
      " 113.  118.   64.  161.   94.   15.   74.   30.   38.    9.   92.   61.\n",
      "  73.   70.  149.   98.  128.   31.   58.   54.  124.  163.   24.   79.\n",
      " 134.   23.   13.  138.  171.  168.   65.   10.  148.  159.  169.  144.\n",
      " 165.   59.   68.   91.  172.   55.  155.   53.   89.   28.   75.  170.\n",
      " 120.   99.  111.   33.  129.  122.  150.  110.  101.  140.  153.  173.\n",
      " 174.   90.  179.  145.  183.  182.   88.  160.  164.   14.  175.  103.\n",
      " 108.  185.  154.  102.  162.  142.   95.  184.  181.  143.  123.  178.\n",
      " 151. ]\n",
      "\n",
      "\n",
      "HiddenScore\n",
      "[4 3 1 2]\n",
      "\n",
      "\n",
      "MonthlyAverageSpend\n",
      "[1.6  1.5  1.   2.7  0.4  0.3  0.6  5.2  2.4  0.1  3.8  2.5  2.   4.7\n",
      " 0.5  0.9  1.2  0.7  3.9  0.2  2.2  3.3  1.8  2.9  1.4  5.   2.3  1.1\n",
      " 4.5  2.1  1.7  0.   2.8  3.5  4.   2.6  1.3  3.   4.6  3.6  1.75 2.67\n",
      " 4.1  1.9  4.3  5.1  3.1  0.8  3.7  0.75 2.33 4.9  0.67 3.2  4.33 4.2\n",
      " 4.4  3.4  1.67 1.33 4.25 4.8  3.25 4.75 4.67 3.67 3.33 2.75]\n",
      "\n",
      "\n",
      "Level\n",
      "[1 2 3]\n"
     ]
    }
   ],
   "source": [
    "#checking unique values in each feature\n",
    "for i in data.columns:\n",
    "    print(\"\\n\")\n",
    "    print(i)\n",
    "    print(data[i].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77318d65",
   "metadata": {},
   "source": [
    "Since Mortgage,customeSince,HighestSpend,MonthlyAverageSpend has more unique values.So I'm doing transformation to only this columns."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a409e49",
   "metadata": {},
   "source": [
    "## Min Max Scaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "afb39433",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "cols=['Mortgage','CustomerSince','HighestSpend','MonthlyAverageSpend']\n",
    "scaler=MinMaxScaler()\n",
    "for i in cols:\n",
    "    data[i]=scaler.fit_transform(data[[i]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d20744c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Mortgage</th>\n",
       "      <th>Security</th>\n",
       "      <th>CreditCard</th>\n",
       "      <th>LoanOnCard</th>\n",
       "      <th>CustomerSince</th>\n",
       "      <th>HighestSpend</th>\n",
       "      <th>HiddenScore</th>\n",
       "      <th>MonthlyAverageSpend</th>\n",
       "      <th>Level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0.229692</td>\n",
       "      <td>4</td>\n",
       "      <td>0.307692</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
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       "      <td>3</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.016807</td>\n",
       "      <td>1</td>\n",
       "      <td>0.192308</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.260870</td>\n",
       "      <td>0.515406</td>\n",
       "      <td>1</td>\n",
       "      <td>0.519231</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.239130</td>\n",
       "      <td>0.207283</td>\n",
       "      <td>4</td>\n",
       "      <td>0.192308</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mortgage  Security  CreditCard  LoanOnCard  CustomerSince  HighestSpend  \\\n",
       "0       0.0         1           0         0.0       0.086957      0.229692   \n",
       "1       0.0         1           0         0.0       0.478261      0.145658   \n",
       "2       0.0         0           0         0.0       0.391304      0.016807   \n",
       "3       0.0         0           0         0.0       0.260870      0.515406   \n",
       "4       0.0         0           1         0.0       0.239130      0.207283   \n",
       "\n",
       "   HiddenScore  MonthlyAverageSpend  Level  \n",
       "0            4             0.307692      1  \n",
       "1            3             0.288462      1  \n",
       "2            1             0.192308      1  \n",
       "3            1             0.519231      2  \n",
       "4            4             0.192308      2  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "27e93e9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "X=data.iloc[:,:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "950e5b62",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=data.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1377bd4",
   "metadata": {},
   "source": [
    "## Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f37d7bba",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0b409d38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Security</th>\n",
       "      <th>CreditCard</th>\n",
       "      <th>LoanOnCard</th>\n",
       "      <th>CustomerSince</th>\n",
       "      <th>HighestSpend</th>\n",
       "      <th>HiddenScore</th>\n",
       "      <th>MonthlyAverageSpend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1522</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.043478</td>\n",
       "      <td>0.521008</td>\n",
       "      <td>4</td>\n",
       "      <td>0.442308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>0.764356</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.782609</td>\n",
       "      <td>0.750700</td>\n",
       "      <td>2</td>\n",
       "      <td>0.750000</td>\n",
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       "    <tr>\n",
       "      <th>358</th>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.195652</td>\n",
       "      <td>0.745098</td>\n",
       "      <td>2</td>\n",
       "      <td>0.832692</td>\n",
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       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.804348</td>\n",
       "      <td>0.190476</td>\n",
       "      <td>3</td>\n",
       "      <td>0.288462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.391304</td>\n",
       "      <td>0.845938</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Mortgage  Security  CreditCard  LoanOnCard  CustomerSince  HighestSpend  \\\n",
       "1522  1.000000         0           1         0.0       0.043478      0.521008   \n",
       "835   0.764356         0           1         0.0       0.782609      0.750700   \n",
       "358   0.000000         0           0         0.0       0.195652      0.745098   \n",
       "138   0.000000         1           1         0.0       0.804348      0.190476   \n",
       "299   0.000000         0           0         1.0       0.391304      0.845938   \n",
       "\n",
       "      HiddenScore  MonthlyAverageSpend  \n",
       "1522            4             0.442308  \n",
       "835             2             0.750000  \n",
       "358             2             0.832692  \n",
       "138             3             0.288462  \n",
       "299             1             1.000000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cc298b93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1522    3\n",
       "835     1\n",
       "358     1\n",
       "138     1\n",
       "299     3\n",
       "Name: Level, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c409fc0f",
   "metadata": {},
   "source": [
    "## Model Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fe8442eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score,classification_report\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier,AdaBoostClassifier,GradientBoostingClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from lightgbm import LGBMClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1779187c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTreeClassifier(max_depth=16)\n",
      " \n",
      "0.7369696969696969\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.81      0.80      0.81       717\n",
      "           2       0.67      0.67      0.67       455\n",
      "           3       0.69      0.71      0.70       478\n",
      "\n",
      "    accuracy                           0.74      1650\n",
      "   macro avg       0.72      0.73      0.72      1650\n",
      "weighted avg       0.74      0.74      0.74      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n",
      "RandomForestClassifier(max_depth=20)\n",
      " \n",
      "0.7533333333333333\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.82      0.81      0.82       712\n",
      "           2       0.67      0.71      0.69       428\n",
      "           3       0.73      0.71      0.72       510\n",
      "\n",
      "    accuracy                           0.75      1650\n",
      "   macro avg       0.74      0.74      0.74      1650\n",
      "weighted avg       0.75      0.75      0.75      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n",
      "AdaBoostClassifier()\n",
      " \n",
      "0.4909090909090909\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.66      0.59      0.62       782\n",
      "           2       0.35      0.36      0.36       436\n",
      "           3       0.38      0.44      0.41       432\n",
      "\n",
      "    accuracy                           0.49      1650\n",
      "   macro avg       0.46      0.46      0.46      1650\n",
      "weighted avg       0.50      0.49      0.50      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n",
      "GradientBoostingClassifier()\n",
      " \n",
      "0.5981818181818181\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.74      0.68      0.71       770\n",
      "           2       0.44      0.53      0.48       376\n",
      "           3       0.54      0.53      0.53       504\n",
      "\n",
      "    accuracy                           0.60      1650\n",
      "   macro avg       0.57      0.58      0.57      1650\n",
      "weighted avg       0.61      0.60      0.60      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n",
      "SVC()\n",
      " \n",
      "0.4618181818181818\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.59      0.58      0.59       718\n",
      "           2       0.39      0.34      0.36       513\n",
      "           3       0.35      0.41      0.37       419\n",
      "\n",
      "    accuracy                           0.46      1650\n",
      "   macro avg       0.44      0.44      0.44      1650\n",
      "weighted avg       0.47      0.46      0.46      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n",
      "KNeighborsClassifier()\n",
      " \n",
      "0.5678787878787879\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.72      0.62      0.67       813\n",
      "           2       0.46      0.52      0.49       402\n",
      "           3       0.45      0.51      0.48       435\n",
      "\n",
      "    accuracy                           0.57      1650\n",
      "   macro avg       0.54      0.55      0.54      1650\n",
      "weighted avg       0.59      0.57      0.57      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n",
      "LGBMClassifier()\n",
      " \n",
      "0.7715151515151515\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.83      0.81      0.82       713\n",
      "           2       0.71      0.73      0.72       442\n",
      "           3       0.75      0.75      0.75       495\n",
      "\n",
      "    accuracy                           0.77      1650\n",
      "   macro avg       0.76      0.76      0.76      1650\n",
      "weighted avg       0.77      0.77      0.77      1650\n",
      "\n",
      "_________________________ THE END  _________________________\n"
     ]
    }
   ],
   "source": [
    "lst=[DecisionTreeClassifier(max_depth=16,criterion='gini'),RandomForestClassifier(max_depth=20,criterion='gini'),AdaBoostClassifier(),GradientBoostingClassifier(),SVC(),KNeighborsClassifier(),LGBMClassifier()]\n",
    "for i in lst:\n",
    "    model=i.fit(X_train,y_train)\n",
    "    y_pred=model.predict(X_test)\n",
    "    print(i)\n",
    "    print(\" \")\n",
    "    print(accuracy_score(y_pred,y_test))\n",
    "    print(classification_report(y_pred,y_test))\n",
    "    print(f\"{'_'*25} THE END  {'_'*25}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeffbb9b",
   "metadata": {},
   "source": [
    "## Hyperparameter Tuning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8106f824",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8042424242424242\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.85      0.85      0.85       706\n",
      "           2       0.75      0.77      0.76       438\n",
      "           3       0.78      0.76      0.77       506\n",
      "\n",
      "    accuracy                           0.80      1650\n",
      "   macro avg       0.80      0.80      0.80      1650\n",
      "weighted avg       0.80      0.80      0.80      1650\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model=RandomForestClassifier(max_depth=20,criterion='entropy',n_estimators=300,max_features='log2',min_samples_leaf=1,min_samples_split=2,random_state=42).fit(X_train,y_train)\n",
    "y_pred=model.predict(X_test)\n",
    "print(accuracy_score(y_pred,y_test))\n",
    "print(classification_report(y_pred,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "cf7c6257",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8115151515151515\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.87      0.85      0.86       726\n",
      "           2       0.73      0.78      0.76       423\n",
      "           3       0.79      0.78      0.79       501\n",
      "\n",
      "    accuracy                           0.81      1650\n",
      "   macro avg       0.80      0.80      0.80      1650\n",
      "weighted avg       0.81      0.81      0.81      1650\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model=LGBMClassifier(n_estimators=200,num_leaves=63,learning_rate=.8,min_child_samples=10,subsample=1,reg_alpha=.5,reg_lambda=0,random_state=42).fit(X_train,y_train)\n",
    "y_pred=model.predict(X_test)\n",
    "print(accuracy_score(y_pred,y_test))\n",
    "print(classification_report(y_pred,y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "642f76ee",
   "metadata": {},
   "source": [
    "## Final Output\n",
    "\n",
    "I have achived 80% accuracy RandomForest Classifier and 81% accuracy from LGBMClassifier.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f81947ec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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