HAC_Kmeans_Clustering.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## Importing the libraries"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "pd.pandas.set_option('display.max_columns',None) #To make sure all the columns are displayed"
      ],
      "outputs": [],
      "execution_count": 4,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Q1  Univariate Analysis"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "dataset = pd.read_excel(\"Credit Card Customer Data.xlsx\")"
      ],
      "outputs": [],
      "execution_count": 5,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.head() #Check the head of the dataframe"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 6,
          "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>Sl_No</th>\n      <th>Customer Key</th>\n      <th>Avg_Credit_Limit</th>\n      <th>Total_Credit_Cards</th>\n      <th>Total_visits_bank</th>\n      <th>Total_visits_online</th>\n      <th>Total_calls_made</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>87073</td>\n      <td>100000</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>38414</td>\n      <td>50000</td>\n      <td>3</td>\n      <td>0</td>\n      <td>10</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>17341</td>\n      <td>50000</td>\n      <td>7</td>\n      <td>1</td>\n      <td>3</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>40496</td>\n      <td>30000</td>\n      <td>5</td>\n      <td>1</td>\n      <td>1</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>47437</td>\n      <td>100000</td>\n      <td>6</td>\n      <td>0</td>\n      <td>12</td>\n      <td>3</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "   Sl_No  Customer Key  Avg_Credit_Limit  Total_Credit_Cards  \\\n0      1         87073            100000                   2   \n1      2         38414             50000                   3   \n2      3         17341             50000                   7   \n3      4         40496             30000                   5   \n4      5         47437            100000                   6   \n\n   Total_visits_bank  Total_visits_online  Total_calls_made  \n0                  1                    1                 0  \n1                  0                   10                 9  \n2                  1                    3                 4  \n3                  1                    1                 4  \n4                  0                   12                 3  "
          },
          "metadata": {}
        }
      ],
      "execution_count": 6,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.info() #Total 660 entries"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 660 entries, 0 to 659\n",
            "Data columns (total 7 columns):\n",
            " #   Column               Non-Null Count  Dtype\n",
            "---  ------               --------------  -----\n",
            " 0   Sl_No                660 non-null    int64\n",
            " 1   Customer Key         660 non-null    int64\n",
            " 2   Avg_Credit_Limit     660 non-null    int64\n",
            " 3   Total_Credit_Cards   660 non-null    int64\n",
            " 4   Total_visits_bank    660 non-null    int64\n",
            " 5   Total_visits_online  660 non-null    int64\n",
            " 6   Total_calls_made     660 non-null    int64\n",
            "dtypes: int64(7)\n",
            "memory usage: 36.2 KB\n"
          ]
        }
      ],
      "execution_count": 7,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "features = ['Total_visits_bank','Total_visits_online','Total_calls_made']"
      ],
      "outputs": [],
      "execution_count": 8,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "for feature in features:\n",
        "    sns.distplot(dataset[feature]) #Checking the distributions of the interactions\n",
        "    plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 9,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.drop(['Sl_No','Customer Key'],axis=1).describe()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 10,
          "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>Avg_Credit_Limit</th>\n      <th>Total_Credit_Cards</th>\n      <th>Total_visits_bank</th>\n      <th>Total_visits_online</th>\n      <th>Total_calls_made</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>660.000000</td>\n      <td>660.000000</td>\n      <td>660.000000</td>\n      <td>660.000000</td>\n      <td>660.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>34574.242424</td>\n      <td>4.706061</td>\n      <td>2.403030</td>\n      <td>2.606061</td>\n      <td>3.583333</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>37625.487804</td>\n      <td>2.167835</td>\n      <td>1.631813</td>\n      <td>2.935724</td>\n      <td>2.865317</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>3000.000000</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>10000.000000</td>\n      <td>3.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>18000.000000</td>\n      <td>5.000000</td>\n      <td>2.000000</td>\n      <td>2.000000</td>\n      <td>3.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>48000.000000</td>\n      <td>6.000000</td>\n      <td>4.000000</td>\n      <td>4.000000</td>\n      <td>5.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>200000.000000</td>\n      <td>10.000000</td>\n      <td>5.000000</td>\n      <td>15.000000</td>\n      <td>10.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "       Avg_Credit_Limit  Total_Credit_Cards  Total_visits_bank  \\\ncount        660.000000          660.000000         660.000000   \nmean       34574.242424            4.706061           2.403030   \nstd        37625.487804            2.167835           1.631813   \nmin         3000.000000            1.000000           0.000000   \n25%        10000.000000            3.000000           1.000000   \n50%        18000.000000            5.000000           2.000000   \n75%        48000.000000            6.000000           4.000000   \nmax       200000.000000           10.000000           5.000000   \n\n       Total_visits_online  Total_calls_made  \ncount           660.000000        660.000000  \nmean              2.606061          3.583333  \nstd               2.935724          2.865317  \nmin               0.000000          0.000000  \n25%               1.000000          1.000000  \n50%               2.000000          3.000000  \n75%               4.000000          5.000000  \nmax              15.000000         10.000000  "
          },
          "metadata": {}
        }
      ],
      "execution_count": 10,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        " 1. There are no missing values\n",
        " 2. A customer carries ~5 CreditCards on an average and visits ~2 times on an average\n",
        " 3. There are customers who do not visit banks / online/calls \n"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "### Creating a new feature with total interaction with banks  for analysis\n",
        "data=dataset.copy() #Copying the dataset into a new memory\n",
        "data['Total_interactions'] = data['Total_visits_bank'] + data['Total_visits_online'] + data['Total_calls_made']\n",
        "# Total interactions = total calls + totals visits in banks + total online visits\n",
        "plt.figure(figsize=(12,8))\n",
        "feature_perc=[]\n",
        "for feature in features:\n",
        "    feature_perc.append((data[feature].sum()/data['Total_interactions'].sum())*100)\n",
        "plt.pie(feature_perc,labels=['Bank Visits','Online Visits','Calls Made'],autopct='%1.2f',colors='RGB',textprops=dict(color=\"w\"))\n",
        "plt.legend()\n",
        "plt.title(\"% age of interactions with respect to the medium\")\n",
        "plt.show()\n",
        "\n"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "C:\\Users\\mohit\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:9: MatplotlibDeprecationWarning: Support for uppercase single-letter colors is deprecated since Matplotlib 3.1 and will be removed in 3.3; please use lowercase instead.\n",
            "  if __name__ == '__main__':\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x576 with 1 Axes>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 11,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "##  Q2,Q3,Q4 - Perform EDA  ,Create Visualizations and present insights"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "#Finding duplicate rows\n",
        "dataset[dataset.duplicated(subset=None, keep='first')]"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 12,
          "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>Sl_No</th>\n      <th>Customer Key</th>\n      <th>Avg_Credit_Limit</th>\n      <th>Total_Credit_Cards</th>\n      <th>Total_visits_bank</th>\n      <th>Total_visits_online</th>\n      <th>Total_calls_made</th>\n    </tr>\n  </thead>\n  <tbody>\n  </tbody>\n</table>\n</div>",
            "text/plain": "Empty DataFrame\nColumns: [Sl_No, Customer Key, Avg_Credit_Limit, Total_Credit_Cards, Total_visits_bank, Total_visits_online, Total_calls_made]\nIndex: []"
          },
          "metadata": {}
        }
      ],
      "execution_count": 12,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "* There are no duplicate entries in the dataset"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "data = dataset.drop(['Sl_No','Customer Key'],axis=1).copy()\n",
        "sns.pairplot(data) #Pairplot from seaborn library"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 13,
          "data": {
            "text/plain": "<seaborn.axisgrid.PairGrid at 0x1b8b41c03c8>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 900x900 with 30 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 13,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "data.corr() #Checking the correlation of the features"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 14,
          "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>Avg_Credit_Limit</th>\n      <th>Total_Credit_Cards</th>\n      <th>Total_visits_bank</th>\n      <th>Total_visits_online</th>\n      <th>Total_calls_made</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Avg_Credit_Limit</th>\n      <td>1.000000</td>\n      <td>0.608860</td>\n      <td>-0.100312</td>\n      <td>0.551385</td>\n      <td>-0.414352</td>\n    </tr>\n    <tr>\n      <th>Total_Credit_Cards</th>\n      <td>0.608860</td>\n      <td>1.000000</td>\n      <td>0.315796</td>\n      <td>0.167758</td>\n      <td>-0.651251</td>\n    </tr>\n    <tr>\n      <th>Total_visits_bank</th>\n      <td>-0.100312</td>\n      <td>0.315796</td>\n      <td>1.000000</td>\n      <td>-0.551861</td>\n      <td>-0.506016</td>\n    </tr>\n    <tr>\n      <th>Total_visits_online</th>\n      <td>0.551385</td>\n      <td>0.167758</td>\n      <td>-0.551861</td>\n      <td>1.000000</td>\n      <td>0.127299</td>\n    </tr>\n    <tr>\n      <th>Total_calls_made</th>\n      <td>-0.414352</td>\n      <td>-0.651251</td>\n      <td>-0.506016</td>\n      <td>0.127299</td>\n      <td>1.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "                     Avg_Credit_Limit  Total_Credit_Cards  Total_visits_bank  \\\nAvg_Credit_Limit             1.000000            0.608860          -0.100312   \nTotal_Credit_Cards           0.608860            1.000000           0.315796   \nTotal_visits_bank           -0.100312            0.315796           1.000000   \nTotal_visits_online          0.551385            0.167758          -0.551861   \nTotal_calls_made            -0.414352           -0.651251          -0.506016   \n\n                     Total_visits_online  Total_calls_made  \nAvg_Credit_Limit                0.551385         -0.414352  \nTotal_Credit_Cards              0.167758         -0.651251  \nTotal_visits_bank              -0.551861         -0.506016  \nTotal_visits_online             1.000000          0.127299  \nTotal_calls_made                0.127299          1.000000  "
          },
          "metadata": {}
        }
      ],
      "execution_count": 14,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Key Observations:\n",
        "\n",
        "**Customers with Avg_Credit_Limit > ~60,000 which maybe loyal customers make fewer calls (0-2.5) than the customers with   Avg_Credit_Limit ~10,000 to 25000**\n",
        "\n",
        "**Customers with 1-4 Credit Cards make more than 5 calls (5-10)**\n",
        "\n",
        "**People with lower limit, makes more visits to the bank**\n",
        "\n",
        "**Customers who visits banks less frequently makes more phone calls**10. "
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Total_Credit_Cards v/s Avg_Credit_Limit"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "sns.scatterplot(x='Avg_Credit_Limit',y='Total_Credit_Cards',data=dataset)"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 15,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b579d948>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x504 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 15,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "1.There are two clusters:\n",
        "    **Customers with Average Credit Limit <100000 And Customers with Average Credit Limit < 75000**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Avg_Credit_Limit vs Total_visits_banks\n"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "sns.scatterplot(x='Total_visits_bank',y='Avg_Credit_Limit',data=dataset) "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 16,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b41ba308>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x504 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 16,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**People with Average Limit > ~70000 make 0 to 1 visits to the bank**\n",
        "**People with Average Credit Limit < ~70000 visit frequently i.e. 2 to 5 times**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Avg_Credit_Limit v/s Total_visits_online "
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "sns.scatterplot(x='Total_visits_online',y='Avg_Credit_Limit',data=dataset) "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 17,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b5b71448>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x504 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 17,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There clearly seems to be differentiated 2 clusters on the basis of above two features**\n",
        "\n",
        "**People with Average Credit Limit >75000 visits more frequently online(>7 times)**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "###  Total_Credit_Cards v/s Total_visits_online graph"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "sns.scatterplot(x='Total_visits_online',y='Total_Credit_Cards',size='Avg_Credit_Limit',data=dataset) "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 18,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b5b483c8>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x504 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 18,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There seems to be two differentiable clusters on the basis of above two features**\n",
        "\n",
        "**Customers with more than 7 credit cards and with Average Limit > 80000 visits  online more frequently**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Total_visits_online v/s Total_calls_made\n"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "sns.scatterplot(x='Total_visits_online',y='Total_calls_made',size='Avg_Credit_Limit',data=dataset) \n",
        "\n",
        "#Dots are sized relative to the Avg_Credit_Limit"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 19,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b5f24288>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x504 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 19,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There seems to be cleary two clusters on the above two features**\n",
        "\n",
        "**Customers who visit less frequently online make more phone calls**\n",
        "\n",
        "**People with Average credit limit >80000 make more frequent online visits**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Creating a new feature with total interaction with banks  for analysis"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "### Creating a new feature with total interaction with banks  for analysis\n",
        "data=dataset.copy() #Copying the dataset into a new memory\n",
        "data['Total_interactions'] = data['Total_visits_bank'] + data['Total_visits_online'] + data['Total_calls_made']\n",
        "# Total interactions = total calls + totals visits in banks + total online visits"
      ],
      "outputs": [],
      "execution_count": 20,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(x='Avg_Credit_Limit',y='Total_interactions',data=data)"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 21,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b56e1188>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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KEOJe4Hr0wood5rRlfGBtoeezMDlN4evyMnhwk74CYY1pJbsrbZ7P/+f93nfYSnNWerYf2lzKQ5tLIxmyIs6Y05bxwMZiHthYHO9QFCGizln4hHpb6VPA/cBnpZQ9wC7g8ahFpVAoFIq4EtLgIKU8gdOqekAIkQ/8NaCm3SgUCsUcJaTbSkKIL+B8p7N2svA0UBSNoBQKhUIRX0J95vAJwCalVKtGFIogZGXpv1VQoYgk0b7OQh0cOgD9lygnOW7nStvwRT5eXsKbHYOU5KzkVM8oh84OUlWcS12ZhdbBC7x04hzbS81UFmUzcfU6J7pH+EP/eR6pKOVY5wgH2vupsuayeVU2K25Zwl6tV2lNXsxf1qGILTf9PX3UjTGn/D2zdRPNJr82b02pmXLXDME7CjLnVB+HSqyus1AHB4nzeUMDcNmzU8qvRTyiGKJ1rrR+8T4++EwDT+zcwq7/bPLzsLzyWD1PHW7lqcOtHPzMPXz6Z0c41TvGG5+6mwdfOOCV/uBn7uEjPzjo71V6fIcaIOYo/v4e+5zx98zWTTSb/EZ5tT6zudDHoRLL6yzU2UqDwF5gAbBM819S43auPFpp42B7P6kpi3ln4Lyuh2WfvY+vvncjd67O4YTLsXTn6hy/9NrjvmU0qOX6c5a57O+Zbdtmk98or9ZnNhf6OFRieZ2FOlvpy8C/AE3AEeCbrn1Jjdu5Ur4qi0OOQWw5aZzs1n+LV6NjgIqiHK80eukDlzF/LuL5xlz298y2bbPJb5RX6zObC30cKrG8zkJ1K90NnMI5nfWTwB+EEO+NeDQxxu1caekaYas1F/vQOBsK9B/yVFtNNHcMeaXRSx+4DLVcf64yl/09s23bbPIb5dX6zOZCH4dKLK+zUG8rfQ2okVLulFJ+AKgCvh7xaGKM27nyzBE720rMTFyd4lZTuq6HpdZm4Uu/PcHhc0NsdDmWDp8b8kuvPe5bRv08uojnG3PZ3zPbts0mv1Ferc9sLvRxqMTyOgv1gXSKlNLu/iClbBVCLAiWSQhRCfyjlLJWCLERp6zvOnAFeNh3aqwQ4jhw3vXRIaXcFWJ8M0LrXHnp+Fl+9Wg9RzuHeO4jVZzuHaXJMUi11UStzYx96AKfuLPM5WS5hRc+Ws3JnhHekD289PB2jnWNcKCtnyqricxlKbzyWD37PF4lM/VlFvUweg6jvZYaWnupL8ubM/6e2bqJZpPfN2+NzcymVdk8d8TOfz60bc70cajE8joLdXDoEkL8JfAczsVvjwGdgTIIIT4PPARMuHZ9E/grKeUJIcQngS8An9OkvwVASlkbTgNmi9u54qYo0ynGu6Mgy8uJtCojlVpbnlfe2/MzPdvClM5HfFxMyqs0v3BfS1vSp7Fai+McTWSZrZtoNvn18n79/Un/xoAZE6vrLNTbSo8C9UAX0AvU4VwYF4g24EOazw+6NBzgHJQu+6TfACwXQrwuhGgQQtwZYmwKRUIxMqI/IUGhiCTRvs4WTE9PR61wIUQx8CMp5Z2afVuBZ4DtUspBzf71wJ3A00AZ8FtASCmnjMpvaWkpBhxRCV6hUCjmPtby8vKzegcC3lYSQvxCSnmfEKIV5+0kL6SUa8KJQgjxYeB/AvdqBwYXZwC7lHIaOCOEGAbyCHL7CmDdunUsXbo0YJqWlhbKy8vDCTdmqNjCJ1HjgsSNLVHjAhXbTJhNXFeuXOH06dMB0wR75vAZ1//fM6MINAghPo5zGmytlFLv99BuYD3waZf5dSXOW1gKhUKhiDEBBwcpZZdr8+tSyge0x4QQrwN/EkolQohFwL/idDS9LIQA2C+l/IoQ4gWcxtdngOeFEI04f6XsDnRLKVJ0n7/Eye5h1loy2d/Wz9t9Y+yutNHSNcKBtj6qrCbqbBYaHQPss/dRU2ph06osnmtu4zZzOuvzM2kbvEBViZnp6Wn22fs50N7HthIzmwuzea65jTW5K6my5rLylhTyDN5DrUhstH6f970rn/LCHBrb+2fsGkpEZutPinZ5sahTL/+SJUuiGHHiEuy20k+B24FCIcQZzaElQNDlvlLKszifIwDorgyTUj6s+fjRYGVGku7zl7j3qT28vKuWnc/u9biSPuzlSrJ7XC5PHbZ7fXa7XZ7YuQXH8LjHt+Sbz53uyfsruTE9raa0Jhm+PpsHNhZz71N7ZuwaSkRm60+KdnmxqNMo/y8ero5KvIlOsNlKjwHvAxpw3lp6r+u/WmBbVCOLAXvO9FJRlMPB9n5DVxJ4u1x8P5/qHWNs8gqn+8aCOmBO9ozyVs9ozNqniAxan02gaySZHT+RdvbEwzUVLQfUoY7hiMWYTAQcHKSUY67Fb48Bj0op23AuYvsKkB6D+KJKk2PA41WCwF4krcvF9/PY5FVaOvUvIG26E90j9F64FMkmKGKA1mcT6BpJZsdPpJ098XBNRcsBdcAxJ99WEJRQ1zm8CHS7tvuAN137kpoqq8njVYLAXiSty8X3c8ayFMoLs4Pm21iQRd5KdUsp2dD6bAJdI8ns+Im0sycerqloOaC2u74f5huhDg45UsonAaSUl6WU3waSvsd2rMmjuWOIbSVmQ1cSeLtcfD+vz8sgY9lS1lkygjpgNuRneq2qViQHWp9NoGskmR0/kXb2xMM1FS0H1NYi/T/85jqh6jMmhRB3SynfABBC1AJJf3+kIH05rz6+g7e6R/jl7joOtPfzmuzmpYe3c7xrhH1tfVRbzdTazBxyDPD4nWXUlpo9s5We/8hW1uVl0j40zlarid88voP9bf3sb+tne6mJ8lXZPN/cxjMffjfvLlazlZIVX7/PxNVrvPr4DpocAzNyDSUis/UnRbu8WNRplL/f0Qqm+fdHXUgrpIUQm4AfAu5hdRD4mJTyrSjGFhT3Cmm1CC56JGpsiRoXJG5siRoXqNhmQoQWwc1shbQbKeUx4FYhhBm4ZrCITaFQKBRzhJAGByFEBU6L6gpggWtRW7GUUilHFQqFYg4S6gPp54D/ApbjFOMNAa9EK6j5RmpqarxDMCSRY1MoFNEj1AfSV6WUTwkhCnE9bwDi+rwhUnSPTbCntY8mxwA1pWbeXZzLooULaGwf4EB7P7U2C1uLTTS2D7C/vY+qYhO1Ngu/PN3BPSKft/vGKM5O41TPKIfODlJlzWVdXiYdoxcpX5XNXnsfje0DVFlN7FiT57c6un98kpbxxXzjJ4cTTsOQyLElEr7KhcrCkniHlDDEQ6ExE0KJM1iaZGlrqIQ6OFwWQmQAErhTSrlXCBHqr46EpXtsgnufbvCsinz6iJ2Dn7nHS4PxwEYrH3xGk8alxXjlsXo+8HQDT+zcwq7/bPJbcv/yrlre71P2+rwMXn18h2eAiIdiIFQSObZEQvWTMcnSN6HEGSxNsrQ1HEL9gv8G8BOct5IeEUK8BRyPWlQxYk+r93L5O1fneGkwAqkS9tn7+PDGYsPjje0DLF+y2G9/g2a1ZjwUA6GSyLElEqqfjEmWvgkWZ2pqatA0ydLWcAh1cDgP3COlvABsxvlmuI9HLaoY0eQY8Ppsy0nz0mAEUiU0OgaoKMoxPN50dsBLt3Ez382LJR6KgVBJ5NgSCdVPxiRL3wSLc+nSpUHTJEtbwyHUweGfpZQ3AKSU41LKN6WU16MYV0yospq8PtuHxr00GIFUCdVWE80dQ4bHq4pNXrqNm/lurtaMh2IgVBI5tkRC9ZMxydI3weK8cuVK0DTJ0tZwCHVwaBNCfE8I8agQ4qPu/6IaWQzYUea9XP7wuSEvDUYgVUKtzcJLJ84aHq8uMXHp2pTf/nrNxRIPxUCoJHJsiYTqJ2OSpW+CxTkxMRE0TbK0NRxCfSB9HliGU9XtZhrnqumkpSAjlVcfq6fB7p6tZCFv5TJ+9WgdTY5B9rf1M3Bxkl89Ws8hxwD7XC//qSm18MtTHfz44Rr+0D/Gcx+p4nTvKIccg1SXmLjNksHbvaP8+rF69tn7Oejop9pqpr7M4jVbyb1cf4/s5qBjKKE0DIkcWyKhp1yoyE9X/UR8FBozIZQ4g6VJlraGQ0j6DDdCiDQppf+9kjgxV/QZ77zzDrfeemu8w9AlUWNL5POZqLElalygYpsJCaHPEEKsB34ErBRCVAJ7gQeklCdnFJnCi4mJiXiHYEgix6ZQKKJHqM8cvgV8GBiSUvYAfwN8L2pRKRQKhSKuhDo4pEopT7s/SCl/CwS+j6NQKBSKpCXUwWFUCLEO50NohBAfBsYCZ1GESnb2/HyZyGxQzieFIrqEOlvp08ALwG1CiCGgE/hIsEyu5xP/KKWsFULYgOdxDjCngb90r51wpV0G/AAwAePAn0spo/7y1u6xCRpa+2g6O8j2UjNbCrOZun6D490jvNU7yiMVNo51DnOgfYCtxbnU2ixcv36d69PQ3DHEgfZ+tpeY2VyYw7PNdm4zp7OlMJsVtyxhr8vZVGU1UV9mITVlIZnLvWcvdJ+/xIHB63y9+feG/qVgaJ0ud5VZ2FKUw4H2ft7uO8/uChtHO4c9XqiZlD+TOOpsZqpLzLR0DvGbP/Z4uWbCcdC40x7vHmV3pY2WzmH2t/WzrTiHzPHJuM8G0WvLkiVLIlZmTamZ8sJsnj1i546CzKT39SiSh1AHh0VSyncLIdJd2yNCiC2BMgghPg88BLifaD4BfElKuU8I8R1gJ/BzTZa/AE5JKf9eCPEg8CXgs+E0Jlx83UpuH8qT91fy0A+beONTd/PgCwf8jr/yWD1/6pXP6U16YucW7v7OGxz8zD185AcH/bxKrzxWz9XrN7/Qus9f4t6n9gT0LwXD1+nywMZidj67l1O9Y7zxqbt54IX9fl6ocMoPFSO3zBM7t/DU4VbP51cf3+HV5kAOGm2Zb3zqbh74/v6Q8sUKozb/4uHqiJfpvrbi3WbF/CHgbSUhxJ1CiK3AL4UQ7wbW4nzpz3bgxSBltwEf0nwuB/a7tn8L3OWTvhqnFtzoeMTxdSuB04dysmeURytsAb1Ket4kOXCeRyttnOgZNcw3NHHlZv1nenXTNYSx5F7rdNG6oAJ5ocIpfyZxaOuSA+epLMoBIDVlsWGb9Rw07jIDtSWe7hqjNh/qGDbIMfMy3f0Y7zYr5g/Bfjm8H6gB8oH/V7N/Cud7HQyRUv5MCFGs2bVASuleVDEOpPtkWYlzsZ3RcUNc83WD0tLS4tkuKyvzcyu5OdE9wqbCLI53GXuVbDlpHOkY8stXviqLYwHybV6VjcPhYMWKFYb1Nzr6uadoBZ2dnQHbk5WVxV77zS96rQsqsBcqtPLdaPstlDi0nOge8fSVLSfNsM0Nrb1sSZ9mZGTEr8xAbfHNFysCtfmAY5B3Zy8KO6ZQ+3E2bQ52LuOJii18ohlXwMFBSvklACHEI1LK52dZ1w3Ndhr+D7QvuPYbHTdkpovgqqwmnj5i90u7sSCLY50jbFxl7FX6dtMZ3XwtXSNsDOBjugFYrVZX/Rd066+2mjGZTJhMJr9jvtSNOW9rgdMF9bHyEr/t2ZQf6kIbbRxaNhZk8R9H2z0xffLda3TbXF+Wh9Va7OkbbZmB2qKXL1YYtXm7NRer1TqjmELpx5m2OVEXc4GKbSZEaBGcIaHOVtojhPi6EOK7LsfS94QQ4a5zOC6EqHVtvxc46HO8CXhfgOMRx9etBE4fyob8TJ5ptgf0Kul5k4QpnWeO2NmYn2mYLyf15iC2Y02ebrr6MGRdWqeL1gUVyAsVTvkziUNblzCle35hTVydMmyznoPGXWagtsTTXWPU5q1FM599Fqwf491mxfwh1AfSPwaOAG/ims46A/4OeEoIkQL8EfgpgBDidZy3r74NfF8I0QhcBaIu9nO7lfba+z1vgit3zVb6wceqeV328KOHt3O8a4QDbf1steZSU2phauo6P/3zGt7sHGZ/Wx81pRbKV2XzXLOd5z+ylcxlKbzyWD377H00Ogaotpqos/nPVipIX86rj++gobXXlc7fvxQMX6fL6KUr/HJ3HQfbB3hD9vDjP69xzfDpo2oG5c80jroyC1VWE8e6hvnEnWVerplQHTTatO62HOsaZr+9n23WHHaIgrg+mDVqS7+jFUyZESmzxmZm06psnjti5z8f2pb0vh5F8hCSW0kIcVxKeUcM4gmLueJWOnv2LMg0UFAAACAASURBVMXFxfEOQ5dE7bdEdT5B4vZZosYFKraZEG23Uqi3lZqEEO8VQiyaUSSKgAwPz3x2y3xFOZ8UiugS6m2lnTgXwk0LIa4DC4BpKWVK1CJTKBQKRdwIdXAojmYQ851EVkEUFRXFOwRdsrL0Z4QpFIrIEHBwEELsllI+C3zBIMnXIh9SbOkem+Bk9whr8zLZ39bvpbs4cm6Q12Wv6wU/ZjpHL1KcncZeex9NjkG2FueyPj+TcyMXWWvJYAHTpCxezF57H4dc5dTYzJzuGWVDQZauPqN/fJKW8cV84yeH+dD6QtZaMtij0W7o6S6M9Aob8jMDqhaMVBR6Covu85fYc6aXt/vG2F2ZwrGuEcO02vJPdo8gTOnsb+t35bWFlNe3XqP232x7H3VjJJ1OIhx1SKTJLizhpeOOuNQdDto+es+t+Wxalc3vzvTS3DFITamF+rLgupVEaWOixRMOwX453OL6f3K0Jkzc+oyXd9V6lBNwU2PxxM4tPH3E7vn868fqeb+ObuOJnVv4b9/fzyuP1fMBzXF3vpd31fL+pxv89Bm+qoTP16/10nno6TRC0SvoqRbCUVFotR5vfOpuPqyjEPFVOLjL1/ZlqHk95yOITsS/7fak0kkYnbtYxN8/Psl9LzQmlH5EDz0dzAef8VfVBNOtONPGt42JFk+4BHwgLaV80vX/L+v9ByCE+EUsAo0Ge1r7qCjK4WB7f0jqhwYD3YYcOM+DdxSz1+B4Y/sAWwpz/PQZWlXCo5U2wzi0uotQ9Ap6qoVwVBRuxUU42op9du++nInyIphOxKjtyaKTiGf8ydJ3RjoYLcF0K6GkjQWJFk+4hDpbKRCrI1BGXGhyDFC+KotDDn35q1tZAARUP5zoHqGiKMfweNNZZz2NjgGvDt9rv3mRBIqj0XEznTaPUaza7b2uL1Z3vkAqCndadztCSauNS9uGcPK6CaQT0bYh1PISjXjGnyx9p40z3Gso0dqYaPGESyQGh5kuios7VVYTLV0jbLXm6h7fWJCFfcj5ymz70DhVVn3dxMaCLJo7hgyPVxU763HrM9zU2W6udA0UR7X1ZjptHqNYtdt1rtXQ7nz2oXE2GOg93Gnd7QglrTYubRvCyevGqP/c7Tdqu1F5iUY840+WvtPGGe41lGhtTLR4wiUSg0PSsqPMQnPHENtKzCGpH+oNdBvClM6Pjp+lzuB4dYmJNzuH/PQZWlXCM0fshnFodReh6BX0VAvhqCjciotwtBW1Nu++nInyIphOxKjtyaKTiGf8ydJ3RjoYLcF0K6GkjQWJFk+4hLRCOhBCiGNSyk0RiicsIrFCuntsgrd6RrnNksGB9n4v3UXzuSFeO9NDtdXE9hIzXWMXWZ2Vxj67M12VNZd1eZl0jFzkNs1spf32PhrPOsvZXmrm7d5Rbs83nq20R3Zz0DHEh24v4jZzOg32fhod/YY6jf7xSV29woaCTM/2Hauy/FQL7nzHu0bYVWnzqCj0FBbd5y/R0NrH6b5RdlfYON49YphWW/5bPaOsyV3JgfZ+TveNhZzXt16j9rvb0NDaS31ZXkLqJAKtXNWeu1D6I5KcHRilued8XOoOhrbPtH30nnflc0dBNg2tvRw+N0StzUxdkJdDRbp/Z7MSOZrnO9orpCMxOMRNrTFX9BmJrIIYGBgIyd4aaxwOR1xMrKGQqNdaosYFKraZkCj6jEAEe+mPIgiJrIII9Z0PsSbW729QKOYbwRbBtaL/wNmtz1gjpfynqESmUCgUirgRbBHce2IShUKhUCgSimBvgmsDcL2D4R5gBc5fDYsAK/C/oh2gIr4kqlspO3vmL9RRKBTBCVW890PAjHNAOITzvdJRf1NbtHD7TtqGL/Lx8hLe7BhEmDJ4q3eUA219bCnKYZvVxOKFC3n1j13sXFfE/jZvn1L70AUqV+dytHOY/3qnh7vLLFQW53KwfYCTPSM8UuF0Ch1oc64crraaSLslhbyV4c1U8HWz1JdZuDENDa197G/ro6Iol7vW5PF23yiWlct5u3eMRscAW4tz2ViQRWrKIo50DHOgrZ+q4lzn7J+MVL+y3e1yDI+z1pLBc81t3GZOZ9OqLMYGL3DU5WHSupz0/E16MbvTGO0P5lNy45tuSealqLy4KJ4+nGR28Sj0SdZzGurgcAdgA74JPAt8EeeAkXRofSetX7yPDz7TwBM7t/DxFw/6+VuevL+S+9YXefmStC6j9z/tzPvU4VYe2Fjs8S698am7edDLKXSzvBs3bni+nMOJ1V33wc/cw6d/dsSv7Jd31fKh5/b5xfnk/ZU89GKj175XH6tn8aKFho6mD79wwONnctbn7+TR8zcZxez2I2m9SdpYgvmkILh3KVLE23+UzC4ehT/JfE5Dna00IKWcBt4B1ksp7UDguaMJitt34nYZpaYsxjE8rutAGbx4OaDLaPmSxciB8zxaacM+dCGoU+hkzyin+rz3hxKrmztX53C6b8yv7NSUxYZeppM9ox4/lHvfW72jobWrwsaJntGgLietK8ao3IbWXpYv8f5bpKIohz0GPqoGH8VAMO9SpFD+I0UkSeZzGurg8LYQ4hvAfuBvhRD/PYy8CYXbd+L2ANly0nizc0g37fClKwF9SracNE50j1C+KouWTufb3AL5YE50j9BzfjLsWN3YctI89fjuD8UP5ab3wmRQR9OJ7hE2FWYFbIuvv0kvZjeNjgG/OMpXZQX1KbkJNd1sUf4jRSRJ5nMa6hf8p4BfSCnfBv43zmcPH4taVFHE7Ttxe4DsQ+NsKczRTZu9fGlAn5J9aJyNBVm0dI1QXuh8QBrIB7OxIIv89NB/Svq6WexD4556fPeH4odyk7dyWVBH08aCLI51jgRsi6+/SS9mN9VWk18cLV0jQX1KbkJNN1uU/0gRSZL5nIY6OPyTlHIfgJTy51LKvwT+JmpRRRG378TtMpq4OoU1O03XgZK74paALqNL16YQpnSeOWLHlrMyqFNoQ34m6y3e+0OJ1c3hc0Oss2T4lT1xdcrQy7QhP9Pjh3Lvuz0vM7R2NdvZmJ8Z1OWkdcUYlVtflsela1Ne+5s7hthh4KOq9/nHE8y7FCmU/0gRSZL5nAbUZwghvofzFaGVwBHNocVArpRyfTiVCSEeAR5xfbwF2AhYpJRjruP/ClQB7j8xd0opzxuVN1N9htt30jY0zsfKSzjaMYQwpXOqd5R9bf2e2UWLFy7gN3/s4oPrijjQ5u1TcgyPU1GUQ0vXMP/1xx7uXpNHxeocGtsHONEzyq6KUo53jXiVl3bLEt3ZSuG4eOpsZm5Mw157H/vs/dy5Oof6sjz+0DeKeeVy/tDnfH/EVmsuG/Kds5Xe7HDONKqymqizmb1mK7nL3upq19mRcW4zZ/B8cxu3WdK5oyCLpYsX0eLyMGldTnr+Jr2Y3WmM9gfzKbnxTmeivkx/VtNsma0PZy66eKLNXI4tWuc0rm4lIUQpzltI3wT+WnNoCnhbSql/sz4EhBD/DpyUUn5Ps68RuC/UcueKWymRY0tUt9LZs2cpLi6Odxi6JOr5TNS4QMU2E+LqVpJStkkpfyelXAt0A2XAu4CRWQ4Mm4G1PgPDQlf53xNCNAkhds+0fEXkSFS30vCw/4N5hUIROUKysgohPgJ8DfgVzgHlA8DfSymfn0mlQoiXgX+TUu7V7EsDPgs8gXMF9l5gt5TyLaNy3L8cZhKDQqFQKIx/OYS6CO4LQIWUchBACPG/cH55Px9uJEKIDOBW7cDg4hLwTSnlJVe6BmADYDg4uFG3laJHosaWqHFB4saWqHGBim0mROi2kiGhzlZa5B4YAFzbNwKkD8R24Hc6+9cAjUKIRUKIJUA1cGyGdSgiRGpqaKu5Y02ixqVQzBVC/eVwSgjxT8Azrs+PAqdmWKcA2j0fhPgcYJdS/koI8SJwGLgGvOBaVxFVtN6T7SVmNhVm8XxzG7fnZ1K+KoufnTzH/RtW4xi+yG2WdBodg07/UmEO1SUmVqQsZsGCBexp7eXtvvPsqijlaOcwB9ud5a3Ly6R18Dx3FptCnlnTPTbBntY+j0OovszC4oULeV323PQPlVnoGL1Ifnoq+9v6vfYvT1nI61Lf5eLxE50doKbEQkWRc93EjWnngrLmjiG2l5ipKTWzPGUhLeOL+cZPDnt5ndz9VVNqZtOqLJ49YmetJYMdLm+Ttk9rSs1Urs7h0tXrvNUzyoF2t2vKzKKF8L3DrWzIy2RzYTbPNtu5PS+LzYXZPNPcylpzBnetyWPJogU0tPo4oC4vJXN8MuEVBIr4k6xuo3gTbLbSn0spvy+ESMVpYK3H+WtjD85nDhdiE6Y+s52t5Os9Afy8QW5nka+7yJ32yfsrAdj2rdd441N387lfvqlb3ud++aahB0gbW/fYhJdryF3Gz3fVYvvaL7z2/fqxeo/PSbv/lcfqKf7fL3vte+2TdzF1Y9rLT6Qt+0912uZbjq/XSa+/fF1JgfI9eX8ll6duePJqy9FuP3l/Jdu+9Zpunyaio2Yu3oaINtGKzejfeDjXTaL2W7zfBPdZACnlhJTy76SUd0gpN0gpPxfvgSESBPILVRbleJxFFUU5HHIMGrqL+i5M8miFzdCp1DZ0geVLFofkATJyDR1sH2B3hc2zr6IohwaDtPvsfXz1vRu99p3uHWNvgLJ9vUdu/4u7nDtX5wT1LKWmLPaL38gH5e67sUtXPI4mra9Ju63nh3I7oJLBUaOIH8nsNoo3SelHihTB/EJuZ1H5qiwaAziWxiavBvQQHe0cxpaTFpIHyMgh1HR2gPJVN1UWgb1EA1QUeStBOkYnDOtvOuvvPQJobL9ZTjBnlLu/fGMy8kG5841NXvXUrfU1GW371pkMjhpF/Ehmt1G8CTY4rBVCtOv85xBCtAfJm/AE8wu5nUUtXSNUB3AsZSxLCegh2lyYjX1oPCQPkJFDqKrYREvXzS/nwF4iE80d3stQijJTDeuvKvb3HgFUl9wsJ5gzyt1fvjEZ+aDc+TKWpXjq1vqajLZ960wGR40ifiSz2yjeBBsc7ECdzn+1rv8nNYH8Qkc6hjzOouaOIbZacw3dRZaVy3im2W7oVCrNWcmla1MheYCMXEPbSkw822z37GvuGKLeIG2tzcKXfnvCa9+6vAzqApTt6z1y+1/c5Rw+NxTUszRxdcovfiMflLvvMpYv9TiatL4m7baeH8rtgEoGR40ifiSz2yjeBHsgfVxKeUcM4wmLSOgztN6T7a7ZN883t7EhP5M7VmXxs7fOcf/tqzk7cpF3mdM55Bj0+JKqrLme2UoNrX2c7htjV0UpLV3DHGgboKbUzFpLBvbBC1QW5xrOVvKNrXtsggZ7H42OAaqtJupsztlKb5zpce0zU28z0zk2Qd7K5Rxo7/ekrbc5Zyu9cUbf5eL2EzU5+qkptbClMJsFwPVp5+2o5o4hakrNbC8xsTxlIb/9QzcHHUNeXid3f9WUmrljVRbPNttZZ8mg3nZztpInjc1MRVEOk1ev81bvKPs1rqlFC50vP9mQn0X5qmyebfbeXmvJZEeZhSWLFrDX7nZAmViXl8HZofNsLUnMWSdz8QFmtIlmbPF0ZUWTaD+QZnp62vC/NWvWfCvQ8Xj/d/To0eKjR49OX758eToYR48eDZomXiRybH/84x/jHYIuiRrX9HTins9EjWt6WsU2E2YT1+XLl6ePHj06ffTo0eJpg+/XYG6lz8xoWFLMGSYmJuIdgi6JGpdCMVeY17OVFAqFQqGPGhwSgERWQZSUlMQ7BF0Suc8UirlAqPqMOUv32AR77c4HuluLc9m0KovMZUvZ09pLk2OAu9fkcWdxLgfbB9jf1s/2EhObCrN5vtnOhvwsthRmc3nqOu/0n2ddXgbLU5awv62PJsegR/UgB86zqSCbzOVLyF3h/2KclotORcVdZRa2FOVwoL2fJsegl56iptTEhvwsL62G80H1At7w6DDMbC7M4dlmOxvyMykvzOanJ8/xZxtW09LpfOFPTamZ8sJsnj1i544C5xvhbkzDGxo1x5+IfG5MT7PP3u+lu1jANAsWLOBNbVmrsvnpW2f5s9tXc7RzmP3t/VQVm9ixxvkiHj2VxsUrU5zoHuHQ2UHuEfmUF2bT0NrL4XNDbC3OZWNBFstTFtF8bpgD7f1UuV5cpN23zZqj9BkKRRQJSdmdqMx2tpKRqkKrawikxNDqHS5P3cCalaqroXCrHp68v5LSnDTPF5rv0v5AdRVnpRrqO/TUEr76j2Dxa8sw0l0YaTaM6ghFpWHUZr126e1T+ozQSdS4QMU2E+Ktz5jTGKkq3LqGO1fnGCoxtHqHdwYukL5sMQfa+w3TLl+ymJM++gnt0v5AdS1cMM1Bg7KN1BJa/Uew+LVlGGkyUlP02xeojgZ7n5eWw7fsQG3Wa5fePqVBUCiiw7weHIz0E1odRDBlBDgXpC1fsphDjsGAaU90j9A5enOWjXZpf6C6FixYELRso/hDyafdNorDqKxAdTQ6vLUcvmWH2r+B9ikNgkIRHeb14GCkn9DqIIIpI8Apwbt0bYqt1tyAaTcWZFGYefNBqnZpf6C6pqeng5ZtFH8o+bTbRnEYlRWojmqrt5bDt+xQ+zfQPqVBUCiiw7weHIxUFW5dw+FzQ4ZKDK3e4VbTSs5PTrG9xGyY9tK1KTb46Ce0S/sD1XVjegHbDMo2Ukto9R/B4teWYaTJmLiq375AddTbLF5aDt+yA7VZr116+5QGQaGIDvP6gTQ4H0rva+unsX2ArdZc7ihwzlZqsPfS6BjgT9bkUbk6l0bHAPvt/Wx3KSOeb25jY77zJTWXp64jB86z1uKcrXTA9fKdrdZc1uW5ZiutyiZzmf5spT3Sqai4a00emwuzOdg+QJNjgBqbmTsKnHqK2hIzt+dnemk1akuds5V+55pZVVNqoXxVNs8129lQkMmmVdmelxUd6xpmv72fGpuZTauyee6InTtWZVFT6lRi/O5ML42OfqqtZu5ek8eN6Wn2t/V76S4WMM2ChQucs5I0Zf305Dn+7PYiWrpG2N/WR5XV+WIg92wlX5XGxStTnOwZ4ZBjkPfcms8dq7JpsPdy5KzTYeWemfRmxzAH2vqpLjGxPi/Ta982aw47REHCPYyGufkAM9qo2MIn2g+k5/3gkAi888473HrrrfEOQ5fR0VEyMzPjHYYfidxniXqtJWpcoGKbCWq20jwgkVUQ7e2JaWZP5D5TKOYCanBQKBQKhR9qcFAoFAqFH2pwSACysvSncyYCeXl58Q5Bl0TuM4ViLhBzt5IQ4jhw3vXRIaXcpTn2OPBJYAr4qpTy19GOp398kpPdIwhTOvs9s4yc3qLp6WnGr1zjWJfTA3TfukLW5WWwp7WPQxq/0cTVazR3DHPo7CDbS8xsKszi+WY7t7vcS08fbmWtJYMdZc6X4Wjr3mfv43j3CLtXZHv5j7YUZjN14wYLFiygyfUSnu0lFmptZvI1Lw0avDjJ6OQ1jnUNI0zpnOoZ5dDZQepsZmptFhYvhOFL12hs73e9yMfCXWssXLs+ze/O9PJ23xi7K20cc800cr7EyERqymKuTF3n9MgUG2+56OmbKquJWpuFH7S0U5q9glqb84U7wxOTTFy9wV67s2+qS5wvHmrpGubQ2SF2V9o87XPHptWIuP1LXv2Xl8X2UhNHzg3yxpk+6mxmqkvMtHQO8Zs/9lE3hlc5CoUicsR0tpIQ4hbg93pvlxNCWIA3gM3ALUAjsFlKecWovNnOVnK7jYzcQD/fVUvvhUmPz6f1i/cZprN97Rde+7TuIu32q4/Ve96W5vYqGfmFjFxGrz6+wzNNtG1onE//7IjH3xRKGVq/USC3EYBl5TLdNr+8q5ayr/3CE8/VqeuGXilAt47XPnkXgJdfKlD/+R7TlpNIA8RcnN0SbVRs4TPXZittAJYLIV4XQjQIIe7UHKsAmqSUV6SU53G+v/r2aAazz+78S9nIDXSwfYArU9epLMrh0UpbwHS7K2xe+7TuorahC57tBnufp+5TvWMB/UIH2we83ETu/ftcZZzqGeVEzyipKYtDLkPrNwrmNhq+dIU/9o/pHm90tflU7xine0dpbB/QTdc2dIHRS1d0j512tSWY+8m97XvM/Vn5lRSKyBPr20qXgH8CngbKgN8KIYSUcgpYyc3bTQDjQHoohbpGwKC0tLR4trOysthr76N8VZahG6jp7AAfvcOKLSctaLryVVk823xzn9sDdKRjiKOdw57tRscA99+Wx17XF3wgv1DT2QFPPi0H2wf4QFkOnWMTnHTVE2oZ2rTB3EZLFy8Cg1+W2jb3nJ/kSId+3xztHPaS5WnpGL3o1zZt/e64tdu+xwAaWnvZkj7NyIh+W+KB9lpLJBI1LlCxzYRoxhXrweEMYJdSTgNnhBDDQB7QCVwAtFa1NGDMvwh/ZnpbqW7MaWatsuby9BG7X56qYhM3pqexD41zy5JFAdMdbPeW+G0syOI/jjrXCGwuzOa55jbA6Rtavnw5dTYLTx22Yx8a52Pl+i/UqSo28Z1DZ/z2bysxsXLlSgozLjI5dYMXW9pDLkNbX6C6NxZkkbtiKQsX6B72anN++jKqik08ddi/bzYXZpO+LEW3jKLMFSxPWaybT9t/2m29z/VleVitxVitVv1gY8xcvA0RbVRs4ROh20qGxPq20m7gnwGEEPk4fy30uo41A9uEELcIIdKBdwGh/SSYIbU2C80dQ4ZuoG0lJpYuXsSRjiGeOWIPmO7ZZrvXPq27qDRnpWe73mbx1L0+LyOgX2hbicnLTeTeX+sqY31+JhvzM5m4OhVyGVq/UTC3UfbypbzLnKF7vNrV5vV5GazLy3QpLvzTleasJHP5Ut1j61xtCeZ+cm/7HnN/Vn4lhSLyxPqBdArwPFAETANfAO7E+WviV67ZSp/AOWh9TUr5s0DlRUKf0T8+yVs9o6zJXcmBducb4aqLTdTYLEwzzfjlaxzvdnqA7ltfyFpLBntb+2g8e9NvNHH1Gm92DnPIMajrXnr6iHO2Ur3Nf7bS/rZ+jnUNs7uyzMt/tLkwm6nr7tlKg66ZRmZqSgPPVjrdO8ohxyB1ZRZqSs2a2UrOGU+1NjM7ypyzlfa09nG6b5TdFTaOd42wz+VRqrLm3pyt1DfGxvysm31jNVFTauHFlnZKc9KoKTV7zVbab3f2zTarmTqbmWOuvttVafO0zx2bdraS27+k7b8N+ZlsKzHRfG6IN870Uldmocpq4ljXMK/+oYv6sjyvchKFufiXZrRRsYWPcisFYK64lRwOR8LcEvGlp6eH/Pz8eIfhRyL3WaJea4kaF6jYZsJcm62k0CGRHqT60tvbGzxRHEjkPlMo5gJqcFAoFAqFH2pwUCgUCoUfMddnJBr945McOTdISfZK3uod5UBbH9tLLc45/Efs3GbJcKo0mObbTWfYkJ9J5WrnC2tOdDu1Gm7dxbXrNzjePcpbvSM8UmHjWOcwB9oHqLLmUl+WR4HmQXKwmNw6ia3FuazPz2RwfJK1eZm0dA5RmLnCo8nYXuJ8eP1scytrcldSZTVx7foN2ofHqVydG/BhrbYet9LixjS8IXs8qow6mzDMd7x7lF0VpRztHOZgez81pRbqy/S1GO97Vz7lhTk0tvez1+5UhJQXul4UtGG1n1rDHYdb79HSNcKBtj62FpvYsSaP5ctD60uFQjEz5vXg4FZYPLFzCx9/8aBnpe5Th+1+Coef76rlT0Q+d3/nDS/9hDN9q0c58dAPG3njU3fz4AsH/I67tRehxOSb9+Vdtdz71B6e2LmFXf/Z5HdcG+uT91eyYmkK93z3d4ZqCaN6nry/kl0/OgTA00fsfnH7aj8+7NVOu6EW44GNxdz71B7ddmn1HL5xGNXxyqN14Z1shUIRFvP6ttI+ex+pKYtxDI8HVTgcbB9gAdM8WmHz6Cd805/sGeXRSpuhkqKhtS+kmHzzpqYs5mB7f0BNhjbWkz2jjF26wvIliw3VEkbaipM9o14rmn3jDkX7sb+tn1OaPgqUttFAERKsL/cpZYZCEVXm9eCw196PLSeNNzsDKxzAqYtYuGABmwqzAionylcZH290BP9C22v3T2PLSeOQYzCo7sId64nuEcYmr2LLSWOvwYCkV49vOXpxu/MFimVvax8dY5e84g+m99CLI3BfDujuVygUkWFeDw51NjP2oXG2FOq7fzYWZGEfGgduqjSOdY6woUD/XQIbC7Jo6TI+Xm0NvpK3zuafxj40zlZrLvah8YB1u2PdWJBFxrIU7EPj1JVZQq7Htxy9uN35AsVSV2ahKOPm7bNAaauKTX71ueMI3Jcm3f0KhSIyzOvBodZmYeLqFNbstKAKh20lJqZZwDPNdo9+wjf9hvxMnjliN1RS1Bt8UfvG5Jt34uoU20rMATUZ2lg35GeSsXwpl65NGaoljLQVG/IzvWR4vnGHov2oKTWzXtNHgdJWGyhCgvVlrVJmKBRRZd6vkO4fn6S5Y4iSrDRO9Y6yr62fWpfC4dlmO+vMGR6VxneazrChIJOKIudspZM9oxxyDHh0F9embnCiZ5STPaM8UlHK8a4RDrT1O2f9lFkMH0b7xqbVSWy1mliXl8HQxcvcZsngWNcwqzJSPZqM7a5ZP88esbtmK+Vy7foNHCMXqSjKCTpbyV2PW2lxYxp+d6aXRkc/1VYztaUmCjNX6OY73jXCIxWltHQNc6BtgNpSM3U+s5Xc5b/vtgI2rcqmyTHA3tY+amxmNq3K5mcnz3H/htV+ag13HN56jz6qrGbqyyxc6DnHu971roDnPF7MxRW10UbFFj5KnxGAuaLPULGFT6LGBYkbW6LGBSq2maD0GQqFQqGIOWpwUCgUCoUfanBQKBQKhR9qcFAoFAqFH/Nan6Gl+/wl9pzp9TiFdqxxupDc+92On2NdI+xv66eiKJvqEjOZy5aQu8J/RlDvhUnGL1+l0eF8yc72FdQ9kAAADytJREFUEgu1Nu8X9UQatydK615yu4pi+UIcPWeTtv5Ax4PlVSgUsUENDjgHBq33x+MUeqyee59uMPAI3XQA3ZjG6wuse2yCc6MTPv4lf09RJNF6ovTcS0aOpWjFYVR/oONAwLwKhSJ2qNtKwJ4zvfouJHsfy5csDugGOqnjWXqrd9TQv7TPHtyvNBPcnqhAvqNYYORsctcf6Pgpgz6LVewKheImanAAmgw8PY0Op/cnmNOoc3TCa1/fhUnD9Afbo+MEcnuiAvmOYoGRs8ldf6DjWh+TXl6FQhE71OAAVBl4eqqtTu9PMKdRYWaq1z7LymWG6beVRMcJ5PZEBfIdxQIjZ5O7/kDHtT4mvbwKhSJ2qMEB2LEmT9+FZLNw6dpUQDfQBh3P0u15mYb+pVpbdL7o3J6oQL6jWGDkbHLXH+j4eoM+i1XsCoXiJjF9IC2EWAI8CxQDS4GvSil/pTn+OeBRYNC165NSShntuArSl/Pq4ztoaO3zOIXqXS4k9/7XZDcvPbzd5fjpp6Ioh+oSk+5spYKMVBYuXMiPH67xzFaqKTVTUxq92UrmtGW89sm7aO4Y4rmPVHG6d4xDjgGPqyhWD3Tdcfg6m9z1Bzse6JhCoYgdsZ6t9HFgWEr5kBAiGzgO/EpzfBPwsJSyJcZxUZC+nIc2l/DQ5hLd/W6EKZ0HN1mDlpe3chl5K5exxrSS3ZW2iMerhzltGR9YWwjAHQVZfm2JFea0ZTywsZgHNhaHfTxYXoVCERtiPTj8BPip5vOUz/Fy4H8IISzAq1LKr8csMoVCoVB4iIuVVQiRhvMXw1NSyh9q9n8F+HfgAvBz4NtSyl8bleO2skY3WoVCoZizGFpZY74ITghRiPOL/0mfgWEB8A0p5XnX51eBOwDDwcGNUnZHj0SNLVHjgsSNLVHjAhXbTIiQstuQWD+QNgOvA5+RUu7xObwSOC2EeBcwAdTjfHitUPiRmpoaPFGcyMrSn06sUCQTsf7l8EUgE/iyEOLLrn1PAalSyu8JIb4I7AWuAHuklL+JcXx+GLl+ei9McuHyVRrbB3izc4jtpRZuz8ukffgClatzk2qGTSCf0ZIlSyLuQpqpP0mbb1txDpnjkwnVzzfj66NuDOWFUiQ1MR0cpJSfBT4b4Ph/AP8Ru4gCY+QBevWxekN30hM7t3DPd3+XND6gYC6klZbCiLqQgtU30zjjjX989oSKT6EIF7UILgB6HqCKohxO9hi7k86OXGT5ksVJ4wMK5kJqOjccURdSsPoinS9WJHp8CkW4qMEhAHoeoPJVWfSNG7uTmjuGsOWkJY0PKJgL6eDZQcPjM3EhBasv0vliRaLHp1CEixocAqDnAWrpGsGSZuxOqijKwT40njQ+oGAupG3FuYbHZ+JCClZfpPPFikSPT6EIFzU4BEDPA9TcMcSGfGN3UnHWCi5dm0oaH1AwF1LV6uyIupCC1RfpfLEi0eNTKMJFvewnAIE8QAsXLuSlh7fT5BikuWOI2lIz6/MyaR8ZT6qHkMFcRxf6OiPqQgpWX6j5tllz2CEKEqaftfE1tPZSX5anvFCKpEYNDkEwcv243UnClO7lTlrr89djMhDIZ3Tt2rWIu5Bm6k/S5nvnnXcS7ovXHd+W9Gms1uI4R6NQzA51W0mRlExMTARPFCdGRvQnKygUyYQaHBQKhULhhxocFAqFQuGHGhwUCoVC4UeyP5BeBHD16tWQEl+5ciWqwcwGFVv4JGpckLixJWpcoGKbCTONS/OducgoTVze5xApWlpaqoGD8Y5DoVAokpRt5eXljXoHkv2Xw5vANqAXuB7nWBQKhSJZWATk4fwO1SWpfzkoFAqFIjqoB9IKhUKh8EMNDgqFQqHwQw0OCoVCofBDDQ4KhUKh8EMNDgqFQqHwI9mnsgZFCLEQeBLYAFwBHpNS2qNU1xLgWaAYWAp8FegCXgFaXcm+LaV8SQjxFeBeYAr4GyllsxDCBjwPTAOngb+UUt7QSzvD+I4D510fHcB3gW+6yn1dSvkPRv0lhLgz1LQziOsR4BHXx1uAjcBHgf8P6HTt/wrONS0xiU0IUQn8o5SyNpzzEom0Yca2Efg3nFO5rwAPSyn7hRD/ClQB465sO4ElwA+BZUAPsEtKeUkI8TjwSVdsX5VS/loIkaOXNszYNhGFa38m/eYT148A91uYioHDUsoHhRC/ArKBa8CklPK90YzL4PviD7OtL1J9Nh9+OdwH3CKlfDfwfwP/HMW6Pg4MSym3Ae8FvgVsAp6QUta6/nvJ9Y+mBqgEHgT+3ZX/CeBLrvwLgJ0B0oaFEOIWAE0cu4Dv4PwSrgYqXXUZ9Vc4acNCSvm8Oy6gBfhrnP32eU28+2MVmxDi88DTOAcqCO+8zCrtDGL7JvBXrr57GfiCa/8m4B5N/50H/h/gh676jgOfFEJYcPZ3FXAP8HUhxFK9tDOILVrXflj95huXlPJBV3/9KTAG/K0rqQ2odsX63mjHhf73RcJca/NhcKgG/gtASnkY2BzFun4CfFnzeQooB+4VQhwQQjwjhEhzxfS6lHJaStkBLBZC5LrS7nfl/S1wV4C04bIBWC6EeF0I0SCE2A4slVK2SSmngdeAHej0lxBiZahpZxCXByHEZmCtlPJ7OPtitxDioBDin4UQi2MYWxvwIc3ncM7LbNOGG9uDUsoTru3FwGXXr6Yy4HtCiCYhxG7XcU+faOqrAJqklFdcA4gduN0gbbixRevaD7fffONy8w/Av0kpe4UQZiADeEUI0SiEeL+mDdGKy+j7IiGutfkwOKzk5q0UgOuuL5qII6W8KKUcd/0j+CnwJaAZ+L+klNuBdpy3R3xjGgfSgQWuLzjtPqO04XIJ+Cecfx1+CnjOtc+3XL/+cu27EEraWfbtF3H+gwV4A/grYDuwwhVzTGKTUv4M560FN+Gcl9mmDSs2KWUvgBBiK/AZ4F+AVJy3mj4OvAf4tBDidp84gsWmlzas2IjetR9Wv+nEhRDChPOPiOddu1Jw/rq8D+dA8i+uNNGMS+/7ImGutfkwOFwA0jSfF0opp6JVmRCiENgL/IeU8ofAz6WULa7DPwfu0IkpDefP2xs6+4zShssZ4AeuvyjO4LyAskKob2GAGCLWt0KIDOBWKeVe165npZTtrgv6l+j3W0xiI7zzMtu0YSOE+DDOW2v3SikHcQ7635RSXpJSjgMNOH85auMIFpte2nCJ1rUfiX77M5y3zdzanT7gO1LKKSnlAM5baSLacel8XyTMtTYfBocm4H0ArgeXp6JVkeun6evAF6SUz7p2vyaEqHBt78B5T70JuEcIsVAIUYTzi2sIOC6EqHWlfS/OB7BGacNlN6777kKIfGA5MCGEKBVCLMD5i8Jdn1d/SSkvAFdDSTuDuNxsB37nKmsB8JYQYpXrmLbf4hFbOOdltmnDQgjxcZy/GGqllO2u3WuARiHEItdDz2rgGJo+0dTXDGwTQtwihEgH3oXzgaVe2nCJ1rU/637DeVvltz6ffwwghFgBrAP+GM24DL4vEuZam/OzlXD+xXK3EOIQzgcxu6JY1xeBTODLQgj3vcTPAd8QQlzF+dfJJ6SUF4QQB4Hf4xyg/9KV9u+Ap4QQKTgvzJ9KKa8bpA2XZ4DnhRCNOGcs7Mb518SLOCVcr0spjwgh3kS/vz4VRtqZIHDeekBKOS2EeAx4WQgxiXMGx1M4byPFI7Zwzsus0oYTlBBiEfCvQAfOvgLYL6X8ihDiReAwztspL0gp3xZCfBX4vnDOThoCPiqlnBDOmU0HXbH9TynlZb204XUZAH8BfCsK1/6s+s2F53oDkFL+VghxjxDiMM5/F1+UUg4JIaIZl973xWeBf02Ea02J9xQKhULhx3y4raRQKBSKMFGDg0KhUCj8UIODQqFQKPxQg4NCoVAo/v/2zifEqjIM479hqIjaDLoKIYPqNVRQ02yRMEVGaenCCkGFSZpq4x+oRdOiRdKqrIUEEoFGRdRCdLAI0hoipHJAJREeVzNQES3aZIyYhIv3u3XwnDvTjDp2Z54fXO49537n+87d3Od83/u9z1vD4mCMMabGbNjKamYwEbGIzGF4smTCXs2+byQ9htaT22jPk/40R66gz/3AELm//T1JayKtGu6W9NY41/WRuQx9l51fByyX9Op/HP81YFjSYER8LenBKf0QM+OxOJhOZyvpUfM8cFXFgbRWOA+sKHv/FwNfRsRDks5cSceSfuHfJLMpe1JJGgQGJ9G+KiK9Ux3XzHyc52A6lpL9+xOwCjhGOlEuBPolPVHabCPdNl8iLSYeAH4mEwF3SRpq0/edZKbwHEl/Vs73AiPl8AsyQWyM9DB6g/zD7Qb2S3q7ZG3vBh4nra+7yYTEofJaQ9pbAAxI2tfmfvponjn8cz4iRoCPgdWkidsuMvnpLuBFSZ9WZi7LSO+qHyStbBrTzG4cczCdzFpgtHhFHQSeIy0R7o2IntJmI/AhmUV9C7CAzJZeMUHfS4CzVWEAkDQkaaQcBrBZ0mqgv3y/jHQ6XR8Rq4ANpKfQQuApUqiq/Z0hRWtvO2GYJL9KWk5mwb4MPEIa8A1cNu728m5hMI1YHEwn8wz5pAzwSTnuIi1TNhRvmTmSjpNP0x8V48FR4OgEff9NLimNx28VoXgYWBcRJ4HvgXnAYnImcUDSX8UU7/NJ/L6p0PILGiWtNC6Wzz3tLzGmjmMOpiOJtFN+jJwl7CBFoYe0W/6AXFLpIT2XIAPKk3kYGgbuiYibJY1Vxt1J+gR9Ry4ntegmixMdKO3mAufIpaauSrtr5ghcuDCNY5kZjGcOplPZAhyVNE/SfEm3A68DLyiL+9xW2rTE4QiwMSK6iittLxl3aKQUSvkM2BOlil5ELCUrrZ1uuOQroD8ibiiunt8C95dxn46Im8pS16MN117k+jyoXbPaJqbzsTiYTqWPrBFd5R3gvohYQC4z/VGxsX6XLHLyI/A+udQyxvhsLW1ORsSpMt5mSU3isJeslXyCnHXsK/GJQ2QA+DS5q6hpl9M3wKYSPB+PTRFxrvJ6ZYL2E3EIONUSP2OqeLeSmRVExFqyGtbhUrfgBJkf8Pt1vjVj/pdYHMysICLuIGMRt5ZTb5Ke9+1yI56VNDwd99YisqLbQNN3kpZM570YY3EwxhhTwzEHY4wxNSwOxhhjalgcjDHG1LA4GGOMqWFxMMYYU+MSOKR79JNOkdcAAAAASUVORK5CYII=\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 21,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Customers can be segmented on the basis of Total interactions or total complaints with bank and the average credit limit**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Q5 Execute KMeans"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "X = dataset.iloc[:,2:].values #Selecting the features"
      ],
      "outputs": [],
      "execution_count": 22,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape "
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 23,
          "data": {
            "text/plain": "(660, 5)"
          },
          "metadata": {}
        }
      ],
      "execution_count": 23,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**As there is a difference in magnitude of Credit Limit and other features, we will scale the features**\n",
        "\n",
        "**As there are not any negative values, we can use MinMaxScaler**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import MinMaxScaler #Importing MinMaxScaler\n",
        "scaler= MinMaxScaler() #Initialising the instance of the scaler\n",
        "scaled_features = scaler.fit_transform(X) #Storing the scaled version of features in scaled_features"
      ],
      "outputs": [],
      "execution_count": 24,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans #Importing KMeans from sklearn"
      ],
      "outputs": [],
      "execution_count": 25,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "## Writing a for loop to plot the graph for within cluster sum of squares"
      ],
      "outputs": [],
      "execution_count": 26,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "wcss = [] #Within cluster sum of squares\n",
        "for i in range(1, 11):\n",
        "    kmeans = KMeans(n_clusters = i, init = 'k-means++', random_state = 42) #Initialising \n",
        "    kmeans.fit(scaled_features) #Fitting on scaled features\n",
        "    wcss.append(kmeans.inertia_) #Appending the wcss to the blank list\n",
        "plt.plot(range(1, 11), wcss)\n",
        "plt.title('The Elbow Method')\n",
        "plt.xlabel('Number of clusters')\n",
        "plt.ylabel('WCSS')\n",
        "plt.show() "
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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muOGs2VLNM4vafz+BiEiUFASdbFrjg+3VPSQiGUJB0MmO3HsPBvSMcd/8ZWyrV/eQiHR9CoJOlpebyxnjhrN6czXPLv4o6nJERHZKQZACZ4U3l83QzWUikgEUBClw1D4D6d8jxj/VPSQiGUBBkAL5ebmcPm4YH26q4vn3djqQqohIpBQEKaKxh0QkUygIUuRTowZRVlLIP+cvo76+IepyRERa1WYQmFl/M+sdTo80s4vN7Jj0lJbZCvJyOb18OCs3VvLCEnUPiUjX1WoQmNkJwAJgvJkNBF4FDgB+aWbnpam+jDZtQvBge409JCJdWVtHBFcBh7v7c8A5wHx3Pxs4AfhuOorLdMeMHkzf4kJmzFP3kIh0XW0FQZG7vxNOHw08CODuG3fyPgkV5OVyavkwVmzYysvLMu7BayKSJdr6QM8xsxwzKwEOB54AMLMeQHE6iusOGoem1tVDItJVtRUE9xE8XP4fwOvuvsDMxgN/C5dJOxw7ehC9iwqYMW8pDQ3qHhKRrqfVIAgfIXkPMBM4OVx8DPA6cFnKK+smCvPzOLV8GMvXb+UVdQ+JSBfU5jOL3f3/mi36K7DO3dv11dbMJgPXuPtUM5sI3ARsA6qB/+fuH5rZjQQPs98Uvu00d9+wK39EVzdt/HDufm0xM+YtY/KIAVGXIyLSRFuXjw4ws+lmNtXMcs3sPmAZ8K6Z7b+zDZvZJcDtQFG46PfAd919KvBP4Efh8knACe4+NfzpViEAcLwNoTRWwPQ31D0kIl1PW+cIbgJeC38+S3APwWDgbIIP9Z1ZBJyZNP8Fd389nM4HqswsFxgN/MnMnjezc3ex/owQy8/jlLFDWfrxFhLvr4u6HBGRJnJa+4ZqZvPcfXw4fSfwkbtfEs4vcPexO9u4mY0E7nX3KUnLDgX+DBwJVAHfB64H8oCngXPdfV5r20wkEiOB99rxt3Upz7y/if98djlf2a8f3z1gYNTliEj22isejy9JXtDWOYLkhDga+EbSfElH9m5mnwcuBz7j7qvNLA/4vbtvDV9/CpgAtBoEjcrLy4nFYh0pIxL7j6/jqpf/wfMfVfOXSZOYM2cO8Xg86rK6jEQiofYIqS2aUns01dH2qK6upqKiosXX2gqCpeEHd0n4MxvAzM4mGHpil4Tv+w9gqrs39o+MAe41s0kE3VSHA3ft6rYzQXFBPifvP5R75y5h7gp1D4lI19HWOYILCIaW+C7wJXevMbPrgSuAH+zKTsJv/jcCpcA/zWy2mV3l7m8R3JfwEvAM8Fd33+WQyRSNQ1PPmLcs4kpERHZo9YjA3ZcDJzVb/Avgh+7ersduufsSoPH8QFkr6/wG+E17tpfpTtxvCD0K85n+xlLOOG5o1OWIiAA7H4b6a2Z2UNKiSwiOEqQDigvyOWm/PXl3zSbeWV8ddTkiIkDb9xF8Fzgf2Ji0+DHg22b2rVQX1l01jj30r2Ubd7KmiEh6tHVE8HXgOHf3xgXu/ixwIkFASAecuO8QSgrzeHzJBqpqt0VdjohIm0FQHw453YS7rwHadY5APqlHrIBvThnDyi213PDsm1GXIyLSZhDUmdkezReGTyvLS11J3d9Pjx9P31gev36yghUbtkZdjohkubaC4GbgUTP7lJn1MbMiMzuc4AE1t6anvO6pT3Eh35qwB1tq6rj0kTlRlyMiWa6tIJhN8IF/J7AW2AL8BbjD3f+Q8sq6uVP27sOkoWX8LfEeL+rh9iISobaC4EXgh8BDwOeAke4+2t11NNAJ8nJzuOH04MrcC+9/Vc80FpHItPVgmj0Jbih7DfgMMMvMnjWzn5rZlNbeJ+132F578MUDRvLa8rXc+eqiqMsRkSzV5g1l7r7I3e9093OBQwhGDf0swXAQ0gmuPnkSJYV5XP7oXDZU1kRdjohkobZuKMsPH0pztZnNJRgP6CDgZ4Aes9VJhvbpwaXHjOOjzVX88on5UZcjIlmordFHPwZeAKYDZ4TjBkkKXHTU/tzx8rvc+NxbfH3yKPYd2DvqkkQki7TVNXQrsAdwLvA1MzssfKKYdLKigjyuPTVOXX0DFz34mh5nKSJp1dbJ4h+6+wEEj5t8D/gOsNDM7jMzDTHRyU4vH8Yxowcx8+0PeOStFVGXIyJZZKff8N19JfB3ghvM/kTwjOGfpbiurJOTk8PvTj+IvNwcLn7gNarrNA6RiKRHWyeLTzWza8zseWApwT0FlcDn3X1IugrMJmMH9eFbh47h3TWbuPHZt6MuR0SyRFsni78DPAVcCCTa+zAa2T1XnjCB/5mzhF8+OY+zD9yLwb069HhoEZF2a+sJZcensxAJ9C2J8YuTJvLt6S9z2SNz+csXD4u6JBHp5nQVUBf0jcmjmDikL399bTEvL9U4RCKSWgqCLigvN5cbztA4RCKSHm2dI9htZjYZuMbdp5rZKIKRTBuACuACd683sysIxjKqAy5091dSWVOmOGLvgXxu4gj+7/Wl3J1YzDkH7RN1SSLSTaXsiMDMLgFuB4rCRdcDP3H3I4Ac4DQzmwQcBUwGvgBoeOskvzk5TnFBHpc+MoeNVRqHSERSI5VHBIsIbka7O5yPs2OwuseA4wEHZrl7A7AsHN9ogLvvtGO8oqIiBSWnVyKR2Ok6X9m3jD/NX81373mS7x0wMA1VRac97ZEt1BZNqT2a6uz2SFkQuPsMMxuZtCgn/MAH2AT0BnoRPPSGZst3GgTl5eXEYrFOqjb9EokE8Xh8p+vtP76Omdc8yP8u/JjLTzucMQN6paG69Gtve2QDtUVTao+mOtoe1dXVrX6BTufJ4uT7EEqB9cDGcLr5cgkVF+Tzm1Pi1G6r5+IHXou6HBHphtIZBHPNbGo4fSLwHPA8cIKZ5ZrZcCDX3deksaaMMG38cKbuM5BH31rBYxqHSEQ6WTqD4GLgKjN7ESgEprt7giAQXgRmABeksZ6M0TgOUW5ODhc98Bo1GodIRDpRSi8fDZ9hMCWcXkhwhVDzda4ErkxlHd3B+CF9+Y9DRvPHFxZy87+di6buH3VJItJN6IayDHLVpydSVlLIL56Yx4ebKqMuR0S6CQVBBunXI8bPPz2RjVW1XP7o3KjLEZFuQkGQYc6bMppxg/tw56uLeHWZzquLyO5TEGSY/Lxcbjj9IBoaNA6RiHQOBUEGmjpqENPGD+elpWv425z3oi5HRDKcgiBDXXtKnKL8YByiTVW1UZcjIhlMQZChRpT15D8/NZaVGyv5r3/Nj7ocEclgCoIMdsnRYxnWp4TfPfMW767ZGHU5IpKhFAQZrKQwn2tOjlOzrZ4fPqjRGUWkYxQEGe5zE0dw5N578NCC95nlH0RdjohkIAVBhms+DlHttvqdv0lEJImCoBuYuGcZ500ZzVsfbuC/n/eoyxGRDKMg6CZ+/ukJ9Cku5KqZb/CRxiESkV2gIOgm+vcs4qoTJrChqpafPPZ61OWISAZREHQj5x86hrGDenPHK++SWL52528QEUFB0K3k5+Xyu9OCcYh+cP+rNDRoHCIR2TkFQTdzzJjBnD5uGM8vWc3/zF0SdTkikgEUBN3Qb0+JE8vP5ccPz2FLtcYhEpG2KQi6ob36lXLx1P1ZsWErVz9VEXU5ItLFpfSZxc2Z2VeBr4azRcBE4EvAtcDycPkV7v5MOuvqjn58dDl3vbqY62a/ydcOHsXe/UqjLklEuqi0HhG4+53uPtXdpwIJ4HvAJOCSxuUKgc7RI1bA1SdPorqunv98SOMQiUjrcqK4ssTMDgR+6+5TzewxoB7oBbwC/Mjd61p7byKRGAnoaSzt0NDQwDefXMIbqyu5+ejhHDyoZ9QliUj09orH40uSF6S1ayjJZcBV4fQTwP0EH+63AOcDN+9sA+Xl5cRisZQVmGqJRIJ4PJ7y/dw+aC8OvuFR/vjmBr7x6SMoyOuap4XS1R6ZQG3RlNqjqY62R3V1NRUVLZ8zTPungpn1AfZ196fDRXe4+2J3bwAeAA5Id03d2aSh/fj65FEsWLWBW17QOEQi8klRfD08EngSwMxygHlmNjR87RiCcwfSiX554gH0LirgypnzWL25KupyRKSLiSIIDFgMEB4FfAP4p5k9A5QAt0VQU7c2oGcRV5wwgfWVNfzscY1DJCJNpf0cgbtf22x+FjAr3XVkm28fZtz20jvc9tI7/MchY5i4Z1nUJYlIF9E1zxxKpyvIy+X60w6koQEu1DhEIpJEQZBFjrchnDJ2KM8t/oj/e31p1OWISBehIMgy1516IIV5ufzo4QRba1q9XUNEsoiCIMvs07+UHxy1H8vXb+U3Ty2IuhwR6QIUBFno0mPGMbhXMdc+vYAl6zZHXY6IRExBkIVKiwr4r89MoqpuG8fd8gT3JBazrb4+6rJEJCIKgiz15Ul7cdFR+7N8/VbO+fvzTPztw8yYt5T6el1NJJJtFARZKjc3h2tPjfP2j0/jawfvg6/eyOfuepaDb3iUR958X5eXimQRBUGWG1nWk9s/fygVl5zKFw8YyesfrOPUPz/N4Tc9zr8WrlQgiGQBBYEAMGZAL+45+whev/hkzhg3nJeWruH4W5/k2D8+wfPvfRR1eSKSQgoCaaJ8cF+mf/UoXrnwJE7cb09mL/qQI2+eyUm3/YvXlq+NujwRSQEFgbQoPqwfD3/jaJ77zgl8atRAZr79AZNveJRpd85m/sqPoy5PRDqRgkDadOhee/Dkt47nifOP5ZARA7h//nIOuO5hvnzPcyxcvTHq8kSkEygIpF2OHj2Y5757Ag9942gmDinj3rlLGHvNg3z93hd0U5pIhlMQSLvl5ORw0n578uoPTuIf5xzFfgN7ceeri9j36ge4YMbLrNiwNeoSRaQDFASyy3Jycjhz/HDmXnwyd3/5cEb07cEtLyxk9K/v4+IHXuOjTZVRlygiu0BBIB2Wl5vLlybtxYJLTuW2zx3CwNJibnj2LUb9+n4uf3Qu67ZWR12iiLSDgkB2W35eLudOHsXbPz6Nm888mF5FBVz9rwr2+dV9/GLWPDZW1URdooi0QUEgnSaWn8e3DjMWXno6154SpzAvlytnvsE+v7qPa59awJbq2qhLFJEWpP2ZxWY2F9gQzr4H3Ar8HqgDZrn7VemuSTpXSWE+F03dn/OmjOamf7/Nb59ewI8fmcPvnn2Ty44Zx3mHjCaWnxd1mSISSusRgZkVAbj71PDna8AtwJeAw4HJZjYpnTVJ6pQWFXDZseNYdPkZXH7sOLbU1PH9+1/F/ut+bnvpHWq3aehrka4g3V1DE4ASM5tlZk+Z2ZFAzN0XuXsDMBM4Js01SYr1LYnx8xMn8u5lZ3Dx1P1Zvbma8//xEvtf8wB3v6ZnIYhELSedo0ua2ThgCnA7MBp4DFjv7vHw9XOBvd39J61tI5FIjCToUpIMtaaylr8sWMN9735MXT2M7FXI1GG92K+siH3LihhUUkBOTk7UZYp0V3vF4/ElyQvSfY5gIfBu+O1/oZltAMqSXi8F1rdnQ+Xl5cRisRSUmB6JRIJ4PB51GZE54XBYum4zv3pyPne+uog7F6zZ/lr/HjEmDe1HfGjZ9t/D+/bImnDI9v83mlN7NNXR9qiurqaioqLF19IdBOcC44Bvm9kQoATYYmb7AIuBEwCdLM4SI8p68qfPHcI1J0/i3qdfYmNRPxLvr2XO++uY5R8wyz/Yvm7/HjEO2LOM+LB+xLMwHERSKd1B8GfgTjP7N9BAEAz1wN+APIKrhl5Oc00Ssb4lMQ4e1JN4vHz7snVbq5nz/jrmvL+WxPvrSCxfyxMLV/LEwpXb1+lXEmPS0CAcJg0tIz60HyMUDiK7LK1B4O41BFcINTclnXVI11dWEuPYMYM5dszg7cuah8Oc9xUOIp0h7fcRiHRUS+HwcRgOiZ2EwwFDy7afczhwmMJBJJmCQDJa35IYx4wZzDEthMOOgFjLkwtX8mRSOJSVFH7ihPTIsp4KB8lKCgLpdtoTDnPeX/eJcOhTXMjwPj0Y0ruYIb1K2LN3CUN6F7Nn73C6VzH9exSRm6uwkO5FQSBZobVwmLtiHYnlQThUrFrPe+s2M6+NR3EW5OUypFcQDoN7JYVEGBSN8yWF+qclmUP/t0rW6lsS4+jRgzl69OAmyzdV1fLBxq2s2LCVFRsq+WDD1rTWiQIAAAtnSURBVHA+mF6xYSsvL1vDtvrWb8bsU1zInr2LGRweWezZuzgMix3ze/QsIi9X4z5K9BQEIs2UFhVgRb2xPXq3us62+npWb64Ow2IrKzZuDQJjQyUrkoJjwaoNrW4jLzeHQaXF20NizzAkqtetZ23PDxhUWsyg0iJ1R0nKKQhEOiAvN5dBvYoZ1KuY+LB+ra63taZueyis2LC1xaOLuSs+5pVla5u+8aUdN9Pl5eawR88iBpUWM7A0+D2oVxASA0uLm8yXxjQ8h+w6BYFICpUU5jOqfy9G9e/V6jr19Q2s3brj6OKl+W9TVLYHqzZVsWpTJR9urGTVpip89QbmrljX5v6KC/LCI4liBvYqYmDPMDB6FW8/wggCpZiiAg0FLgEFgUjEcnNzGNCziAE9i5i4ZxmDKj8kHh/f4rqbq2tZtamSVRvDkNhU+Yn5DzdV8eryNdS1cQ4DgvMYycEwqFfSdGlwDqNfjxj9SgopKczXkUY3piAQySA9YwWMihW0eYQBwVHGx5U1YUhUhiERhEXjssb5tz/auNP9xvJz6VcSo1+PGP17xCgLpxuXlSW91risT1Ghzm1kCAWBSDeUm5sTfFD3iDF2UJ82163dVs9Hm6u2B8aqTZV8tKmKDzdXsXZLNWu3VrMu/L3s4y3MX9muAYLJzcmhb3Fhk8DYMV3YJEz6J71WqKfXpZ2CQCTLFeTlbr//oT1qt9Wzbmv19pDYERY1rN1azZotQYCs21qz/fVFaze1ebltsp6x/CZHGjlVWxi5uJY+xYX0LioIfidPb/9dSM+YurA6QkEgIrukIC+XgeG5hPZqaGhgQ1VtC+FRHYZHdRgeO157+6MNbK3ZFmxg2c67ryC4wqp3UQG9iwq3h0TvZmHRp7hxWTjdbN2CvOy7t0NBICIpl5OTQ5/i4AN3H0rb/b7K2jqeffk1ho/ejw1VNayvrGFDZS3rq2rYGP7eUBksX19Vy8bKmnBZLe+s2cjm6rpdrrWkMI8+28OhkN5hWPQqKqBnLJ/SWAGlsQJ6bJ/Op2e4bMd0Pj0LCzLmHImCQES6rOKCfPoXF7DfwNZv7mtL3bZ6NlbXhmGRHBy1bGwMlqra7b83VNaEgVPLh5uqWLh6406vvmpLSWHe9uAojQVBkhwUpUVBmPQsLKDn9ukwYIo+OZ2foqMVBYGIdFv5ebmUlQTnGjqioaGBrTV1rK+qZXN1LZuq69hUXcumqlo21wTTm5OmN1XXsjlcZ3N1XZP3fLipis01tezOY+LLSgq57vA96ewHdyoIRERakZOTQ49YAT1iBZ2yvfr6BrbW1m0Pi01hUGxOmt6SFB7J620Ju7l6Fnb+UYGCQEQkTXJzc+gZK6BnrIBBtP9ke7JEItHJVUH2nR4XEZEm0npEYGYFwB3ASCAG/BJ4H3gIeCdc7Y/u/r/prEtEJJulu2vobGCtu3/FzPoBc4GfA9e7+3VprkVEREh/EPwDmJ40XwfEATOz0wiOCi50901prktEJGvlNOzOtUwdZGalwIPAbQRdRPPcPWFmlwN93f2Hrb03kUiMBN5LS6EiIt3PXvF4fEnygrRfNWRmw4D7gP9297+bWR93bxzF6j7gpvZsp7y8nFisY9cGdwWJRIJ4vLOvBs5cao8d1BZNqT2a6mh7VFdXU1FR0eJrab1qyMwGArOAH7n7HeHimWZ2cDh9DND510aJiEir0n1EcBnQF/ipmf00XHYRcIOZ1QCrgG/uZBt5ADU1NSkrMl2qq6ujLqFLUXvsoLZoSu3RVEfaI+kz8xPjfEdyjmB3JBKJw4Hnoq5DRCRDHRGPx/+dvCAT7yx+FTgCWAlsi7gWEZFMkQcMJvgMbSLjjghERKRzaYgJEZEspyAQEclyCgIRkSynIBARyXIKAhGRLJeJl49mrJaG4Xb3ByMtqgswsz0I7ig/zt3fjrqeKJnZpcCpQCHBMCx/jrikSIT/Vu4i+LeyDTgvW//fMLPJwDXuPtXMRgF3Ag1ABXCBu9fv7j50RJBejcNwHwGcCNwccT2RC//B3wpURl1L1MxsKnAocBhwFDAs0oKidRKQ7+6HEgxV/6uI64mEmV0C3A4UhYuuB34SfobkAKd1xn4UBOn1D+CnSfN1URXShfwWuAX4IOpCuoATgPkEgy8+BDwcbTmRWgjkm1ku0AuojbieqCwCzkyajwPPhNOPAcd2xk4UBGnk7pvdfVM4DPd04CdR1xQlM/sqsNrdZ0ZdSxfRHzgQ+CxwPvA3M8uJtqTIbCboFnqbYLj6GyOtJiLuPoOmIZjj7o13AW8CenfGfhQEaRYOw/00cLe7/z3qeiJ2LnCcmc0GJgJ/NbNB0ZYUqbXATHevcXcHqoABEdcUlR8QtMUYYAJwl5kV7eQ92SD5fEApsL61FXeFThanUdIw3N9x939FXU/U3P3IxukwDM5391XRVRS5fwPfN7PrCcaE6UEQDtnoY3Z8E14HFNDCqJlZaK6ZTXX32QTnGZ/ujI0qCNKrpWG4T3T3rD9RKuDuD5vZkcArBEfrF7h7tg6s+DvgDjN7juAKqsvcfUvENXUFFwO3mVkh8BZNH/3bYRp0TkQky+kcgYhIllMQiIhkOQWBiEiWUxCIiGQ5BYGISJZTEEiXZGYjzazBzI5rtnyJmY3shO13ynZ2so/hZuZm9np4N/nO1u/QJXxm9hczG9GR94qAgkC6tlqCa6Z3+iHaRU0FEu4+0d03pXA/nyIYgEykQ3RDmXRlHwBPANcB30x+IRyp80p3nxrO3wnMDn/uJxijZiwwB3gB+CrBzXxnuPtb4WauNLMJBEM5/Ie7zwvv/r6VYOTPeuBSd3/SzK4EpgDDgZvc/Y9JtYwB/gSUAVuA7xGE2C+BnmZ2i7ufn7R+GfBnYF+gGrjI3Z9Kev1KAHe/MpxfQhAqvcL95Ic1fw2YBgwBHjWzI4C9CW7GKgHWhH/Xe+Gd2+vCNjk7rLE83OV/u/ttLf0HkOygIwLp6i4GTmjeRbQT44FrCMaoOQwY6e6HAP9D00B5x90PAH5BMPY9wO+BO9w9TvBcgFuTjkiK3H3/5BAI3QPc6O7jCcbImU5w1+fPgAeTQyD0C+Bdd98P+ArtH2L5B8B17n4gwUBsU9z9aoLAPIlgELLbgS+5+ySCAE3+gJ/n7kYQEmXh3/4Z4Ih27l+6KQWBdGnuvhE4j13rIlrl7nPDB3a8DzSO67SU4Kig0e3hPh4FRphZH4JhfX9uZq8TDPNbAOwTrv9y8x2ZWU9glLv/M9zWSwTfvK2N+o4C7g7Xnx+GVHs8AtxsZn8GNgDNBy0cE9b6YFj/NQRHCI0a668ISreZBCOd/mc79y/dlIJAujx3n8WOLqJGDTTtFy9Imq5ptonWnvuQvDyHoDsnDzg67NefCEwmeEYAtPzwnJb+DeXQdrdrLUH9AJjZvuG4+41a/NvcfTowiWAsoh8QPMchWR6wOKn2OHB40uuV4XbWEnQR3UQQWHPCEJQspSCQTHExwYNbBofza4C9zawo7HPvSPfGlwHM7AzgrXBQs6eAb4fL9yf49lzS2gbCI5bFZnZm+J4pwKDwfa15FvhiuP6+wOMkBUP4t40NXz+Y8G82s/8FDnL3WwkecDQpXL+OIHjeBsrCcwUQDPP9iaHOzexUgiOSRwjOFWwmu5+GlvUUBJIRkrqICsP5BQQfZAsInvz2XAc2OybsQrkIOCdc9l1gipnNA/4XOLsdV/ycDXzPzOYTPH70THdvflSS7ApgtJm9AfwN+ErSw0YA7iX4QH8zrGduuPzXwOVmNgf4DfCtcPnDwKMEJ40/C1wX1n8O8PUW9v8YwdHBAoKji3vcfX4L60mW0OijIiJZTkcEIiJZTkEgIpLlFAQiIllOQSAikuUUBCIiWU5BICKS5RQEIiJZ7v8DNfAZ91CgxxwAAAAASUVORK5CYII=\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 27,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**As there is smooth descent afer n_clusters = 3 we will choose number of clusters as 3**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "## Training the K-Means model on the dataset"
      ],
      "outputs": [],
      "execution_count": 28,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install yellowbrick"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: yellowbrick in c:\\users\\mohit\\anaconda3\\lib\\site-packages (1.1)\n",
            "Requirement already satisfied: numpy>=1.13.0 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from yellowbrick) (1.18.1)\n",
            "Requirement already satisfied: scikit-learn>=0.20 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from yellowbrick) (0.22.1)\n",
            "Requirement already satisfied: matplotlib!=3.0.0,>=2.0.2 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from yellowbrick) (3.1.3)\n",
            "Requirement already satisfied: scipy>=1.0.0 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from yellowbrick) (1.4.1)\n",
            "Requirement already satisfied: cycler>=0.10.0 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from yellowbrick) (0.10.0)\n",
            "Requirement already satisfied: joblib>=0.11 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from scikit-learn>=0.20->yellowbrick) (0.14.1)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from matplotlib!=3.0.0,>=2.0.2->yellowbrick) (2.4.6)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from matplotlib!=3.0.0,>=2.0.2->yellowbrick) (2.8.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from matplotlib!=3.0.0,>=2.0.2->yellowbrick) (1.1.0)\n",
            "Requirement already satisfied: six in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from cycler>=0.10.0->yellowbrick) (1.14.0)\n",
            "Requirement already satisfied: setuptools in c:\\users\\mohit\\anaconda3\\lib\\site-packages (from kiwisolver>=1.0.1->matplotlib!=3.0.0,>=2.0.2->yellowbrick) (45.2.0.post20200210)\n"
          ]
        }
      ],
      "execution_count": 29,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from yellowbrick.cluster import SilhouetteVisualizer\n",
        "kmeans=KMeans(n_clusters = 3, init = 'k-means++', random_state = 42) #Initialising \n",
        "visualizer = SilhouetteVisualizer(kmeans, colors='yellowbrick')\n",
        "visualizer.fit(scaled_features)        # Fit the data to the visualizer\n",
        "visualizer.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "execution_count": 30,
          "data": {
            "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1b8b7328608>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 30,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "kmeans = KMeans(n_clusters = 3, init = 'k-means++', random_state = 42)\n",
        "y_kmeans = kmeans.fit_predict(X)"
      ],
      "outputs": [],
      "execution_count": 50,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "print(y_kmeans)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0 0 0 2 0 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0\n",
            " 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0\n",
            " 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 2 0 0\n",
            " 2 0 2 2 0 0 0 0 0 0 0 0 2 2 0 0 0 2 0 0 0 0 0 2 0 2 0 0 2 2 0 0 0 2 0 2 0\n",
            " 0 0 0 0 0 0 0 0 2 0 2 2 0 2 0 0 0 2 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 2\n",
            " 0 0 0 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 0 2 0 0 2 0 2 0 0 2 0 0\n",
            " 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 2 0 0 0 0 1 0 1 1 0 1 1 1 1 1 1 1 1 0 1 1 0\n",
            " 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1 1]\n"
          ]
        }
      ],
      "execution_count": 51,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "Segment = pd.DataFrame(y_kmeans,columns=['Segment']) #Converting the cluster to data frame\n",
        "Segment"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 52,
          "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>Segment</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>655</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>656</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>657</th>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>658</th>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>659</th>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>660 rows × 1 columns</p>\n</div>",
            "text/plain": "     Segment\n0          0\n1          0\n2          0\n3          2\n4          0\n..       ...\n655        0\n656        0\n657        1\n658        1\n659        1\n\n[660 rows x 1 columns]"
          },
          "metadata": {}
        }
      ],
      "execution_count": 52,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "data=dataset.copy()\n",
        "data=pd.concat([data,Segment],axis=1)"
      ],
      "outputs": [],
      "execution_count": 53,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "features = ['Avg_Credit_Limit','Total_Credit_Cards','Total_visits_bank','Total_visits_online','Total_calls_made']"
      ],
      "outputs": [],
      "execution_count": 54,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "## Analyzing the results"
      ],
      "outputs": [],
      "execution_count": 36,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "for feature in features:  #Loop to plot boxplot of each cluster\n",
        "    sns.boxplot(x='Segment',y=feature,data=data)\n",
        "    plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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z5mU0Zte8BfjL5vN+rdxokqR2azXSfzvw0cx8HHhnB/JIkkrkwuiSVCOtRvrPi4ivH2X7oeUSn1VCJklSSVqV/teAl3ciiCSpfK1Kfz4z/60jSSRJpWt1Tv/vO5JCktQRy5Z+Zr6tU0EkSeXz6h1JqhFLX5JqxNKXpBqx9CWpRix9SaoRS1+SasTSl6QasfQlqUYsfUmqEUtfkmrE0pekGrH0JalGLH1JqhFLX5JqxNKXpBqx9CWpRix9SaoRS1+SasTSl6QasfQlqUYsfUmqEUtfkmrE0pekGjmpkweLiLXABHAm0A+8JzPv6GQGSaqzTo/03wj8IDMvAC4BPtDh40tSrXV0pA98AvjkkvsHOnz8FRsfH2f79u1t3++uXbsAGB0dbfu+N2/ezNjYWNv3Kx3LTM8axjdsrDpGIft7egB42uJixUmKm+lZw8lt2ldHSz8z9wJExAYa5X9Vq+dMTU2VHWtZ09PTzM/Pt32/a9euBShl39PT00xOTrZ9v9LRrF+/no2nnVZ1jMIOPPooACcNDlacpLiNNP6e2/F73emRPhFxBnA78MHMvKXV9w8PD9Pf319+sGMYGRmp7NhSN7j11lurjrAih15db926teIk5Zibm1t2sNzpN3KHgM8Ab8vMz3Xy2JKkzo/0rwQGgasj4urmtksyc3+Hc0hSLXX6nP7bgbd38piSpMP8cJYk1YilL0k1YulLUo1Y+pJUI5a+JNWIpS9JNWLpS1KNWPqSVCOWviTViKUvSTVi6UtSjVj6klQjlr4k1YilL0k1YulLUo1Y+pJUIx1fI1eSihgfH2f79u1t3++uXbuAw2vlttvmzZsZGxsrZd/tYOlLqpV169ZVHaFSlr6kVWlsbGxVj5i7lef0JalGLH1JqhFLX5JqxNKXpBqx9CWpRix9SaoRS1+SamQ1X6ffCzA/P191DknqGks6s/doj6/m0j8dYMeOHVXnkKRudDrw0JEbV3Pp3wdcADwMLFScRZK6RS+Nwr/vaA/2LC4udjaOJKkyvpErSTVi6UtSjVj6klQjlr4k1YilL0k1spov2TxhRcQa4IPA84E54L9m5teqTaWViIjzgOsyc1PVWVRcRKwFJoAzgX7gPZl5R6WhOsyRfjV+HliXmS8GrgDeV3EerUBEXA78OVDvdfe60xuBH2TmBcAlwAcqztNxln41fgb4vwCZeS/wU9XG0Qo9BLyq6hA6Lp8Arl5y/0BVQapi6VdjANiz5P5CRHiqrUtk5l8BT1SdQyuXmXsz87GI2AB8Eriq6kydZulXYwbYsOT+msys3YhDqkJEnAHcBdycmbdUnafTLP1q/D3wcoCIeBHwQLVxpHqIiCHgM8DvZuZE1Xmq4CmFatwOvCwi/gHoAd5ScR6pLq4EBoGrI+LQuf1LMnN/hZk6ygnXJKlGPL0jSTVi6UtSjVj6klQjlr4k1YilL0k14iWbqoWI+EXgXTR+5tcAH8vM91ab6rCIuCszf7bqHDrxOdLXCS8ifpjGpHYXZebzgRcDvxwRr6g22ZNsqjqA6sGRvurgNGAtcDKNGRb3RsSbgdmIeCEw3nzsEeBXM/MbETEM3ETjd+RuGh/geXZE3AQ8DpwD/AcaH/a5lMY02X+dme+MiF7gvTSKvBe4KTPHI2JT8/v3Ac+l8Uns1wPXA0TEFzPzvJL/LlRzjvR1wsvMLwN/A3w9Iv4xIq6jUcbfojFF8usz8xwarwZuaD7to8A1mfkC4Os8eYD0Q81psa8FbgTeCrwAuCwiTgUuax73HOBc4JURcUHzuecDb6NR+j8KXJyZv9n8fgtfpbP0VQuZ+Ws0Fs74n8AzgXtprGXwY8AdEfHPwHXAsyJiI3BmZv5t8+lHztFyZ/PrvwFTmbkrMx8DdtP4iP9m4BXNfX4R+BHgJ5rPmcrMb2fmQeCrwMa2/2GlZXh6Rye8iBgFTsnMj9MYmd8YEZfROLXy9eZonuZpmSFggcacSMcyv+T20WZH7QUuz8zbmvs9DdgLvAiYXfJ9iy2OI7WdI33VwT7gTyLiTICI6KFxOuZeYOOSUy9bgFsycw/wUERc0tz+ehoFXdTnaZzqWRsRpwD30Cj85bimgjrC0tcJLzPvAv4Q+HREJPAgjdH8HwC/BLwvIv4FeDPwK82nvQm4JiLuB84DVjIL44eAfwW+BPwTcGNmfqHFc/4G+HJEuASjSuUsm9JRRMQ1wA2Z+XBEvAp4Q2a+uupc0lPly0np6L4FfDYingAe5fArAKmrOdKXpBrxnL4k1YilL0k1YulLUo1Y+pJUI5a+JNXI/wPN9jR6ibcJPwAAAABJRU5ErkJggg==\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 55,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Q6 Hierarchical Clustering"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import scipy.cluster.hierarchy as sch #import the library\n",
        "plt.figure(figsize=(12,8)) #Canvas size\n",
        "dendrogram = sch.dendrogram(sch.linkage(scaled_features, method = 'ward'))\n",
        "plt.title('Dendrogram')\n",
        "plt.xlabel('Customers')\n",
        "plt.ylabel('Euclidean distances')\n",
        "plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 864x576 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 38,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Based on the dendrogram number of clusters = 3**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.cluster.hierarchy import cophenet"
      ],
      "outputs": [],
      "execution_count": 39,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "cophenet_ =np.mean(cophenet(sch.linkage(scaled_features)))\n",
        "cophenet_"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 40,
          "data": {
            "text/plain": "0.21442781737262284"
          },
          "metadata": {}
        }
      ],
      "execution_count": 40,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import AgglomerativeClustering #Importing lib\n",
        "hc = AgglomerativeClustering(n_clusters = 3, affinity = 'euclidean', linkage = 'ward') #Euclidean distance, and ward linkage\n",
        "y_hc = hc.fit_predict(X) #TrainingTheModel"
      ],
      "outputs": [],
      "execution_count": 41,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "y_hc #Predictions"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 42,
          "data": {
            "text/plain": "array([1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n       1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1,\n       1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,\n       0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0,\n       1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0,\n       0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1,\n       0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0,\n       0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0,\n       1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0,\n       1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1,\n       1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 2, 1, 2, 1,\n       1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2,\n       2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 2],\n      dtype=int64)"
          },
          "metadata": {}
        }
      ],
      "execution_count": 42,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "df_yhc = pd.DataFrame(y_hc,columns=['HCluster'])"
      ],
      "outputs": [],
      "execution_count": 43,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "data= dataset.copy()\n",
        "data = pd.concat([data,df_yhc],axis=1)\n",
        "data.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 44,
          "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>Sl_No</th>\n      <th>Customer Key</th>\n      <th>Avg_Credit_Limit</th>\n      <th>Total_Credit_Cards</th>\n      <th>Total_visits_bank</th>\n      <th>Total_visits_online</th>\n      <th>Total_calls_made</th>\n      <th>HCluster</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>87073</td>\n      <td>100000</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>38414</td>\n      <td>50000</td>\n      <td>3</td>\n      <td>0</td>\n      <td>10</td>\n      <td>9</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>17341</td>\n      <td>50000</td>\n      <td>7</td>\n      <td>1</td>\n      <td>3</td>\n      <td>4</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>40496</td>\n      <td>30000</td>\n      <td>5</td>\n      <td>1</td>\n      <td>1</td>\n      <td>4</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>47437</td>\n      <td>100000</td>\n      <td>6</td>\n      <td>0</td>\n      <td>12</td>\n      <td>3</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
            "text/plain": "   Sl_No  Customer Key  Avg_Credit_Limit  Total_Credit_Cards  \\\n0      1         87073            100000                   2   \n1      2         38414             50000                   3   \n2      3         17341             50000                   7   \n3      4         40496             30000                   5   \n4      5         47437            100000                   6   \n\n   Total_visits_bank  Total_visits_online  Total_calls_made  HCluster  \n0                  1                    1                 0         1  \n1                  0                   10                 9         0  \n2                  1                    3                 4         0  \n3                  1                    1                 4         0  \n4                  0                   12                 3         1  "
          },
          "metadata": {}
        }
      ],
      "execution_count": 44,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "for feature in features:  #Loop to plot boxplot of each cluster\n",
        "    sns.boxplot(x='HCluster',y=feature,data=data)\n",
        "    plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 432x288 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 45,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Q7 Calculate avg silhoutte scores"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import silhouette_score"
      ],
      "outputs": [],
      "execution_count": 46,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "kmeans_score= silhouette_score(scaled_features,y_kmeans)\n",
        "kmeans_score"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 56,
          "data": {
            "text/plain": "0.1467806616998487"
          },
          "metadata": {}
        }
      ],
      "execution_count": 56,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "hc_score= silhouette_score(scaled_features,y_hc)\n",
        "hc_score"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 57,
          "data": {
            "text/plain": "0.11914770655113151"
          },
          "metadata": {}
        }
      ],
      "execution_count": 57,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"The silhoutte score of kmeans and Hierarchical Cluster are {} and {} respectively\".format(kmeans_score,hc_score))\n"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The silhoutte score of kmeans and Hierarchical Cluster are 0.058573709938719964 and 0.11914770655113151 respectively\n"
          ]
        }
      ],
      "execution_count": 49,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**The hc_score is greater than kmeans_score**\n",
        "\n",
        "Its analysis is as follows −\n",
        "\n",
        "+1 Score − Near +1 Silhouette score indicates that the sample is far away from its neighboring cluster.\n",
        "\n",
        "0 Score − 0 Silhouette score indicates that the sample is on or very close to the decision boundary separating two neighboring clusters.\n",
        "\n",
        "-1 Score − 1 Silhouette score indicates that the samples have been assigned to the wrong clusters."
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Q8 Comparing the clusters"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "Overall for this dataset Agglomerative Clustering has given better results.\n",
        "The silhoutte score of kmeans and Hierarchical Cluster are 0.058573709938719964 and 0.11914770655113151 respectively\n",
        "HC has higher silhoutte score."
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Q9 Final answers"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Kmeans Clusters"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Segment 0 has low credit limit and more number of total credit cards.\n",
        "\n",
        "    -This maybe the indication that they have high credit usage and low income.\n",
        "\n",
        "    -Segment 0 makes complaints by the medium of phone calls. \n",
        "\n",
        "    -The bank can arrange periodical feedback phone calls from Relationship Managers at the bank\n",
        "    \n",
        "    **They can be targeted for cross selling by the medium of phone calls**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "2. Segment 1 makes \n",
        "\n",
        "    -less number of phone calls \n",
        "\n",
        "    -highest number of online visits\n",
        "\n",
        "    -does not visit the bank at all\n",
        "\n",
        "    -This maybe the indication that Segment 1 is literate and premium customers of the bank with higher income.\n",
        "\n",
        "    **Luxury offers through emails and offers related to online shopping or coupons can be targeted to this segment**\n",
        "    **They have the potential of being most profitable customers**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "3. Segment 2 have almsot similar characterstics:\n",
        "    \n",
        "    -Median of 3 visits to the bank\n",
        "    \n",
        "    -Relatively higher visits to the bank\n",
        "    \n",
        "    -holds 4-6 Total Credit Cards\n",
        "    \n",
        "    **Both can targeted for cross selling through in bank managers and promotional advertisements in the bank**\n",
        "    \n",
        "    **Servicescape Promotions are Promotions done in the environment where the service is offered**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## hierarchial Clusters"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Observations**:\n",
        "\n",
        "**Cluster 0**\n",
        "\n",
        "-highest number of phone calls made\n",
        "\n",
        "-Less online presence/visits\n",
        "\n",
        "-high number of visits to the bank\n",
        "\n",
        "-low limit\n",
        "\n",
        "-lowest number of cards\n",
        "\n",
        "**The cluster 0 should be targeted through phone calls with Relationship Managers and cross selling through phone calls**\n",
        "    "
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Observations**:\n",
        "\n",
        "**Cluster 1**\n",
        "\n",
        "-medium number of calls made\n",
        "\n",
        "-lowest online visits\n",
        "\n",
        "-More number of visits in the bank\n",
        "\n",
        "-medium limit and cards\n",
        "\n",
        "\n",
        "**Customers in Cluster 1 should be targeted for cross selling through banks branches**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Observations**:\n",
        "\n",
        "**Cluster 2**\n",
        "\n",
        "-lowest number of calls made\n",
        "\n",
        "-highest online visits\n",
        "\n",
        "-negligible number of visits in the bank\n",
        "\n",
        "-high limit and cards\n",
        "\n",
        "\n",
        "**Platinum tier customers**\n",
        "\n",
        "**Affluent and premium customers are present in cluster 2.They should be targeted through loyalty prograns and luxury offers**"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Cluster 0 and Cluster 1 should be targeted to cover the operational costs\n",
        "\n",
        "\n",
        "## Cluster 2 should be targeted to reap profits"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Thank You!"
      ],
      "metadata": {}
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.4"
    },
    "nteract": {
      "version": "0.27.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}