diff --git a/211090_Swastik_1.ipynb b/211090_Swastik_1.ipynb
new file mode 100644
index 0000000..b31ae28
--- /dev/null
+++ b/211090_Swastik_1.ipynb
@@ -0,0 +1,2594 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "id": "e8e55d7e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.cluster import KMeans\n",
+    "from sklearn import metrics\n",
+    "from scipy.spatial.distance import cdist\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "id": "9ec79003",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>CUST_ID</th>\n",
+       "      <th>BALANCE</th>\n",
+       "      <th>BALANCE_FREQUENCY</th>\n",
+       "      <th>PURCHASES</th>\n",
+       "      <th>ONEOFF_PURCHASES</th>\n",
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+       "      <th>PURCHASES_FREQUENCY</th>\n",
+       "      <th>ONEOFF_PURCHASES_FREQUENCY</th>\n",
+       "      <th>PURCHASES_INSTALLMENTS_FREQUENCY</th>\n",
+       "      <th>CASH_ADVANCE_FREQUENCY</th>\n",
+       "      <th>CASH_ADVANCE_TRX</th>\n",
+       "      <th>PURCHASES_TRX</th>\n",
+       "      <th>CREDIT_LIMIT</th>\n",
+       "      <th>PAYMENTS</th>\n",
+       "      <th>MINIMUM_PAYMENTS</th>\n",
+       "      <th>PRC_FULL_PAYMENT</th>\n",
+       "      <th>TENURE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
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+       "      <td>0.222222</td>\n",
+       "      <td>12</td>\n",
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+       "    <tr>\n",
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+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
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+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
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+       "    <tr>\n",
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+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     CUST_ID      BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
+       "0     C10001    40.900749           0.818182      95.40              0.00   \n",
+       "1     C10002  3202.467416           0.909091       0.00              0.00   \n",
+       "2     C10003  2495.148862           1.000000     773.17            773.17   \n",
+       "3     C10004  1666.670542           0.636364    1499.00           1499.00   \n",
+       "4     C10005   817.714335           1.000000      16.00             16.00   \n",
+       "...      ...          ...                ...        ...               ...   \n",
+       "8945  C19186    28.493517           1.000000     291.12              0.00   \n",
+       "8946  C19187    19.183215           1.000000     300.00              0.00   \n",
+       "8947  C19188    23.398673           0.833333     144.40              0.00   \n",
+       "8948  C19189    13.457564           0.833333       0.00              0.00   \n",
+       "8949  C19190   372.708075           0.666667    1093.25           1093.25   \n",
+       "\n",
+       "      INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                      95.40      0.000000             0.166667   \n",
+       "1                       0.00   6442.945483             0.000000   \n",
+       "2                       0.00      0.000000             1.000000   \n",
+       "3                       0.00    205.788017             0.083333   \n",
+       "4                       0.00      0.000000             0.083333   \n",
+       "...                      ...           ...                  ...   \n",
+       "8945                  291.12      0.000000             1.000000   \n",
+       "8946                  300.00      0.000000             1.000000   \n",
+       "8947                  144.40      0.000000             0.833333   \n",
+       "8948                    0.00     36.558778             0.000000   \n",
+       "8949                    0.00    127.040008             0.666667   \n",
+       "\n",
+       "      ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
+       "0                       0.000000                          0.083333   \n",
+       "1                       0.000000                          0.000000   \n",
+       "2                       1.000000                          0.000000   \n",
+       "3                       0.083333                          0.000000   \n",
+       "4                       0.083333                          0.000000   \n",
+       "...                          ...                               ...   \n",
+       "8945                    0.000000                          0.833333   \n",
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+       "8947                    0.000000                          0.666667   \n",
+       "8948                    0.000000                          0.000000   \n",
+       "8949                    0.666667                          0.000000   \n",
+       "\n",
+       "      CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
+       "0                   0.000000                 0              2        1000.0   \n",
+       "1                   0.250000                 4              0        7000.0   \n",
+       "2                   0.000000                 0             12        7500.0   \n",
+       "3                   0.083333                 1              1        7500.0   \n",
+       "4                   0.000000                 0              1        1200.0   \n",
+       "...                      ...               ...            ...           ...   \n",
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+       "8947                0.000000                 0              5        1000.0   \n",
+       "8948                0.166667                 2              0         500.0   \n",
+       "8949                0.333333                 2             23        1200.0   \n",
+       "\n",
+       "         PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT  TENURE  \n",
+       "0      201.802084        139.509787          0.000000      12  \n",
+       "1     4103.032597       1072.340217          0.222222      12  \n",
+       "2      622.066742        627.284787          0.000000      12  \n",
+       "3        0.000000               NaN          0.000000      12  \n",
+       "4      678.334763        244.791237          0.000000      12  \n",
+       "...           ...               ...               ...     ...  \n",
+       "8945   325.594462         48.886365          0.500000       6  \n",
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+       "8947    81.270775         82.418369          0.250000       6  \n",
+       "8948    52.549959         55.755628          0.250000       6  \n",
+       "8949    63.165404         88.288956          0.000000       6  \n",
+       "\n",
+       "[8950 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = pd.read_csv(r'C:\\Users\\Hp\\Downloads\\Dataset.csv')\n",
+    "\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "4079f20a",
+   "metadata": {},
+   "outputs": [
+    {
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+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>7500.0</td>\n",
+       "      <td>622.066742</td>\n",
+       "      <td>627.284787</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1666.670542</td>\n",
+       "      <td>0.636364</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>205.788017</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7500.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>817.714335</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>678.334763</td>\n",
+       "      <td>244.791237</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>28.493517</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>291.12</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>291.12</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>325.594462</td>\n",
+       "      <td>48.886365</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>19.183215</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>300.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>300.00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>275.861322</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>23.398673</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>144.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>144.40</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>81.270775</td>\n",
+       "      <td>82.418369</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>13.457564</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>36.558778</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>500.0</td>\n",
+       "      <td>52.549959</td>\n",
+       "      <td>55.755628</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>372.708075</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1093.25</td>\n",
+       "      <td>1093.25</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>127.040008</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>23</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>63.165404</td>\n",
+       "      <td>88.288956</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
+       "0       40.900749           0.818182      95.40              0.00   \n",
+       "1     3202.467416           0.909091       0.00              0.00   \n",
+       "2     2495.148862           1.000000     773.17            773.17   \n",
+       "3     1666.670542           0.636364    1499.00           1499.00   \n",
+       "4      817.714335           1.000000      16.00             16.00   \n",
+       "...           ...                ...        ...               ...   \n",
+       "8945    28.493517           1.000000     291.12              0.00   \n",
+       "8946    19.183215           1.000000     300.00              0.00   \n",
+       "8947    23.398673           0.833333     144.40              0.00   \n",
+       "8948    13.457564           0.833333       0.00              0.00   \n",
+       "8949   372.708075           0.666667    1093.25           1093.25   \n",
+       "\n",
+       "      INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                      95.40      0.000000             0.166667   \n",
+       "1                       0.00   6442.945483             0.000000   \n",
+       "2                       0.00      0.000000             1.000000   \n",
+       "3                       0.00    205.788017             0.083333   \n",
+       "4                       0.00      0.000000             0.083333   \n",
+       "...                      ...           ...                  ...   \n",
+       "8945                  291.12      0.000000             1.000000   \n",
+       "8946                  300.00      0.000000             1.000000   \n",
+       "8947                  144.40      0.000000             0.833333   \n",
+       "8948                    0.00     36.558778             0.000000   \n",
+       "8949                    0.00    127.040008             0.666667   \n",
+       "\n",
+       "      ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
+       "0                       0.000000                          0.083333   \n",
+       "1                       0.000000                          0.000000   \n",
+       "2                       1.000000                          0.000000   \n",
+       "3                       0.083333                          0.000000   \n",
+       "4                       0.083333                          0.000000   \n",
+       "...                          ...                               ...   \n",
+       "8945                    0.000000                          0.833333   \n",
+       "8946                    0.000000                          0.833333   \n",
+       "8947                    0.000000                          0.666667   \n",
+       "8948                    0.000000                          0.000000   \n",
+       "8949                    0.666667                          0.000000   \n",
+       "\n",
+       "      CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
+       "0                   0.000000                 0              2        1000.0   \n",
+       "1                   0.250000                 4              0        7000.0   \n",
+       "2                   0.000000                 0             12        7500.0   \n",
+       "3                   0.083333                 1              1        7500.0   \n",
+       "4                   0.000000                 0              1        1200.0   \n",
+       "...                      ...               ...            ...           ...   \n",
+       "8945                0.000000                 0              6        1000.0   \n",
+       "8946                0.000000                 0              6        1000.0   \n",
+       "8947                0.000000                 0              5        1000.0   \n",
+       "8948                0.166667                 2              0         500.0   \n",
+       "8949                0.333333                 2             23        1200.0   \n",
+       "\n",
+       "         PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT  TENURE  \n",
+       "0      201.802084        139.509787          0.000000      12  \n",
+       "1     4103.032597       1072.340217          0.222222      12  \n",
+       "2      622.066742        627.284787          0.000000      12  \n",
+       "3        0.000000               NaN          0.000000      12  \n",
+       "4      678.334763        244.791237          0.000000      12  \n",
+       "...           ...               ...               ...     ...  \n",
+       "8945   325.594462         48.886365          0.500000       6  \n",
+       "8946   275.861322               NaN          0.000000       6  \n",
+       "8947    81.270775         82.418369          0.250000       6  \n",
+       "8948    52.549959         55.755628          0.250000       6  \n",
+       "8949    63.165404         88.288956          0.000000       6  \n",
+       "\n",
+       "[8950 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = data.drop(['CUST_ID'],axis=1)\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "1df9d17d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data2 = data.dropna(thresh=6250,axis=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "id": "0217edb5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>BALANCE</th>\n",
+       "      <th>BALANCE_FREQUENCY</th>\n",
+       "      <th>PURCHASES</th>\n",
+       "      <th>ONEOFF_PURCHASES</th>\n",
+       "      <th>INSTALLMENTS_PURCHASES</th>\n",
+       "      <th>CASH_ADVANCE</th>\n",
+       "      <th>PURCHASES_FREQUENCY</th>\n",
+       "      <th>ONEOFF_PURCHASES_FREQUENCY</th>\n",
+       "      <th>PURCHASES_INSTALLMENTS_FREQUENCY</th>\n",
+       "      <th>CASH_ADVANCE_FREQUENCY</th>\n",
+       "      <th>CASH_ADVANCE_TRX</th>\n",
+       "      <th>PURCHASES_TRX</th>\n",
+       "      <th>CREDIT_LIMIT</th>\n",
+       "      <th>PAYMENTS</th>\n",
+       "      <th>MINIMUM_PAYMENTS</th>\n",
+       "      <th>PRC_FULL_PAYMENT</th>\n",
+       "      <th>TENURE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>40.900749</td>\n",
+       "      <td>0.818182</td>\n",
+       "      <td>95.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>95.40</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>201.802084</td>\n",
+       "      <td>139.509787</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3202.467416</td>\n",
+       "      <td>0.909091</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>6442.945483</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7000.0</td>\n",
+       "      <td>4103.032597</td>\n",
+       "      <td>1072.340217</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2495.148862</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>773.17</td>\n",
+       "      <td>773.17</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>7500.0</td>\n",
+       "      <td>622.066742</td>\n",
+       "      <td>627.284787</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1666.670542</td>\n",
+       "      <td>0.636364</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>205.788017</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7500.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>864.206542</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>817.714335</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>678.334763</td>\n",
+       "      <td>244.791237</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>28.493517</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>291.12</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>291.12</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>325.594462</td>\n",
+       "      <td>48.886365</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>19.183215</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>300.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>300.00</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>275.861322</td>\n",
+       "      <td>864.206542</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>23.398673</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>144.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>144.40</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>81.270775</td>\n",
+       "      <td>82.418369</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>13.457564</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>36.558778</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>500.0</td>\n",
+       "      <td>52.549959</td>\n",
+       "      <td>55.755628</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>372.708075</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1093.25</td>\n",
+       "      <td>1093.25</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>127.040008</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>23</td>\n",
+       "      <td>1200.0</td>\n",
+       "      <td>63.165404</td>\n",
+       "      <td>88.288956</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
+       "0       40.900749           0.818182      95.40              0.00   \n",
+       "1     3202.467416           0.909091       0.00              0.00   \n",
+       "2     2495.148862           1.000000     773.17            773.17   \n",
+       "3     1666.670542           0.636364    1499.00           1499.00   \n",
+       "4      817.714335           1.000000      16.00             16.00   \n",
+       "...           ...                ...        ...               ...   \n",
+       "8945    28.493517           1.000000     291.12              0.00   \n",
+       "8946    19.183215           1.000000     300.00              0.00   \n",
+       "8947    23.398673           0.833333     144.40              0.00   \n",
+       "8948    13.457564           0.833333       0.00              0.00   \n",
+       "8949   372.708075           0.666667    1093.25           1093.25   \n",
+       "\n",
+       "      INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                      95.40      0.000000             0.166667   \n",
+       "1                       0.00   6442.945483             0.000000   \n",
+       "2                       0.00      0.000000             1.000000   \n",
+       "3                       0.00    205.788017             0.083333   \n",
+       "4                       0.00      0.000000             0.083333   \n",
+       "...                      ...           ...                  ...   \n",
+       "8945                  291.12      0.000000             1.000000   \n",
+       "8946                  300.00      0.000000             1.000000   \n",
+       "8947                  144.40      0.000000             0.833333   \n",
+       "8948                    0.00     36.558778             0.000000   \n",
+       "8949                    0.00    127.040008             0.666667   \n",
+       "\n",
+       "      ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
+       "0                       0.000000                          0.083333   \n",
+       "1                       0.000000                          0.000000   \n",
+       "2                       1.000000                          0.000000   \n",
+       "3                       0.083333                          0.000000   \n",
+       "4                       0.083333                          0.000000   \n",
+       "...                          ...                               ...   \n",
+       "8945                    0.000000                          0.833333   \n",
+       "8946                    0.000000                          0.833333   \n",
+       "8947                    0.000000                          0.666667   \n",
+       "8948                    0.000000                          0.000000   \n",
+       "8949                    0.666667                          0.000000   \n",
+       "\n",
+       "      CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
+       "0                   0.000000                 0              2        1000.0   \n",
+       "1                   0.250000                 4              0        7000.0   \n",
+       "2                   0.000000                 0             12        7500.0   \n",
+       "3                   0.083333                 1              1        7500.0   \n",
+       "4                   0.000000                 0              1        1200.0   \n",
+       "...                      ...               ...            ...           ...   \n",
+       "8945                0.000000                 0              6        1000.0   \n",
+       "8946                0.000000                 0              6        1000.0   \n",
+       "8947                0.000000                 0              5        1000.0   \n",
+       "8948                0.166667                 2              0         500.0   \n",
+       "8949                0.333333                 2             23        1200.0   \n",
+       "\n",
+       "         PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT  TENURE  \n",
+       "0      201.802084        139.509787          0.000000      12  \n",
+       "1     4103.032597       1072.340217          0.222222      12  \n",
+       "2      622.066742        627.284787          0.000000      12  \n",
+       "3        0.000000        864.206542          0.000000      12  \n",
+       "4      678.334763        244.791237          0.000000      12  \n",
+       "...           ...               ...               ...     ...  \n",
+       "8945   325.594462         48.886365          0.500000       6  \n",
+       "8946   275.861322        864.206542          0.000000       6  \n",
+       "8947    81.270775         82.418369          0.250000       6  \n",
+       "8948    52.549959         55.755628          0.250000       6  \n",
+       "8949    63.165404         88.288956          0.000000       6  \n",
+       "\n",
+       "[8950 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 106,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "column_means = data2.mean()\n",
+    "data2 = data2.fillna(column_means)\n",
+    "data2\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "id": "7fd47015",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x20f8e9bb880>"
+      ]
+     },
+     "execution_count": 107,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.displot(data2, x=\"BALANCE\", kind=\"kde\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "id": "9bddef60",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x20fa5ac78e0>"
+      ]
+     },
+     "execution_count": 108,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "sns.displot(data, x=\"BALANCE_FREQUENCY\", kind=\"kde\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "id": "495120f6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x20fa5afe530>"
+      ]
+     },
+     "execution_count": 109,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 360x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.displot(data2, x=\"PURCHASES\", kind=\"kde\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "id": "8b976db8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "y=data2['BALANCE']\n",
+    "\n",
+    "plt.plot(y)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "2d1bc407",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "BALANCE                              2.393386\n",
+       "BALANCE_FREQUENCY                   -2.023266\n",
+       "PURCHASES                            8.144269\n",
+       "ONEOFF_PURCHASES                    10.045083\n",
+       "INSTALLMENTS_PURCHASES               7.299120\n",
+       "CASH_ADVANCE                         5.166609\n",
+       "PURCHASES_FREQUENCY                  0.060164\n",
+       "ONEOFF_PURCHASES_FREQUENCY           1.535613\n",
+       "PURCHASES_INSTALLMENTS_FREQUENCY     0.509201\n",
+       "CASH_ADVANCE_FREQUENCY               1.828686\n",
+       "CASH_ADVANCE_TRX                     5.721298\n",
+       "PURCHASES_TRX                        4.630655\n",
+       "CREDIT_LIMIT                         1.522549\n",
+       "PAYMENTS                             5.907620\n",
+       "MINIMUM_PAYMENTS                    13.867357\n",
+       "PRC_FULL_PAYMENT                     1.942820\n",
+       "TENURE                              -2.943017\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 111,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data2.skew(axis = 0, skipna = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "49dad5e5",
+   "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>BALANCE</th>\n",
+       "      <th>BALANCE_FREQUENCY</th>\n",
+       "      <th>PURCHASES</th>\n",
+       "      <th>ONEOFF_PURCHASES</th>\n",
+       "      <th>INSTALLMENTS_PURCHASES</th>\n",
+       "      <th>CASH_ADVANCE</th>\n",
+       "      <th>PURCHASES_FREQUENCY</th>\n",
+       "      <th>ONEOFF_PURCHASES_FREQUENCY</th>\n",
+       "      <th>PURCHASES_INSTALLMENTS_FREQUENCY</th>\n",
+       "      <th>CASH_ADVANCE_FREQUENCY</th>\n",
+       "      <th>CASH_ADVANCE_TRX</th>\n",
+       "      <th>PURCHASES_TRX</th>\n",
+       "      <th>CREDIT_LIMIT</th>\n",
+       "      <th>PAYMENTS</th>\n",
+       "      <th>MINIMUM_PAYMENTS</th>\n",
+       "      <th>PRC_FULL_PAYMENT</th>\n",
+       "      <th>TENURE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>6.395369</td>\n",
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+       "      <td>9.767292</td>\n",
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+       "      <td>0.000000</td>\n",
+       "      <td>3.464102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>56.590347</td>\n",
+       "      <td>0.953463</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>80.267961</td>\n",
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+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>83.666003</td>\n",
+       "      <td>64.054919</td>\n",
+       "      <td>32.746606</td>\n",
+       "      <td>0.471404</td>\n",
+       "      <td>3.464102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>49.951465</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>27.805935</td>\n",
+       "      <td>27.805935</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.464102</td>\n",
+       "      <td>86.602540</td>\n",
+       "      <td>24.941266</td>\n",
+       "      <td>25.045654</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.464102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>40.824877</td>\n",
+       "      <td>0.797724</td>\n",
+       "      <td>38.716921</td>\n",
+       "      <td>38.716921</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>14.345313</td>\n",
+       "      <td>0.288675</td>\n",
+       "      <td>0.288675</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.288675</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>86.602540</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>29.397390</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.464102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>28.595705</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>4.000000</td>\n",
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+       "      <td>26.044861</td>\n",
+       "      <td>15.645806</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.464102</td>\n",
+       "    </tr>\n",
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+       "      <td>...</td>\n",
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+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>5.337932</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>17.062239</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>17.062239</td>\n",
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+       "      <td>6.991879</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>4.379865</td>\n",
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+       "      <td>17.320508</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>17.320508</td>\n",
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+       "      <td>1.000000</td>\n",
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+       "      <td>2.449490</td>\n",
+       "      <td>31.622777</td>\n",
+       "      <td>16.609073</td>\n",
+       "      <td>29.397390</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.449490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>4.837217</td>\n",
+       "      <td>0.912871</td>\n",
+       "      <td>12.016655</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12.016655</td>\n",
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+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
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+       "      <td>2.449490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>3.668455</td>\n",
+       "      <td>0.912871</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
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+       "      <td>6.046386</td>\n",
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+       "      <td>0.408249</td>\n",
+       "      <td>1.414214</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>22.360680</td>\n",
+       "      <td>7.249135</td>\n",
+       "      <td>7.466969</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>2.449490</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>19.305649</td>\n",
+       "      <td>0.816497</td>\n",
+       "      <td>33.064331</td>\n",
+       "      <td>33.064331</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>11.271203</td>\n",
+       "      <td>0.816497</td>\n",
+       "      <td>0.816497</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.577350</td>\n",
+       "      <td>1.414214</td>\n",
+       "      <td>4.795832</td>\n",
+       "      <td>34.641016</td>\n",
+       "      <td>7.947667</td>\n",
+       "      <td>9.396220</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.449490</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
+       "0      6.395369           0.904534   9.767292          0.000000   \n",
+       "1     56.590347           0.953463   0.000000          0.000000   \n",
+       "2     49.951465           1.000000  27.805935         27.805935   \n",
+       "3     40.824877           0.797724  38.716921         38.716921   \n",
+       "4     28.595705           1.000000   4.000000          4.000000   \n",
+       "...         ...                ...        ...               ...   \n",
+       "8945   5.337932           1.000000  17.062239          0.000000   \n",
+       "8946   4.379865           1.000000  17.320508          0.000000   \n",
+       "8947   4.837217           0.912871  12.016655          0.000000   \n",
+       "8948   3.668455           0.912871   0.000000          0.000000   \n",
+       "8949  19.305649           0.816497  33.064331         33.064331   \n",
+       "\n",
+       "      INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                   9.767292      0.000000             0.408249   \n",
+       "1                   0.000000     80.267961             0.000000   \n",
+       "2                   0.000000      0.000000             1.000000   \n",
+       "3                   0.000000     14.345313             0.288675   \n",
+       "4                   0.000000      0.000000             0.288675   \n",
+       "...                      ...           ...                  ...   \n",
+       "8945               17.062239      0.000000             1.000000   \n",
+       "8946               17.320508      0.000000             1.000000   \n",
+       "8947               12.016655      0.000000             0.912871   \n",
+       "8948                0.000000      6.046386             0.000000   \n",
+       "8949                0.000000     11.271203             0.816497   \n",
+       "\n",
+       "      ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
+       "0                       0.000000                          0.288675   \n",
+       "1                       0.000000                          0.000000   \n",
+       "2                       1.000000                          0.000000   \n",
+       "3                       0.288675                          0.000000   \n",
+       "4                       0.288675                          0.000000   \n",
+       "...                          ...                               ...   \n",
+       "8945                    0.000000                          0.912871   \n",
+       "8946                    0.000000                          0.912871   \n",
+       "8947                    0.000000                          0.816497   \n",
+       "8948                    0.000000                          0.000000   \n",
+       "8949                    0.816497                          0.000000   \n",
+       "\n",
+       "      CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
+       "0                   0.000000          0.000000       1.414214     31.622777   \n",
+       "1                   0.500000          2.000000       0.000000     83.666003   \n",
+       "2                   0.000000          0.000000       3.464102     86.602540   \n",
+       "3                   0.288675          1.000000       1.000000     86.602540   \n",
+       "4                   0.000000          0.000000       1.000000     34.641016   \n",
+       "...                      ...               ...            ...           ...   \n",
+       "8945                0.000000          0.000000       2.449490     31.622777   \n",
+       "8946                0.000000          0.000000       2.449490     31.622777   \n",
+       "8947                0.000000          0.000000       2.236068     31.622777   \n",
+       "8948                0.408249          1.414214       0.000000     22.360680   \n",
+       "8949                0.577350          1.414214       4.795832     34.641016   \n",
+       "\n",
+       "       PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT    TENURE  \n",
+       "0     14.205706         11.811426          0.000000  3.464102  \n",
+       "1     64.054919         32.746606          0.471404  3.464102  \n",
+       "2     24.941266         25.045654          0.000000  3.464102  \n",
+       "3      0.000000         29.397390          0.000000  3.464102  \n",
+       "4     26.044861         15.645806          0.000000  3.464102  \n",
+       "...         ...               ...               ...       ...  \n",
+       "8945  18.044236          6.991879          0.707107  2.449490  \n",
+       "8946  16.609073         29.397390          0.000000  2.449490  \n",
+       "8947   9.015031          9.078456          0.500000  2.449490  \n",
+       "8948   7.249135          7.466969          0.500000  2.449490  \n",
+       "8949   7.947667          9.396220          0.000000  2.449490  \n",
+       "\n",
+       "[8950 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 112,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_sqrt = np.sqrt(data2)\n",
+    "data_sqrt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "e5d3e42d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = data_sqrt['BALANCE']\n",
+    "plt.plot(x)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "id": "cfdc7435",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>],\n",
+       "       [<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>],\n",
+       "       [<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>],\n",
+       "       [<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>],\n",
+       "       [<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>]],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2160x1440 with 20 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_sqrt.plot(subplots=True, layout=(5,4), figsize=(30,20))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "id": "f75e2ef8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "BALANCE                             0.829498\n",
+       "BALANCE_FREQUENCY                  -2.819495\n",
+       "PURCHASES                           1.730752\n",
+       "ONEOFF_PURCHASES                    2.129460\n",
+       "INSTALLMENTS_PURCHASES              1.546939\n",
+       "CASH_ADVANCE                        1.486159\n",
+       "PURCHASES_FREQUENCY                -0.421872\n",
+       "ONEOFF_PURCHASES_FREQUENCY          0.724607\n",
+       "PURCHASES_INSTALLMENTS_FREQUENCY    0.130409\n",
+       "CASH_ADVANCE_FREQUENCY              0.706976\n",
+       "CASH_ADVANCE_TRX                    1.417779\n",
+       "PURCHASES_TRX                       1.185757\n",
+       "CREDIT_LIMIT                        0.680933\n",
+       "PAYMENTS                            1.951535\n",
+       "MINIMUM_PAYMENTS                    3.805340\n",
+       "PRC_FULL_PAYMENT                    1.297280\n",
+       "TENURE                             -3.064332\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 115,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_sqrt.skew(axis = 0, skipna = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "aab3375c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "corrMat = data_sqrt.corr()\n",
+    "plt.figure(figsize=(10,10))\n",
+    "heat_map = sns.heatmap( corrMat, linewidth = 1 , annot = True)\n",
+    "plt.title( \"HeatMap for Correlation Matrix\" )\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "89f5b470",
+   "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>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>10</th>\n",
+       "      <th>11</th>\n",
+       "      <th>12</th>\n",
+       "      <th>13</th>\n",
+       "      <th>14</th>\n",
+       "      <th>15</th>\n",
+       "      <th>16</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-1.078055</td>\n",
+       "      <td>-0.097126</td>\n",
+       "      <td>-0.596901</td>\n",
+       "      <td>-0.724371</td>\n",
+       "      <td>-0.209397</td>\n",
+       "      <td>-0.732851</td>\n",
+       "      <td>-0.455097</td>\n",
+       "      <td>-0.881832</td>\n",
+       "      <td>-0.350094</td>\n",
+       "      <td>-0.861347</td>\n",
+       "      <td>-0.772904</td>\n",
+       "      <td>-0.578392</td>\n",
+       "      <td>-1.212811</td>\n",
+       "      <td>-0.885440</td>\n",
+       "      <td>-0.667902</td>\n",
+       "      <td>-0.636182</td>\n",
+       "      <td>0.353481</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.053619</td>\n",
+       "      <td>0.190539</td>\n",
+       "      <td>-1.042337</td>\n",
+       "      <td>-0.724371</td>\n",
+       "      <td>-0.837899</td>\n",
+       "      <td>2.447876</td>\n",
+       "      <td>-1.511903</td>\n",
+       "      <td>-0.881832</td>\n",
+       "      <td>-1.040015</td>\n",
+       "      <td>0.933739</td>\n",
+       "      <td>0.629493</td>\n",
+       "      <td>-1.136616</td>\n",
+       "      <td>0.855514</td>\n",
+       "      <td>1.274046</td>\n",
+       "      <td>0.522544</td>\n",
+       "      <td>0.788874</td>\n",
+       "      <td>0.353481</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.771680</td>\n",
+       "      <td>0.464146</td>\n",
+       "      <td>0.225748</td>\n",
+       "      <td>0.686250</td>\n",
+       "      <td>-0.837899</td>\n",
+       "      <td>-0.732851</td>\n",
+       "      <td>1.076731</td>\n",
+       "      <td>2.081316</td>\n",
+       "      <td>-1.040015</td>\n",
+       "      <td>-0.861347</td>\n",
+       "      <td>-0.772904</td>\n",
+       "      <td>0.230748</td>\n",
+       "      <td>0.972220</td>\n",
+       "      <td>-0.420372</td>\n",
+       "      <td>0.084642</td>\n",
+       "      <td>-0.636182</td>\n",
+       "      <td>0.353481</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.384093</td>\n",
+       "      <td>-0.725092</td>\n",
+       "      <td>0.723342</td>\n",
+       "      <td>1.239775</td>\n",
+       "      <td>-0.837899</td>\n",
+       "      <td>-0.164399</td>\n",
+       "      <td>-0.764630</td>\n",
+       "      <td>-0.026447</td>\n",
+       "      <td>-1.040015</td>\n",
+       "      <td>0.175044</td>\n",
+       "      <td>-0.071706</td>\n",
+       "      <td>-0.741892</td>\n",
+       "      <td>0.972220</td>\n",
+       "      <td>-1.500837</td>\n",
+       "      <td>0.332096</td>\n",
+       "      <td>-0.636182</td>\n",
+       "      <td>0.353481</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-0.135254</td>\n",
+       "      <td>0.464146</td>\n",
+       "      <td>-0.859918</td>\n",
+       "      <td>-0.521447</td>\n",
+       "      <td>-0.837899</td>\n",
+       "      <td>-0.732851</td>\n",
+       "      <td>-0.764630</td>\n",
+       "      <td>-0.026447</td>\n",
+       "      <td>-1.040015</td>\n",
+       "      <td>-0.861347</td>\n",
+       "      <td>-0.772904</td>\n",
+       "      <td>-0.741892</td>\n",
+       "      <td>-1.092859</td>\n",
+       "      <td>-0.372564</td>\n",
+       "      <td>-0.449866</td>\n",
+       "      <td>-0.636182</td>\n",
+       "      <td>0.353481</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>-1.122962</td>\n",
+       "      <td>0.464146</td>\n",
+       "      <td>-0.264216</td>\n",
+       "      <td>-0.724371</td>\n",
+       "      <td>0.260016</td>\n",
+       "      <td>-0.732851</td>\n",
+       "      <td>1.076731</td>\n",
+       "      <td>-0.881832</td>\n",
+       "      <td>1.141709</td>\n",
+       "      <td>-0.861347</td>\n",
+       "      <td>-0.772904</td>\n",
+       "      <td>-0.169743</td>\n",
+       "      <td>-1.212811</td>\n",
+       "      <td>-0.719154</td>\n",
+       "      <td>-0.941958</td>\n",
+       "      <td>1.501403</td>\n",
+       "      <td>-4.276127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>-1.163649</td>\n",
+       "      <td>0.464146</td>\n",
+       "      <td>-0.252438</td>\n",
+       "      <td>-0.724371</td>\n",
+       "      <td>0.276635</td>\n",
+       "      <td>-0.732851</td>\n",
+       "      <td>1.076731</td>\n",
+       "      <td>-0.881832</td>\n",
+       "      <td>1.141709</td>\n",
+       "      <td>-0.861347</td>\n",
+       "      <td>-0.772904</td>\n",
+       "      <td>-0.169743</td>\n",
+       "      <td>-1.212811</td>\n",
+       "      <td>-0.781326</td>\n",
+       "      <td>0.332096</td>\n",
+       "      <td>-0.636182</td>\n",
+       "      <td>-4.276127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>-1.144226</td>\n",
+       "      <td>-0.048112</td>\n",
+       "      <td>-0.494319</td>\n",
+       "      <td>-0.724371</td>\n",
+       "      <td>-0.064656</td>\n",
+       "      <td>-0.732851</td>\n",
+       "      <td>0.851185</td>\n",
+       "      <td>-0.881832</td>\n",
+       "      <td>0.911379</td>\n",
+       "      <td>-0.861347</td>\n",
+       "      <td>-0.772904</td>\n",
+       "      <td>-0.253986</td>\n",
+       "      <td>-1.212811</td>\n",
+       "      <td>-1.110302</td>\n",
+       "      <td>-0.823308</td>\n",
+       "      <td>0.875319</td>\n",
+       "      <td>-4.276127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>-1.193861</td>\n",
+       "      <td>-0.048112</td>\n",
+       "      <td>-1.042337</td>\n",
+       "      <td>-0.724371</td>\n",
+       "      <td>-0.837899</td>\n",
+       "      <td>-0.493255</td>\n",
+       "      <td>-1.511903</td>\n",
+       "      <td>-0.881832</td>\n",
+       "      <td>-1.040015</td>\n",
+       "      <td>0.604336</td>\n",
+       "      <td>0.218740</td>\n",
+       "      <td>-1.136616</td>\n",
+       "      <td>-1.580910</td>\n",
+       "      <td>-1.186802</td>\n",
+       "      <td>-0.914943</td>\n",
+       "      <td>0.875319</td>\n",
+       "      <td>-4.276127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>-0.529782</td>\n",
+       "      <td>-0.614723</td>\n",
+       "      <td>0.465556</td>\n",
+       "      <td>0.953013</td>\n",
+       "      <td>-0.837899</td>\n",
+       "      <td>-0.286215</td>\n",
+       "      <td>0.601708</td>\n",
+       "      <td>1.537568</td>\n",
+       "      <td>-1.040015</td>\n",
+       "      <td>1.211439</td>\n",
+       "      <td>0.218740</td>\n",
+       "      <td>0.756414</td>\n",
+       "      <td>-1.092859</td>\n",
+       "      <td>-1.156541</td>\n",
+       "      <td>-0.805239</td>\n",
+       "      <td>-0.636182</td>\n",
+       "      <td>-4.276127</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            0         1         2         3         4         5         6   \\\n",
+       "0    -1.078055 -0.097126 -0.596901 -0.724371 -0.209397 -0.732851 -0.455097   \n",
+       "1     1.053619  0.190539 -1.042337 -0.724371 -0.837899  2.447876 -1.511903   \n",
+       "2     0.771680  0.464146  0.225748  0.686250 -0.837899 -0.732851  1.076731   \n",
+       "3     0.384093 -0.725092  0.723342  1.239775 -0.837899 -0.164399 -0.764630   \n",
+       "4    -0.135254  0.464146 -0.859918 -0.521447 -0.837899 -0.732851 -0.764630   \n",
+       "...        ...       ...       ...       ...       ...       ...       ...   \n",
+       "8945 -1.122962  0.464146 -0.264216 -0.724371  0.260016 -0.732851  1.076731   \n",
+       "8946 -1.163649  0.464146 -0.252438 -0.724371  0.276635 -0.732851  1.076731   \n",
+       "8947 -1.144226 -0.048112 -0.494319 -0.724371 -0.064656 -0.732851  0.851185   \n",
+       "8948 -1.193861 -0.048112 -1.042337 -0.724371 -0.837899 -0.493255 -1.511903   \n",
+       "8949 -0.529782 -0.614723  0.465556  0.953013 -0.837899 -0.286215  0.601708   \n",
+       "\n",
+       "            7         8         9         10        11        12        13  \\\n",
+       "0    -0.881832 -0.350094 -0.861347 -0.772904 -0.578392 -1.212811 -0.885440   \n",
+       "1    -0.881832 -1.040015  0.933739  0.629493 -1.136616  0.855514  1.274046   \n",
+       "2     2.081316 -1.040015 -0.861347 -0.772904  0.230748  0.972220 -0.420372   \n",
+       "3    -0.026447 -1.040015  0.175044 -0.071706 -0.741892  0.972220 -1.500837   \n",
+       "4    -0.026447 -1.040015 -0.861347 -0.772904 -0.741892 -1.092859 -0.372564   \n",
+       "...        ...       ...       ...       ...       ...       ...       ...   \n",
+       "8945 -0.881832  1.141709 -0.861347 -0.772904 -0.169743 -1.212811 -0.719154   \n",
+       "8946 -0.881832  1.141709 -0.861347 -0.772904 -0.169743 -1.212811 -0.781326   \n",
+       "8947 -0.881832  0.911379 -0.861347 -0.772904 -0.253986 -1.212811 -1.110302   \n",
+       "8948 -0.881832 -1.040015  0.604336  0.218740 -1.136616 -1.580910 -1.186802   \n",
+       "8949  1.537568 -1.040015  1.211439  0.218740  0.756414 -1.092859 -1.156541   \n",
+       "\n",
+       "            14        15        16  \n",
+       "0    -0.667902 -0.636182  0.353481  \n",
+       "1     0.522544  0.788874  0.353481  \n",
+       "2     0.084642 -0.636182  0.353481  \n",
+       "3     0.332096 -0.636182  0.353481  \n",
+       "4    -0.449866 -0.636182  0.353481  \n",
+       "...        ...       ...       ...  \n",
+       "8945 -0.941958  1.501403 -4.276127  \n",
+       "8946  0.332096 -0.636182 -4.276127  \n",
+       "8947 -0.823308  0.875319 -4.276127  \n",
+       "8948 -0.914943  0.875319 -4.276127  \n",
+       "8949 -0.805239 -0.636182 -4.276127  \n",
+       "\n",
+       "[8950 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 117,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.preprocessing import StandardScaler\n",
+    "std_data = StandardScaler().fit_transform(data_sqrt)\n",
+    "std_data = pd.DataFrame(std_data)\n",
+    "std_data\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "3133eb19",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Cumulative explained variance')"
+      ]
+     },
+     "execution_count": 118,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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aFiVBrA2L9f0VeMbMNgOrIjxvMLAm8TzAhCbH/AT4l5ldAeQCJzd3IjObSjCqm8LCwggvLY1q6ur50RMLeWzuWj536H788otj6N5NjdEi0roovZjOChd/YmbPE3zTf6qdXn8y8Ed3/5WZHQX8ycxGu3tDkximA9MBiouLvZ1eu9Mr31HD1++fy+yVm5l2UhHTTioiI0ON0SISTZRG6t8CD7n7q+7+YhvOvY6PzhsxJNyW6KvAqQDu/pqZZQMFBHNOyCeweMN2vnrvbEq31/DbyYdz5phBcYckImkmSiP1XODHZrbMzH5pZsURzz0bKDKzEWbWjaARekaTY1YDJwGY2acIutGWRjy/7MGbKyo457ZXqalr4OHLjlJyEJG90mqCcPd73f10gp5Mi4EbzawkwvPqgMuBp4H3CHorvWtm15vZmeFh3wWmmNnbwIPApe6uW0ifwJyVFVx6z5sMyMtixuXHMHZo77hDEpE0FWmgXOgA4CBgGMEHfqvCMQ0zm2y7NmF5EXBMG2KQFsxbvZlL75nNwLxsHpwykf7qqSQin0CrVxBm9ovwiuF64B2g2N3PSHpk0iYL1m7hkrvepG+Pbjyg5CAi7SDKFcQy4Ch3L0t2MLJ3Fq7bykV3vkHv3K48OGUiA3spOYjIJxelm+sfOiIQ2Tvvrd/GRXe9Qc/srjzwtYkM6t097pBEpJOI0otJUtTiDdu58M436N41kwenTGRofk7cIYlIJ6IEkaaWbtrOhXe+TpcM44EpEynsq+QgIu1rj7eYzCy/pSe6e0X7hyNRLC/dweQ73gCMB6dOZERBbtwhiUgn1FIbxFyCYnoGFAKbw+XeBAPcRiQ7OPm4VeWVXHDHGzQ0OA9Nncj+/XrEHZKIdFJ7vMXk7iPcfSTwLHCGuxe4e1/g88C/OipA+dCaiiomT3+dmrp6HpgykaIBmuxPRJInShvExMRJfNz9n8DRyQtJmrN2cxWT73idyl313P+1CRw4UMlBRJIryjiID8zsx8D94fqFaN6GDrV+604uuOMNtu6s5YGvTeSQQb3iDklE9gFRriAmA/2AJ4DHw+XJyQxKPrRxWzWTp7/O5spd/OmrEzh0iJKDiHSMKAPlKoBpZpbr7pUdEJOENm2vZvIdr1O6vYb7vjpBhfdEpENFqcV0tJktIizQZ2ZjzExzRydZ2Y4aLrzjDTZsreaPXzmS8cP6xB2SiOxjotxiuhn4LFAO4O5vA8clM6h9XUXlLi668w3WbK7i7kuP4IjhLQ5JERFJikgjqd19TZNN9UmIRYAtVUFyWFFWyV2XHMHEkX3jDklE9lFRejGtMbOjATezrsA0Is4HIW2zdWctX7rrTZaW7uDOi4s55oCCuEMSkX1YlCuIrwPfAgYTzCk9NlyXdlRdW8+l97zJ4g3b+cNF4zluVL+4QxKRfVyUXkxlBGMfJEncne89+jbz12zhtgvHccJB/eMOSUSk9QRhZv2AKcDwxOPd/SvJC2vfcsuzJfx9wXquPu0gTh29X9zhiIgA0dog/gbMIqjJpMbpdjbj7Q/4zXMlfHH8EC47bmTc4YiI7BYlQeS4+w+SHsk+6K3Vm/neo29z5PB8/uesQzGzuEMSEdktSiP1383s9L05uZmdamaLzWypmV3dzP6bzWx++FhiZlv25nXS0botO5ly31wG5mVz+5fG062L5m4SkdQS5QpiGvBDM6sBagnmhHB3z2vpSWaWCdwKnAKsBWab2Qx3X9R4jLt/J+H4K4DD2/4W0k9lTR1fu3cONbX1PDhlAvm53eIOSUTkY1r92uruPd09w927u3teuN5icggdCSx19+Xuvgt4CJjUwvGTgQejhZ2+6hucaQ/NZ8nG7fz+wnGa00FEUlZLU44e5O7vm9m45va7+7xWzj0YSByBvRaYsIfXGkYwQ92/97B/KjAVoLCwsJWXTW03PvU+z763kesnHcJnNNZBRFJYS7eYriL4UP5VM/scOLEd4zgfeMzdm+0l5e7TgekAxcXF3o6v26Eenr2a6S8t5+KjhnHxUcPjDkdEpEV7TBDuPjX8ecJennsdMDRhfUi4rTnn08lHZ7++vJwfPbGQY4sKuPbzB8cdjohIq6I0UmNmo4GDgezGbe5+XytPmw0UmdkIgsRwPnBBM+c+COgDvBYx5rSzsqySr98/l2F9c/j9BePokqkeSyKS+qKMpL4OOJ4gQcwETgNeBlpMEO5eZ2aXA08DmcDd7v6umV0PzHH3GeGh5wMPuXva3jpqydadtXz13tkYcPelR9Cre9e4QxIRiSTKFcS5wBjgLXf/spkN4MP5qVvk7jMJkkritmubrP8kWqjpp66+gcsfmMfqiiru/+oEhvXNjTskEZHIotzr2OnuDUCdmeUBm/ho24I0w935yZPvMqukjP8561AmaF4HEUkzUa4g5phZb+AOYC6wg07cXtBe7n11Jfe/vprLPjOS/yxWPhWR9BOl3Pc3w8XbzewpIM/dFyQ3rPT2wuJNXP/3RZxy8AB+8NmD4g5HRGSvtDRQrtkBco37IgyU2yeVbNzOFQ+8xYED87jlvLFkZKgAn4ikp5auIJobINeovQfKdQrlO2r4yr2zye6WyV2XFJObFakXsYhISmppoNzeDpDbJ9XU1fP1++eyaVsND192FIN6d487JBGRTyTKOIhs4JvApwmuHGYBt7t7dZJjSxvuzg8fX8jslZv53eTDGTu0d9whiYh8YlHugdwHbAd+F65fAPwJ+GKygko3t7+4nL/MW8uVJxdxxphBcYcjItIuoiSI0e6eWDzoeTNbtMej9zHPLtrIjU+9zxljBjHtpKK4wxERaTdRBsrNM7OJjStmNgGYk7yQ0seGrdV877G3GT04j5vOPUxThopIpxLlCmI88KqZrQ7XC4HFZvYOwcxyhyUtuhTW0OBc9ch8amob+M35h5PdNTPukERE2lWUBHFq0qNIQ9NnLefVZeXceM6h7N+vR9zhiIi0uygJosjdn03cYGaXuPu9SYop5S1Yu4VfPr2Y00YPVBkNEem0orRBXGtmt5lZrpkNMLMngTOSHViqqqypY9pD8+nXM4ufn32o2h1EpNOKkiA+AywD5hPMA/GAu5+bzKBS2fVPLmJleSU3nzeW3jnd4g5HRCRpoiSIPsCRBEmiBhhm++jX5pnvrOfhOWv45vH7M1Hlu0Wkk4uSIF4HnnL3U4EjgEHAK0mNKgV9sGUnV/9lAWOG9ubKk0fFHY6ISNJFaaQ+2d1XA7j7TuDbZnZccsNKLfUNzpUPz6e+wfnt+WPpqjmlRWQfEOWTrszM/p+Z3QFgZkVAXnLDSi23v7iMN1dUcP2k0Zo2VET2GVESxD0EbQ9HhevrgJ8lLaIU89bqzfz6mSWcMWYQZ48bHHc4IiIdJkqC2N/dfwHUArh7FRCpkdrMTjWzxWa21Myu3sMx/2lmi8zsXTN7IHLkHWB7dS3THprPwLxsfvaF0erSKiL7lChtELvMrDtBqW/MbH+CK4oWmVkmcCtwCrAWmG1mM9x9UcIxRcA1wDHuvtnM+u/Fe0ia62a8y9rNVTxy2VH06t417nBERDpUlCuI64CngKFm9mfgOeC/IjzvSGCpuy93913AQ8CkJsdMAW51980A7r4pcuRJ9rf563h83jquOLGI4uH5cYcjItLhWr2CcPdnzGweMJHg1tI0dy+LcO7BwJqE9bXAhCbHjAIws1eATOAn7v5U0xOZ2VRgKkBhYWGEl/5k1lRU8eMnFjJ+WB+uOPGApL+eiEgqijRpsruXA/9I0usXAccDQ4CXzOxQd9/S5PWnA9MBiouLPQlx7FZX38CVD88H4JbzxtJFXVpFZB+VzE+/dUBiJbsh4bZEa4EZ7l7r7iuAJQQJIza/f34pc1dt5mdnjWZofk6coYiIxCqZCWI2UGRmI8ysG3A+MKPJMX8luHrAzAoIbjktT2JMLZqzsoLfPlfC2YcPZtJYdWkVkX1bpARhZp82sy+Hy/3MbERrz3H3OuBy4GngPeARd3/XzK43szPDw54GysMpTJ8Hvh/ezupw28IurUP65PDTSYfEEYKISEpptQ3CzK4DioEDCQbNdQXuB45p7bnuPhOY2WTbtQnLDlwVPmLj7vzoiYVs2FbNY18/ip7Z6tIqIhLlCuIs4EygEsDdPwB6JjOojvb4vHU8+fYHfOfkIg4v7BN3OCIiKSFKgtgVftNvHCjXqYoRrSqv5Nq/LeTIEfl843h1aRURaRQlQTxiZn8AepvZFOBZ4I7khtUxausb+PZD88nMMG4+byyZGSqlISLSKMpAuV+a2SnANoJ2iGvd/ZmkR9YBfvNsCW+v2cKtF4xjcO/ucYcjIpJSojRSXwU83FmSQqPXl5dz6wtL+c/iIXzusP3iDkdEJOVEucXUE/iXmc0ys8vNbECyg0q2mrp6rnp4PsP75nLdGerSKiLSnFYThLv/1N0PAb4F7Ae8aGbPJj2yJJqzcjMfbK3mmtMOIjcrUrUREZF9TltGUm8CNgDlQEqV5W6rl0pK6ZppHHNAQdyhiIikrFYThJl908xeICjz3ReY4u6HJTuwZJq1pIzxw/ro6kFEpAVRPiGHAle6+/wkx9IhSrfXsGj9Nr7/2QPjDkVEJKXtMUGYWZ67bwNuCtc/MmuOu1ckObakeGVpMJXFcUX9Yo5ERCS1tXQF8QDweWAuwSjqxFFkDoxMYlxJ81JJKX1yunLIoLy4QxERSWl7TBDu/vnwZ6uVW9OFuzOrpIxPF/UjQ6OmRURaFKWR+rko29LB4o3bKd1ew7FF6r0kItKaltogsoEcoMDM+vDhLaY8gvmm086sJUH7gxKEiEjrWmqDuAy4EhhE0A7RmCC2Ab9PbljJ8VJJKUX9e7BfL9VdEhFpTUttEL8BfmNmV7j77zowpqSorq3nzRUVXDRxWNyhiIikhSjVXH9nZqOBg4HshO33JTOw9vbmigpq6hp0e0lEJKKoU44eT5AgZgKnAS8DaZUgZpWU0i0zgwkj+sYdiohIWohSi+lc4CRgg7t/GRgD9EpqVEkwq6SMI0b0oXu3zLhDERFJC1ESxE53bwDqzCyPoGjf0OSG1b42bavm/Q3bOVajp0VEIouSIOaYWW+CaUbnAvOA16Kc3MxONbPFZrbUzK5uZv+lZlZqZvPDx9faEnxUs0rUvVVEpK2iNFJ/M1y83cyeAvLcfUFrzzOzTOBW4BRgLTDbzGa4+6Imhz7s7pe3Me42mVVSSkGPbnxqoMpriIhE1dJAuXEt7XP3ea2c+0hgqbsvD5/zEDAJaJogkqqhwXl5aRmfPqBA5TVERNqgpSuIX7Wwz4ETWzn3YGBNwvpaYEIzx51jZscBS4DvuPuapgeY2VRgKkBhYWErL/tR723YRtmOXWp/EBFpo5YGyp3QAa//JPCgu9eY2WXAvTSTeNx9OjAdoLi42NvyAmp/EBHZO1HGQVzc3PYIA+XW8dHeTkPCbYnnKE9YvRP4RWvxtNWsklIOGtiT/nnZrR8sIiK7RZlR7oiE5WyCMRHzaH2g3GygyMxGECSG84ELEg8ws/3cfX24eibwXpSgo9q5q57ZKzZzydEqryEi0lZRejFdkbgednl9KMLz6szscuBpIBO4293fNbPrgTnuPgP4tpmdCdQBFcClbX4HLXhjRTm76hvU/iAisheiXEE0VQlEmkTI3WcSlOdI3HZtwvI1wDV7EUMks0rK6NYlgyNH5Ld+sIiIfESUNognCXotQTCw7mDgkWQG1V5mlZQyYUQ+2V1VXkNEpK2iXEH8MmG5Dljl7muTFE+72bC1miUbd3Du+CFxhyIikpaitEG8CBDWYeoSLue7e0WSY/tEZpWUAqj9QURkL0W5xTQVuB6oBhoIZpZzYGRyQ/tkZpWUUdAji4MG9ow7FBGRtBTlFtP3gdHuXpbsYNpLY3mN40f1w0zlNURE9kaUaq7LgKpkB9KeFq3fRkXlLo4dpdHTIiJ7K8oVxDXAq2b2BlDTuNHdv520qD6hl8L2h2MOUIIQEdlbURLEH4B/A+8QtEGkvFlLyvjUfnn076nyGiIieytKgujq7lclPZJ2UrWrjjmrKvjKMZHG8omIyB5EaYP4p5lNNbP9zCy/8ZH0yPbSG8srqK13dW8VEfmEolxBTA5/JpbESNluri+VlJLVJYPi4X3iDkVEJK1FGSiXVvdqZpWUMWFkX5XXEBH5hJI5H0SH+2DLTpZu2sH5Rwxt/WAREWlRMueD6HAv7549Tu0PIiKfVNLmg4jDSyWl9O+ZxagBPeIORUQk7UXpxdRU5PkgOlJ9WF7j2CKV1xARaQ+dZj6Idz/YypaqWo5TeQ0RkXbRaeaDmBW2P6i8hohI+9hjgjCzA4ABjfNBJGw/xsyy3H1Z0qNrg5eWlHLIoDwKemTFHYqISKfQUhvELcC2ZrZvC/eljB01dcxdtVm9l0RE2lFLCWKAu7/TdGO4bXiUk5vZqWa22MyWmtnVLRx3jpm5mRVHOW9Try8rp67BOa5It5dERNpLSwmidwv7urd2YjPLBG4FTiNo2J5sZgc3c1xPYBrwRmvn3JNZJaVkd81gvMpriIi0m5YSxBwzm9J0o5l9DZgb4dxHAkvdfbm77yIYOzGpmeP+G7iRYErTvTKrpIyJI/uS1UXlNURE2ktLvZiuBJ4wswv5MCEUA92AsyKcezCwJmF9LTAh8QAzGwcMdfd/mNn393SicF7sqQCFhYUf2bemoorlZZVcOHFYhJBERCSqPSYId98IHG1mJwCjw83/cPd/t8cLm1kG8Gvg0taOdffpwHSA4uJiT9z38tKge6vaH0RE2leUUhvPA8/vxbnXAYlV84aE2xr1JEg8L4QjnwcCM8zsTHefE/VFZpWUMjAvmwP6q7yGiEh72ptSG1HNBorMbISZdQPOB2Y07nT3re5e4O7D3X048DrQpuRQ3+C8XFLGcaMKVF5DRKSdJS1BuHsdcDnwNPAe8Ii7v2tm15vZme3xGgvWbmFbdZ3GP4iIJEGUUht7zd1nAjObbLt2D8ce39bzzyopw0zlNUREkiGZt5iSblZJKYcO7kV+bre4QxER6XTSNkFsr65l3uotHKveSyIiSZG2CeK1ZeXUN7jaH0REkiRtE8SskjJyumUyrlDlNUREkiGNE0QpR43sS7cuafsWRERSWlp+uq4ur2JleZXaH0REkigtE8SspaUAHDtK7Q8iIsmSngliSRmDe3dnZEFu3KGIiHRaaZcgHHhlWRnHFqm8hohIMiV1JHUy7NxVT5XKa4iIJF3aXUFsr64Ny2v0jTsUEZFOLe0SxI6aOg4b0pveOSqvISKSTGmXIKp21WtyIBGRDpB2CQJQ+4OISAdIuwSRYcbhhb3jDkNEpNNLuwSRn9uNrplpF7aISNpJu0/a/Xplxx2CiMg+Ie0ShIiIdAwlCBERaZYShIiINEsJQkREmpXUBGFmp5rZYjNbamZXN7P/62b2jpnNN7OXzezgZMYjIiLRJS1BmFkmcCtwGnAwMLmZBPCAux/q7mOBXwC/TlY8IiLSNsm8gjgSWOruy919F/AQMCnxAHfflrCaS1DNW0REUkAyy30PBtYkrK8FJjQ9yMy+BVwFdANObO5EZjYVmApQWFjY7oGKiMjHxT4fhLvfCtxqZhcAPwYuaeaY6cB0ADPbbmaLOzbKVhUAZXEH0UQqxgSpGZdiikYxRZeKcR3Y1ickM0GsA4YmrA8Jt+3JQ8BtEc672N2LP0lg7c3M5iimaFIxLsUUjWKKLhXjMrM5bX1OMtsgZgNFZjbCzLoB5wMzEg8ws6KE1c8BJUmMR0RE2iBpVxDuXmdmlwNPA5nA3e7+rpldD8xx9xnA5WZ2MlALbKaZ20siIhKPpLZBuPtMYGaTbdcmLE/bi9NO/6RxJYFiii4V41JM0Sim6FIxrjbHZO7qWSoiIh+nUhsiItIsJQgREWlWWiWI1mo7xRDPUDN73swWmdm7ZrY3bSpJYWaZZvaWmf097lgAzKy3mT1mZu+b2XtmdlQKxPSd8N9toZk9aGaxzEZlZneb2SYzW5iwLd/MnjGzkvBnnxSI6abw32+BmT1hZr3jjilh33fNzM2sIBViMrMrwt/Vu2b2i46MaU9xmdlYM3s9rH03x8yObO08aZMgItZ26mh1wHfd/WBgIvCtFIip0TTgvbiDSPAb4Cl3PwgYQ8yxmdlg4NtAsbuPJuhpd35M4fwROLXJtquB59y9CHguXI87pmeA0e5+GLAEuCYFYsLMhgL/Aazu4HigmZjM7ASCskJj3P0Q4JepEBdBvbufhrXvrg3XW5Q2CYIItZ06mruvd/d54fJ2gg+9wXHGBGBmQwjGldwZdywAZtYLOA64C8Ddd7n7lliDCnQBuptZFyAH+CCOINz9JaCiyeZJwL3h8r3AF+KOyd3/5e514errBINfY40pdDPwX8RQy20PMX0DuMHda8JjNqVIXA7khcu9iPD3nk4JornaTrF/GDcys+HA4cAbMYcCcAvBf5iGmONoNAIoBe4Jb3vdaWa5cQbk7usIvtmtBtYDW939X3HG1MQAd18fLm8ABsQZTDO+Avwz7iDMbBKwzt3fjjuWBKOAY83sDTN70cyOiDug0JXATWa2huBvv9UrwHRKECnLzHoAfwGubFKhNo5YPg9scve5ccbRRBdgHHCbux8OVNLxt0w+IrynP4kgeQ0Ccs3sojhj2hMP+qKnTH90M/sRwe3VP8ccRw7wQ4LbJamkC5BPcNv5+8AjZmbxhgQEVzbfcfehwHcIr+hbkk4Joq21nTqEmXUlSA5/dvfH444HOAY408xWEtyGO9HM7o83JNYCa9298erqMYKEEaeTgRXuXurutcDjwNExx5Roo5ntBxD+7PDbFM0xs0uBzwMXevyDqPYnSPBvh3/vQ4B5ZjYw1qiCv/fHPfAmwZV8hzae78ElBH/nAI8S3LZvUToliFZrO3W08FvBXcB77p4Skx25+zXuPsTdhxP8jv7t7rF+M3b3DcAaM2usJnkSsCjGkCC4tTTRzHLCf8eTSK1G/Rl8WHrmEuBvMcYCBL0ICW5dnunuVXHH4+7vuHt/dx8e/r2vBcaFf29x+itwAoCZjSKYyiAVKrt+AHwmXD6RKLXv3D1tHsDpBL0nlgE/SoF4Pk1w6b8AmB8+To87roT4jgf+HnccYSxjgTnh7+qvQJ8UiOmnwPvAQuBPQFZMcTxI0A5SS/Ah91WgL0HvpRLgWSA/BWJaStAO2Pi3fnvcMTXZvxIoiDsmgoRwf/h3NQ84MUX+pj4NzAXeJmgrHd/aeVRqQ0REmpVOt5hERKQDKUGIiEizlCBERKRZShAiItIsJQgREWmWEoR0iLDS5q8S1r9nZj9pp3P/0czObY9ztfI6Xwwr0T6f7NeKm5n9MO4YJH5KENJRaoCzO7occ2vCQn1RfRWY4u4nJCueFKIEIUoQ0mHqCObE/U7THU2vAMxsR/jz+LDY2d/MbLmZ3WBmF5rZm2b2jpntn3Cak8Ma90vCelSNc2LcZGazwzkMLks47ywzm0EzI7rNbHJ4/oVmdmO47VqCgUZ3mdlNzTznB+Fz3jazG8JtjfX3G+dP6BNuf8HMbg7jfc/MjjCzxy2Y++Fn4THDw/kE/hwe81hYewgzOyksevhOWPc/K9y+0sx+ambzwn0Hhdtzw+PeDJ83Kdx+afi6T4Wv/Ytw+w0EVW7nh6+fa2b/CN/bQjM7rw3/7pLOOnqEnx775gPYQVBqeCVBqeHvAT8J9/0RODfx2PDn8cAWYD8gi6D21k/DfdOAWxKe/xTBF54igpGj2cBU4MfhMVkEI7lHhOetBEY0E+cggjIc/QiKrv0b+EK47wWC+SOaPuc04FUgJ1zPD38uAD4TLl+fEO8LwI0J7+ODhPe4lmAU9XCCUfrHhMfdHf7OsglGM48Kt99HUCSS8Hd7Rbj8TeDOcPl/gYvC5d4E1QhygUuB5eG/RzawChia+G8QLp8D3JGw3ivuvyc9OuahKwjpMB5Uur2PYKKeqGZ7MO9GDUGJlcaS3O8QfIg2esTdG9y9hOBD7yCCSWQuNrP5BKUF+hIkEIA33X1FM693BPCCB0X8GiuWHtdKjCcD93hYn8jdKyyYA6O3u78YHnNvk/M01hF7B3g34T0u58OilGvc/ZVw+X6CK5gDCYoMLtnDeRuLsc3lw9/PfwBXh7+HFwiSQWG47zl33+ru1QRXU8OaeX/vAKeY2Y1mdqy7b23l9yGdRFvuv4q0h1sI6tPck7CtjvB2p5llENSyaVSTsNyQsN7AR/9+m9aMccAIvlE/nbjDzI4nuIKIU+L7aPoeG99Xc+8p6nnrE85jwDnuvjjxQDOb0OS1E5/z4Yu6LzGzcQS10H5mZs+5+/URYpE0pysI6VDuXgE8QtDg22glMD5cPhPouhen/qKZZYTtEiOBxcDTwDcsKMmOmY2y1icqehP4jJkVWDDN7WTgxVae8wzw5YQ2gvzwW/ZmMzs2POZLEc7TVKF9OHf3BcDL4fsabmYHtOG8TwNXhFVrMbPDI7x2bcLvbRBQ5e73AzcRf6l26SC6gpA4/Aq4PGH9DuBvZvY2QVvC3ny7X03w4Z4HfN3dq83sToLbLPPCD8dSWpm6093Xm9nVwPME37z/4e4tltp296fMbCwwx8x2ATMJegFdAtweJo7lwJfb+J4WE8xzfjfB7Z/bwvf1ZeDRsAfWbOD2Vs7z3wRXbgvCK7QVBHM6tGR6ePw8gtuCN5lZA0F10G+08X1ImlI1V5EUZMEUtn9399FxxyL7Lt1iEhGRZukKQkREmqUrCBERaZYShIiINEsJQkREmqUEISIizVKCEBGRZv1/T4Sn48oxYXAAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sklearn.decomposition import PCA\n",
+    "pca = PCA().fit(std_data)\n",
+    "plt.plot(np.cumsum(pca.explained_variance_ratio_))\n",
+    "plt.xlim(0,18,1)\n",
+    "plt.xlabel('Number of components')\n",
+    "plt.ylabel('Cumulative explained variance')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "0ad0a883",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-0.885122</td>\n",
+       "      <td>-2.483017</td>\n",
+       "      <td>0.230902</td>\n",
+       "      <td>0.807129</td>\n",
+       "      <td>0.043370</td>\n",
+       "      <td>-0.382026</td>\n",
+       "      <td>-0.357206</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
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+       "      <td>-3.000343</td>\n",
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+       "      <td>-0.165334</td>\n",
+       "      <td>-1.087171</td>\n",
+       "      <td>1.670938</td>\n",
+       "      <td>-0.288015</td>\n",
+       "      <td>0.942749</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.191726</td>\n",
+       "      <td>0.385174</td>\n",
+       "      <td>-1.926789</td>\n",
+       "      <td>1.859338</td>\n",
+       "      <td>-0.550103</td>\n",
+       "      <td>-0.230068</td>\n",
+       "      <td>0.522876</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-0.794805</td>\n",
+       "      <td>0.218433</td>\n",
+       "      <td>-1.661542</td>\n",
+       "      <td>1.195618</td>\n",
+       "      <td>0.058950</td>\n",
+       "      <td>0.798510</td>\n",
+       "      <td>-0.086756</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-1.265058</td>\n",
+       "      <td>-1.593317</td>\n",
+       "      <td>-0.689436</td>\n",
+       "      <td>1.339644</td>\n",
+       "      <td>-0.114019</td>\n",
+       "      <td>-0.837737</td>\n",
+       "      <td>0.231600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>0.668484</td>\n",
+       "      <td>-2.871696</td>\n",
+       "      <td>1.452469</td>\n",
+       "      <td>-2.236975</td>\n",
+       "      <td>-2.854943</td>\n",
+       "      <td>0.766981</td>\n",
+       "      <td>2.343375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>0.262604</td>\n",
+       "      <td>-2.240280</td>\n",
+       "      <td>1.844972</td>\n",
+       "      <td>-0.568118</td>\n",
+       "      <td>-3.339266</td>\n",
+       "      <td>1.706628</td>\n",
+       "      <td>1.774529</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>0.105962</td>\n",
+       "      <td>-3.066758</td>\n",
+       "      <td>1.189320</td>\n",
+       "      <td>-1.775107</td>\n",
+       "      <td>-2.965850</td>\n",
+       "      <td>1.263333</td>\n",
+       "      <td>1.979732</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>-2.847160</td>\n",
+       "      <td>-2.517979</td>\n",
+       "      <td>-0.295195</td>\n",
+       "      <td>-2.148352</td>\n",
+       "      <td>-2.990361</td>\n",
+       "      <td>0.696690</td>\n",
+       "      <td>1.774277</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>-0.164604</td>\n",
+       "      <td>-0.524308</td>\n",
+       "      <td>-1.644250</td>\n",
+       "      <td>-1.315554</td>\n",
+       "      <td>-4.692532</td>\n",
+       "      <td>1.532319</td>\n",
+       "      <td>0.092815</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             0         1         2         3         4         5         6\n",
+       "0    -0.885122 -2.483017  0.230902  0.807129  0.043370 -0.382026 -0.357206\n",
+       "1    -3.000343  2.015089 -0.165334 -1.087171  1.670938 -0.288015  0.942749\n",
+       "2     1.191726  0.385174 -1.926789  1.859338 -0.550103 -0.230068  0.522876\n",
+       "3    -0.794805  0.218433 -1.661542  1.195618  0.058950  0.798510 -0.086756\n",
+       "4    -1.265058 -1.593317 -0.689436  1.339644 -0.114019 -0.837737  0.231600\n",
+       "...        ...       ...       ...       ...       ...       ...       ...\n",
+       "8945  0.668484 -2.871696  1.452469 -2.236975 -2.854943  0.766981  2.343375\n",
+       "8946  0.262604 -2.240280  1.844972 -0.568118 -3.339266  1.706628  1.774529\n",
+       "8947  0.105962 -3.066758  1.189320 -1.775107 -2.965850  1.263333  1.979732\n",
+       "8948 -2.847160 -2.517979 -0.295195 -2.148352 -2.990361  0.696690  1.774277\n",
+       "8949 -0.164604 -0.524308 -1.644250 -1.315554 -4.692532  1.532319  0.092815\n",
+       "\n",
+       "[8950 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 119,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.decomposition import PCA \n",
+    "sklearn_pca = PCA(n_components=7)\n",
+    "pca_data = sklearn_pca.fit_transform(std_data)\n",
+    "pca_data = pd.DataFrame(pca_data)\n",
+    "pca_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "id": "a78c9de2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.783441</td>\n",
+       "      <td>6.165373</td>\n",
+       "      <td>0.053316</td>\n",
+       "      <td>0.651457</td>\n",
+       "      <td>0.001881</td>\n",
+       "      <td>0.145944</td>\n",
+       "      <td>0.127596</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>9.002061</td>\n",
+       "      <td>4.060585</td>\n",
+       "      <td>0.027335</td>\n",
+       "      <td>1.181941</td>\n",
+       "      <td>2.792035</td>\n",
+       "      <td>0.082953</td>\n",
+       "      <td>0.888776</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.420211</td>\n",
+       "      <td>0.148359</td>\n",
+       "      <td>3.712516</td>\n",
+       "      <td>3.457137</td>\n",
+       "      <td>0.302613</td>\n",
+       "      <td>0.052931</td>\n",
+       "      <td>0.273399</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.631715</td>\n",
+       "      <td>0.047713</td>\n",
+       "      <td>2.760721</td>\n",
+       "      <td>1.429501</td>\n",
+       "      <td>0.003475</td>\n",
+       "      <td>0.637619</td>\n",
+       "      <td>0.007527</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.600373</td>\n",
+       "      <td>2.538660</td>\n",
+       "      <td>0.475322</td>\n",
+       "      <td>1.794645</td>\n",
+       "      <td>0.013000</td>\n",
+       "      <td>0.701803</td>\n",
+       "      <td>0.053639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>0.446871</td>\n",
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+       "      <td>2.109666</td>\n",
+       "      <td>5.004059</td>\n",
+       "      <td>8.150698</td>\n",
+       "      <td>0.588260</td>\n",
+       "      <td>5.491405</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>0.068961</td>\n",
+       "      <td>5.018853</td>\n",
+       "      <td>3.403921</td>\n",
+       "      <td>0.322758</td>\n",
+       "      <td>11.150697</td>\n",
+       "      <td>2.912578</td>\n",
+       "      <td>3.148955</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>0.011228</td>\n",
+       "      <td>9.405002</td>\n",
+       "      <td>1.414482</td>\n",
+       "      <td>3.151006</td>\n",
+       "      <td>8.796269</td>\n",
+       "      <td>1.596011</td>\n",
+       "      <td>3.919340</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>8.106321</td>\n",
+       "      <td>6.340221</td>\n",
+       "      <td>0.087140</td>\n",
+       "      <td>4.615415</td>\n",
+       "      <td>8.942258</td>\n",
+       "      <td>0.485377</td>\n",
+       "      <td>3.148060</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>0.027095</td>\n",
+       "      <td>0.274899</td>\n",
+       "      <td>2.703558</td>\n",
+       "      <td>1.730682</td>\n",
+       "      <td>22.019853</td>\n",
+       "      <td>2.348003</td>\n",
+       "      <td>0.008615</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             0         1         2         3          4         5         6\n",
+       "0     0.783441  6.165373  0.053316  0.651457   0.001881  0.145944  0.127596\n",
+       "1     9.002061  4.060585  0.027335  1.181941   2.792035  0.082953  0.888776\n",
+       "2     1.420211  0.148359  3.712516  3.457137   0.302613  0.052931  0.273399\n",
+       "3     0.631715  0.047713  2.760721  1.429501   0.003475  0.637619  0.007527\n",
+       "4     1.600373  2.538660  0.475322  1.794645   0.013000  0.701803  0.053639\n",
+       "...        ...       ...       ...       ...        ...       ...       ...\n",
+       "8945  0.446871  8.246640  2.109666  5.004059   8.150698  0.588260  5.491405\n",
+       "8946  0.068961  5.018853  3.403921  0.322758  11.150697  2.912578  3.148955\n",
+       "8947  0.011228  9.405002  1.414482  3.151006   8.796269  1.596011  3.919340\n",
+       "8948  8.106321  6.340221  0.087140  4.615415   8.942258  0.485377  3.148060\n",
+       "8949  0.027095  0.274899  2.703558  1.730682  22.019853  2.348003  0.008615\n",
+       "\n",
+       "[8950 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 120,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pca_data = pca_data.transform(lambda x: x*x)\n",
+    "pca_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "id": "da53f020",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = np.array(list(zip(pca_data[0], pca_data[1]))).reshape(len(pca_data[0]), 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "id": "de3af131",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inertias = []\n",
+    "mapping = {}\n",
+    "K = range(1, 10)\n",
+    "for k in K:\n",
+    "    \n",
+    "    kmeanModel = KMeans(n_clusters=k).fit(X)\n",
+    "    kmeanModel.fit(X)\n",
+    "  \n",
+    "    \n",
+    "    inertias.append(kmeanModel.inertia_)\n",
+    "  \n",
+    "    \n",
+    "    mapping[k] = kmeanModel.inertia_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "13b252db",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(K, inertias, 'bx-')\n",
+    "plt.xlabel('Values of K')\n",
+    "plt.ylabel('Inertia')\n",
+    "plt.title('The Elbow Method using Inertia')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "0212c090",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x20fa9b53af0>"
+      ]
+     },
+     "execution_count": 127,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "kmeans = KMeans(n_clusters=4)\n",
+    "kmeans.fit(X)\n",
+    "plt.scatter(X[:,0],X[:,1], c=kmeans.labels_, cmap='rainbow')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68ad94bf",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Assignment 2/Swastik_211090_Credit Risk Modelling.ipynb b/Assignment 2/Swastik_211090_Credit Risk Modelling.ipynb
new file mode 100644
index 0000000..cb905a0
--- /dev/null
+++ b/Assignment 2/Swastik_211090_Credit Risk Modelling.ipynb	
@@ -0,0 +1,1166 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "717dfb06",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.model_selection import RepeatedStratifiedKFold\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn import metrics\n",
+    "from sklearn.metrics import roc_auc_score\n",
+    "from sklearn.metrics import confusion_matrix\n",
+    "from sklearn.metrics import precision_recall_curve\n",
+    "from sklearn.feature_selection import SelectFpr, f_classif\n",
+    "from sklearn.pipeline import Pipeline\n",
+    "from sklearn.base import BaseEstimator\n",
+    "from sklearn.base import TransformerMixin\n",
+    "from scipy.stats import chi2_contingency\n",
+    "from datetime import date\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a346a2dd",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Hp\\AppData\\Local\\Temp\\ipykernel_14504\\3973402256.py:1: DtypeWarning: Columns (19) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  df = pd.read_csv('credit_risk_dataset (1).csv')\n"
+     ]
+    },
+    {
+     "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>member_id</th>\n",
+       "      <th>loan_amnt</th>\n",
+       "      <th>funded_amnt</th>\n",
+       "      <th>funded_amnt_inv</th>\n",
+       "      <th>term</th>\n",
+       "      <th>int_rate</th>\n",
+       "      <th>installment</th>\n",
+       "      <th>grade</th>\n",
+       "      <th>sub_grade</th>\n",
+       "      <th>...</th>\n",
+       "      <th>total_bal_il</th>\n",
+       "      <th>il_util</th>\n",
+       "      <th>open_rv_12m</th>\n",
+       "      <th>open_rv_24m</th>\n",
+       "      <th>max_bal_bc</th>\n",
+       "      <th>all_util</th>\n",
+       "      <th>total_rev_hi_lim</th>\n",
+       "      <th>inq_fi</th>\n",
+       "      <th>total_cu_tl</th>\n",
+       "      <th>inq_last_12m</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1077501</td>\n",
+       "      <td>1296599</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>4975.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>10.65</td>\n",
+       "      <td>162.87</td>\n",
+       "      <td>B</td>\n",
+       "      <td>B2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1077430</td>\n",
+       "      <td>1314167</td>\n",
+       "      <td>2500</td>\n",
+       "      <td>2500</td>\n",
+       "      <td>2500.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>15.27</td>\n",
+       "      <td>59.83</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1077175</td>\n",
+       "      <td>1313524</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>2400.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>15.96</td>\n",
+       "      <td>84.33</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1076863</td>\n",
+       "      <td>1277178</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>13.49</td>\n",
+       "      <td>339.31</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1075358</td>\n",
+       "      <td>1311748</td>\n",
+       "      <td>3000</td>\n",
+       "      <td>3000</td>\n",
+       "      <td>3000.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>12.69</td>\n",
+       "      <td>67.79</td>\n",
+       "      <td>B</td>\n",
+       "      <td>B5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 74 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        id  member_id  loan_amnt  funded_amnt  funded_amnt_inv        term  \\\n",
+       "0  1077501    1296599       5000         5000           4975.0   36 months   \n",
+       "1  1077430    1314167       2500         2500           2500.0   60 months   \n",
+       "2  1077175    1313524       2400         2400           2400.0   36 months   \n",
+       "3  1076863    1277178      10000        10000          10000.0   36 months   \n",
+       "4  1075358    1311748       3000         3000           3000.0   60 months   \n",
+       "\n",
+       "   int_rate  installment grade sub_grade  ... total_bal_il il_util  \\\n",
+       "0     10.65       162.87     B        B2  ...          NaN     NaN   \n",
+       "1     15.27        59.83     C        C4  ...          NaN     NaN   \n",
+       "2     15.96        84.33     C        C5  ...          NaN     NaN   \n",
+       "3     13.49       339.31     C        C1  ...          NaN     NaN   \n",
+       "4     12.69        67.79     B        B5  ...          NaN     NaN   \n",
+       "\n",
+       "  open_rv_12m  open_rv_24m max_bal_bc all_util total_rev_hi_lim inq_fi  \\\n",
+       "0         NaN          NaN        NaN      NaN              NaN    NaN   \n",
+       "1         NaN          NaN        NaN      NaN              NaN    NaN   \n",
+       "2         NaN          NaN        NaN      NaN              NaN    NaN   \n",
+       "3         NaN          NaN        NaN      NaN              NaN    NaN   \n",
+       "4         NaN          NaN        NaN      NaN              NaN    NaN   \n",
+       "\n",
+       "  total_cu_tl inq_last_12m  \n",
+       "0         NaN          NaN  \n",
+       "1         NaN          NaN  \n",
+       "2         NaN          NaN  \n",
+       "3         NaN          NaN  \n",
+       "4         NaN          NaN  \n",
+       "\n",
+       "[5 rows x 74 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('credit_risk_dataset (1).csv')\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d74cdd20",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "id                       0\n",
+       "member_id                0\n",
+       "loan_amnt                0\n",
+       "funded_amnt              0\n",
+       "funded_amnt_inv          0\n",
+       "                     ...  \n",
+       "all_util            466285\n",
+       "total_rev_hi_lim     70276\n",
+       "inq_fi              466285\n",
+       "total_cu_tl         466285\n",
+       "inq_last_12m        466285\n",
+       "Length: 74, dtype: int64"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nullCol = df.isnull().sum()\n",
+    "nullCol"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "6dfa446a",
+   "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>id</th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>loan_amnt</th>\n",
+       "      <th>funded_amnt</th>\n",
+       "      <th>funded_amnt_inv</th>\n",
+       "      <th>term</th>\n",
+       "      <th>int_rate</th>\n",
+       "      <th>installment</th>\n",
+       "      <th>grade</th>\n",
+       "      <th>sub_grade</th>\n",
+       "      <th>...</th>\n",
+       "      <th>last_pymnt_d</th>\n",
+       "      <th>last_pymnt_amnt</th>\n",
+       "      <th>last_credit_pull_d</th>\n",
+       "      <th>collections_12_mths_ex_med</th>\n",
+       "      <th>policy_code</th>\n",
+       "      <th>application_type</th>\n",
+       "      <th>acc_now_delinq</th>\n",
+       "      <th>tot_coll_amt</th>\n",
+       "      <th>tot_cur_bal</th>\n",
+       "      <th>total_rev_hi_lim</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1077501</td>\n",
+       "      <td>1296599</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>4975.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>10.65</td>\n",
+       "      <td>162.87</td>\n",
+       "      <td>B</td>\n",
+       "      <td>B2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-15</td>\n",
+       "      <td>171.62</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1077430</td>\n",
+       "      <td>1314167</td>\n",
+       "      <td>2500</td>\n",
+       "      <td>2500</td>\n",
+       "      <td>2500.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>15.27</td>\n",
+       "      <td>59.83</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Apr-13</td>\n",
+       "      <td>119.66</td>\n",
+       "      <td>Sep-13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1077175</td>\n",
+       "      <td>1313524</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>2400.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>15.96</td>\n",
+       "      <td>84.33</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jun-14</td>\n",
+       "      <td>649.91</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1076863</td>\n",
+       "      <td>1277178</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>13.49</td>\n",
+       "      <td>339.31</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-15</td>\n",
+       "      <td>357.48</td>\n",
+       "      <td>Jan-15</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1075358</td>\n",
+       "      <td>1311748</td>\n",
+       "      <td>3000</td>\n",
+       "      <td>3000</td>\n",
+       "      <td>3000.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>12.69</td>\n",
+       "      <td>67.79</td>\n",
+       "      <td>B</td>\n",
+       "      <td>B5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>67.79</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 52 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        id  member_id  loan_amnt  funded_amnt  funded_amnt_inv        term  \\\n",
+       "0  1077501    1296599       5000         5000           4975.0   36 months   \n",
+       "1  1077430    1314167       2500         2500           2500.0   60 months   \n",
+       "2  1077175    1313524       2400         2400           2400.0   36 months   \n",
+       "3  1076863    1277178      10000        10000          10000.0   36 months   \n",
+       "4  1075358    1311748       3000         3000           3000.0   60 months   \n",
+       "\n",
+       "   int_rate  installment grade sub_grade  ... last_pymnt_d last_pymnt_amnt  \\\n",
+       "0     10.65       162.87     B        B2  ...       Jan-15          171.62   \n",
+       "1     15.27        59.83     C        C4  ...       Apr-13          119.66   \n",
+       "2     15.96        84.33     C        C5  ...       Jun-14          649.91   \n",
+       "3     13.49       339.31     C        C1  ...       Jan-15          357.48   \n",
+       "4     12.69        67.79     B        B5  ...       Jan-16           67.79   \n",
+       "\n",
+       "  last_credit_pull_d  collections_12_mths_ex_med policy_code application_type  \\\n",
+       "0             Jan-16                         0.0           1       INDIVIDUAL   \n",
+       "1             Sep-13                         0.0           1       INDIVIDUAL   \n",
+       "2             Jan-16                         0.0           1       INDIVIDUAL   \n",
+       "3             Jan-15                         0.0           1       INDIVIDUAL   \n",
+       "4             Jan-16                         0.0           1       INDIVIDUAL   \n",
+       "\n",
+       "  acc_now_delinq tot_coll_amt tot_cur_bal total_rev_hi_lim  \n",
+       "0            0.0          NaN         NaN              NaN  \n",
+       "1            0.0          NaN         NaN              NaN  \n",
+       "2            0.0          NaN         NaN              NaN  \n",
+       "3            0.0          NaN         NaN              NaN  \n",
+       "4            0.0          NaN         NaN              NaN  \n",
+       "\n",
+       "[5 rows x 52 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = df.dropna(axis=1,thresh = 320000)\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2dfe8fcc",
+   "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>id</th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>loan_amnt</th>\n",
+       "      <th>funded_amnt</th>\n",
+       "      <th>funded_amnt_inv</th>\n",
+       "      <th>term</th>\n",
+       "      <th>int_rate</th>\n",
+       "      <th>installment</th>\n",
+       "      <th>grade</th>\n",
+       "      <th>sub_grade</th>\n",
+       "      <th>...</th>\n",
+       "      <th>last_pymnt_d</th>\n",
+       "      <th>last_pymnt_amnt</th>\n",
+       "      <th>last_credit_pull_d</th>\n",
+       "      <th>collections_12_mths_ex_med</th>\n",
+       "      <th>policy_code</th>\n",
+       "      <th>application_type</th>\n",
+       "      <th>acc_now_delinq</th>\n",
+       "      <th>tot_coll_amt</th>\n",
+       "      <th>tot_cur_bal</th>\n",
+       "      <th>total_rev_hi_lim</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1077501</td>\n",
+       "      <td>1296599</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>4975.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>10.65</td>\n",
+       "      <td>162.87</td>\n",
+       "      <td>B</td>\n",
+       "      <td>B2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-15</td>\n",
+       "      <td>171.62</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1077430</td>\n",
+       "      <td>1314167</td>\n",
+       "      <td>2500</td>\n",
+       "      <td>2500</td>\n",
+       "      <td>2500.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>15.27</td>\n",
+       "      <td>59.83</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Apr-13</td>\n",
+       "      <td>119.66</td>\n",
+       "      <td>Sep-13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1077175</td>\n",
+       "      <td>1313524</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>2400.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>15.96</td>\n",
+       "      <td>84.33</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jun-14</td>\n",
+       "      <td>649.91</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1076863</td>\n",
+       "      <td>1277178</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>13.49</td>\n",
+       "      <td>339.31</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-15</td>\n",
+       "      <td>357.48</td>\n",
+       "      <td>Jan-15</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1075358</td>\n",
+       "      <td>1311748</td>\n",
+       "      <td>3000</td>\n",
+       "      <td>3000</td>\n",
+       "      <td>3000.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>12.69</td>\n",
+       "      <td>67.79</td>\n",
+       "      <td>B</td>\n",
+       "      <td>B5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>67.79</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>466280</th>\n",
+       "      <td>8598660</td>\n",
+       "      <td>1440975</td>\n",
+       "      <td>18400</td>\n",
+       "      <td>18400</td>\n",
+       "      <td>18400.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>14.47</td>\n",
+       "      <td>432.64</td>\n",
+       "      <td>C</td>\n",
+       "      <td>C2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>432.64</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>294998.0</td>\n",
+       "      <td>29900.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>466281</th>\n",
+       "      <td>9684700</td>\n",
+       "      <td>11536848</td>\n",
+       "      <td>22000</td>\n",
+       "      <td>22000</td>\n",
+       "      <td>22000.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>19.97</td>\n",
+       "      <td>582.50</td>\n",
+       "      <td>D</td>\n",
+       "      <td>D5</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Dec-14</td>\n",
+       "      <td>17.50</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>221830.0</td>\n",
+       "      <td>39400.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>466282</th>\n",
+       "      <td>9584776</td>\n",
+       "      <td>11436914</td>\n",
+       "      <td>20700</td>\n",
+       "      <td>20700</td>\n",
+       "      <td>20700.0</td>\n",
+       "      <td>60 months</td>\n",
+       "      <td>16.99</td>\n",
+       "      <td>514.34</td>\n",
+       "      <td>D</td>\n",
+       "      <td>D1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>514.34</td>\n",
+       "      <td>Dec-15</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>73598.0</td>\n",
+       "      <td>13100.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>466283</th>\n",
+       "      <td>9604874</td>\n",
+       "      <td>11457002</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>2000.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>7.90</td>\n",
+       "      <td>62.59</td>\n",
+       "      <td>A</td>\n",
+       "      <td>A4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Dec-14</td>\n",
+       "      <td>1500.68</td>\n",
+       "      <td>Apr-15</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>591610.0</td>\n",
+       "      <td>53100.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>466284</th>\n",
+       "      <td>9199665</td>\n",
+       "      <td>11061576</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>9975.0</td>\n",
+       "      <td>36 months</td>\n",
+       "      <td>19.20</td>\n",
+       "      <td>367.58</td>\n",
+       "      <td>D</td>\n",
+       "      <td>D3</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>367.58</td>\n",
+       "      <td>Jan-16</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INDIVIDUAL</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>57477.0</td>\n",
+       "      <td>16000.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>466285 rows × 52 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             id  member_id  loan_amnt  funded_amnt  funded_amnt_inv  \\\n",
+       "0       1077501    1296599       5000         5000           4975.0   \n",
+       "1       1077430    1314167       2500         2500           2500.0   \n",
+       "2       1077175    1313524       2400         2400           2400.0   \n",
+       "3       1076863    1277178      10000        10000          10000.0   \n",
+       "4       1075358    1311748       3000         3000           3000.0   \n",
+       "...         ...        ...        ...          ...              ...   \n",
+       "466280  8598660    1440975      18400        18400          18400.0   \n",
+       "466281  9684700   11536848      22000        22000          22000.0   \n",
+       "466282  9584776   11436914      20700        20700          20700.0   \n",
+       "466283  9604874   11457002       2000         2000           2000.0   \n",
+       "466284  9199665   11061576      10000        10000           9975.0   \n",
+       "\n",
+       "              term  int_rate  installment grade sub_grade  ... last_pymnt_d  \\\n",
+       "0        36 months     10.65       162.87     B        B2  ...       Jan-15   \n",
+       "1        60 months     15.27        59.83     C        C4  ...       Apr-13   \n",
+       "2        36 months     15.96        84.33     C        C5  ...       Jun-14   \n",
+       "3        36 months     13.49       339.31     C        C1  ...       Jan-15   \n",
+       "4        60 months     12.69        67.79     B        B5  ...       Jan-16   \n",
+       "...            ...       ...          ...   ...       ...  ...          ...   \n",
+       "466280   60 months     14.47       432.64     C        C2  ...       Jan-16   \n",
+       "466281   60 months     19.97       582.50     D        D5  ...       Dec-14   \n",
+       "466282   60 months     16.99       514.34     D        D1  ...       Jan-16   \n",
+       "466283   36 months      7.90        62.59     A        A4  ...       Dec-14   \n",
+       "466284   36 months     19.20       367.58     D        D3  ...       Jan-16   \n",
+       "\n",
+       "       last_pymnt_amnt last_credit_pull_d  collections_12_mths_ex_med  \\\n",
+       "0               171.62             Jan-16                         0.0   \n",
+       "1               119.66             Sep-13                         0.0   \n",
+       "2               649.91             Jan-16                         0.0   \n",
+       "3               357.48             Jan-15                         0.0   \n",
+       "4                67.79             Jan-16                         0.0   \n",
+       "...                ...                ...                         ...   \n",
+       "466280          432.64             Jan-16                         0.0   \n",
+       "466281           17.50             Jan-16                         0.0   \n",
+       "466282          514.34             Dec-15                         0.0   \n",
+       "466283         1500.68             Apr-15                         0.0   \n",
+       "466284          367.58             Jan-16                         0.0   \n",
+       "\n",
+       "       policy_code application_type acc_now_delinq tot_coll_amt tot_cur_bal  \\\n",
+       "0                1       INDIVIDUAL            0.0          NaN         NaN   \n",
+       "1                1       INDIVIDUAL            0.0          NaN         NaN   \n",
+       "2                1       INDIVIDUAL            0.0          NaN         NaN   \n",
+       "3                1       INDIVIDUAL            0.0          NaN         NaN   \n",
+       "4                1       INDIVIDUAL            0.0          NaN         NaN   \n",
+       "...            ...              ...            ...          ...         ...   \n",
+       "466280           1       INDIVIDUAL            0.0          0.0    294998.0   \n",
+       "466281           1       INDIVIDUAL            0.0          0.0    221830.0   \n",
+       "466282           1       INDIVIDUAL            0.0          0.0     73598.0   \n",
+       "466283           1       INDIVIDUAL            0.0          0.0    591610.0   \n",
+       "466284           1       INDIVIDUAL            0.0          0.0     57477.0   \n",
+       "\n",
+       "       total_rev_hi_lim  \n",
+       "0                   NaN  \n",
+       "1                   NaN  \n",
+       "2                   NaN  \n",
+       "3                   NaN  \n",
+       "4                   NaN  \n",
+       "...                 ...  \n",
+       "466280          29900.0  \n",
+       "466281          39400.0  \n",
+       "466282          13100.0  \n",
+       "466283          53100.0  \n",
+       "466284          16000.0  \n",
+       "\n",
+       "[466285 rows x 52 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def getDuplicateColumns(df):\n",
+    "    \n",
+    "    \n",
+    "    duplicateColumnNames = set()\n",
+    "    \n",
+    "    for x in range(df.shape[1]):\n",
+    "    \n",
+    "        col = df.iloc[:, x]\n",
+    "\n",
+    "        for y in range(x + 1, df.shape[1]):\n",
+    "            \n",
+    "            otherCol = df.iloc[:, y]\n",
+    "            \n",
+    "            if col.equals(otherCol):\n",
+    "                duplicateColumnNames.add(df.columns.values[y])\n",
+    "    return list(duplicateColumnNames)\n",
+    "df = df.drop(columns=getDuplicateColumns(df))\n",
+    "df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "b163a679",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['id', 'member_id', 'loan_amnt', 'funded_amnt', 'funded_amnt_inv', 'term', 'int_rate', 'installment', 'grade', 'sub_grade', 'emp_title', 'emp_length', 'home_ownership', 'annual_inc', 'verification_status', 'issue_d', 'loan_status', 'pymnt_plan', 'url', 'purpose', 'title', 'zip_code', 'addr_state', 'dti', 'delinq_2yrs', 'earliest_cr_line', 'inq_last_6mths', 'open_acc', 'pub_rec', 'revol_bal', 'revol_util', 'total_acc', 'initial_list_status', 'out_prncp', 'out_prncp_inv', 'total_pymnt', 'total_pymnt_inv', 'total_rec_prncp', 'total_rec_int', 'total_rec_late_fee', 'recoveries', 'collection_recovery_fee', 'last_pymnt_d', 'last_pymnt_amnt', 'last_credit_pull_d', 'collections_12_mths_ex_med', 'policy_code', 'application_type', 'acc_now_delinq', 'tot_coll_amt', 'tot_cur_bal', 'total_rev_hi_lim']\n"
+     ]
+    }
+   ],
+   "source": [
+    "my_list = list(df)\n",
+    "print(my_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "2a7c0552",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#I have chosen Loan_Status as my target variable because by use of other attributes we can create a model and then we can test on this target column.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c9318e17",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0          True\n",
+       "1         False\n",
+       "2          True\n",
+       "3          True\n",
+       "4          True\n",
+       "          ...  \n",
+       "466280     True\n",
+       "466281    False\n",
+       "466282     True\n",
+       "466283     True\n",
+       "466284     True\n",
+       "Name: Target, Length: 466285, dtype: bool"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['Target'] = (df['loan_status'] != \"Charged Off\")\n",
+    "df['Target']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "dc677428",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df=df.drop(['policy_code','initial_list_status','pub_rec','int_rate','installment','collection_recovery_fee','total_rec_prncp','total_rec_late_fee','emp_title','url','sub_grade','id','member_id'],axis=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ab43c512",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(373028, 39)\n",
+      "(93257, 39)\n"
+     ]
+    }
+   ],
+   "source": [
+    "y=df.Target\n",
+    "x=df.drop('Target',axis=1)\n",
+    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2)\n",
+    "print(x_train.shape)\n",
+    "print(x_test.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "072e2653",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df['issue_date'] = [0 if pd.isna(x) else x for x in df['issue_d']]\n",
+    "df['earliest_cr_line'] = [0 if pd.isna(x) else x for x in df['earliest_cr_line']]\n",
+    "df['last_pymnt_d'] = [0 if pd.isna(x) else x for x in df['last_pymnt_d']]\n",
+    "df['last_credit_pull_d'] = [0 if pd.isna(x) else x for x in df['last_credit_pull_d']]\n",
+    "#Converted NaN date values to 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "14f9f367",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         Dec-11\n",
+       "1         Dec-11\n",
+       "2         Dec-11\n",
+       "3         Dec-11\n",
+       "4         Dec-11\n",
+       "           ...  \n",
+       "466280    Jan-14\n",
+       "466281    Jan-14\n",
+       "466282    Jan-14\n",
+       "466283    Jan-14\n",
+       "466284    Jan-14\n",
+       "Name: issue_date, Length: 466285, dtype: object"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['issue_date']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "0c59588f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "375372     78\n",
+       "18168     117\n",
+       "265747     73\n",
+       "365113     78\n",
+       "4880      110\n",
+       "         ... \n",
+       "147376     92\n",
+       "214140    102\n",
+       "5422      110\n",
+       "58282      85\n",
+       "234635     72\n",
+       "Name: issue_d_diff, Length: 373028, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def date_conv(date):\n",
+    "    s = 0\n",
+    "    if(date[:3]==\"Jan\"):\n",
+    "        s=11\n",
+    "    elif(date[:3]==\"Feb\"):\n",
+    "        s=10\n",
+    "    elif(date[:3]==\"Mar\"):\n",
+    "        s=9\n",
+    "    elif(date[:3]==\"Apr\"):\n",
+    "        s=8\n",
+    "    elif(date[:3]==\"May\"):\n",
+    "        s=7\n",
+    "    elif(date[:3]==\"Jun\"):\n",
+    "        s=6\n",
+    "    elif(date[:3]==\"Jul\"):\n",
+    "        s=5\n",
+    "    elif(date[:3]==\"Aug\"):\n",
+    "        s=4\n",
+    "    elif(date[:3]==\"Sep\"):\n",
+    "        s=3\n",
+    "    elif(date[:3]==\"Oct\"):\n",
+    "        s=2\n",
+    "    elif(date[:3]==\"Nov\"):\n",
+    "        s=1\n",
+    "    elif(date[:3]==\"Dec\"):\n",
+    "        s=0\n",
+    "    s =s + (20 -int(date[4:8]))*12\n",
+    "    return s\n",
+    "x_train['issue_d_diff'] = [0 if x==0 else date_conv(x) for x in x_train['issue_d']]\n",
+    "x_train['issue_d_diff']\n",
+    "#converted date to numeric form(months)\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d80abb07",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5f5a650e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}