diff --git a/Assignment 1/210171_Anuraag_1/Project.ipynb b/Assignment 1/210171_Anuraag_1/Project.ipynb
new file mode 100644
index 0000000..00282f6
--- /dev/null
+++ b/Assignment 1/210171_Anuraag_1/Project.ipynb	
@@ -0,0 +1,5610 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "1e90432b",
+   "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"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "adcfeab4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df=pd.read_csv(\"dataset.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2aa6521c",
+   "metadata": {},
+   "outputs": [
+    {
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+       "      <th></th>\n",
+       "      <th>CUST_ID</th>\n",
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+       "      <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",
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+       "    </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",
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+       "3                       0.083333                          0.000000   \n",
+       "4                       0.083333                          0.000000   \n",
+       "...                          ...                               ...   \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",
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+       "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",
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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": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "41510d81",
+   "metadata": {},
+   "outputs": [
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+       "      <td>773.17</td>\n",
+       "      <td>0.0</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>C10004</td>\n",
+       "      <td>1666.670542</td>\n",
+       "      <td>0.636364</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>0.0</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>C10005</td>\n",
+       "      <td>817.714335</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>0.0</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",
+       "  </tbody>\n",
+       "</table>\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",
+       "   INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                    95.4      0.000000             0.166667   \n",
+       "1                     0.0   6442.945483             0.000000   \n",
+       "2                     0.0      0.000000             1.000000   \n",
+       "3                     0.0    205.788017             0.083333   \n",
+       "4                     0.0      0.000000             0.083333   \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",
+       "   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",
+       "      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  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a9b5afd4",
+   "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>CUST_ID</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>8945</th>\n",
+       "      <td>C19186</td>\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>0.50</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>C19187</td>\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>0.00</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>C19188</td>\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>0.25</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>C19189</td>\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>0.25</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>C19190</td>\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>0.00</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     CUST_ID     BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\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",
+       "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",
+       "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",
+       "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",
+       "8945  325.594462         48.886365              0.50       6  \n",
+       "8946  275.861322               NaN              0.00       6  \n",
+       "8947   81.270775         82.418369              0.25       6  \n",
+       "8948   52.549959         55.755628              0.25       6  \n",
+       "8949   63.165404         88.288956              0.00       6  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "cc72bbb9",
+   "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>count</th>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8949.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8637.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "      <td>8950.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>1564.474828</td>\n",
+       "      <td>0.877271</td>\n",
+       "      <td>1003.204834</td>\n",
+       "      <td>592.437371</td>\n",
+       "      <td>411.067645</td>\n",
+       "      <td>978.871112</td>\n",
+       "      <td>0.490351</td>\n",
+       "      <td>0.202458</td>\n",
+       "      <td>0.364437</td>\n",
+       "      <td>0.135144</td>\n",
+       "      <td>3.248827</td>\n",
+       "      <td>14.709832</td>\n",
+       "      <td>4494.449450</td>\n",
+       "      <td>1733.143852</td>\n",
+       "      <td>864.206542</td>\n",
+       "      <td>0.153715</td>\n",
+       "      <td>11.517318</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2081.531879</td>\n",
+       "      <td>0.236904</td>\n",
+       "      <td>2136.634782</td>\n",
+       "      <td>1659.887917</td>\n",
+       "      <td>904.338115</td>\n",
+       "      <td>2097.163877</td>\n",
+       "      <td>0.401371</td>\n",
+       "      <td>0.298336</td>\n",
+       "      <td>0.397448</td>\n",
+       "      <td>0.200121</td>\n",
+       "      <td>6.824647</td>\n",
+       "      <td>24.857649</td>\n",
+       "      <td>3638.815725</td>\n",
+       "      <td>2895.063757</td>\n",
+       "      <td>2372.446607</td>\n",
+       "      <td>0.292499</td>\n",
+       "      <td>1.338331</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.019163</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>128.281915</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>39.635000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1600.000000</td>\n",
+       "      <td>383.276166</td>\n",
+       "      <td>169.123707</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>873.385231</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>361.280000</td>\n",
+       "      <td>38.000000</td>\n",
+       "      <td>89.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.083333</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>3000.000000</td>\n",
+       "      <td>856.901546</td>\n",
+       "      <td>312.343947</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>2054.140036</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1110.130000</td>\n",
+       "      <td>577.405000</td>\n",
+       "      <td>468.637500</td>\n",
+       "      <td>1113.821139</td>\n",
+       "      <td>0.916667</td>\n",
+       "      <td>0.300000</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>17.000000</td>\n",
+       "      <td>6500.000000</td>\n",
+       "      <td>1901.134317</td>\n",
+       "      <td>825.485459</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>19043.138560</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>49039.570000</td>\n",
+       "      <td>40761.250000</td>\n",
+       "      <td>22500.000000</td>\n",
+       "      <td>47137.211760</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>123.000000</td>\n",
+       "      <td>358.000000</td>\n",
+       "      <td>30000.000000</td>\n",
+       "      <td>50721.483360</td>\n",
+       "      <td>76406.207520</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            BALANCE  BALANCE_FREQUENCY     PURCHASES  ONEOFF_PURCHASES  \\\n",
+       "count   8950.000000        8950.000000   8950.000000       8950.000000   \n",
+       "mean    1564.474828           0.877271   1003.204834        592.437371   \n",
+       "std     2081.531879           0.236904   2136.634782       1659.887917   \n",
+       "min        0.000000           0.000000      0.000000          0.000000   \n",
+       "25%      128.281915           0.888889     39.635000          0.000000   \n",
+       "50%      873.385231           1.000000    361.280000         38.000000   \n",
+       "75%     2054.140036           1.000000   1110.130000        577.405000   \n",
+       "max    19043.138560           1.000000  49039.570000      40761.250000   \n",
+       "\n",
+       "       INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "count             8950.000000   8950.000000          8950.000000   \n",
+       "mean               411.067645    978.871112             0.490351   \n",
+       "std                904.338115   2097.163877             0.401371   \n",
+       "min                  0.000000      0.000000             0.000000   \n",
+       "25%                  0.000000      0.000000             0.083333   \n",
+       "50%                 89.000000      0.000000             0.500000   \n",
+       "75%                468.637500   1113.821139             0.916667   \n",
+       "max              22500.000000  47137.211760             1.000000   \n",
+       "\n",
+       "       ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
+       "count                 8950.000000                       8950.000000   \n",
+       "mean                     0.202458                          0.364437   \n",
+       "std                      0.298336                          0.397448   \n",
+       "min                      0.000000                          0.000000   \n",
+       "25%                      0.000000                          0.000000   \n",
+       "50%                      0.083333                          0.166667   \n",
+       "75%                      0.300000                          0.750000   \n",
+       "max                      1.000000                          1.000000   \n",
+       "\n",
+       "       CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
+       "count             8950.000000       8950.000000    8950.000000   8949.000000   \n",
+       "mean                 0.135144          3.248827      14.709832   4494.449450   \n",
+       "std                  0.200121          6.824647      24.857649   3638.815725   \n",
+       "min                  0.000000          0.000000       0.000000     50.000000   \n",
+       "25%                  0.000000          0.000000       1.000000   1600.000000   \n",
+       "50%                  0.000000          0.000000       7.000000   3000.000000   \n",
+       "75%                  0.222222          4.000000      17.000000   6500.000000   \n",
+       "max                  1.500000        123.000000     358.000000  30000.000000   \n",
+       "\n",
+       "           PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT       TENURE  \n",
+       "count   8950.000000       8637.000000       8950.000000  8950.000000  \n",
+       "mean    1733.143852        864.206542          0.153715    11.517318  \n",
+       "std     2895.063757       2372.446607          0.292499     1.338331  \n",
+       "min        0.000000          0.019163          0.000000     6.000000  \n",
+       "25%      383.276166        169.123707          0.000000    12.000000  \n",
+       "50%      856.901546        312.343947          0.000000    12.000000  \n",
+       "75%     1901.134317        825.485459          0.142857    12.000000  \n",
+       "max    50721.483360      76406.207520          1.000000    12.000000  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1c748d81",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8950, 18)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "07eda6fd",
+   "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>CUST_ID</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>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8948</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8949</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8950 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      CUST_ID  BALANCE  BALANCE_FREQUENCY  PURCHASES  ONEOFF_PURCHASES  \\\n",
+       "0       False    False              False      False             False   \n",
+       "1       False    False              False      False             False   \n",
+       "2       False    False              False      False             False   \n",
+       "3       False    False              False      False             False   \n",
+       "4       False    False              False      False             False   \n",
+       "...       ...      ...                ...        ...               ...   \n",
+       "8945    False    False              False      False             False   \n",
+       "8946    False    False              False      False             False   \n",
+       "8947    False    False              False      False             False   \n",
+       "8948    False    False              False      False             False   \n",
+       "8949    False    False              False      False             False   \n",
+       "\n",
+       "      INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                      False         False                False   \n",
+       "1                      False         False                False   \n",
+       "2                      False         False                False   \n",
+       "3                      False         False                False   \n",
+       "4                      False         False                False   \n",
+       "...                      ...           ...                  ...   \n",
+       "8945                   False         False                False   \n",
+       "8946                   False         False                False   \n",
+       "8947                   False         False                False   \n",
+       "8948                   False         False                False   \n",
+       "8949                   False         False                False   \n",
+       "\n",
+       "      ONEOFF_PURCHASES_FREQUENCY  PURCHASES_INSTALLMENTS_FREQUENCY  \\\n",
+       "0                          False                             False   \n",
+       "1                          False                             False   \n",
+       "2                          False                             False   \n",
+       "3                          False                             False   \n",
+       "4                          False                             False   \n",
+       "...                          ...                               ...   \n",
+       "8945                       False                             False   \n",
+       "8946                       False                             False   \n",
+       "8947                       False                             False   \n",
+       "8948                       False                             False   \n",
+       "8949                       False                             False   \n",
+       "\n",
+       "      CASH_ADVANCE_FREQUENCY  CASH_ADVANCE_TRX  PURCHASES_TRX  CREDIT_LIMIT  \\\n",
+       "0                      False             False          False         False   \n",
+       "1                      False             False          False         False   \n",
+       "2                      False             False          False         False   \n",
+       "3                      False             False          False         False   \n",
+       "4                      False             False          False         False   \n",
+       "...                      ...               ...            ...           ...   \n",
+       "8945                   False             False          False         False   \n",
+       "8946                   False             False          False         False   \n",
+       "8947                   False             False          False         False   \n",
+       "8948                   False             False          False         False   \n",
+       "8949                   False             False          False         False   \n",
+       "\n",
+       "      PAYMENTS  MINIMUM_PAYMENTS  PRC_FULL_PAYMENT  TENURE  \n",
+       "0        False             False             False   False  \n",
+       "1        False             False             False   False  \n",
+       "2        False             False             False   False  \n",
+       "3        False              True             False   False  \n",
+       "4        False             False             False   False  \n",
+       "...        ...               ...               ...     ...  \n",
+       "8945     False             False             False   False  \n",
+       "8946     False              True             False   False  \n",
+       "8947     False             False             False   False  \n",
+       "8948     False             False             False   False  \n",
+       "8949     False             False             False   False  \n",
+       "\n",
+       "[8950 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "19b31328",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "314"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "4707a8dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CUST_ID                               0\n",
+       "BALANCE                               0\n",
+       "BALANCE_FREQUENCY                     0\n",
+       "PURCHASES                             0\n",
+       "ONEOFF_PURCHASES                      0\n",
+       "INSTALLMENTS_PURCHASES                0\n",
+       "CASH_ADVANCE                          0\n",
+       "PURCHASES_FREQUENCY                   0\n",
+       "ONEOFF_PURCHASES_FREQUENCY            0\n",
+       "PURCHASES_INSTALLMENTS_FREQUENCY      0\n",
+       "CASH_ADVANCE_FREQUENCY                0\n",
+       "CASH_ADVANCE_TRX                      0\n",
+       "PURCHASES_TRX                         0\n",
+       "CREDIT_LIMIT                          1\n",
+       "PAYMENTS                              0\n",
+       "MINIMUM_PAYMENTS                    313\n",
+       "PRC_FULL_PAYMENT                      0\n",
+       "TENURE                                0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ce9d0116",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df1=df.fillna({'CREDIT_LIMIT':'df[CREDIT_LIMIT].mean()'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7bd927da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "<div>\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <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",
+       "      <th>INSTALLMENTS_PURCHASES</th>\n",
+       "      <th>CASH_ADVANCE</th>\n",
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+       "      <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>C10001</td>\n",
+       "      <td>40.900749</td>\n",
+       "      <td>0.818182</td>\n",
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+       "      <td>0.00</td>\n",
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+       "      <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>C10002</td>\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",
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+       "      <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>C10003</td>\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>C10004</td>\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",
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+       "      <td>1</td>\n",
+       "      <td>7500.0</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>C10005</td>\n",
+       "      <td>817.714335</td>\n",
+       "      <td>1.000000</td>\n",
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+       "      <td>244.791237</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
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+       "    <tr>\n",
+       "      <th>8945</th>\n",
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+       "      <td>48.886365</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8946</th>\n",
+       "      <td>C19187</td>\n",
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+       "      <td>6</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>275.861322</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>C19188</td>\n",
+       "      <td>23.398673</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>144.40</td>\n",
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+       "      <td>5</td>\n",
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+       "      <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>C19189</td>\n",
+       "      <td>13.457564</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.00</td>\n",
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+       "      <td>0.166667</td>\n",
+       "      <td>2</td>\n",
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+       "      <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>C19190</td>\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 × 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",
+       "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 18 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "60b8bae1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CUST_ID                               0\n",
+       "BALANCE                               0\n",
+       "BALANCE_FREQUENCY                     0\n",
+       "PURCHASES                             0\n",
+       "ONEOFF_PURCHASES                      0\n",
+       "INSTALLMENTS_PURCHASES                0\n",
+       "CASH_ADVANCE                          0\n",
+       "PURCHASES_FREQUENCY                   0\n",
+       "ONEOFF_PURCHASES_FREQUENCY            0\n",
+       "PURCHASES_INSTALLMENTS_FREQUENCY      0\n",
+       "CASH_ADVANCE_FREQUENCY                0\n",
+       "CASH_ADVANCE_TRX                      0\n",
+       "PURCHASES_TRX                         0\n",
+       "CREDIT_LIMIT                          0\n",
+       "PAYMENTS                              0\n",
+       "MINIMUM_PAYMENTS                    313\n",
+       "PRC_FULL_PAYMENT                      0\n",
+       "TENURE                                0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "cc65303a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df2=df1.fillna(method='bfill',axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "d2fa43b9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "      <th></th>\n",
+       "      <th>CUST_ID</th>\n",
+       "      <th>BALANCE</th>\n",
+       "      <th>BALANCE_FREQUENCY</th>\n",
+       "      <th>PURCHASES</th>\n",
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+       "      <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",
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+       "      <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>C10002</td>\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>C10003</td>\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>C10004</td>\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>244.791237</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>C10005</td>\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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>C19186</td>\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>C19187</td>\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>82.418369</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>C19188</td>\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>C19189</td>\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>C19190</td>\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 × 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",
+       "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        244.791237          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         82.418369          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 18 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "1ae3b7d5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df3=df2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "051960b0",
+   "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>CUST_ID</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>C10001</td>\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>C10002</td>\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>C10003</td>\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>C10004</td>\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>244.791237</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>C10005</td>\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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>C19186</td>\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>C19187</td>\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>82.418369</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>C19188</td>\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>C19189</td>\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>C19190</td>\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 × 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",
+       "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        244.791237          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         82.418369          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 18 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "e3cdf803",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df3=df.fillna(method='pad',axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "72613030",
+   "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>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>C10001</td>\n",
+       "      <td>40.900749</td>\n",
+       "      <td>0.818182</td>\n",
+       "      <td>95.40</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>95.4</td>\n",
+       "      <td>0.000000</td>\n",
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+       "      <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>C10002</td>\n",
+       "      <td>3202.467416</td>\n",
+       "      <td>0.909091</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</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>C10003</td>\n",
+       "      <td>2495.148862</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>773.17</td>\n",
+       "      <td>773.17</td>\n",
+       "      <td>0.0</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>C10004</td>\n",
+       "      <td>1666.670542</td>\n",
+       "      <td>0.636364</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>0.0</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>627.284787</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>C10005</td>\n",
+       "      <td>817.714335</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>16.00</td>\n",
+       "      <td>0.0</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",
+       "  </tbody>\n",
+       "</table>\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",
+       "   INSTALLMENTS_PURCHASES  CASH_ADVANCE  PURCHASES_FREQUENCY  \\\n",
+       "0                    95.4      0.000000             0.166667   \n",
+       "1                     0.0   6442.945483             0.000000   \n",
+       "2                     0.0      0.000000             1.000000   \n",
+       "3                     0.0    205.788017             0.083333   \n",
+       "4                     0.0      0.000000             0.083333   \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",
+       "   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",
+       "      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        627.284787          0.000000      12  \n",
+       "4   678.334763        244.791237          0.000000      12  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "be751b42",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CUST_ID                             0\n",
+       "BALANCE                             0\n",
+       "BALANCE_FREQUENCY                   0\n",
+       "PURCHASES                           0\n",
+       "ONEOFF_PURCHASES                    0\n",
+       "INSTALLMENTS_PURCHASES              0\n",
+       "CASH_ADVANCE                        0\n",
+       "PURCHASES_FREQUENCY                 0\n",
+       "ONEOFF_PURCHASES_FREQUENCY          0\n",
+       "PURCHASES_INSTALLMENTS_FREQUENCY    0\n",
+       "CASH_ADVANCE_FREQUENCY              0\n",
+       "CASH_ADVANCE_TRX                    0\n",
+       "PURCHASES_TRX                       0\n",
+       "CREDIT_LIMIT                        0\n",
+       "PAYMENTS                            0\n",
+       "MINIMUM_PAYMENTS                    0\n",
+       "PRC_FULL_PAYMENT                    0\n",
+       "TENURE                              0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "03cd8a46",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.isnull().sum().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "150630a6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <th>CUST_ID</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>C10001</td>\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>C10002</td>\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>C10003</td>\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>C10004</td>\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>627.284787</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>C10005</td>\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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>C19186</td>\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>C19187</td>\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>48.886365</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>C19188</td>\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>C19189</td>\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>C19190</td>\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 × 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",
+       "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        627.284787          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         48.886365          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 18 columns]"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "fbc72b81",
+   "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>CUST_ID</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>C10001</td>\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>C10002</td>\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>C10003</td>\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>C10004</td>\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>C10005</td>\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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8945</th>\n",
+       "      <td>C19186</td>\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>C19187</td>\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>C19188</td>\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>C19189</td>\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>C19190</td>\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 × 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",
+       "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 18 columns]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "65a042d7",
+   "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",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\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>CUST_ID</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>C10001</td>\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>C10002</td>\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>C10003</td>\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>C10004</td>\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>C10005</td>\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",
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+       "      <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>C19186</td>\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>C19187</td>\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>C19188</td>\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>C19189</td>\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>C19190</td>\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 × 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",
+       "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 18 columns]"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "b5eb9f20",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\AppData\\Local\\Temp\\ipykernel_20316\\3045539152.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
+      "  df3.skew()\n"
+     ]
+    },
+    {
+     "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                         1.522590\n",
+       "PAYMENTS                             5.907620\n",
+       "MINIMUM_PAYMENTS                    13.404947\n",
+       "PRC_FULL_PAYMENT                     1.942820\n",
+       "TENURE                              -2.943017\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.skew()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "75fb125a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "8ffe08e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>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",
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+       "      <td>0.000000</td>\n",
+       "      <td>12</td>\n",
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+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>3202.467416</td>\n",
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+       "      <td>0.000000</td>\n",
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+       "      <td>4</td>\n",
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+       "      <td>12</td>\n",
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+       "    <tr>\n",
+       "      <th>2</th>\n",
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+       "      <td>0</td>\n",
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+       "      <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",
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+       "    <tr>\n",
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+       "    <tr>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8947</th>\n",
+       "      <td>23.398673</td>\n",
+       "      <td>0.833333</td>\n",
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+       "    <tr>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
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+       "      <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        627.284787          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         48.886365          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": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3=df3.drop(['CUST_ID'],axis=1)\n",
+    "df3"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "fbee5a56",
+   "metadata": {},
+   "source": [
+    "df3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "966bc3b4",
+   "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>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>627.284787</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>48.886365</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        627.284787          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         48.886365          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": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "462b2419",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "df2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "de57ea78",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8950, 17)"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "bb0fd931",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.stats import skew"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "0d9e8c2c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "BALANCE\n",
+      "2.392984897743557\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "BALANCE_FREQUENCY\n",
+      "-2.022926407947498\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PURCHASES\n",
+      "8.14290403970826\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ONEOFF_PURCHASES\n",
+      "10.043399272872994\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INSTALLMENTS_PURCHASES\n",
+      "7.297896535603957\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CASH_ADVANCE\n",
+      "5.165743121623765\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PURCHASES_FREQUENCY\n",
+      "0.06015415199708297\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ONEOFF_PURCHASES_FREQUENCY\n",
+      "1.535355406271309\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PURCHASES_INSTALLMENTS_FREQUENCY\n",
+      "0.5091158200492595\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CASH_ADVANCE_FREQUENCY\n",
+      "1.828379768476593\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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eICLiWeD0jPLrCj4H8KHBjKs/Nu1JLnHts4upK0Hs2M/rThi88REzs1IYqpe5DmmbG9NLXPtoFYyuyTOyOs+6nX78qJkNP04Qx2DTnoPklDz3oTeSqB9T6wRhZsOSE8Qx2Nh4kBnjR1Kd7/vwJQnCz6c2s+HHCeIYbGo82Gf3Upf6uuReiKaWtjJHZWZWWk4Qx2DTnpYep9jo7sUrmdzNZGbDixNEP7W2dbCz+VDxLYiCK5nMzIYTJ4h+2pxe4jpnUnEJYsKoGqrz8jiEmQ07ThD9tCm9xLXYG9/yOTFv0mh3MZnZsFPJ50EMS13PgSh2DAJgfn0dz+xoPqLs5gc2HlXvHefMGVhwZmYl5BZEP21qPMiI6hz1dbVFr3P8lDo27D7IofaOMkZmZlZaThD9tGlPcolrOpdUUU6aPoaOzmCtB6rNbBhxguinYqb57m7h9LEAPLV1XzlCMjMrCyeIfoiI9Ca54scfAOZOGs2omjxPbXOCMLPhwwmiH5pa2mg+1N7vFkQ+J06aNsYtCDMbVpwg+qG/l7gWWjhjLE9t20cyk7mZ2dDnBNEPXZe4zulnCwJg4fRxNLe2s3mPny5nZsODE0Q/bGhM7oYu9i7qQgtnpAPVHocws2HCCaIfNu4+yOS6Gupq+39/4YlTx5ATPLmlqQyRmZmVnhNEP2zYffCYupcARtbkOWXGOB54rrHEUZmZlYcTRD9sbDzI3Emjj3n98+dP4tGNe2k57DuqzWzo81xMRTrU3sHWppZjbkEAnDd/Et+6+1ke3rBnwPFkzeUEns/JzEpn0FsQkmZLukvS05KelPSXGXUulNQkaUX6+sxgx9nd5j0tRMDcYxig7vLqeROpyon71u0qYWRmZuVRiRZEO/BXEfGIpDHAw5LuiIinutW7JyIuq0B8mTbuTi5xHUiCGF1bxRmzx/O7dbt5e8Oxb8fMbDAMegsiIrZFxCPp52bgaWDmYMfRXxt2p5e4Tjz2MQiA84+fzBOb97L/UHspwjIzK5uKDlJLmgecCTyQsfg8SY9J+oWkU3rZxhJJyyUt37lzZ7lCZUPjQUbV5JlcVzOg7Vx22nQ6Ax4pwTiEmVk5VSxBSKoDfgx8JCK63z32CDA3Ik4H/i/w0562ExHXR0RDRDTU19eXLd6N6SWu/ZnmO8sJU8dw9ryJPLi+kU5Pu2FmQ1hFEoSkapLk8P2I+En35RGxLyL2p59vBaolTR7kMI/w3K4DzBvAJa6F3nnuHBoPHGadnw9hZkNYJa5iEvAd4OmI+HIPdaal9ZB0NkmcuwcvyiMdau9g/e4DLJhaV5LtXXLqNEbXVnHH09vp6HQrwsyGpkpcxXQB8N+AJyStSMs+DcwBiIjrgCuBD0hqB1qAq6KC06A+t+sAnQELpo4pyfZqq/JcfvoMlj64kbtW7+CNJ08tyXb7w/dRmFlfBj1BRMS9QK8d+RFxLXDt4ETUtzXbk66gBVNK04IAeOXMcayaPZ67Vu1g/MhqGuZNLNm2zcxKwVNtFGHNjv3kBMdNLs0YRJfLz5jB8VPq+MmjW7jjqefd3WRmQ4oTRBHW7mhm7qTRjKjOl3S7tVV5rj5vHq+aO4G7Vu/kz258iKaWtpLuw8zsWDlBFGHN9v0cX8LupUL5nHjbmTO54owZ3LduF2//1v0839Raln2ZmfWHE0Qf2jo6eW7XgZKOP3QniXOOm8QN17yazXtauPK6+9iUPr3OzKxSPJtrH9bvOkB7Z5TsEtfevGZBPUvfdy7v+s4DvP1b93Pz+85lXonHPUop60ooXwVl9tLhFkQfVj3fDMCCKaW5xLUvr5w1jqXvO5fW9k7+9Fv3s9Y305lZhThB9GHFpr3UVuU4cdrgJAhInl99y5Jz6Qx46zd+x61PbBu0fZuZdXEXUx8e3biH02aNozo/uLn0hKljWPbB8/nw0kf54Pcf4fTZ47l44VQmjKphX2sb9zyzkwOHOxhZnWfq2BG8cuY4RtaU9iorM3t5c4LoxaH2DlZu3cc158+ryP5nTxzFj95/Ht///QZufnAjX7ht9QvLqvNidG0VLYc7ONTeyX89sZU/OL6eK181i5oqNwzNbOCcIHrx9LZmDrd3cubs8RWLoTqf45oLjuOaC47j4OF2mlraGDuimv9csfWFOlv2tnDPmp3ctXoHl197L19bfCYnlGhaEDN7+fKfmr1YsTF5ZsMZc8ZXNpDUqJoqpo8byejaI/P6zPEjuerVc7j6vLns2n+Iy6+9lx8+tIkKTl9lZi8BbkH04tFNe5k2dgTTx42sdChFOWnaWD78h8fzkVtW8Nc/fpx71u7ir990IrMnHvl4032tbazbuZ/m1jYiYMqYEUwdV0tVrjx/L3hiQLPhyQmiBxHBg881ctbc8ZUOpV+mjBnB9957Dt+4ay1f+/Uabn1iG6+aO4G5E0exr7WNNdv38+yuA0etN6omz1lzJvCaBZOPSihm9vLkBNGDxzc3sa2plY+fNPhTcQ9UPif+xxsWcGXDLG783XoeWt/Ib5/ZybiR1cyfUsfbzprJ7v2HmTCqhk6C55taWbmlifvW7eLCL/6Gy0+fwftfN39QL+01s6HHCaIHtz35PPmceMPJUyodyjGbPm4kn1p0cuaywm6fKWNGcNqs8TS1tLF7/yFufnAjyx7dwitnjuOC4ycze+JIhGht66ClrYNDbR0gsbnxILMmjmLqmNoBP4q1N+6iMqsMJ4ge/PLJ5zn3FRMZP6qm0qEMmnEjq/nAhfP58B8ezy0PbeK2J5/n2/c8S3vGNOQSdI2Bjx9VzavmTqBhrp9pYfZS4gSRYe2OZp7deYD3VOj+h0obP6qG979uPu9/3Xw6OoMdza0IMbI6T211jtqqHO2dwXW/Wcdzuw7w+JYmfvX0Du5atYNHN+7hHefM4bUL6snlyteqMLPyc4LI8L37N1CVExefMq3SoVRcPqfMq7iq82JSXS2T6mppmDeR3fsP8dD6PTy8YQ+3P7WdsSOqOGPOBKaNrWXD7oN0BnRG0NkZdETQGfDYpr2cPH0MDfMmsnD62LImFE8saNZ/ThDdbGtqYemDm7jyVbOYOnbEoO57OPe1T6qr5ZJTp/Fv734Vdz61g3vW7OSJLU2sfn4fza3t5CVyOZET5CRyElv3tvCD5ZuApJvqnOMmcv78yTTMm8Bxk0czqmbonJ5OMPZyNHT+Bw4R37hrHZ0RfOj1x1c6lGGptirPm0+bzptPm/5CWU+Jb/HZs3l+XysPPNvIfet28bu1u7ntye0vLM/nRFVOBEBAkLQ8RlTnGTeiil+v2s6ciaM5YWodC6bWMXvCKMaPqulxqpGuGwfLOaBu9lLiBFHgtief598f2MA7zp4zpO4F6OkX7HAnJd1XbzlzJm85cyYAmxoPsmLTXjY2HuTg4XbaO4OVm5uQhAQCWto62dfSxuY9Ldy7dhetbZ1HbHd0TZ4R1XnaO4P2jk7a0vfOgLzEmBFVjBlRxb1rdzJ74ijmTBzFjHEjqRtRxah03a6usI7O5NX1AKfRtcm6gz15o1klVCRBSLoE+CqQB74dEZ/vtlzp8kXAQeCaiHiknDHdtWoHf3nLo5w2azx/9+aF5dxVWQ20K6TSXSmzJ446Kjn31vXW2Rls2dvCM9ub2dbUyt6Dh2k80Mah9g6q87mkFZIXq7c1k8uJ9o6gubWN5tZ2Vm1r5s6ndnC4ozNz+70ZWZ3npvvXM3P8SGaMH8nMCSOZXFfLyOo8I2tyjKjKU12Vozqfozovbn9yO1U5kc+JmqocNVU5rj5v3rEcIrNBM+gJQlIe+DpwEbAZeEjSzyLiqYJqlwIL0tc5wDfT95Jrbm3jkz95gv96fBsnTK3j21c3eNrsQVKKZJTLKTOpFLuvzs5ge3Mr25paOXiog/2H2jnU3kFOyS/zfE7kJe5Zs5MI2H+oneZD7exraWPMiCo272nhofWN7Gtt71fcAH//86cYWZNndE0VI6pz5NJW0r7Wdro6wXJpd9iE0TWI5PLiqnxyJdmI6jwjut6rk/eafI41O/a/0D3XlZTOP34yNflckrRyoiqfoyovqnM5cjkQL7bQCltrye6T7SRXsOWprUr2X5vuv8qtqZesSrQgzgbWRsSzAJJuAa4AChPEFcBNkXQa/17SeEnTI6LkT84ZVVPF9qZW/uqiE1jyuldQW/XSSw4D7aLqz/qDua+Brt+fBLWj+VCvdZtb22g8cJjWtk5a2jpoOdxBe2cnbR2dtHUEd63aQUdn0N4ZHG7v5HBHJwum1HHwcAcHD7fT0tZJRBDAhl0H6LrzJAKCZEJGCCKgrTNobeug6eBhtrd10treQWtbMu374fZOWts66H7rys8fL99Dp/I5UZu2lrKGd3oa8elpLEgvLM/eSmF5Vl31WbeH/eroz31ta6iYMLqGZR+8oOTbrUSCmAlsKvi+maNbB1l1ZgJHneWSlgBL0q/7Ja3uXqcYPwb+4lhWPNJkYFf3wncOfLvllBnzEDcZ2FWO49qfbfZz/8P2OFc6iH562casDx3zqnN7WlCJBJGVfLvfqltMnaQw4nrg+oEGVQqSlkdEQ6Xj6A/HPDgc8+BwzKVVic7DzcDsgu+zgK3HUMfMzMqoEgniIWCBpOMk1QBXAT/rVudnwNVKnAs0lWP8wczMejboXUwR0S7pw8BtJJe53hART0p6f7r8OuBWkktc15Jc5vqewY7zGA2Jrq5+csyDwzEPDsdcQvJjKc3MLIsvYDYzs0xOEGZmlskJokiSLpG0WtJaSZ/MWC5JX0uXPy7prGLXrWDM70xjfVzSfZJOL1i2XtITklZIWj6EYr5QUlMa1wpJnyl23QrF+4mCWFdK6pA0MV1WqWN8g6Qdklb2sHwonst9xTwUz+W+Yh5S53KmiPCrjxfJYPo64BVADfAYsLBbnUXAL0ju4TgXeKDYdSsY8/nAhPTzpV0xp9/XA5OH4HG+EPh/x7JuJeLtVv+PgF9X8hin+30tcBawsoflQ+pcLjLmIXUuFxnzkDmXe3q5BVGcF6YHiYjDQNf0IIVemB4kIn4PjJc0vch1KxJzRNwXEXvSr78nud+kkgZyrCpxnPu7z8XA0jLH1KeIuBto7KXKUDuX+4x5CJ7LxRznnlTsOHfnBFGcnqb+KKZOMeuWQ3/3+16Svxq7BHC7pIfT6UwGQ7ExnyfpMUm/kHRKP9ctpaL3KWkUcAnJrC5dKnGMizHUzuX+GgrncrGGyrmcyc+DKM5ApgcpetqQEit6v5JeT/Kf6g8Kii+IiK2SpgB3SFqV/kVUTsXE/AgwNyL2S1oE/JRk1t9KHOf+7POPgN9FROFflJU4xsUYaudy0YbQuVyMoXQuZ3ILojgDmR6kUtOGFLVfSacB3wauiIjdXeURsTV93wEsI2n2llufMUfEvojYn36+FaiWNLmYdcugP/u8im7dSxU6xsUYaudyUYbYudynIXYuZ6vEwMdwe5G0tJ4FjuPFQaNTutV5M0cO7D1Y7LoVjHkOyd3q53crHw2MKfh8H3DJEIl5Gi/e4Hk2sDE95oN+nIvdJzCOpC96dKWPccH+59Hz4OmQOpeLjHlInctFxjxkzuWeXu5iKkIMYHqQntYdIjF/BpgEfEPJZPftkcwqORVYlpZVATdHxC+HSMxXAh+Q1A60AFdF8j9s0I9zkfECvBW4PSIOFKxekWMMIGkpyRU0kyVtBj4LVBfEPKTO5SJjHlLncpExD5lzuSeeasPMzDJ5DMLMzDI5QZiZWSYnCDMzy+QEYWZmmZwgzMwskxOEmZllcoKwkpA0TdItktZJekrSrZJOSJd9VFKrpHEF9UdJ+n46DfNKSfdKqkuX7e+27WskXVtEDI+l154Xlt0o6bl02TOSbpI0M132G0lv6lb/I5K+kX6ul9Qm6c+71Vkv6ccF36+UdGPB90slLZf0tKRVkr6Yln9O0paC6Z1XSBrfw8/SfSroOzO28ZSkxRk/a9c69xUse4uSqbBXpcf7yoJlv5HUUPB9ntIpqjPiWCHpjemykPSlgvU+LulzBd+vTvf1ZBrrxyX9k6R/KagzV9KzPR0HqywnCBswJXchLQN+ExHzI2Ih8GmSm5QgmcX0IZIbxrr8JbA9Il4ZEaeSzJ/TNoAYTiY5n18raXS3xZ+IiNOBE4FHgbsk1ZBMfXFVt7qFU2L8CcnMoIs5WoNenFytMI5TgWuBd0XEycCpJHfFdvlKRJxR8Nrby491T0G9N3bfBskMn9+SVN3tZ+1a5/w0ptOBL5JMQXESybxQ/yLpVb3su6c4zoiIO9PyQ8DblEwP0f04XAp8BLg4Ik4hmfa6CfjfwBXpvxfAV4H/2cdxsApxgrBSeD3QVnDnMBGxIiLukTQfqAP+jiN/0U4HthTUXx0RhwYQwzuA7wG3A5dnVYjEV4DnSZ4Z8CPgMkm1kPzlDMwA7k1XWQz8FTCrq9VR4IskSbC7vwb+MSJWpftsj4hvDODn6lFErCG503lCH1U/DvxTRDyXrvcc8E8kP9tAtAPXAx/NWPYp4OPx4jxIrRHxbxHRAnyM5I7nS0mmwfj+AOOwMnGCsFI4FXi4h2Vdz0C4BzhRyYyaADcAfyPpfkn/IGlBwTojC7s0gL8vIoa3Az9I95X1F3+hR4CTIpnQ7UGSabghaT38ICJC0mxgWkQ8CPww3X6hHwJnSTq+W3lvxwLgowU/2119xPmagrp/232hkie9rYlkErouXyhYp+sX7ykZMS0HFvax/6w4VqRJv8vXgXeqoPsw1eNxiGRiukbgJuCDRcZgFeC5mKzcrgLeGhGdkn5C0m3z9YhYIekVwMXAG4GHJJ0XEU8DLWkXCpCMQQANR2/6heWvBnZGxAYlc97cIGlCvPgAmaNWKfjc1c30n+n7nxXE/cP08y3Ad4AvF6zXAXyB5C/lwmcP9OUrEfHFIuveExGXZZR/VNL7SJ44dkm3ZZ+IiB91KxO9T0+fNd9OYVlPcRAR+yTdBPwFyXxCxfo6MDIiVvdjHRtkbkFYKTwJHNWfrWT65QUkc/CvJ/ml+8Jf9xGxPyJ+EhEfBP6dZIK4Y7EYOCndxzpgLPDHvdQ/E3g6/fxT4A3pX+MjI+KRgm1ek27zZ8Dp3Vo5kHRpvZZkJtEumceixL4SESeStGpukjSij/pPcnSCPYukFQGwmyO7qSYCu/oRz/8hGUMqHPvp6zh0pi8bwpwgrBR+DdSmf9UCL/xV/1XgcxExL33NAGamV65cIGlCWreGpLtjQ393LClH0io5rWs/JIO3R3UzKfEXJOMfv4QkSQG/IenyWprWO5Fkau6ZBdv8Z7oNaEdEG/AVksHYLl8APq0Xr+DKSfpYf3+uYkTET0h+yb+7j6pfBD6VjrF0jbV8JI0Vkp//XenFBqTb66v7qzCORpLW1nsLiv8Z+FdJ09J91qbH3oYRJwgbsHSK4rcCFym5zPVJ4HMkUx0v61Z9Gckv2vnAbyU9QXJl0XKOfBxnsV4LbImILQVldwMLlTxHGZJ++ceAZ4BXA6+P5Fm/XZYCp5N0JUGSXLrH/WOyxza+Q0FXbUQ8TvLLd6mkp4GVJAmpS+EYxIquX9oD8PfAx9JECUeOQayQVBMRK4C/AX4u6RmS4/CBgu6d64Fm4LH0ONWRJJUu3ccgruRoXwJeuJopHWf4OnBnej48jLu0hx1P9232MiPp88A5wJu6JUqzIzhBmJlZJjf5bNhIL/X8k27F/xER/1iJeEpByZ3c/9Kt+LmIeGtWfbPB5BaEmZll8iC1mZllcoIwM7NMThBmZpbJCcLMzDL9f1BjP+DEgY35AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CASH_ADVANCE_TRX\n",
+      "5.720339281754528\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PURCHASES_TRX\n",
+      "4.629879142324137\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CREDIT_LIMIT\n",
+      "1.52233441043849\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PAYMENTS\n",
+      "5.906629644423578\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MINIMUM_PAYMENTS\n",
+      "13.402700266701002\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PRC_FULL_PAYMENT\n",
+      "1.942494313531204\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TENURE\n",
+      "-2.942524021534386\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ADHI ANAND\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
+    {
+     "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": [
+    "for x in df3:\n",
+    "    print(x)\n",
+    "    print(skew(df3[x]))\n",
+    "    \n",
+    "    plt.figure()\n",
+    "    sns.distplot(df3[x])\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "0b54738c",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1224x1224 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.heatmap(df3.corr(),square=True,annot=True,cmap='cubehelix')\n",
+    "plt.figure(figsize=(17,17))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "49f18bca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "newdf3=np.sqrt(df3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "ee60f187",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "StandardScaler()"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.preprocessing import StandardScaler\n",
+    "scaler=StandardScaler()\n",
+    "scaler.fit(df3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "a9da89fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Scaled_data=scaler.transform(df3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "a356c34b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-0.73198937, -0.24943448, -0.42489974, ..., -0.3053336 ,\n",
+       "        -0.52555097,  0.36067954],\n",
+       "       [ 0.78696085,  0.13432467, -0.46955188, ...,  0.08714014,\n",
+       "         0.2342269 ,  0.36067954],\n",
+       "       [ 0.44713513,  0.51808382, -0.10766823, ..., -0.10010994,\n",
+       "        -0.52555097,  0.36067954],\n",
+       "       ...,\n",
+       "       [-0.7403981 , -0.18547673, -0.40196519, ..., -0.32935392,\n",
+       "         0.32919999, -4.12276757],\n",
+       "       [-0.74517423, -0.18547673, -0.46955188, ..., -0.34057185,\n",
+       "         0.32919999, -4.12276757],\n",
+       "       [-0.57257511, -0.88903307,  0.04214581, ..., -0.32688396,\n",
+       "        -0.52555097, -4.12276757]])"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Scaled_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "b066c011",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Cumulative explained variance')"
+      ]
+     },
+     "execution_count": 52,
+     "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": [
+    "from sklearn.decomposition import PCA\n",
+    "pca = PCA().fit(Scaled_data)\n",
+    "plt.plot(np.cumsum(pca.explained_variance_ratio_))\n",
+    "plt.xlim(0,17,1)\n",
+    "plt.xlabel('Number of components')\n",
+    "plt.ylabel('Cumulative explained variance')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "cf4ff958",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#since major variance is covered in first 10 components we can drop last 4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "b6ffe2a2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pca=PCA(n_components=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "875c571d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PCA(n_components=10)"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pca.fit(Scaled_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "757aff49",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_pca=pca.transform(Scaled_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "9ab3e6f6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8950, 10)"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_pca.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "01b8fdb2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-1.68059222e+00, -1.07744417e+00,  4.96943178e-01, ...,\n",
+       "        -3.54031964e-02,  1.11141930e-01, -7.77018521e-02],\n",
+       "       [-1.14087871e+00,  2.50596529e+00,  5.97101813e-01, ...,\n",
+       "         1.06184311e-01,  6.93201687e-01, -7.77543112e-01],\n",
+       "       [ 9.70322308e-01, -3.82118372e-01,  1.09571902e-01, ...,\n",
+       "        -1.40569654e-01, -8.91228636e-01, -2.01263714e-03],\n",
+       "       ...,\n",
+       "       [-9.23637329e-01, -1.81049690e+00, -4.92325560e-01, ...,\n",
+       "        -3.97099363e-01,  8.41471293e-01, -8.29806394e-01],\n",
+       "       [-2.33494824e+00, -6.58132639e-01,  9.61488573e-01, ...,\n",
+       "         8.74221485e-02,  1.26896872e+00,  2.68805301e-01],\n",
+       "       [-5.54822694e-01, -3.97795153e-01,  9.96130738e-01, ...,\n",
+       "        -3.72304519e-01, -8.23856383e-01,  3.45778911e-01]])"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_pca"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45ca8667",
+   "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": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Assignment 1/demo b/Assignment 1/demo
new file mode 100644
index 0000000..e965047
--- /dev/null
+++ b/Assignment 1/demo	
@@ -0,0 +1 @@
+Hello