diff --git a/files_for_lab/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/files_for_lab/.ipynb_checkpoints/Untitled-checkpoint.ipynb
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@@ -0,0 +1,1804 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "54824057",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'# Lab | Customer Analysis Round 5\\n\\nFor this lab, we still keep using the `marketing_customer_analysis.csv` file that you can find in the `files_for_lab` folder.\\n\\n### Get the data\\n\\nWe are using the `marketing_customer_analysis.csv` file.\\n\\n### Dealing with the data\\n\\nAlready done in the round 2.\\n\\n### Explore the data\\n\\nDone in the round 3.\\n\\n### Processing Data\\n\\n(_Further processing..._)\\n\\n- X-y split.\\n- Normalize (numerical).\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'''# Lab | Customer Analysis Round 5\n",
+    "\n",
+    "For this lab, we still keep using the `marketing_customer_analysis.csv` file that you can find in the `files_for_lab` folder.\n",
+    "\n",
+    "### Get the data\n",
+    "\n",
+    "We are using the `marketing_customer_analysis.csv` file.\n",
+    "\n",
+    "### Dealing with the data\n",
+    "\n",
+    "Already done in the round 2.\n",
+    "\n",
+    "### Explore the data\n",
+    "\n",
+    "Done in the round 3.\n",
+    "\n",
+    "### Processing Data\n",
+    "\n",
+    "(_Further processing..._)\n",
+    "\n",
+    "- X-y split.\n",
+    "- Normalize (numerical).\n",
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2228a747",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "import seaborn as sns\n",
+    "from sklearn import linear_model\n",
+    "from sklearn.metrics import mean_squared_error, r2_score\n",
+    "\n",
+    "import statsmodels.api as sm\n",
+    "from statsmodels.formula.api import ols"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7e8f4127",
+   "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>Customer</th>\n",
+       "      <th>State</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Response</th>\n",
+       "      <th>Coverage</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Effective To Date</th>\n",
+       "      <th>EmploymentStatus</th>\n",
+       "      <th>Gender</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Months Since Policy Inception</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Number of Policies</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Policy</th>\n",
+       "      <th>Renew Offer Type</th>\n",
+       "      <th>Sales Channel</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Vehicle Size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>BU79786</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2763.519279</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/24/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>56274</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>384.811147</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>6979.535903</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/31/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>42</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>1131.464935</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>12887.431650</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/19/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>48767</td>\n",
+       "      <td>...</td>\n",
+       "      <td>38</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>566.472247</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7645.861827</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/20/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>529.881344</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>HB64268</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2813.692575</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>43836</td>\n",
+       "      <td>...</td>\n",
+       "      <td>44</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>138.130879</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9129</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/10/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>89</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9130</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/12/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9131</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/6/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9132</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L2</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Large</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9133</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/14/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>90</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9134 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer       State  Customer Lifetime Value Response  Coverage  \\\n",
+       "0     BU79786  Washington              2763.519279       No     Basic   \n",
+       "1     QZ44356     Arizona              6979.535903       No  Extended   \n",
+       "2     AI49188      Nevada             12887.431650       No   Premium   \n",
+       "3     WW63253  California              7645.861827       No     Basic   \n",
+       "4     HB64268  Washington              2813.692575       No     Basic   \n",
+       "...       ...         ...                      ...      ...       ...   \n",
+       "9129  LA72316  California             23405.987980       No     Basic   \n",
+       "9130  PK87824  California              3096.511217      Yes  Extended   \n",
+       "9131  TD14365  California              8163.890428       No  Extended   \n",
+       "9132  UP19263  California              7524.442436       No  Extended   \n",
+       "9133  Y167826  California              2611.836866       No  Extended   \n",
+       "\n",
+       "     Education Effective To Date EmploymentStatus Gender  Income  ...  \\\n",
+       "0     Bachelor           2/24/11         Employed      F   56274  ...   \n",
+       "1     Bachelor           1/31/11       Unemployed      F       0  ...   \n",
+       "2     Bachelor           2/19/11         Employed      F   48767  ...   \n",
+       "3     Bachelor           1/20/11       Unemployed      M       0  ...   \n",
+       "4     Bachelor            2/3/11         Employed      M   43836  ...   \n",
+       "...        ...               ...              ...    ...     ...  ...   \n",
+       "9129  Bachelor           2/10/11         Employed      M   71941  ...   \n",
+       "9130   College           2/12/11         Employed      F   21604  ...   \n",
+       "9131  Bachelor            2/6/11       Unemployed      M       0  ...   \n",
+       "9132   College            2/3/11         Employed      M   21941  ...   \n",
+       "9133   College           2/14/11       Unemployed      M       0  ...   \n",
+       "\n",
+       "     Months Since Policy Inception Number of Open Complaints  \\\n",
+       "0                                5                         0   \n",
+       "1                               42                         0   \n",
+       "2                               38                         0   \n",
+       "3                               65                         0   \n",
+       "4                               44                         0   \n",
+       "...                            ...                       ...   \n",
+       "9129                            89                         0   \n",
+       "9130                            28                         0   \n",
+       "9131                            37                         3   \n",
+       "9132                             3                         0   \n",
+       "9133                            90                         0   \n",
+       "\n",
+       "      Number of Policies     Policy Type        Policy  Renew Offer Type  \\\n",
+       "0                      1  Corporate Auto  Corporate L3            Offer1   \n",
+       "1                      8   Personal Auto   Personal L3            Offer3   \n",
+       "2                      2   Personal Auto   Personal L3            Offer1   \n",
+       "3                      7  Corporate Auto  Corporate L2            Offer1   \n",
+       "4                      1   Personal Auto   Personal L1            Offer1   \n",
+       "...                  ...             ...           ...               ...   \n",
+       "9129                   2   Personal Auto   Personal L1            Offer2   \n",
+       "9130                   1  Corporate Auto  Corporate L3            Offer1   \n",
+       "9131                   2  Corporate Auto  Corporate L2            Offer1   \n",
+       "9132                   3   Personal Auto   Personal L2            Offer3   \n",
+       "9133                   1  Corporate Auto  Corporate L3            Offer4   \n",
+       "\n",
+       "      Sales Channel Total Claim Amount  Vehicle Class Vehicle Size  \n",
+       "0             Agent         384.811147   Two-Door Car      Medsize  \n",
+       "1             Agent        1131.464935  Four-Door Car      Medsize  \n",
+       "2             Agent         566.472247   Two-Door Car      Medsize  \n",
+       "3       Call Center         529.881344            SUV      Medsize  \n",
+       "4             Agent         138.130879  Four-Door Car      Medsize  \n",
+       "...             ...                ...            ...          ...  \n",
+       "9129            Web         198.234764  Four-Door Car      Medsize  \n",
+       "9130         Branch         379.200000  Four-Door Car      Medsize  \n",
+       "9131         Branch         790.784983  Four-Door Car      Medsize  \n",
+       "9132         Branch         691.200000  Four-Door Car        Large  \n",
+       "9133    Call Center         369.600000   Two-Door Car      Medsize  \n",
+       "\n",
+       "[9134 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(r\"C:\\Users\\filip\\OneDrive\\Desktop\\IRONHACK\\Labs\\Week3\\lab-customer-analysis-round-5\\files_for_lab\\csv_files\\marketing_customer_analysis.csv\", sep = ',')\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "95be6257",
+   "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>customer</th>\n",
+       "      <th>state</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>response</th>\n",
+       "      <th>coverage</th>\n",
+       "      <th>education</th>\n",
+       "      <th>effective_to_date</th>\n",
+       "      <th>employmentstatus</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>income</th>\n",
+       "      <th>...</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>policy</th>\n",
+       "      <th>renew_offer_type</th>\n",
+       "      <th>sales_channel</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>vehicle_size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>BU79786</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2763.519279</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/24/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>56274</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>384.811147</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>6979.535903</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/31/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>42</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>1131.464935</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>12887.431650</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/19/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>48767</td>\n",
+       "      <td>...</td>\n",
+       "      <td>38</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>566.472247</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7645.861827</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/20/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>529.881344</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>HB64268</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2813.692575</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>43836</td>\n",
+       "      <td>...</td>\n",
+       "      <td>44</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>138.130879</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9129</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/10/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>89</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9130</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/12/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9131</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/6/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9132</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L2</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Large</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9133</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/14/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>90</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9134 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer       state  customer_lifetime_value response  coverage  \\\n",
+       "0     BU79786  Washington              2763.519279       No     Basic   \n",
+       "1     QZ44356     Arizona              6979.535903       No  Extended   \n",
+       "2     AI49188      Nevada             12887.431650       No   Premium   \n",
+       "3     WW63253  California              7645.861827       No     Basic   \n",
+       "4     HB64268  Washington              2813.692575       No     Basic   \n",
+       "...       ...         ...                      ...      ...       ...   \n",
+       "9129  LA72316  California             23405.987980       No     Basic   \n",
+       "9130  PK87824  California              3096.511217      Yes  Extended   \n",
+       "9131  TD14365  California              8163.890428       No  Extended   \n",
+       "9132  UP19263  California              7524.442436       No  Extended   \n",
+       "9133  Y167826  California              2611.836866       No  Extended   \n",
+       "\n",
+       "     education effective_to_date employmentstatus gender  income  ...  \\\n",
+       "0     Bachelor           2/24/11         Employed      F   56274  ...   \n",
+       "1     Bachelor           1/31/11       Unemployed      F       0  ...   \n",
+       "2     Bachelor           2/19/11         Employed      F   48767  ...   \n",
+       "3     Bachelor           1/20/11       Unemployed      M       0  ...   \n",
+       "4     Bachelor            2/3/11         Employed      M   43836  ...   \n",
+       "...        ...               ...              ...    ...     ...  ...   \n",
+       "9129  Bachelor           2/10/11         Employed      M   71941  ...   \n",
+       "9130   College           2/12/11         Employed      F   21604  ...   \n",
+       "9131  Bachelor            2/6/11       Unemployed      M       0  ...   \n",
+       "9132   College            2/3/11         Employed      M   21941  ...   \n",
+       "9133   College           2/14/11       Unemployed      M       0  ...   \n",
+       "\n",
+       "     months_since_policy_inception number_of_open_complaints  \\\n",
+       "0                                5                         0   \n",
+       "1                               42                         0   \n",
+       "2                               38                         0   \n",
+       "3                               65                         0   \n",
+       "4                               44                         0   \n",
+       "...                            ...                       ...   \n",
+       "9129                            89                         0   \n",
+       "9130                            28                         0   \n",
+       "9131                            37                         3   \n",
+       "9132                             3                         0   \n",
+       "9133                            90                         0   \n",
+       "\n",
+       "      number_of_policies     policy_type        policy  renew_offer_type  \\\n",
+       "0                      1  Corporate Auto  Corporate L3            Offer1   \n",
+       "1                      8   Personal Auto   Personal L3            Offer3   \n",
+       "2                      2   Personal Auto   Personal L3            Offer1   \n",
+       "3                      7  Corporate Auto  Corporate L2            Offer1   \n",
+       "4                      1   Personal Auto   Personal L1            Offer1   \n",
+       "...                  ...             ...           ...               ...   \n",
+       "9129                   2   Personal Auto   Personal L1            Offer2   \n",
+       "9130                   1  Corporate Auto  Corporate L3            Offer1   \n",
+       "9131                   2  Corporate Auto  Corporate L2            Offer1   \n",
+       "9132                   3   Personal Auto   Personal L2            Offer3   \n",
+       "9133                   1  Corporate Auto  Corporate L3            Offer4   \n",
+       "\n",
+       "      sales_channel total_claim_amount  vehicle_class vehicle_size  \n",
+       "0             Agent         384.811147   Two-Door Car      Medsize  \n",
+       "1             Agent        1131.464935  Four-Door Car      Medsize  \n",
+       "2             Agent         566.472247   Two-Door Car      Medsize  \n",
+       "3       Call Center         529.881344            SUV      Medsize  \n",
+       "4             Agent         138.130879  Four-Door Car      Medsize  \n",
+       "...             ...                ...            ...          ...  \n",
+       "9129            Web         198.234764  Four-Door Car      Medsize  \n",
+       "9130         Branch         379.200000  Four-Door Car      Medsize  \n",
+       "9131         Branch         790.784983  Four-Door Car      Medsize  \n",
+       "9132         Branch         691.200000  Four-Door Car        Large  \n",
+       "9133    Call Center         369.600000   Two-Door Car      Medsize  \n",
+       "\n",
+       "[9134 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cols = []\n",
+    "\n",
+    "for i in range(len(df.columns)):\n",
+    "    cols.append(df.columns[i].lower().replace(' ','_'))\n",
+    "    \n",
+    "df.columns = cols\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a6cf1193",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                          object\n",
+       "state                             object\n",
+       "customer_lifetime_value          float64\n",
+       "response                          object\n",
+       "coverage                          object\n",
+       "education                         object\n",
+       "effective_to_date                 object\n",
+       "employmentstatus                  object\n",
+       "gender                            object\n",
+       "income                             int64\n",
+       "location_code                     object\n",
+       "marital_status                    object\n",
+       "monthly_premium_auto               int64\n",
+       "months_since_last_claim            int64\n",
+       "months_since_policy_inception      int64\n",
+       "number_of_open_complaints          int64\n",
+       "number_of_policies                 int64\n",
+       "policy_type                       object\n",
+       "policy                            object\n",
+       "renew_offer_type                  object\n",
+       "sales_channel                     object\n",
+       "total_claim_amount               float64\n",
+       "vehicle_class                     object\n",
+       "vehicle_size                      object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bdcf00f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                         0\n",
+       "state                            0\n",
+       "customer_lifetime_value          0\n",
+       "response                         0\n",
+       "coverage                         0\n",
+       "education                        0\n",
+       "effective_to_date                0\n",
+       "employmentstatus                 0\n",
+       "gender                           0\n",
+       "income                           0\n",
+       "location_code                    0\n",
+       "marital_status                   0\n",
+       "monthly_premium_auto             0\n",
+       "months_since_last_claim          0\n",
+       "months_since_policy_inception    0\n",
+       "number_of_open_complaints        0\n",
+       "number_of_policies               0\n",
+       "policy_type                      0\n",
+       "policy                           0\n",
+       "renew_offer_type                 0\n",
+       "sales_channel                    0\n",
+       "total_claim_amount               0\n",
+       "vehicle_class                    0\n",
+       "vehicle_size                     0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ae87fdaa",
+   "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>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>months_since_last_claim</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>8004.940475</td>\n",
+       "      <td>37657.380009</td>\n",
+       "      <td>93.219291</td>\n",
+       "      <td>15.097000</td>\n",
+       "      <td>48.064594</td>\n",
+       "      <td>0.384388</td>\n",
+       "      <td>2.966170</td>\n",
+       "      <td>434.088794</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>6870.967608</td>\n",
+       "      <td>30379.904734</td>\n",
+       "      <td>34.407967</td>\n",
+       "      <td>10.073257</td>\n",
+       "      <td>27.905991</td>\n",
+       "      <td>0.910384</td>\n",
+       "      <td>2.390182</td>\n",
+       "      <td>290.500092</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1898.007675</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>61.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.099007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>3994.251794</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>68.000000</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>272.258244</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>5780.182197</td>\n",
+       "      <td>33889.500000</td>\n",
+       "      <td>83.000000</td>\n",
+       "      <td>14.000000</td>\n",
+       "      <td>48.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>383.945434</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>8962.167041</td>\n",
+       "      <td>62320.000000</td>\n",
+       "      <td>109.000000</td>\n",
+       "      <td>23.000000</td>\n",
+       "      <td>71.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>547.514839</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>83325.381190</td>\n",
+       "      <td>99981.000000</td>\n",
+       "      <td>298.000000</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>99.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>2893.239678</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       customer_lifetime_value        income  monthly_premium_auto  \\\n",
+       "count              9134.000000   9134.000000           9134.000000   \n",
+       "mean               8004.940475  37657.380009             93.219291   \n",
+       "std                6870.967608  30379.904734             34.407967   \n",
+       "min                1898.007675      0.000000             61.000000   \n",
+       "25%                3994.251794      0.000000             68.000000   \n",
+       "50%                5780.182197  33889.500000             83.000000   \n",
+       "75%                8962.167041  62320.000000            109.000000   \n",
+       "max               83325.381190  99981.000000            298.000000   \n",
+       "\n",
+       "       months_since_last_claim  months_since_policy_inception  \\\n",
+       "count              9134.000000                    9134.000000   \n",
+       "mean                 15.097000                      48.064594   \n",
+       "std                  10.073257                      27.905991   \n",
+       "min                   0.000000                       0.000000   \n",
+       "25%                   6.000000                      24.000000   \n",
+       "50%                  14.000000                      48.000000   \n",
+       "75%                  23.000000                      71.000000   \n",
+       "max                  35.000000                      99.000000   \n",
+       "\n",
+       "       number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "count                9134.000000         9134.000000         9134.000000  \n",
+       "mean                    0.384388            2.966170          434.088794  \n",
+       "std                     0.910384            2.390182          290.500092  \n",
+       "min                     0.000000            1.000000            0.099007  \n",
+       "25%                     0.000000            1.000000          272.258244  \n",
+       "50%                     0.000000            2.000000          383.945434  \n",
+       "75%                     0.000000            4.000000          547.514839  \n",
+       "max                     5.000000            9.000000         2893.239678  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "19370c03",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.distplot(df['income'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a3d5f67e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df['income'].replace(0, np.nan, inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "3ff74435",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.distplot(df['customer_lifetime_value'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ebfec677",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=df['income'], y=df['customer_lifetime_value'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7d533072",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=df['income'], y=df['monthly_premium_auto'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "107d80eb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.boxplot(x=df['income'], data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e22e3409",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.boxplot(x=df['income'], y = df['monthly_premium_auto'], data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "536abfed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "6925bcbe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# X-y split\n",
+    "df_train, df_test = train_test_split(df, test_size=0.2, random_state=33)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "641a702c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                          object\n",
+       "state                             object\n",
+       "customer_lifetime_value          float64\n",
+       "response                          object\n",
+       "coverage                          object\n",
+       "education                         object\n",
+       "effective_to_date                 object\n",
+       "employmentstatus                  object\n",
+       "gender                            object\n",
+       "income                           float64\n",
+       "location_code                     object\n",
+       "marital_status                    object\n",
+       "monthly_premium_auto               int64\n",
+       "months_since_last_claim            int64\n",
+       "months_since_policy_inception      int64\n",
+       "number_of_open_complaints          int64\n",
+       "number_of_policies                 int64\n",
+       "policy_type                       object\n",
+       "policy                            object\n",
+       "renew_offer_type                  object\n",
+       "sales_channel                     object\n",
+       "total_claim_amount               float64\n",
+       "vehicle_class                     object\n",
+       "vehicle_size                      object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "cbf0e81c",
+   "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>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>months_since_last_claim</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5318</th>\n",
+       "      <td>11121.621790</td>\n",
+       "      <td>44299.0</td>\n",
+       "      <td>106</td>\n",
+       "      <td>25</td>\n",
+       "      <td>76</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>754.260616</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6980</th>\n",
+       "      <td>5365.932820</td>\n",
+       "      <td>62808.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>33</td>\n",
+       "      <td>37</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>211.515893</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8691</th>\n",
+       "      <td>6006.211611</td>\n",
+       "      <td>85510.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>19</td>\n",
+       "      <td>68</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>355.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5385</th>\n",
+       "      <td>8749.496793</td>\n",
+       "      <td>52373.0</td>\n",
+       "      <td>111</td>\n",
+       "      <td>2</td>\n",
+       "      <td>37</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>186.160527</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9110</th>\n",
+       "      <td>34611.378960</td>\n",
+       "      <td>20090.0</td>\n",
+       "      <td>109</td>\n",
+       "      <td>10</td>\n",
+       "      <td>59</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>523.200000</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>3958.002823</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101</td>\n",
+       "      <td>29</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>484.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>578</th>\n",
+       "      <td>7785.004214</td>\n",
+       "      <td>44897.0</td>\n",
+       "      <td>99</td>\n",
+       "      <td>22</td>\n",
+       "      <td>46</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>580.725310</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5848</th>\n",
+       "      <td>5175.289340</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>71</td>\n",
+       "      <td>0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>340.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2439</th>\n",
+       "      <td>27382.818930</td>\n",
+       "      <td>45473.0</td>\n",
+       "      <td>76</td>\n",
+       "      <td>10</td>\n",
+       "      <td>29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>188.938397</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7188</th>\n",
+       "      <td>3230.576665</td>\n",
+       "      <td>62873.0</td>\n",
+       "      <td>81</td>\n",
+       "      <td>0</td>\n",
+       "      <td>41</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>207.751860</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7307 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      customer_lifetime_value   income  monthly_premium_auto  \\\n",
+       "5318             11121.621790  44299.0                   106   \n",
+       "6980              5365.932820  62808.0                    66   \n",
+       "8691              6006.211611  85510.0                    74   \n",
+       "5385              8749.496793  52373.0                   111   \n",
+       "9110             34611.378960  20090.0                   109   \n",
+       "...                       ...      ...                   ...   \n",
+       "57                3958.002823      NaN                   101   \n",
+       "578               7785.004214  44897.0                    99   \n",
+       "5848              5175.289340      NaN                    71   \n",
+       "2439             27382.818930  45473.0                    76   \n",
+       "7188              3230.576665  62873.0                    81   \n",
+       "\n",
+       "      months_since_last_claim  months_since_policy_inception  \\\n",
+       "5318                       25                             76   \n",
+       "6980                       33                             37   \n",
+       "8691                       19                             68   \n",
+       "5385                        2                             37   \n",
+       "9110                       10                             59   \n",
+       "...                       ...                            ...   \n",
+       "57                         29                             12   \n",
+       "578                        22                             46   \n",
+       "5848                        0                             26   \n",
+       "2439                       10                             29   \n",
+       "7188                        0                             41   \n",
+       "\n",
+       "      number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "5318                          5                   2          754.260616  \n",
+       "6980                          0                   4          211.515893  \n",
+       "8691                          0                   4          355.200000  \n",
+       "5385                          0                   9          186.160527  \n",
+       "9110                          0                   2          523.200000  \n",
+       "...                         ...                 ...                 ...  \n",
+       "57                            0                   1          484.800000  \n",
+       "578                           1                   7          580.725310  \n",
+       "5848                          0                   9          340.800000  \n",
+       "2439                          0                   2          188.938397  \n",
+       "7188                          0                   1          207.751860  \n",
+       "\n",
+       "[7307 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_data = df_train[['customer_lifetime_value', 'income','monthly_premium_auto','months_since_last_claim','months_since_policy_inception', 'number_of_open_complaints', 'number_of_policies', 'total_claim_amount' ]]\n",
+    "num_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "8d4e7d14",
+   "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>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>months_since_last_claim</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.113274</td>\n",
+       "      <td>0.380926</td>\n",
+       "      <td>0.190678</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.767677</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.260672</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.042589</td>\n",
+       "      <td>0.586710</td>\n",
+       "      <td>0.021186</td>\n",
+       "      <td>0.942857</td>\n",
+       "      <td>0.373737</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.375</td>\n",
+       "      <td>0.073075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.050452</td>\n",
+       "      <td>0.839111</td>\n",
+       "      <td>0.055085</td>\n",
+       "      <td>0.542857</td>\n",
+       "      <td>0.686869</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.375</td>\n",
+       "      <td>0.122739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.084142</td>\n",
+       "      <td>0.470693</td>\n",
+       "      <td>0.211864</td>\n",
+       "      <td>0.057143</td>\n",
+       "      <td>0.373737</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.064311</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.401749</td>\n",
+       "      <td>0.111770</td>\n",
+       "      <td>0.203390</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.595960</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.180807</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7302</th>\n",
+       "      <td>0.025299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.169492</td>\n",
+       "      <td>0.828571</td>\n",
+       "      <td>0.121212</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.167535</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7303</th>\n",
+       "      <td>0.072298</td>\n",
+       "      <td>0.387574</td>\n",
+       "      <td>0.161017</td>\n",
+       "      <td>0.628571</td>\n",
+       "      <td>0.464646</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.200691</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7304</th>\n",
+       "      <td>0.040248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.042373</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.262626</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.117762</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7305</th>\n",
+       "      <td>0.312976</td>\n",
+       "      <td>0.393978</td>\n",
+       "      <td>0.063559</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.292929</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.065271</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7306</th>\n",
+       "      <td>0.016365</td>\n",
+       "      <td>0.587432</td>\n",
+       "      <td>0.084746</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.414141</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.071774</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7307 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      customer_lifetime_value    income  monthly_premium_auto  \\\n",
+       "0                    0.113274  0.380926              0.190678   \n",
+       "1                    0.042589  0.586710              0.021186   \n",
+       "2                    0.050452  0.839111              0.055085   \n",
+       "3                    0.084142  0.470693              0.211864   \n",
+       "4                    0.401749  0.111770              0.203390   \n",
+       "...                       ...       ...                   ...   \n",
+       "7302                 0.025299       NaN              0.169492   \n",
+       "7303                 0.072298  0.387574              0.161017   \n",
+       "7304                 0.040248       NaN              0.042373   \n",
+       "7305                 0.312976  0.393978              0.063559   \n",
+       "7306                 0.016365  0.587432              0.084746   \n",
+       "\n",
+       "      months_since_last_claim  months_since_policy_inception  \\\n",
+       "0                    0.714286                       0.767677   \n",
+       "1                    0.942857                       0.373737   \n",
+       "2                    0.542857                       0.686869   \n",
+       "3                    0.057143                       0.373737   \n",
+       "4                    0.285714                       0.595960   \n",
+       "...                       ...                            ...   \n",
+       "7302                 0.828571                       0.121212   \n",
+       "7303                 0.628571                       0.464646   \n",
+       "7304                 0.000000                       0.262626   \n",
+       "7305                 0.285714                       0.292929   \n",
+       "7306                 0.000000                       0.414141   \n",
+       "\n",
+       "      number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "0                           1.0               0.125            0.260672  \n",
+       "1                           0.0               0.375            0.073075  \n",
+       "2                           0.0               0.375            0.122739  \n",
+       "3                           0.0               1.000            0.064311  \n",
+       "4                           0.0               0.125            0.180807  \n",
+       "...                         ...                 ...                 ...  \n",
+       "7302                        0.0               0.000            0.167535  \n",
+       "7303                        0.2               0.750            0.200691  \n",
+       "7304                        0.0               1.000            0.117762  \n",
+       "7305                        0.0               0.125            0.065271  \n",
+       "7306                        0.0               0.000            0.071774  \n",
+       "\n",
+       "[7307 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Normalize (numerical)\n",
+    "\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "\n",
+    "scaler = MinMaxScaler()\n",
+    "normalized_data = scaler.fit_transform(num_data)\n",
+    "normalized_data = pd.DataFrame(normalized_data, columns = num_data.columns)\n",
+    "normalized_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fecba592",
+   "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/files_for_lab/[lab-customer-analysis-round-5]Filipa T.ipynb b/files_for_lab/[lab-customer-analysis-round-5]Filipa T.ipynb
new file mode 100644
index 0000000..310de4b
--- /dev/null
+++ b/files_for_lab/[lab-customer-analysis-round-5]Filipa T.ipynb	
@@ -0,0 +1,1804 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "54824057",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'# Lab | Customer Analysis Round 5\\n\\nFor this lab, we still keep using the `marketing_customer_analysis.csv` file that you can find in the `files_for_lab` folder.\\n\\n### Get the data\\n\\nWe are using the `marketing_customer_analysis.csv` file.\\n\\n### Dealing with the data\\n\\nAlready done in the round 2.\\n\\n### Explore the data\\n\\nDone in the round 3.\\n\\n### Processing Data\\n\\n(_Further processing..._)\\n\\n- X-y split.\\n- Normalize (numerical).\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'''# Lab | Customer Analysis Round 5\n",
+    "\n",
+    "For this lab, we still keep using the `marketing_customer_analysis.csv` file that you can find in the `files_for_lab` folder.\n",
+    "\n",
+    "### Get the data\n",
+    "\n",
+    "We are using the `marketing_customer_analysis.csv` file.\n",
+    "\n",
+    "### Dealing with the data\n",
+    "\n",
+    "Already done in the round 2.\n",
+    "\n",
+    "### Explore the data\n",
+    "\n",
+    "Done in the round 3.\n",
+    "\n",
+    "### Processing Data\n",
+    "\n",
+    "(_Further processing..._)\n",
+    "\n",
+    "- X-y split.\n",
+    "- Normalize (numerical).\n",
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2228a747",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "import seaborn as sns\n",
+    "from sklearn import linear_model\n",
+    "from sklearn.metrics import mean_squared_error, r2_score\n",
+    "\n",
+    "import statsmodels.api as sm\n",
+    "from statsmodels.formula.api import ols"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7e8f4127",
+   "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>Customer</th>\n",
+       "      <th>State</th>\n",
+       "      <th>Customer Lifetime Value</th>\n",
+       "      <th>Response</th>\n",
+       "      <th>Coverage</th>\n",
+       "      <th>Education</th>\n",
+       "      <th>Effective To Date</th>\n",
+       "      <th>EmploymentStatus</th>\n",
+       "      <th>Gender</th>\n",
+       "      <th>Income</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Months Since Policy Inception</th>\n",
+       "      <th>Number of Open Complaints</th>\n",
+       "      <th>Number of Policies</th>\n",
+       "      <th>Policy Type</th>\n",
+       "      <th>Policy</th>\n",
+       "      <th>Renew Offer Type</th>\n",
+       "      <th>Sales Channel</th>\n",
+       "      <th>Total Claim Amount</th>\n",
+       "      <th>Vehicle Class</th>\n",
+       "      <th>Vehicle Size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>BU79786</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2763.519279</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/24/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>56274</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>384.811147</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>6979.535903</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/31/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>42</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>1131.464935</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>12887.431650</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/19/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>48767</td>\n",
+       "      <td>...</td>\n",
+       "      <td>38</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>566.472247</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7645.861827</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/20/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>529.881344</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>HB64268</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2813.692575</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>43836</td>\n",
+       "      <td>...</td>\n",
+       "      <td>44</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>138.130879</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9129</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/10/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>89</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9130</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/12/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9131</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/6/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9132</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L2</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Large</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9133</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/14/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>90</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9134 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Customer       State  Customer Lifetime Value Response  Coverage  \\\n",
+       "0     BU79786  Washington              2763.519279       No     Basic   \n",
+       "1     QZ44356     Arizona              6979.535903       No  Extended   \n",
+       "2     AI49188      Nevada             12887.431650       No   Premium   \n",
+       "3     WW63253  California              7645.861827       No     Basic   \n",
+       "4     HB64268  Washington              2813.692575       No     Basic   \n",
+       "...       ...         ...                      ...      ...       ...   \n",
+       "9129  LA72316  California             23405.987980       No     Basic   \n",
+       "9130  PK87824  California              3096.511217      Yes  Extended   \n",
+       "9131  TD14365  California              8163.890428       No  Extended   \n",
+       "9132  UP19263  California              7524.442436       No  Extended   \n",
+       "9133  Y167826  California              2611.836866       No  Extended   \n",
+       "\n",
+       "     Education Effective To Date EmploymentStatus Gender  Income  ...  \\\n",
+       "0     Bachelor           2/24/11         Employed      F   56274  ...   \n",
+       "1     Bachelor           1/31/11       Unemployed      F       0  ...   \n",
+       "2     Bachelor           2/19/11         Employed      F   48767  ...   \n",
+       "3     Bachelor           1/20/11       Unemployed      M       0  ...   \n",
+       "4     Bachelor            2/3/11         Employed      M   43836  ...   \n",
+       "...        ...               ...              ...    ...     ...  ...   \n",
+       "9129  Bachelor           2/10/11         Employed      M   71941  ...   \n",
+       "9130   College           2/12/11         Employed      F   21604  ...   \n",
+       "9131  Bachelor            2/6/11       Unemployed      M       0  ...   \n",
+       "9132   College            2/3/11         Employed      M   21941  ...   \n",
+       "9133   College           2/14/11       Unemployed      M       0  ...   \n",
+       "\n",
+       "     Months Since Policy Inception Number of Open Complaints  \\\n",
+       "0                                5                         0   \n",
+       "1                               42                         0   \n",
+       "2                               38                         0   \n",
+       "3                               65                         0   \n",
+       "4                               44                         0   \n",
+       "...                            ...                       ...   \n",
+       "9129                            89                         0   \n",
+       "9130                            28                         0   \n",
+       "9131                            37                         3   \n",
+       "9132                             3                         0   \n",
+       "9133                            90                         0   \n",
+       "\n",
+       "      Number of Policies     Policy Type        Policy  Renew Offer Type  \\\n",
+       "0                      1  Corporate Auto  Corporate L3            Offer1   \n",
+       "1                      8   Personal Auto   Personal L3            Offer3   \n",
+       "2                      2   Personal Auto   Personal L3            Offer1   \n",
+       "3                      7  Corporate Auto  Corporate L2            Offer1   \n",
+       "4                      1   Personal Auto   Personal L1            Offer1   \n",
+       "...                  ...             ...           ...               ...   \n",
+       "9129                   2   Personal Auto   Personal L1            Offer2   \n",
+       "9130                   1  Corporate Auto  Corporate L3            Offer1   \n",
+       "9131                   2  Corporate Auto  Corporate L2            Offer1   \n",
+       "9132                   3   Personal Auto   Personal L2            Offer3   \n",
+       "9133                   1  Corporate Auto  Corporate L3            Offer4   \n",
+       "\n",
+       "      Sales Channel Total Claim Amount  Vehicle Class Vehicle Size  \n",
+       "0             Agent         384.811147   Two-Door Car      Medsize  \n",
+       "1             Agent        1131.464935  Four-Door Car      Medsize  \n",
+       "2             Agent         566.472247   Two-Door Car      Medsize  \n",
+       "3       Call Center         529.881344            SUV      Medsize  \n",
+       "4             Agent         138.130879  Four-Door Car      Medsize  \n",
+       "...             ...                ...            ...          ...  \n",
+       "9129            Web         198.234764  Four-Door Car      Medsize  \n",
+       "9130         Branch         379.200000  Four-Door Car      Medsize  \n",
+       "9131         Branch         790.784983  Four-Door Car      Medsize  \n",
+       "9132         Branch         691.200000  Four-Door Car        Large  \n",
+       "9133    Call Center         369.600000   Two-Door Car      Medsize  \n",
+       "\n",
+       "[9134 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(r\"C:\\Users\\filip\\OneDrive\\Desktop\\IRONHACK\\Labs\\Week3\\lab-customer-analysis-round-5\\files_for_lab\\csv_files\\marketing_customer_analysis.csv\", sep = ',')\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "95be6257",
+   "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>customer</th>\n",
+       "      <th>state</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>response</th>\n",
+       "      <th>coverage</th>\n",
+       "      <th>education</th>\n",
+       "      <th>effective_to_date</th>\n",
+       "      <th>employmentstatus</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>income</th>\n",
+       "      <th>...</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>policy</th>\n",
+       "      <th>renew_offer_type</th>\n",
+       "      <th>sales_channel</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>vehicle_size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>BU79786</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2763.519279</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/24/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>56274</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>384.811147</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>6979.535903</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/31/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>42</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>1131.464935</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>12887.431650</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/19/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>48767</td>\n",
+       "      <td>...</td>\n",
+       "      <td>38</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>566.472247</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7645.861827</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>1/20/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>529.881344</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>HB64268</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>2813.692575</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>43836</td>\n",
+       "      <td>...</td>\n",
+       "      <td>44</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>138.130879</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9129</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/10/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>89</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9130</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/12/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9131</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2/6/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9132</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/3/11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L2</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Large</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9133</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2/14/11</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>90</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9134 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer       state  customer_lifetime_value response  coverage  \\\n",
+       "0     BU79786  Washington              2763.519279       No     Basic   \n",
+       "1     QZ44356     Arizona              6979.535903       No  Extended   \n",
+       "2     AI49188      Nevada             12887.431650       No   Premium   \n",
+       "3     WW63253  California              7645.861827       No     Basic   \n",
+       "4     HB64268  Washington              2813.692575       No     Basic   \n",
+       "...       ...         ...                      ...      ...       ...   \n",
+       "9129  LA72316  California             23405.987980       No     Basic   \n",
+       "9130  PK87824  California              3096.511217      Yes  Extended   \n",
+       "9131  TD14365  California              8163.890428       No  Extended   \n",
+       "9132  UP19263  California              7524.442436       No  Extended   \n",
+       "9133  Y167826  California              2611.836866       No  Extended   \n",
+       "\n",
+       "     education effective_to_date employmentstatus gender  income  ...  \\\n",
+       "0     Bachelor           2/24/11         Employed      F   56274  ...   \n",
+       "1     Bachelor           1/31/11       Unemployed      F       0  ...   \n",
+       "2     Bachelor           2/19/11         Employed      F   48767  ...   \n",
+       "3     Bachelor           1/20/11       Unemployed      M       0  ...   \n",
+       "4     Bachelor            2/3/11         Employed      M   43836  ...   \n",
+       "...        ...               ...              ...    ...     ...  ...   \n",
+       "9129  Bachelor           2/10/11         Employed      M   71941  ...   \n",
+       "9130   College           2/12/11         Employed      F   21604  ...   \n",
+       "9131  Bachelor            2/6/11       Unemployed      M       0  ...   \n",
+       "9132   College            2/3/11         Employed      M   21941  ...   \n",
+       "9133   College           2/14/11       Unemployed      M       0  ...   \n",
+       "\n",
+       "     months_since_policy_inception number_of_open_complaints  \\\n",
+       "0                                5                         0   \n",
+       "1                               42                         0   \n",
+       "2                               38                         0   \n",
+       "3                               65                         0   \n",
+       "4                               44                         0   \n",
+       "...                            ...                       ...   \n",
+       "9129                            89                         0   \n",
+       "9130                            28                         0   \n",
+       "9131                            37                         3   \n",
+       "9132                             3                         0   \n",
+       "9133                            90                         0   \n",
+       "\n",
+       "      number_of_policies     policy_type        policy  renew_offer_type  \\\n",
+       "0                      1  Corporate Auto  Corporate L3            Offer1   \n",
+       "1                      8   Personal Auto   Personal L3            Offer3   \n",
+       "2                      2   Personal Auto   Personal L3            Offer1   \n",
+       "3                      7  Corporate Auto  Corporate L2            Offer1   \n",
+       "4                      1   Personal Auto   Personal L1            Offer1   \n",
+       "...                  ...             ...           ...               ...   \n",
+       "9129                   2   Personal Auto   Personal L1            Offer2   \n",
+       "9130                   1  Corporate Auto  Corporate L3            Offer1   \n",
+       "9131                   2  Corporate Auto  Corporate L2            Offer1   \n",
+       "9132                   3   Personal Auto   Personal L2            Offer3   \n",
+       "9133                   1  Corporate Auto  Corporate L3            Offer4   \n",
+       "\n",
+       "      sales_channel total_claim_amount  vehicle_class vehicle_size  \n",
+       "0             Agent         384.811147   Two-Door Car      Medsize  \n",
+       "1             Agent        1131.464935  Four-Door Car      Medsize  \n",
+       "2             Agent         566.472247   Two-Door Car      Medsize  \n",
+       "3       Call Center         529.881344            SUV      Medsize  \n",
+       "4             Agent         138.130879  Four-Door Car      Medsize  \n",
+       "...             ...                ...            ...          ...  \n",
+       "9129            Web         198.234764  Four-Door Car      Medsize  \n",
+       "9130         Branch         379.200000  Four-Door Car      Medsize  \n",
+       "9131         Branch         790.784983  Four-Door Car      Medsize  \n",
+       "9132         Branch         691.200000  Four-Door Car        Large  \n",
+       "9133    Call Center         369.600000   Two-Door Car      Medsize  \n",
+       "\n",
+       "[9134 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cols = []\n",
+    "\n",
+    "for i in range(len(df.columns)):\n",
+    "    cols.append(df.columns[i].lower().replace(' ','_'))\n",
+    "    \n",
+    "df.columns = cols\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a6cf1193",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                          object\n",
+       "state                             object\n",
+       "customer_lifetime_value          float64\n",
+       "response                          object\n",
+       "coverage                          object\n",
+       "education                         object\n",
+       "effective_to_date                 object\n",
+       "employmentstatus                  object\n",
+       "gender                            object\n",
+       "income                             int64\n",
+       "location_code                     object\n",
+       "marital_status                    object\n",
+       "monthly_premium_auto               int64\n",
+       "months_since_last_claim            int64\n",
+       "months_since_policy_inception      int64\n",
+       "number_of_open_complaints          int64\n",
+       "number_of_policies                 int64\n",
+       "policy_type                       object\n",
+       "policy                            object\n",
+       "renew_offer_type                  object\n",
+       "sales_channel                     object\n",
+       "total_claim_amount               float64\n",
+       "vehicle_class                     object\n",
+       "vehicle_size                      object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bdcf00f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                         0\n",
+       "state                            0\n",
+       "customer_lifetime_value          0\n",
+       "response                         0\n",
+       "coverage                         0\n",
+       "education                        0\n",
+       "effective_to_date                0\n",
+       "employmentstatus                 0\n",
+       "gender                           0\n",
+       "income                           0\n",
+       "location_code                    0\n",
+       "marital_status                   0\n",
+       "monthly_premium_auto             0\n",
+       "months_since_last_claim          0\n",
+       "months_since_policy_inception    0\n",
+       "number_of_open_complaints        0\n",
+       "number_of_policies               0\n",
+       "policy_type                      0\n",
+       "policy                           0\n",
+       "renew_offer_type                 0\n",
+       "sales_channel                    0\n",
+       "total_claim_amount               0\n",
+       "vehicle_class                    0\n",
+       "vehicle_size                     0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ae87fdaa",
+   "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>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>months_since_last_claim</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "      <td>9134.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>8004.940475</td>\n",
+       "      <td>37657.380009</td>\n",
+       "      <td>93.219291</td>\n",
+       "      <td>15.097000</td>\n",
+       "      <td>48.064594</td>\n",
+       "      <td>0.384388</td>\n",
+       "      <td>2.966170</td>\n",
+       "      <td>434.088794</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>6870.967608</td>\n",
+       "      <td>30379.904734</td>\n",
+       "      <td>34.407967</td>\n",
+       "      <td>10.073257</td>\n",
+       "      <td>27.905991</td>\n",
+       "      <td>0.910384</td>\n",
+       "      <td>2.390182</td>\n",
+       "      <td>290.500092</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1898.007675</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>61.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.099007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>3994.251794</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>68.000000</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>272.258244</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>5780.182197</td>\n",
+       "      <td>33889.500000</td>\n",
+       "      <td>83.000000</td>\n",
+       "      <td>14.000000</td>\n",
+       "      <td>48.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>383.945434</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>8962.167041</td>\n",
+       "      <td>62320.000000</td>\n",
+       "      <td>109.000000</td>\n",
+       "      <td>23.000000</td>\n",
+       "      <td>71.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>547.514839</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>83325.381190</td>\n",
+       "      <td>99981.000000</td>\n",
+       "      <td>298.000000</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>99.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>2893.239678</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       customer_lifetime_value        income  monthly_premium_auto  \\\n",
+       "count              9134.000000   9134.000000           9134.000000   \n",
+       "mean               8004.940475  37657.380009             93.219291   \n",
+       "std                6870.967608  30379.904734             34.407967   \n",
+       "min                1898.007675      0.000000             61.000000   \n",
+       "25%                3994.251794      0.000000             68.000000   \n",
+       "50%                5780.182197  33889.500000             83.000000   \n",
+       "75%                8962.167041  62320.000000            109.000000   \n",
+       "max               83325.381190  99981.000000            298.000000   \n",
+       "\n",
+       "       months_since_last_claim  months_since_policy_inception  \\\n",
+       "count              9134.000000                    9134.000000   \n",
+       "mean                 15.097000                      48.064594   \n",
+       "std                  10.073257                      27.905991   \n",
+       "min                   0.000000                       0.000000   \n",
+       "25%                   6.000000                      24.000000   \n",
+       "50%                  14.000000                      48.000000   \n",
+       "75%                  23.000000                      71.000000   \n",
+       "max                  35.000000                      99.000000   \n",
+       "\n",
+       "       number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "count                9134.000000         9134.000000         9134.000000  \n",
+       "mean                    0.384388            2.966170          434.088794  \n",
+       "std                     0.910384            2.390182          290.500092  \n",
+       "min                     0.000000            1.000000            0.099007  \n",
+       "25%                     0.000000            1.000000          272.258244  \n",
+       "50%                     0.000000            2.000000          383.945434  \n",
+       "75%                     0.000000            4.000000          547.514839  \n",
+       "max                     5.000000            9.000000         2893.239678  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "19370c03",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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9p08B6Nlnn7V1HURERET9pk99gACgqqoK//znP/HMM8+goqICQNutr4KCApsVR0RERGQPfWoBOnHiBGbPng2DwYDz58/jvvvug7+/P7Zv346cnBxs3rzZ1nUSERER2UyfWoAee+wxrFy5EhkZGdDr9dbt8+fPx969e21WHBEREZE99CkA/fjjj7j//vu7bA8PD0dxcfFVF0VERERkT30KQHq9HjU1NV22nzlzBgMGDLjqosh2LBaBkwXV+CGzDLnl9XKXQ0RE5BD61Ado0aJFeOGFF/Dhhx8CACRJQm5uLp5++mn8/Oc/t2mB1Hc/nq/Aw1tSYKw1AQDUKgl3TIxCbKiPzJURERHJq08tQC+//DJKS0sRFBSExsZGTJ8+HUOHDoW3tzdeeuklW9dIfVBnasWjW4/BWGuCp5saQd46mC0CWw7nIq2wa+sdERGRkvQpAPn4+OCHH37Atm3bsH79eqxatQpffvkl9uzZA09Pzx4fZ926dZgwYQK8vb0RFBSExYsX48yZM30piS7yx6/TUVDViEh/dxz5zWysvi4G8eEGmIXA+z/morK+We4SiYiIZNPrW2AWiwXvvPMOtm3bhvPnz0OSJERHRyMkJARCCEiS1ONj7dmzBw8//DAmTJiA1tZW/OY3v8GcOXOQlpbWqyBFnR3JrsDmgzkAgPVLEuCp00CtknDL+EjUNrXifHk9fsgqw8KEMJkrJSIikkevWoCEELjppptw7733oqCgAPHx8Rg1ahRycnKwcuVK3Hzzzb06+ddff42VK1di1KhRGD16NDZt2oTc3FwkJyf36jjU2bqvTgMAbh0fiWuHBlq3q1USZg5v66SedL4CDaZWWeojIiKSW69agN555x3s3bsX33//PWbOnNnpuZ07d2Lx4sXYvHkz7rrrrj4VU11dDQDw9/fv0+sJyCqtw9HcKqhVEp6YO7zL80ODvBBq0KOougmHsitwXWyQDFUSERHJq1ctQO+//z5+/etfdwk/AHDdddfh6aefxpYtW/pUiBACjz32GKZOnYq4uLhu9zGZTKipqen0oM62p7QtRTJ92AAM8NZ1eV6SJEyLaWsFOniuHC1mS7/WR0RE5Ah6FYBOnDiBefPmXfL5+fPn4/jx430qZNWqVThx4gTef//9S+6zbt06GAwG6yMyMrJP53JVFovA9qNtAWjJ2PBL7hcfboCvuxb1plakFlT3V3lEREQOo1cBqKKiAsHBwZd8Pjg4GJWVlb0uYvXq1fjss8+wa9cuREREXHK/Z555BtXV1dZHXl5er8/lyg5nV6CgqhHeeg1mj7j0n5NaJWHsQD8A4JB4IiJSpF71ATKbzdBoLv0StVqN1taed6wVQmD16tXYvn07du/ejejo6Mvur9PpoNN1va1Dbbal5AMAbkwIhV6rvuy+I0N9sDPdiAxjLVrMFmjVfZoRgYiIyCn1KgAJIbBy5cpLhhCTydSrkz/88MN477338J///Afe3t7WdcQMBgPc3d17dSylM7Wa8dXJtuu3ZOylW9E6hBr08HXXoqqxBZnGOozg7NBERKQgvQpAK1asuOI+vRkBtmHDBgDAjBkzOm3ftGkTVq5c2ZvSFC8lpwp1plYEeukwvv321uVIkoTYUB8cOleO00U1DEBERKQovQpAmzZtsunJhRA2PZ6SHcgqAwBcOzSgx5NRjuwIQMW1sAgBVS8msSQiInJm7PjhIn7I7AhAgVfY8yeDAj2g06hQb2pFXkWDvUojIiJyOAxALqCmqQXH86oA9C4AaVQqDA/xBgCcLuJoMCIiUg4GIBdw+FwFLAKIDvREuG/vOo/HtgegrNJ6e5RGRETkkBiAXMD+zJ/6//TWoIC2RWcLqxphajHbtC4iIiJHxQDkAjoC0NRe3P7q4OvhBj8PLQSAHPYDIiIihWAAcnIlNU3IMNZBkoApg3sfgIC2W2cAcL6Mt8GIiEgZGICc3OHsCgBAXJgBBg9tn47RcRssmwGIiIgUggHIyR3LrQIAjOvB5IeX0tEClF/ZyNXhiYhIERiAnNyxvLbFZ0dHGvp8DH9PN3jrNTALwfmAiIhIERiAnFhzqwUn21dzHxPZ9xYgSZJ+ug1WzttgRETk+hiAnFh6cQ2aWy3w9dBiUIDHVR2LHaGJiEhJGICc2LH22Z9HR/j2eP2vS+loAcqtaIDZwjXaiIjItTEAObGODtBjIn2v+lhBPjq4aVRoMQuU1pqu+nhERESOjAHIiXW0AI2J8r3qY6kkybqMRn4lO0ITEZFrYwByUtUNLTjX3l9nTISvTY4Z4dcRgBptcjwiIiJHxQDkpI7lVwEABgZ4wM/TzSbHjPBr60idX8UWICIicm0MQE7qeMftLxv0/+nQ0QJUXN3ECRGJiMilMQA5qZMF1QCA+PC+T4B4MV93LTx1GlgEUFTdZLPjEhERORoGICeVVtQ2AeKoMNsFIEmSEMGO0EREpAAMQE6ourHF2lF5ZKiPTY8d4c+O0ERE5PoYgJzQ6fbWn3Bf9z6vAH8pEb7tHaHZAkRERC6MAcgJpbWv/zUyzLatP8BPHaHL6prR2Gy2+fGJiIgcAQOQE+ro/2Pr218A4KnTwK+9VamwmrfBiIjINTEAOSF7tgABQKihrRWoqIoBiIiIXBMDkJNpbrUgw1gLwD4tQAAQ5qsHwKHwRETkuhiAnEymsQ4tZgFvvcbaX8fWrC1ADEBEROSiGICczIX9fyRJsss5wtrnAjLWckZoIiJyTQxATsbe/X8AwEevgYebGhYBGGtMdjsPERGRXBiAnExaUdsSGLacAfpikiQhrP02GEeCERGRK2IAciJCCJwpbusAHRvibddzhRo6OkIzABERkethAHIipXUmVDa0QCUBQ4O87Hqu0PaRYIVV7AhNRESuhwHIiZwtrgMADAzwhF6rtuu5OkaCFVc3wSKEXc9FRETU3zRyF0A9d7ak7fbXsGD7tv4AQKCXDhqVhGazBRX1zQj00tn9nM7gvcO5Nj3e7ZOibHo8IiLqGbYAOZGOADQ82L79fwBArZIQYui4DcZ+QERE5FoYgJzImfYAFNMPAQjghIhEROS6GICchBACGSVtfYCG23kEWIeflsRgCxAREbkWBiAnUVjdhDpTK7RqCYMCPPvlnD8tisoWICIici0MQE7ibPv8P9GBnnDT9M8fW4iPHhKAWlMrapta+uWcRERE/YEByEn8NAKsf25/AYCbRmUd/cV+QERE5EoYgJzEGRkCEPDThIhFHAlGREQuhAHIScjRAgTggjXB2AJERESugwHICZgtApnG/h0B1oFrghERkStiAHICeRUNaGqxQKdRIcrfo1/PHerb1gJUXtcMU6u5X89NRERkLwxATqCj/8/QIC+oVVK/nttLp4GPXgOBtnXBiIiIXAEDkBPI6MclMLoTyn5ARETkYhiAnMCZ9hmg+2sJjItxJBgREbkaBiAnYG0BCrH/KvDd4ZpgRETkahiAHFyL2YKs0vYWoCB5WoDC2keCFdc0wWwRstRARERkSwxADu58WT1azAKebmqEt4/I6m/+nm7Qa1UwWwSMtWwFIiIi56eRuwC6vLMX9P9R9fMIsA6SJCHU4I7ssnoUVjVZb4kpnRACuRUNOFtSi+yyBlQ2NMMiBFSShGAfHSL8PBAb4o1wX3dIkjx/dkRE1D0GIAf30xIY8vT/6RBm0LcFoOpGjIOfrLXITQiBDGMddqUbkVPR0O0+1Y0tOFtSh53pRoQZ9Jg8OACJUX79Po0BERF1jwHIwXWsAt/fS2BcrGNCxEKFjwRrajHj02MFOJFfDQDQqCSMCvPB4EAvhBj0UKsktJgtKKxuwvmyepwuqkFhdRO2HS3A/qwyLIgLlW00HxER/YQByMGdNXaMAJP3SzPM96eRYBahzI7QaYU1+MeuTFTUN0MlAVMGB2DasAHw0Wu77DswwBNTBgegobkVSecrsedsKUpqTNh04DwSI32xcHQY9Fq1DO+CiIgABiCH1tRixvmyegDytwAN8NJBo5LQ3GpBRX2zrLXI4WhuJe76vyOobWqFr4cWt46PxMAAzyu+zsNNg58NG4AJg/yxM70EB7LKcTSvCtll9bh1QmQ/VE5ERN3hKDAHllVaB4sADO5aBHnrZK1FrZIQ0j4cXmm3wZLOV2D5223hZ2CAB1bPjOlR+LmQu5saNySE4X9/Nhj+nm6oamzBW/vO4V8Hz0MotEWNiEhODEAOLKN9BNiwYC+HGEUU1rEkRpVyhsJnGmtx96YfUWdqxTVDAnD3NdFwd+v7rauBAZ5YPXMo4sMNsAjg//3nFJ7+JBUtZosNqyYioithAHJgP40Ac4xOs9YlMaqV0QJUWd+Me95JQq2pFRMH+eP/Vk6Am+bq/8rotGosmxCJ+XEhUEnAB0l5uOedH1Hb1GKDqomIqCcYgBxYxwgwuTtAd/ipBajR5W/btJgteODfycitaECkvzveWD7Opp2WJUnCtJgBeHvFBHi4qbEvowxL3ziomHBJRCQ3BiAH5mgtQCEGPVQSUN9sRnGNa98G+9v3GTicXQEvnQZvr5gAf083u5xnZmwQPrx/CgZ465BeXIvFr+1HWmGNXc5FREQ/YQByUPWmVuRXtrUGOEoA0qpVGNDeGftUget+SR/JrsBruzIBAOuWxNv9+seFG7D9oWsQE+SFkhoTbtl4EHvPltr1nERESscA5KAyjG0doAd46+zW+tAXHbfBTrloK0V1Ywt++cExWATw87ERWDg6rF/OG+HngY8fvAZTBgegztSKe975ER8m5fXLuYmIlIgByEFZ+/84SOtPh44ZoU8VVstciX2s/eI0CqoaEeXvgecXjerXcxvctXj3nolYPCYMrRaBJz8+gT/vOOvy/a2IiOTAiRAdlKP1/+kQ1j4XkDO0AL13OLdX+58rrcMH7a0u80aF4LNjhfYo67LcNCr8+dYxCPdzx2u7svDX7zNQWNWItUvioVXz3ytERLbC36gO6qyDLIJ6sY6V4AuqGlHpQjNCt5gt+PRYAQBg4iB/DArs3USHtiRJEn41NxZrb46HSgI+Ss7nMHkiIhtjAHJQZzoWQXWQIfAd3N3U1j5JaUWO3wrUU3vOlqKsrhneeg3mjgqRuxwAwO2TovDPFePhrm0bJn/LxkMornbt0XdERP2FAcgBVTU0w1hrAgDEBDlWCxAAhLbfBjtZ4Br9gCrrm62jrm5MCLuqmZ5t7brYYHxw/2QEernhdFENbn59P47nVcldFhGR02MAckBn25fACPd1h3c3K43LLdzXtUaCfXWyCK0WgcEDPBEX5iN3OV0kRPhi+0PXYsgATxRVN2HpGwfx/pHe9W8iIqLOGIAcUEcHaEeZAfpioQbXGQmWVVqHk4U1kADcGB/mEGuudSfS3wPbH74Wc0YGo9lswTPbUvHUxyfQ1GKWuzQiIqfEAOSAOobAO9oIsA5h7WuCnSurR0Nzq8zV9J1FCHxxoggAMDHa37ravaPy0Wvxxp3j8OS84dY1xJa+cRB5FQ1yl0ZE5HQYgBzQTy1Ajtf/BwC89VoM8NZBCDj1sg0n8qtRXNMEvVaF2SOC5S6nR1QqCQ/NGIrN90yCv6cbUguqMe8ve/He4VzOF0RE1AsMQA5GCGEdAh8T5JgtQAAwOsIAADjmpB1yzRaB706XAACmxQyAp865psSaGhOIz1dPxYRBfqhvNuPX21OxYtOPXEyViKiHZA1Ae/fuxcKFCxEW1tb34tNPP5WzHIdQWmtCVUMLVBIw1AFHgHUYE+kLwHkDUEpOJSrqm+HppsY1QwLkLqdPwn3dsfV/p+C3N4yATqPC3rOlmPPnvfg4OZ+tQUREVyBrAKqvr8fo0aPxj3/8Q84yHErHCLBBAZ7Qax1nOPbFEqP8ADhnAGoxW7DzjBEAMGN4EHQax73OV6JWSbh32mB88cg0jI70RW1TK5746DiWvnHQZaYpICKyB1nb/efPn4/58+fLWYLDcdQlMC6WEGGAJAH5lY0orTVZV4l3BkeyK1Dd2AKDuxYTo/3lLscmhgZ54ZMHpuCtfdn42/cZSMqpxMJ//IBbx0fiibnDEejlPH8+RET9wak6PphMJphMJuvPNTXO2wH3Us466AzQF/PWazF0gBcyjHU4lleF60c6RydiU6sZu9tbf64bHiT7+lq9Xa/sSgzuWux8YjrWf5WO/xwrxNYf8/DFiSI8MGMIVl4zyOn6OhER2YtT/TZct24dnn/+ebnLsCvrCDAHbwEC2voBtQWgSqcJQAeyylHfbEaApxvGDvSTuxy72JVeiknRAQjx0eO/J4pQUNWIP31zBq/tysT0YQMwKToAbpqeB7/bJ0XZsVoiInk41SiwZ555BtXV1dZHXl6e3CXZlMUikOGgi6B2x9n6ATU2m7Evo23Ji1kjgqFWOeakh7YyMMATD84YgqXjIhDg6YaGZjO+OlmMl789gx8yy9DcapG7RCIi2ThVC5BOp4NO57p9GQqqGlHfbIZWLcm6GnlPdYwEO55XDbNFOHyg2JtRiqYWC0J89EhoH8bv6lSShMQoPyRE+OJYXiV2phtR2dCCL1OLsCvdiMmD/TF5cIBDLrlCRGRPThWAXF2Gsa31Z8gAL9n7pvTEsGAvuGvVqDO1Iqu0zqE7btc2teBAVhkAYPaIYKgcdMkLe1GrJIwb6I/Rkb44mlOFPRmlqKhvxq4zpdiXUYbEKD9MGxqIQCfqzE5EdDVkDUB1dXXIzMy0/pydnY1jx47B398fUVHK63dwprhtCLwjB4kLadQqxEcYcCS7Asdyqxy67t1nS9FiFojwc8eIUMet0940KhUmRPtj3CA/nCqswb6MUuRXNuLH8xVIOl+BEaE+mBYTiCh/D4ddF42IyBZkDUBJSUmYOXOm9efHHnsMALBixQq88847MlUln7MOvghqd8ZG+eFIdgWScipwy4RIucvpVlVDM45kVwAA5owM4Rc72m6NxYcbEBfmg/PlDdiXUYr04lqkFdUgragGYb56TBkcgIQIX7lLJSKyC1kD0IwZMzhj7QXOOPgiqN2ZGO2HN/bAGjAc0c50I8wWgcGBnhgywPH7VvUnSZIQHeiJ6EBPlNQ0YX9mGY7lVaGwqgmfpBTgy9RiFFY34s5JAxHp7yF3uURENuP4HU0UosVsQaax7RaYMwyB7zB+kD8kCThf3oCSmia5y+mirNaElNxKAMCckcFs/bmMYB89loyNwNPzYjFvVAh8PbRobDFj455zmP6nXbhvcxL2nC2F2cJ/tBCR82MnaAeRVVqHZrMF3joNIvzc5S6nx3z0WowM9cGpwhoczq7ATaPD5C6pk+/SS2ARQGyIN6IC2PrTEx46DX42bACmxgQivagW58vr8UNmGXaklWBHWgnCDHr8Ynwklo6LYKsQETktBiAHcbqobVbrEaE+UDn4cPKLTYoOaAtA58odKgAVVTfiRH7belizRzjHRI2ORCVJGBnmgxdvjkOmsRb/PpSLbSn5KKxuwt++z8Dfd2bg2iGBuGl0GOaOCoHBw3mH0ptazWhsNqO+2YzG5lY0NlvwzaliaNQStGoVtGoV3NSqXk0geTFOKEnkWBiAHERaYUcAcp7bXx0mDfbH/+3Pdrh+QDvSSgAA8eEGhPk6T6uaIxoa5I3nbhqFp+fH4ptTxfgwKQ/7M8vxQ2YZfsgsw28+TcW0mAG4MSEUs0cGw8fB5hVqaG7FudJ6ZJXWIbusHoVVjSiqbkJx+6PW1Nqj47hr1TC4a+HjroHB3Q0Bnm4I9tEj2EcHg7uWt1iJnAgDkINIa28BGhnmI3MlvTdhUNuCohnGOpTXmRDgAAtvpuRWIr24FhLY+mNLeq0ai8aEY9GYcORVNODTowX474kinCmpxc50I3amG6FWSUiM9MW0mAH42bBAJET42n2SzI411RqbzTDWNsFYY2r7b60JxloTqhtbenQctUqCm1oFrVqCQFvfvFazQGt7v6fGFjMaW8wo7mYZQp1GhWAfPUINeoT7uiPM1x3BPnqHnyCUSKkYgByAEAKni9pGgI0Mdb4Ziv093TA82BtnSmpxJLsC8+ND5S4JL39zBgAwdqCfU61U70wi/T2welYMVs+KQUZJLT4/UYQvThQiq7QeSTmVSMqpxJ+/OwsfvQZx4QbEhRswKswHo8J8MCjAE5o+TvZpajWjqKoJBVWNyC6rR6axDnszSlFaY7psS46HmxoDvHQI9NbBz8MNBnettTXHW6eFm0Z1ybBiEQLNrRZUN7agurEFNY0tqGpsQWmtCSU1TSirM8HUakFuRQNyKxqsr1OrJIT4tAUioK01cliIF3QadZ/eOxHZDgOQAyipMaGivhlqlYQYJ1gDrDsTo/1xpqQWhx0gAB3ILMOBrHKoJQnXxQbJWotSxAR747HrvfHY9cOQV9GAHzLLsC+jFD9klKGmqRUHsspxIKvcur9KAgK9dAgx6BHso0eQtw5umra+NmqVBI1KQrPZgtqmVtQ2tVoDR1FVI4y1psvWYnDXIshb1/ZoP/YALx08dH3/daeSJOi1aui1agT76Ls832qxoLyuGUXVTSisamx7VDeiqcWCgqpGFFQ14sj5tlvEWrWEYcHeiAszIC6ibS6mEaE+0GsZioj6EwOQA+joAD1kgKfT/hKcNNgf/zqUg4MXfMnJQQiBP33b1vozIdoffh5ustbjCjpuL/XW1KEDcM2QQBR3hILqRhRWNaGouhEtZmG9PQVU9/rYeq0K4b7uiPL3wLBgb5TVNbcFHW+dLH+HNCpVe18gvXWNPIsQqKxvRkFV2/sWEEgtqEZVQwtOFdbgVGENPkhqW9BZrZIQE+SFUWEGxIf7IC7cgJFhPvBw469oInvh3y4HYO3/E+p8/X86XDskECoJOFNSi8KqRtk6He9IK8HR3CrotSrMHD5AlhroJypJQlh7f5gOFiEwZ2QwSmpMKK5pQnFNE0prTWg1W9BqEWg1C5gtFqhVKvi4a+Cj18Jbr4GPuxZhBneE+7nDz6Nzh+O+hjR7UkkSArx0CPDSISGibRSYEAIFVY04WVCNkwU1OFlYjZMF1Sira0Z6cS3Si2vxSUrb6yWpbV3A2BBvDAvueHhhYIAn+xUR2QADkAP4aQSY8wYgP083JEb5ITmnErvPlMoy5LfVbMEfvk4HANxzbTRXOHdQKknCd6eN1p/VUls/mctpMQuU1zWjvK4ZqQW9bzFyFJIkIcLPAxF+HpgX13arWAiBkhoTUgvawtCpwmqkFlSjpMaETGNd+wSpRdZjuGlUGDLAC8OCvTAs2BsxQW3/jfT3YDAi6gUGIAdw2olHgF1oxrABSM6pxK4zRlkC0AdJecgqrYe/pxsemDEE/z1edOUXEclMkiSEGPQIMehx/cifRiwaa5twqrAGZ4trcbakDmdLapFhrEVTiwWni2qsvzc6aNUSgn30iPTzQKS/B6L8Pbq0lF0J5yoiJWEAkllDcyuyy+sBOHcLEADMjA3CKzvOYn9mGUyt5n4d6VJvasWfd2QAAB65bqjDzUND1FtB3noEDddj5vCfOvJbLAL5lY04W1KLMyW12JFWgpL2W4gt5rbn8isbcfBcW188T50GgwM9MTTIC0ODvNgnjugCDEAySyusgRBAkLcOgQ4wf87VGBnqgwHeOpTWmvBjdiWmxgT227nf2ncOZXUmDAzwwO2TBvbbeYl6ytb9lPw83HDL+EgAbf2qKuqaUVDdiLyKBuRVNKCwqgn1plakFlRbbxsGeLohJtjbOhUBb5mRkjEAyaxjqYaECF95C7EBlUrCjGED8FFyPnadMfZbADLWNuHNvecAAE/Ojb2q5QqInJFKkhDo3TbH0ej23yUtZgsKKhuRWdrWjyi/sgHl9c0oP1eOQ+fK4eGmxohQH8SF+WBIkBc0Kv69IWVhAJJZx7/MEiKcbwLE7syMDcJHyfnYfcaI/3fjyH4551++y0BDsxljIn2xID6kX85J5Oi0ahUGBXpiUKAnZo8IRlOLGedK63C6uBani2rQ0GxGck4lknMq4eGmRkJE20SVCREGLulBisAAJLMT+VUAgHgXCUBTYwKhUUnIKq1HRkktYoLtu7ZZprEWH/zYNpfKrxeM4C9uokvQa9UYGWbAyDADzBaB8+X1OFVYjVMFNag1teLQuQosem0/hgZ5YcnYcNycGI5QA9fQI9fFNk8Z1Ta14FxZWwfohHDXCEA+ei1mtM+/8+mxArufb/1X6TBbBK4fGYyJ0f52Px+RK1CrJAwZ4IWbRofjqfmxWHnNIIyOMECvVSHTWIc/fn0G16zfiTv/eRifHi1AU4tZ7pKJbI4BSEYnC9o6QIf7ujvEAqK2smhMOADgP8cKYWlfRNIedqaX4LvTRmhUEp6aF2u38xC5MpXUtjTHrROi8ONvZuOPP0/AxGh/CAH8kFmGRz84hgkvfodfb0/F0dxKCGG/v9NE/Ym3wGSUWlAFwHX6/3SYPSIYXjoN8isbkZxbaV0t3paaWsx47rM0AMA9U6MxNMg511AjciTeei1umRCJWyZEIq+iAR8n5+Pj5HwUVDXivcO5eO9wLmKCvLB0fARuTozgQsPk1NgCJKOOEWCu0v+ng7ubGnNHtXVG/vSofW6DbdxzDrkVDQj20eGRWTF2OQeRkkX6e+CX1w/Dvidn4r17J2HxmDDoNCpkGOuw9st0TF73Pe59NwnfnCpGc6tF7nKJeo0tQDKyjgAL95W3EDu4OTEcn6Tk44vUIjy7cJRNh6Znl9Xj9d2ZAID/d+NIeF3FKt9EdHkqlYRrhgbimqGBeKGpBZ8fL8RHSfk4lleF706X4LvTJTC4azFvVAhuGhOGyYMDOL8QOQV+c8ikqqEZOeUNAIB4F+kAfaEpQwIQ5K2DsdaEHWkluCEh1CbHNVsEfvXRcZhaLZgWE4gb4m1zXCK6Mh+9FndMGog7Jg1ERkktPkrOx/ajBSitNeGDpDx8kJSHQC8d5seF4PqRwZg02L9fZ4Qn6g0GIJl0tP4MCvCAwcP1lm1QqyQsmxCJv+3MxMa9WVgQH2KTIervHjiPpJxKeLqpsW5JPIe9E9lQb2erHhTgiTWzYpBdVo8T+R0r25vwr0M5+NehHOg0KswaEYTZI4IxLWYA+wyRQ2EAksmx3CoAQLwLzAB9KSuuGYQ3953DifxqHMgqx7VDr25m6Oyyevzxm7bV3n99wwhE+HnYokwiugoqqW1Ifduw+jBkGuuQVlSD9OIa1Da14svUYnyZWgwAiA3xxjVDAnHt0ABMjPaHN9fsIxkxAMkkKacSADAuylfeQuwowEuHZROi8M6B89iwO+uqAlBTixkPb0lBU4sF1wwJwO0TuWo1kaNRqyQMD/HG8BBvWEQYCqsaoVZJ+P60sT0U1SK9uBb/tz8bKgmIDfHBuIF+1keEnztbdanfMADJwGIRSMltC0Dj7TBE3JHcOy0a/zqUgx8yy5CaX93nEW8v/DcNaUU1CPB0w6u3jOEvSSIHp5IkRPh54PZJUXh8znCU15lw8Fw59meWY39mGXIrGpBWVIO0ohr861AOAGCAtw7jotrCUGKUL+LCDdBr2YeI7IMBSAZnjbWobWqFh5sasSH2XSpCbhF+Hlg0Ogzbjhbg91+kYet9k6G6xAiRS/U/SMmtxMfJ+ZAA3DQ6DDvTjXasmIjsIcBLhxsTwnBjQhgAoLi6CSm5ldb1yE4VVqO01oSvTxXj61Ntt8y0agkjQ32QGNUWiMZGsZWIbIcBSAbJ7be/xkT6QqN2/amYfnn9MHx9qhhHsivw7sHzuPva6B6/9mxJLbal5AMAZgwPsvvaYkRkW1fqWN3Rf6jFHI6CykbkVDQgr6IBuRUNqDO14nh+NY7nV+OdA237B3rpMDbKF4lRfhgb5Yv4CAM83PhVRr3HT40Mks+33/4a6CdzJf0j0t8Dz8yPxf/7zyn84et0zBwehEGBnld8XW5FA7YczoFFtM2WPWtEUD9US0RyuHD1egAQQqCqoQW5FQ3IrWwLRYVVjSirM+HbtBJ8m1bS/joJ4wb6YVrMAEwfNgAjQ30u2cpMdCEGIBlYO0C7eP+fC90xaSC+TC3GwXPleGhLCjb/z0QEXmb9s7TCanyYnI8Ws0BMkBd+MS4CKjZ7EymGJEnw83SDn6cbRkf6AgBazBYUVjW2haL2lqKapraV7A+dq8CfvjkDTzc1YkN9kBBhwOBArx5Nynj7JA6qUCIGoH5mrG1CbkUDJAlIdOERYBdTqST88RcJWPTafqQV1WDpGwex+Z6JiPTvPJS9xWzBnrOl1n4+gwd44vZJUdCoXP9WIRFdnlatwsAATwwM+KkFubzOhLPGOmSW1CKrrB71zWZrvyJPNzXiwg0YHeGLgQEe7DtEnTAA9bOO21/Dg73ho7A5MCL9PfDxA1Ow/O0jyC6rx4K/7sNNY8Iwd1QITK0W7DpjxMGsctSZWgEAkwcH4Ib4UE6rT0SXFOClwxQvHaYMDkCrxYKc8gakFrRNyljfbMbh7Aoczq5AkLcOk6L9MTbKD7qLRpb1dgLIK2GLknNgAOpnHbe/xg9SRv+fiw0e4IVtD12D/3n3R5wsqMGWw7nYctEvH18PLa4fEYzEKGVeIyLqG41KZe1UvTAhDFmldTiRX4WTBTUw1prw+Yki7DhdgimDAzBlSCDXEVQ4/un3s8PZ5QCA8QOV0//nYsE+enz28FQcyCrHR8l5OJZXBV93LUytFowKM2BMpC9bfYjoqqhVEoYFe2NYsDduTDDjaF4VDmaVoayuGbvOlGJ/VjmmDg3E1KGBnGtIoRiA+lFFfTNOFdYAAK4ZGiBzNfJSqSRMjQnE1JifZoe2dTM0EREA6LVqTBkcgEnR/kgrrMHus0YUVjVhZ7oRh86VY96oEIwd6MeBFgrDANSPDmaVQwhgWLAXgrz1cpdDRKQoKklCXLgBo8J8cLKwBjvSSlBWZ8K2owU4cr4CNyeGI9TgLneZ1E84tKYf7c8qA4CrXhSUiIj6TpIkxIcbsGZWDBbEhUCnUSG/shGv78rC9+klMFuE3CVSP2AA6kf7M9sC0FQGICIi2alVEqbGDMAvZw/DiFAfmIXA96eN2Lg3CxX1zXKXR3bGANRP8ioakFPeALVKwqTByu7/Q0TkSHzctbhzUhRuHR8Jd60a+ZWN+PvODKQWVMtdGtkRA1A/6Wj9GRPpy6GXREQORpIkjI70xerrhmKgvwdMrRa8fyQXX58sgkXwlpgrYgDqJ/uz2oa/s/8PEZHj8vVww73TBuNn7SNU92aU4d0D59HUYpa5MrI1BqB+YLYI9v8hInISapWEeXGhWDYhElq1hAxjHd7adw41TS1yl0Y2xADUD47mVqKivhneeo2i1v8iInJmCRG++N+fDYGXToOi6ia8sScLpbUmucsiG2EA6gffppUAAGbFBkGr5iUnInIW4b7ueGD6EAR4uqGqoQVv7MlCbnm93GWRDfDb2M6EEPjmVDEAYM6oEJmrISKi3vL3dMP904cgws8djS1mvL0/G+nFNXKXRVeJAcjOMox1yClvgJtGhenDBshdDhER9YGXToN7pw7G8GBvtJgFthzKRVohQ5AzYwCys2/bW3+mDQ2EJ4e/ExE5LTeNCndOHoiECAPMQuC9Izk4ybmCnBYDkJ119P+ZMypY5kqIiOhqqVUSlo6LxOgIAywC2PpjLidMdFIMQHZUUNWIE/nVkCRg1ggGICIiV6BWSVg6PhKJkb6wCOCDH3NxIr9K7rKolxiA7OjTowUAgImD/BHopZO5GiIishWVJOHn4yIwNsqvPQTl4ThDkFNhALITIQQ+Ts4HAPxiXITM1RARka2pJAlLxoZj3EA/CAAf/pjHliAnwgBkJ8k5lcguq4eHmxoL4kPlLoeIiOxAJUm4OTEc46LaQ1BSHr44USR3WdQDDEB28lFSW+vPgvhQjv4iInJhKknCzWPDrbfDHtl6FF+mMgQ5On4z20FDcyu+aP/wL+XtLyIil9dxO0wIgaN5VVj9/lFIAObzDoDDYguQHXyVWow6Uyui/D0wMdpf7nKIiKgfdHSMXpIYDrNFYPX7R/H1yWK5y6JLYACyMSEE3tp3DgBw64RISJIkc0VERNRfVJKEPy0djcVjwtBqEVj1Xop1QlxyLAxANrb7bCnSi2vh4abGHZOi5C6HiIj6mVol4ZVbxmBRewh6+L0U7GifFJccBwOQjb2xOwsAcPvEKPh6uMlcDRERyUGtkvDK0tFYODoMLWaBh7Yk4zuGIIfCAGRDR3MrcTi7Alq1hP+ZFi13OUREJCONWoU/3zIaNyaEosUs8OCWZI4OcyAMQDb0952ZAIBFY8IRanCXuRoiIpKbRq3CX24dYw1BD7+XgncPnJe7LAIDkM3sPmPEznQjNCoJD84YInc5RETkIDRqFf66LBF3To6CEMCzn53Cn75JhxBC7tIUjQHIBppbLXjh8zQAwMprBmHIAC+ZKyIiIkeiVkn4/aI4PH79MADAa7uy8OTHJ9BitshcmXIxANnAOweyca6sHoFeOjwyO0bucoiIyAFJkoTVs2Kwfkk8VBLwUXI+/ufdJFQ3tMhdmiIxAF2lrNI6/OW7DADAU/OGw0evlbkiIiJyZMsmRuHN5eOh16qw92wpFr32A86W1MpdluIwAF2FxmYzHt6SgoZmMyYP9sfPx3LZCyIiurLZI4Px8QPXINzXHefLG7D4tf34KCmP/YL6EdcCuwrPfXYK6cW1CPRyw9+WJUKlUs6sz+8dzpW7BCIipxYXbsDnq6di9fsp2J9Zjl99fAJ7M8rw4qI4GDx4N8He2ALUR6/tysQHSXmQJOCvyxIR5KOXuyQiInIy/p5u2HzPJPxq7nCoVRI+P16I2X/eg684X5DdMQD1weu7M/Gnb84AAJ6ZH4trhwbKXBERETkrtUrCwzOH4qMHpmDIAE+U1prw4JYU3L3pCDKN7BtkLwxAvdBituClL9Lwx6/bws+v5g7H//6Mc/4QEdHVGxvlhy8emYbV1w2FRiVh15lSzP3LPjyzLRV5FQ1yl+dyGIB6KL+yAbduPIi39mUDAB6/fhgenjlU5qqIiMiV6LVqPD5nOL795c9w/chgmC0C7x/JxcyXd+OxD4/heF6V3CW6DNkD0Ouvv47o6Gjo9XqMGzcO+/btk7ukTmqaWvDHr9Mx65U9SMmtgrdegzfuHIvVszjfDxER2cfgAV54667x+PD+KZgWE4hWi8C2lAIsem0/bvz7Pvxz3zkUVTfKXaZTk4SMY+4++OADLF++HK+//jquvfZabNy4Ef/85z+RlpaGqKioK76+pqYGBoMB1dXV8PHxsWltJwuqsfXHXPznaCFqTa0AgInR/nj5F6MRFeBh03P1B47aIiLqH7dPuvL3V28dy6vCuwfO44vUIjS3/jR7dHy4AT8bFogpgwMRF+4DXw83m5/bHuz5/d1TsgagSZMmYezYsdiwYYN124gRI7B48WKsW7fuiq+31wV8Y08W1n+Vbv15aJAXnpoXi9kjgiBJzjnUnQGIiKh/2CMAdaiob8bnxwvx3xOF+PF8ZZfnI/zcER9uQFy4AZH+Hgj3dUe4rzuCvHUONVWLIwQg2eYBam5uRnJyMp5++ulO2+fMmYMDBw7IVFWbmcOD8Oq3ZzFnVDBumxiFKYMDHOqDQ0REyuTv6YYV1wzCimsGwVjThH0ZZdibUYpjeVXIKW9AfmUj8isb8dXJ4k6v06olBHrpYHDXwsddCx+9FgZ3LfRaFXQaNXRaFdzUKujaf3bTqKCWJGhUEqICPDB5cIBM79h+ZAtAZWVlMJvNCA4O7rQ9ODgYxcXF3b7GZDLBZDJZf66urgbQliRtKdQD+P6RiTC4t01EVVfn/MMQG+qd/z0QETkDW38nXYoewPUxPrg+pq0FpbqxBemFNUgrrsaZ4joUVTWhsLoRxloTTCaBgoZ6FPThPPPjQjAycLRNa++4RnLOfC37TNAX31ISQlzyNtO6devw/PPPd9keGRlpl9qIiIh66z65C7CxNwG8ea99jl1bWwuDwWCfg1+BbAEoMDAQarW6S2uP0Wjs0irU4ZlnnsFjjz1m/dlisaCiogIBAQGQJAk1NTWIjIxEXl6ebPcUHRGvS/d4XbriNeker0v3eF264jXp3sXXRQiB2tpahIWFyVaTbAHIzc0N48aNw44dO3DzzTdbt+/YsQOLFi3q9jU6nQ46na7TNl9f3y77+fj48IPXDV6X7vG6dMVr0j1el+7xunTFa9K9C6+LXC0/HWS9BfbYY49h+fLlGD9+PKZMmYI333wTubm5eOCBB+Qsi4iIiFycrAHo1ltvRXl5OV544QUUFRUhLi4OX375JQYOHChnWUREROTiZO8E/dBDD+Ghhx6yybF0Oh2effbZLrfJlI7XpXu8Ll3xmnSP16V7vC5d8Zp0zxGvi6wTIRIRERHJQfa1wIiIiIj6GwMQERERKQ4DEBERESmOwwWg8+fP43/+538QHR0Nd3d3DBkyBM8++yyam5s77Zebm4uFCxfC09MTgYGBeOSRR7rsk5qaiunTp8Pd3R3h4eF44YUXuky7vWfPHowbNw56vR6DBw/GG2+80aWmTz75BCNHjoROp8PIkSOxfft2279xO3n99dcRHR0NvV6PcePGYd++fXKX1Cfr1q3DhAkT4O3tjaCgICxevBhnzpzptI8QAs899xzCwsLg7u6OGTNm4NSpU532MZlMWL16NQIDA+Hp6YmbbroJ+fn5nfaprKzE8uXLYTAYYDAYsHz5clRVVXXapyefPzmsW7cOkiTh0UcftW5T6nUpKCjAnXfeiYCAAHh4eGDMmDFITk62Pq/E69La2orf/va31t+vgwcPxgsvvACL5afVxV39uuzduxcLFy5EWFgYJEnCp59+2ul5R3v/Pfkes4XLXZeWlhY89dRTiI+Ph6enJ8LCwnDXXXehsLCw0zGc7roIB/PVV1+JlStXim+++UZkZWWJ//znPyIoKEg8/vjj1n1aW1tFXFycmDlzpkhJSRE7duwQYWFhYtWqVdZ9qqurRXBwsFi2bJlITU0Vn3zyifD29hYvv/yydZ9z584JDw8PsWbNGpGWlibeeustodVqxccff2zd58CBA0KtVou1a9eK06dPi7Vr1wqNRiMOHTrUPxfkKmzdulVotVrx1ltvibS0NLFmzRrh6ekpcnJy5C6t1+bOnSs2bdokTp48KY4dOyZuuOEGERUVJerq6qz7rF+/Xnh7e4tPPvlEpKamiltvvVWEhoaKmpoa6z4PPPCACA8PFzt27BApKSli5syZYvTo0aK1tdW6z7x580RcXJw4cOCAOHDggIiLixM33nij9fmefP7kcOTIETFo0CCRkJAg1qxZY92uxOtSUVEhBg4cKFauXCkOHz4ssrOzxXfffScyMzOt+yjxurz44osiICBA/Pe//xXZ2dnio48+El5eXuIvf/mLdR9Xvy5ffvml+M1vfiM++eQTAUBs37690/OO9P578j3WH9elqqpKzJ49W3zwwQciPT1dHDx4UEyaNEmMGzeu0zGc7bo4XADqzh//+EcRHR1t/fnLL78UKpVKFBQUWLe9//77QqfTierqaiGEEK+//rowGAyiqanJus+6detEWFiYsFgsQgghnnzySREbG9vpXPfff7+YPHmy9edbbrlFzJs3r9M+c+fOFcuWLbPdG7STiRMnigceeKDTttjYWPH000/LVJHtGI1GAUDs2bNHCCGExWIRISEhYv369dZ9mpqahMFgEG+88YYQou0vsVarFVu3brXuU1BQIFQqlfj666+FEEKkpaUJAJ0C7sGDBwUAkZ6eLoTo2eevv9XW1oqYmBixY8cOMX36dGsAUup1eeqpp8TUqVMv+bxSr8sNN9wg7rnnnk7blixZIu68804hhPKuy8Vf9I72/nvyPWYP3QXDix05ckQAsP6D2hmvi8PdAutOdXU1/P39rT8fPHgQcXFxndYQmTt3Lkwmk7WJ++DBg5g+fXqnOQfmzp2LwsJCnD9/3rrPnDlzOp1r7ty5SEpKQktLy2X3OXDggE3fo601NzcjOTm5S+1z5sxx+Np7orq6GgCsn4vs7GwUFxd3er86nQ7Tp0+3vt/k5GS0tLR02icsLAxxcXHWfQ4ePAiDwYBJkyZZ95k8eTIMBkOnfa70+etvDz/8MG644QbMnj2703alXpfPPvsM48ePx9KlSxEUFITExES89dZb1ueVel2mTp2K77//HmfPngUAHD9+HD/88AMWLFgAQLnXpYOjvf+efI/Jpbq6GpIkWZejcsbr4vABKCsrC3//+987LY9RXFzcZcFUPz8/uLm5WRdX7W6fjp+vtE9rayvKysouu8/Fi7g6mrKyMpjNZqes/UqEEHjssccwdepUxMXFAfjpz/Ry77e4uBhubm7w8/O77D5BQUFdzhkUFHTZz83Fn7/+tHXrViQnJ2PdunVdnlPqdTl37hw2bNiAmJgYfPPNN3jggQfwyCOPYPPmzdZaAeVdl6eeegq33XYbYmNjodVqkZiYiEcffRS33XabtVZAedelg6O9/558j8mhqakJTz/9NG6//Xbrul7OeF36LQA999xzkCTpso+kpKROryksLMS8efOwdOlS3HvvvZ2ekySpyzmEEJ22X7yPaO8gZYt9uju/I3Lm2i9l1apVOHHiBN5///0uz/Xl/V7pc9PXffpDXl4e1qxZgy1btkCv119yP6VdF4vFgrFjx2Lt2rVITEzE/fffj/vuuw8bNmzotJ/SrssHH3yAf//733jvvfeQkpKCd999Fy+//DLefffdTvsp7bpczJHef0++o/pTS0sLli1bBovFgtdff/2K+zvydem3ALRq1SqcPn36so+Of80DbeFn5syZ1kVSLxQSEtIl5VVWVqKlpcWaArvbx2g0AsAV99FoNAgICLjsPhenT0cTGBgItVrtlLVfzurVq/HZZ59h165diIiIsG4PCQkB0DX9X/h+Q0JC0NzcjMrKysvuU1JS0uW8paWll/3cXPz56y/JyckwGo0YN24cNBoNNBoN9uzZg7/97W/QaDSX/FeRq1+X0NBQjBw5stO2ESNGIDc3F4ByPy+/+tWv8PTTT2PZsmWIj4/H8uXL8ctf/tLaeqjU69LB0d5/T77H+lNLSwtuueUWZGdnY8eOHZ1Wu3fK69Lj3kL9KD8/X8TExIhly5Z16j3eoaOTVGFhoXXb1q1bu3SS8vX1FSaTybrP+vXru3SCHjFiRKdjP/DAA106Qc+fP7/TPvPmzXOaTtAPPvhgp20jRoxwyk7QFotFPPzwwyIsLEycPXu22+dDQkLEH/7wB+s2k8nUbefFDz74wLpPYWFht530Dh8+bN3n0KFD3XbSu9znr7/U1NSI1NTUTo/x48eLO++8U6Smpir2utx2221dOkE/+uijYsqUKUII5X5e/P39xeuvv95p29q1a0VMTIwQQnnXBZfoBO0o778n32P2cPF1EUKI5uZmsXjxYjFq1ChhNBq7vMYZr4vDBaCCggIxdOhQcd1114n8/HxRVFRkfXToGCY3a9YskZKSIr777jsRERHRaZhcVVWVCA4OFrfddptITU0V27ZtEz4+Pt0Og//lL38p0tLSxNtvv91lGPz+/fuFWq0W69evF6dPnxbr1693umHwb7/9tkhLSxOPPvqo8PT0FOfPn5e7tF578MEHhcFgELt37+70mWhoaLDus379emEwGMS2bdtEamqquO2227odvhoRESG+++47kZKSIq677rpuh2kmJCSIgwcPioMHD4r4+Phuh2le7vMnpwtHgQmhzOty5MgRodFoxEsvvSQyMjLEli1bhIeHh/j3v/9t3UeJ12XFihUiPDzcOgx+27ZtIjAwUDz55JPWfVz9utTW1oqjR4+Ko0ePCgDi1VdfFUePHrWOZnKk99+T77H+uC4tLS3ipptuEhEREeLYsWOdfgdfGEKc7bo4XADatGmTANDt40I5OTnihhtuEO7u7sLf31+sWrWq05A4IYQ4ceKEmDZtmtDpdCIkJEQ899xzXdLh7t27RWJionBzcxODBg0SGzZs6FLTRx99JIYPHy60Wq2IjY0Vn3zyie3fuJ289tprYuDAgcLNzU2MHTvWOmzc2VzqM7Fp0ybrPhaLRTz77LMiJCRE6HQ68bOf/UykpqZ2Ok5jY6NYtWqV8Pf3F+7u7uLGG28Uubm5nfYpLy8Xd9xxh/D29hbe3t7ijjvuEJWVlZ326cnnTy4XByClXpfPP/9cxMXFCZ1OJ2JjY8Wbb77Z6XklXpeamhqxZs0aERUVJfR6vRg8eLD4zW9+0+lLzNWvy65du7r9XbJixQohhOO9/558j9n7umRnZ1/yd/CuXbuc9rpwNXgiIiJSHIcfBk9ERERkawxAREREpDgMQERERKQ4DEBERESkOAxAREREpDgMQERERKQ4DEBERESkOAxAREREpDgMQETUZzNmzMCjjz4qdxlERL3GmaCJqM8qKiqg1Wrh7e0tdylERL3CAERERESKw1tgRNRnF94CGzRoENauXYt77rkH3t7eiIqKwptvvtlp//z8fCxbtgz+/v7w9PTE+PHjcfjwYevzGzZswJAhQ+Dm5obhw4fjX//6V6fXS5KEjRs34sYbb4SHhwdGjBiBgwcPIjMzEzNmzICnpyemTJmCrKysTq/7/PPPMW7cOOj1egwePBjPP/88Wltb7XNRiMgpMAARkc288sorGD9+PI4ePYqHHnoIDz74INLT0wEAdXV1mD59OgoLC/HZZ5/h+PHjePLJJ2GxWAAA27dvx5o1a/D444/j5MmTuP/++3H33Xdj165dnc7x+9//HnfddReOHTuG2NhY3H777bj//vvxzDPPICkpCQCwatUq6/7ffPMN7rzzTjzyyCNIS0vDxo0b8c477+Cll17qp6tCRA6pV2vHExFdYPr06WLNmjVCCCEGDhwo7rzzTutzFotFBAUFiQ0bNgghhNi4caPw9vYW5eXl3R7rmmuuEffdd1+nbUuXLhULFiyw/gxA/Pa3v7X+fPDgQQFAvP3229Zt77//vtDr9dafp02bJtauXdvpuP/6179EaGhoL98tEbkStgARkc0kJCRY/1+SJISEhMBoNAIAjh07hsTERPj7+3f72tOnT+Paa6/ttO3aa6/F6dOnL3mO4OBgAEB8fHynbU1NTaipqQEAJCcn44UXXoCXl5f1cd9996GoqAgNDQ1X8W6JyJlp5C6AiFyHVqvt9LMkSdZbXO7u7ld8vSRJnX4WQnTZduE5Op7rblvHeS0WC55//nksWbKky/n0ev0VayIi18QWICLqFwkJCTh27BgqKiq6fX7EiBH44YcfOm07cOAARowYcVXnHTt2LM6cOYOhQ4d2eahU/BVIpFRsASKifnHbbbdh7dq1WLx4MdatW4fQ0FAcPXoUYWFhmDJlCn71q1/hlltuwdixYzFr1ix8/vnn2LZtG7777rurOu/vfvc73HjjjYiMjMTSpUuhUqlw4sQJpKam4sUXX7TRuyMiZ8N//hBRv3Bzc8O3336LoKAgLFiwAPHx8Vi/fj3UajUAYPHixfjrX/+KP/3pTxg1ahQ2btyITZs2YcaMGVd13rlz5+K///0vduzYgQkTJmDy5Ml49dVXMXDgQBu8KyJyVpwIkYiIiBSHLUBERESkOAxAREREpDgMQERERKQ4DEBERESkOAxAREREpDgMQERERKQ4DEBERESkOAxAREREpDgMQERERKQ4DEBERESkOAxAREREpDgMQERERKQ4/x83TPwGzfRrPQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.distplot(df['income'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a3d5f67e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df['income'].replace(0, np.nan, inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "3ff74435",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.distplot(df['customer_lifetime_value'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ebfec677",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=df['income'], y=df['customer_lifetime_value'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7d533072",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(x=df['income'], y=df['monthly_premium_auto'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "107d80eb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.boxplot(x=df['income'], data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e22e3409",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.boxplot(x=df['income'], y = df['monthly_premium_auto'], data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "536abfed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "6925bcbe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# X-y split\n",
+    "df_train, df_test = train_test_split(df, test_size=0.2, random_state=33)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "641a702c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "customer                          object\n",
+       "state                             object\n",
+       "customer_lifetime_value          float64\n",
+       "response                          object\n",
+       "coverage                          object\n",
+       "education                         object\n",
+       "effective_to_date                 object\n",
+       "employmentstatus                  object\n",
+       "gender                            object\n",
+       "income                           float64\n",
+       "location_code                     object\n",
+       "marital_status                    object\n",
+       "monthly_premium_auto               int64\n",
+       "months_since_last_claim            int64\n",
+       "months_since_policy_inception      int64\n",
+       "number_of_open_complaints          int64\n",
+       "number_of_policies                 int64\n",
+       "policy_type                       object\n",
+       "policy                            object\n",
+       "renew_offer_type                  object\n",
+       "sales_channel                     object\n",
+       "total_claim_amount               float64\n",
+       "vehicle_class                     object\n",
+       "vehicle_size                      object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "cbf0e81c",
+   "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>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>months_since_last_claim</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5318</th>\n",
+       "      <td>11121.621790</td>\n",
+       "      <td>44299.0</td>\n",
+       "      <td>106</td>\n",
+       "      <td>25</td>\n",
+       "      <td>76</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>754.260616</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6980</th>\n",
+       "      <td>5365.932820</td>\n",
+       "      <td>62808.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>33</td>\n",
+       "      <td>37</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>211.515893</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8691</th>\n",
+       "      <td>6006.211611</td>\n",
+       "      <td>85510.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>19</td>\n",
+       "      <td>68</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>355.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5385</th>\n",
+       "      <td>8749.496793</td>\n",
+       "      <td>52373.0</td>\n",
+       "      <td>111</td>\n",
+       "      <td>2</td>\n",
+       "      <td>37</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>186.160527</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9110</th>\n",
+       "      <td>34611.378960</td>\n",
+       "      <td>20090.0</td>\n",
+       "      <td>109</td>\n",
+       "      <td>10</td>\n",
+       "      <td>59</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>523.200000</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>3958.002823</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101</td>\n",
+       "      <td>29</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>484.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>578</th>\n",
+       "      <td>7785.004214</td>\n",
+       "      <td>44897.0</td>\n",
+       "      <td>99</td>\n",
+       "      <td>22</td>\n",
+       "      <td>46</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>580.725310</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5848</th>\n",
+       "      <td>5175.289340</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>71</td>\n",
+       "      <td>0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>340.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2439</th>\n",
+       "      <td>27382.818930</td>\n",
+       "      <td>45473.0</td>\n",
+       "      <td>76</td>\n",
+       "      <td>10</td>\n",
+       "      <td>29</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>188.938397</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7188</th>\n",
+       "      <td>3230.576665</td>\n",
+       "      <td>62873.0</td>\n",
+       "      <td>81</td>\n",
+       "      <td>0</td>\n",
+       "      <td>41</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>207.751860</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7307 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      customer_lifetime_value   income  monthly_premium_auto  \\\n",
+       "5318             11121.621790  44299.0                   106   \n",
+       "6980              5365.932820  62808.0                    66   \n",
+       "8691              6006.211611  85510.0                    74   \n",
+       "5385              8749.496793  52373.0                   111   \n",
+       "9110             34611.378960  20090.0                   109   \n",
+       "...                       ...      ...                   ...   \n",
+       "57                3958.002823      NaN                   101   \n",
+       "578               7785.004214  44897.0                    99   \n",
+       "5848              5175.289340      NaN                    71   \n",
+       "2439             27382.818930  45473.0                    76   \n",
+       "7188              3230.576665  62873.0                    81   \n",
+       "\n",
+       "      months_since_last_claim  months_since_policy_inception  \\\n",
+       "5318                       25                             76   \n",
+       "6980                       33                             37   \n",
+       "8691                       19                             68   \n",
+       "5385                        2                             37   \n",
+       "9110                       10                             59   \n",
+       "...                       ...                            ...   \n",
+       "57                         29                             12   \n",
+       "578                        22                             46   \n",
+       "5848                        0                             26   \n",
+       "2439                       10                             29   \n",
+       "7188                        0                             41   \n",
+       "\n",
+       "      number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "5318                          5                   2          754.260616  \n",
+       "6980                          0                   4          211.515893  \n",
+       "8691                          0                   4          355.200000  \n",
+       "5385                          0                   9          186.160527  \n",
+       "9110                          0                   2          523.200000  \n",
+       "...                         ...                 ...                 ...  \n",
+       "57                            0                   1          484.800000  \n",
+       "578                           1                   7          580.725310  \n",
+       "5848                          0                   9          340.800000  \n",
+       "2439                          0                   2          188.938397  \n",
+       "7188                          0                   1          207.751860  \n",
+       "\n",
+       "[7307 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_data = df_train[['customer_lifetime_value', 'income','monthly_premium_auto','months_since_last_claim','months_since_policy_inception', 'number_of_open_complaints', 'number_of_policies', 'total_claim_amount' ]]\n",
+    "num_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "8d4e7d14",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\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>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>months_since_last_claim</th>\n",
+       "      <th>months_since_policy_inception</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>number_of_policies</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.113274</td>\n",
+       "      <td>0.380926</td>\n",
+       "      <td>0.190678</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.767677</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.260672</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.042589</td>\n",
+       "      <td>0.586710</td>\n",
+       "      <td>0.021186</td>\n",
+       "      <td>0.942857</td>\n",
+       "      <td>0.373737</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.375</td>\n",
+       "      <td>0.073075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.050452</td>\n",
+       "      <td>0.839111</td>\n",
+       "      <td>0.055085</td>\n",
+       "      <td>0.542857</td>\n",
+       "      <td>0.686869</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.375</td>\n",
+       "      <td>0.122739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.084142</td>\n",
+       "      <td>0.470693</td>\n",
+       "      <td>0.211864</td>\n",
+       "      <td>0.057143</td>\n",
+       "      <td>0.373737</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.064311</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.401749</td>\n",
+       "      <td>0.111770</td>\n",
+       "      <td>0.203390</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.595960</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.180807</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7302</th>\n",
+       "      <td>0.025299</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.169492</td>\n",
+       "      <td>0.828571</td>\n",
+       "      <td>0.121212</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.167535</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7303</th>\n",
+       "      <td>0.072298</td>\n",
+       "      <td>0.387574</td>\n",
+       "      <td>0.161017</td>\n",
+       "      <td>0.628571</td>\n",
+       "      <td>0.464646</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.200691</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7304</th>\n",
+       "      <td>0.040248</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.042373</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.262626</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.117762</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7305</th>\n",
+       "      <td>0.312976</td>\n",
+       "      <td>0.393978</td>\n",
+       "      <td>0.063559</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.292929</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.065271</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7306</th>\n",
+       "      <td>0.016365</td>\n",
+       "      <td>0.587432</td>\n",
+       "      <td>0.084746</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.414141</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.071774</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7307 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      customer_lifetime_value    income  monthly_premium_auto  \\\n",
+       "0                    0.113274  0.380926              0.190678   \n",
+       "1                    0.042589  0.586710              0.021186   \n",
+       "2                    0.050452  0.839111              0.055085   \n",
+       "3                    0.084142  0.470693              0.211864   \n",
+       "4                    0.401749  0.111770              0.203390   \n",
+       "...                       ...       ...                   ...   \n",
+       "7302                 0.025299       NaN              0.169492   \n",
+       "7303                 0.072298  0.387574              0.161017   \n",
+       "7304                 0.040248       NaN              0.042373   \n",
+       "7305                 0.312976  0.393978              0.063559   \n",
+       "7306                 0.016365  0.587432              0.084746   \n",
+       "\n",
+       "      months_since_last_claim  months_since_policy_inception  \\\n",
+       "0                    0.714286                       0.767677   \n",
+       "1                    0.942857                       0.373737   \n",
+       "2                    0.542857                       0.686869   \n",
+       "3                    0.057143                       0.373737   \n",
+       "4                    0.285714                       0.595960   \n",
+       "...                       ...                            ...   \n",
+       "7302                 0.828571                       0.121212   \n",
+       "7303                 0.628571                       0.464646   \n",
+       "7304                 0.000000                       0.262626   \n",
+       "7305                 0.285714                       0.292929   \n",
+       "7306                 0.000000                       0.414141   \n",
+       "\n",
+       "      number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "0                           1.0               0.125            0.260672  \n",
+       "1                           0.0               0.375            0.073075  \n",
+       "2                           0.0               0.375            0.122739  \n",
+       "3                           0.0               1.000            0.064311  \n",
+       "4                           0.0               0.125            0.180807  \n",
+       "...                         ...                 ...                 ...  \n",
+       "7302                        0.0               0.000            0.167535  \n",
+       "7303                        0.2               0.750            0.200691  \n",
+       "7304                        0.0               1.000            0.117762  \n",
+       "7305                        0.0               0.125            0.065271  \n",
+       "7306                        0.0               0.000            0.071774  \n",
+       "\n",
+       "[7307 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Normalize (numerical)\n",
+    "\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "\n",
+    "scaler = MinMaxScaler()\n",
+    "normalized_data = scaler.fit_transform(num_data)\n",
+    "normalized_data = pd.DataFrame(normalized_data, columns = num_data.columns)\n",
+    "normalized_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fecba592",
+   "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}