diff --git a/ [lab-customer-analysis-round-5]Giuliana.ipynb b/ [lab-customer-analysis-round-5]Giuliana.ipynb
new file mode 100644
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+++ b/ [lab-customer-analysis-round-5]Giuliana.ipynb	
@@ -0,0 +1,931 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a43b4e39",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\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"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e2c0597e",
+   "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>unnamed:_0</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>...</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",
+       "      <th>vehicle_type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>DK49336</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>4809.216960</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-02-18</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Agent</td>\n",
+       "      <td>292.800000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>KX64629</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2228.525238</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-01-18</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>744.924331</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>LZ68649</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>14947.917300</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-02-10</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Call Center</td>\n",
+       "      <td>480.000000</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>XL78013</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>22332.439460</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-01-11</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>484.013411</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>QA50777</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>9025.067525</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-01-17</td>\n",
+       "      <td>Medical Leave</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L2</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>707.925645</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10905</th>\n",
+       "      <td>10905</td>\n",
+       "      <td>FE99816</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>15563.369440</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-01-19</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer3</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>1214.400000</td>\n",
+       "      <td>Luxury Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10906</th>\n",
+       "      <td>10906</td>\n",
+       "      <td>KX53892</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>5259.444853</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-01-06</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L3</td>\n",
+       "      <td>Offer2</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>273.018929</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10907</th>\n",
+       "      <td>10907</td>\n",
+       "      <td>TL39050</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>23893.304100</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Extended</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-02-06</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Corporate L3</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>381.306996</td>\n",
+       "      <td>Luxury SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10908</th>\n",
+       "      <td>10908</td>\n",
+       "      <td>WA60547</td>\n",
+       "      <td>California</td>\n",
+       "      <td>11971.977650</td>\n",
+       "      <td>No</td>\n",
+       "      <td>Premium</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2011-02-13</td>\n",
+       "      <td>Employed</td>\n",
+       "      <td>F</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer1</td>\n",
+       "      <td>Branch</td>\n",
+       "      <td>618.288849</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10909</th>\n",
+       "      <td>10909</td>\n",
+       "      <td>IV32877</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>6857.519928</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Basic</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>2011-01-08</td>\n",
+       "      <td>Unemployed</td>\n",
+       "      <td>M</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Personal L1</td>\n",
+       "      <td>Offer4</td>\n",
+       "      <td>Web</td>\n",
+       "      <td>1021.719397</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>Medsize</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10910 rows × 26 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       unnamed:_0 customer       state  customer_lifetime_value response  \\\n",
+       "0               0  DK49336     Arizona              4809.216960       No   \n",
+       "1               1  KX64629  California              2228.525238       No   \n",
+       "2               2  LZ68649  Washington             14947.917300       No   \n",
+       "3               3  XL78013      Oregon             22332.439460      Yes   \n",
+       "4               4  QA50777      Oregon              9025.067525       No   \n",
+       "...           ...      ...         ...                      ...      ...   \n",
+       "10905       10905  FE99816      Nevada             15563.369440       No   \n",
+       "10906       10906  KX53892      Oregon              5259.444853       No   \n",
+       "10907       10907  TL39050     Arizona             23893.304100       No   \n",
+       "10908       10908  WA60547  California             11971.977650       No   \n",
+       "10909       10909  IV32877         NaN              6857.519928      NaN   \n",
+       "\n",
+       "       coverage education effective_to_date employmentstatus gender  ...  \\\n",
+       "0         Basic   College        2011-02-18         Employed      M  ...   \n",
+       "1         Basic   College        2011-01-18       Unemployed      F  ...   \n",
+       "2         Basic  Bachelor        2011-02-10         Employed      M  ...   \n",
+       "3      Extended   College        2011-01-11         Employed      M  ...   \n",
+       "4       Premium  Bachelor        2011-01-17    Medical Leave      F  ...   \n",
+       "...         ...       ...               ...              ...    ...  ...   \n",
+       "10905   Premium  Bachelor        2011-01-19       Unemployed      F  ...   \n",
+       "10906     Basic   College        2011-01-06         Employed      F  ...   \n",
+       "10907  Extended  Bachelor        2011-02-06         Employed      F  ...   \n",
+       "10908   Premium   College        2011-02-13         Employed      F  ...   \n",
+       "10909     Basic  Bachelor        2011-01-08       Unemployed      M  ...   \n",
+       "\n",
+       "       number_of_open_complaints number_of_policies     policy_type  \\\n",
+       "0                            0.0                  9  Corporate Auto   \n",
+       "1                            0.0                  1   Personal Auto   \n",
+       "2                            0.0                  2   Personal Auto   \n",
+       "3                            0.0                  2  Corporate Auto   \n",
+       "4                            NaN                  7   Personal Auto   \n",
+       "...                          ...                ...             ...   \n",
+       "10905                        NaN                  7   Personal Auto   \n",
+       "10906                        0.0                  6   Personal Auto   \n",
+       "10907                        0.0                  2  Corporate Auto   \n",
+       "10908                        4.0                  6   Personal Auto   \n",
+       "10909                        0.0                  3   Personal Auto   \n",
+       "\n",
+       "             policy  renew_offer_type  sales_channel  total_claim_amount  \\\n",
+       "0      Corporate L3            Offer3          Agent          292.800000   \n",
+       "1       Personal L3            Offer4    Call Center          744.924331   \n",
+       "2       Personal L3            Offer3    Call Center          480.000000   \n",
+       "3      Corporate L3            Offer2         Branch          484.013411   \n",
+       "4       Personal L2            Offer1         Branch          707.925645   \n",
+       "...             ...               ...            ...                 ...   \n",
+       "10905   Personal L1            Offer3            Web         1214.400000   \n",
+       "10906   Personal L3            Offer2         Branch          273.018929   \n",
+       "10907  Corporate L3            Offer1            Web          381.306996   \n",
+       "10908   Personal L1            Offer1         Branch          618.288849   \n",
+       "10909   Personal L1            Offer4            Web         1021.719397   \n",
+       "\n",
+       "       vehicle_class vehicle_size vehicle_type  \n",
+       "0      Four-Door Car      Medsize          NaN  \n",
+       "1      Four-Door Car      Medsize          NaN  \n",
+       "2                SUV      Medsize            A  \n",
+       "3      Four-Door Car      Medsize            A  \n",
+       "4      Four-Door Car      Medsize          NaN  \n",
+       "...              ...          ...          ...  \n",
+       "10905     Luxury Car      Medsize            A  \n",
+       "10906  Four-Door Car      Medsize            A  \n",
+       "10907     Luxury SUV      Medsize          NaN  \n",
+       "10908            SUV      Medsize            A  \n",
+       "10909            SUV      Medsize          NaN  \n",
+       "\n",
+       "[10910 rows x 26 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_custumers = pd.read_excel(\"/Users/giulianamiranda/Documents/Labs/lab-customer-analysis-round-2/files_for_lab/excel_files/marketing_customer_analysis.xlsx\")\n",
+    "\n",
+    "\n",
+    "cols = []\n",
+    "\n",
+    "for a in range(len(df_custumers.columns)):\n",
+    "    cols.append(df_custumers.columns[a].lower().replace(' ', '_'))\n",
+    "    \n",
+    "df_custumers.columns = cols\n",
+    "\n",
+    "df_custumers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f05702aa",
+   "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>unnamed:_0</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</td>\n",
+       "      <td>4809.216960</td>\n",
+       "      <td>48029</td>\n",
+       "      <td>61</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>52</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>292.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2228.525238</td>\n",
+       "      <td>0</td>\n",
+       "      <td>64</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>744.924331</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>14947.917300</td>\n",
+       "      <td>22139</td>\n",
+       "      <td>100</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>480.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>22332.439460</td>\n",
+       "      <td>49078</td>\n",
+       "      <td>97</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>484.013411</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>9025.067525</td>\n",
+       "      <td>23675</td>\n",
+       "      <td>117</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>31</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7</td>\n",
+       "      <td>707.925645</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10905</th>\n",
+       "      <td>10905</td>\n",
+       "      <td>15563.369440</td>\n",
+       "      <td>0</td>\n",
+       "      <td>253</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1214.400000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10906</th>\n",
+       "      <td>10906</td>\n",
+       "      <td>5259.444853</td>\n",
+       "      <td>61146</td>\n",
+       "      <td>65</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>273.018929</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10907</th>\n",
+       "      <td>10907</td>\n",
+       "      <td>23893.304100</td>\n",
+       "      <td>39837</td>\n",
+       "      <td>201</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>63</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>381.306996</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10908</th>\n",
+       "      <td>10908</td>\n",
+       "      <td>11971.977650</td>\n",
+       "      <td>64195</td>\n",
+       "      <td>158</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>27</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>618.288849</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10909</th>\n",
+       "      <td>10909</td>\n",
+       "      <td>6857.519928</td>\n",
+       "      <td>0</td>\n",
+       "      <td>101</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1021.719397</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10910 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       unnamed:_0  customer_lifetime_value  income  monthly_premium_auto  \\\n",
+       "0               0              4809.216960   48029                    61   \n",
+       "1               1              2228.525238       0                    64   \n",
+       "2               2             14947.917300   22139                   100   \n",
+       "3               3             22332.439460   49078                    97   \n",
+       "4               4              9025.067525   23675                   117   \n",
+       "...           ...                      ...     ...                   ...   \n",
+       "10905       10905             15563.369440       0                   253   \n",
+       "10906       10906              5259.444853   61146                    65   \n",
+       "10907       10907             23893.304100   39837                   201   \n",
+       "10908       10908             11971.977650   64195                   158   \n",
+       "10909       10909              6857.519928       0                   101   \n",
+       "\n",
+       "       months_since_last_claim  months_since_policy_inception  \\\n",
+       "0                          7.0                             52   \n",
+       "1                          3.0                             26   \n",
+       "2                         34.0                             31   \n",
+       "3                         10.0                              3   \n",
+       "4                          NaN                             31   \n",
+       "...                        ...                            ...   \n",
+       "10905                      NaN                             40   \n",
+       "10906                      7.0                             68   \n",
+       "10907                     11.0                             63   \n",
+       "10908                      0.0                             27   \n",
+       "10909                     31.0                              1   \n",
+       "\n",
+       "       number_of_open_complaints  number_of_policies  total_claim_amount  \n",
+       "0                            0.0                   9          292.800000  \n",
+       "1                            0.0                   1          744.924331  \n",
+       "2                            0.0                   2          480.000000  \n",
+       "3                            0.0                   2          484.013411  \n",
+       "4                            NaN                   7          707.925645  \n",
+       "...                          ...                 ...                 ...  \n",
+       "10905                        NaN                   7         1214.400000  \n",
+       "10906                        0.0                   6          273.018929  \n",
+       "10907                        0.0                   2          381.306996  \n",
+       "10908                        4.0                   6          618.288849  \n",
+       "10909                        0.0                   3         1021.719397  \n",
+       "\n",
+       "[10910 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "numerical = df_custumers.select_dtypes(include=[np.number])\n",
+    "numerical\n",
+    "\n",
+    "numerical"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "77737dd5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# X-y split.\n",
+    "\n",
+    "Y = df_custumers['total_claim_amount']\n",
+    "X = df_custumers.drop(['total_claim_amount'], axis=1) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2e126245",
+   "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>unnamed:_0</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",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.035752</td>\n",
+       "      <td>0.480381</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.525253</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.000092</td>\n",
+       "      <td>0.004059</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.012658</td>\n",
+       "      <td>0.085714</td>\n",
+       "      <td>0.262626</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.000183</td>\n",
+       "      <td>0.160264</td>\n",
+       "      <td>0.221432</td>\n",
+       "      <td>0.164557</td>\n",
+       "      <td>0.971429</td>\n",
+       "      <td>0.313131</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.000275</td>\n",
+       "      <td>0.250953</td>\n",
+       "      <td>0.490873</td>\n",
+       "      <td>0.151899</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.030303</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.000458</td>\n",
+       "      <td>0.034966</td>\n",
+       "      <td>0.505586</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.057143</td>\n",
+       "      <td>0.737374</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.750</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>10272</th>\n",
+       "      <td>0.999542</td>\n",
+       "      <td>0.212833</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.531646</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.323232</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10273</th>\n",
+       "      <td>0.999725</td>\n",
+       "      <td>0.041281</td>\n",
+       "      <td>0.611576</td>\n",
+       "      <td>0.016878</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.686869</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10274</th>\n",
+       "      <td>0.999817</td>\n",
+       "      <td>0.270122</td>\n",
+       "      <td>0.398446</td>\n",
+       "      <td>0.590717</td>\n",
+       "      <td>0.314286</td>\n",
+       "      <td>0.636364</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10275</th>\n",
+       "      <td>0.999908</td>\n",
+       "      <td>0.123717</td>\n",
+       "      <td>0.642072</td>\n",
+       "      <td>0.409283</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.272727</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10276</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.060907</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.168776</td>\n",
+       "      <td>0.885714</td>\n",
+       "      <td>0.010101</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10277 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       unnamed:_0  customer_lifetime_value    income  monthly_premium_auto  \\\n",
+       "0        0.000000                 0.035752  0.480381              0.000000   \n",
+       "1        0.000092                 0.004059  0.000000              0.012658   \n",
+       "2        0.000183                 0.160264  0.221432              0.164557   \n",
+       "3        0.000275                 0.250953  0.490873              0.151899   \n",
+       "4        0.000458                 0.034966  0.505586              0.000000   \n",
+       "...           ...                      ...       ...                   ...   \n",
+       "10272    0.999542                 0.212833  0.000000              0.531646   \n",
+       "10273    0.999725                 0.041281  0.611576              0.016878   \n",
+       "10274    0.999817                 0.270122  0.398446              0.590717   \n",
+       "10275    0.999908                 0.123717  0.642072              0.409283   \n",
+       "10276    1.000000                 0.060907  0.000000              0.168776   \n",
+       "\n",
+       "       months_since_last_claim  months_since_policy_inception  \\\n",
+       "0                     0.200000                       0.525253   \n",
+       "1                     0.085714                       0.262626   \n",
+       "2                     0.971429                       0.313131   \n",
+       "3                     0.285714                       0.030303   \n",
+       "4                     0.057143                       0.737374   \n",
+       "...                        ...                            ...   \n",
+       "10272                 0.400000                       0.323232   \n",
+       "10273                 0.200000                       0.686869   \n",
+       "10274                 0.314286                       0.636364   \n",
+       "10275                 0.000000                       0.272727   \n",
+       "10276                 0.885714                       0.010101   \n",
+       "\n",
+       "       number_of_open_complaints  number_of_policies  \n",
+       "0                            0.0               1.000  \n",
+       "1                            0.0               0.000  \n",
+       "2                            0.0               0.125  \n",
+       "3                            0.0               0.125  \n",
+       "4                            0.0               0.750  \n",
+       "...                          ...                 ...  \n",
+       "10272                        0.0               0.125  \n",
+       "10273                        0.0               0.625  \n",
+       "10274                        0.0               0.125  \n",
+       "10275                        0.8               0.625  \n",
+       "10276                        0.0               0.250  \n",
+       "\n",
+       "[10277 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Normalize (numerical)\n",
+    "\n",
+    "numerical.isnull().sum()\n",
+    "numerical = numerical.dropna()\n",
+    "\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "\n",
+    "num_data = numerical.drop(['total_claim_amount'], axis = 1)\n",
+    "scaler = MinMaxScaler() \n",
+    "normalized_df = scaler.fit_transform(num_data) \n",
+    "normalized_df = pd.DataFrame(normalized_df, columns = num_data.columns)\n",
+    "normalized_df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "51e4161b",
+   "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": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}