From f748777d3d0d8b0dc028427a0dd0400acabc008a Mon Sep 17 00:00:00 2001
From: LeonardoPagliacci <pagliaccileo@gmail.com>
Date: Fri, 6 Oct 2023 14:25:14 +0100
Subject: [PATCH] added the ypnb file with the solution of the lab

---
 .DS_Store                                     |  Bin 0 -> 8196 bytes
 ...ound1] leonardo_pagliacci-checkpoint.ipynb | 1547 +++++++++++++++++
 ..._analysis_round1] leonardo_pagliacci.ipynb | 1547 +++++++++++++++++
 files_for_lab/.DS_Store                       |  Bin 0 -> 6148 bytes
 4 files changed, 3094 insertions(+)
 create mode 100644 .DS_Store
 create mode 100644 .ipynb_checkpoints/[lab_customer_analysis_round1] leonardo_pagliacci-checkpoint.ipynb
 create mode 100644 [lab_customer_analysis_round1] leonardo_pagliacci.ipynb
 create mode 100644 files_for_lab/.DS_Store

diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..202ba5f668f6f1543cb994fa5e7f7235d058bc74
GIT binary patch
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diff --git a/.ipynb_checkpoints/[lab_customer_analysis_round1] leonardo_pagliacci-checkpoint.ipynb b/.ipynb_checkpoints/[lab_customer_analysis_round1] leonardo_pagliacci-checkpoint.ipynb
new file mode 100644
index 0000000..cb4aab0
--- /dev/null
+++ b/.ipynb_checkpoints/[lab_customer_analysis_round1] leonardo_pagliacci-checkpoint.ipynb	
@@ -0,0 +1,1547 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 347,
+   "id": "958305e9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 348,
+   "id": "ff4186ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read the three files into python as dataframes\n",
+    "\n",
+    "cus_data1 = pd.read_csv(\"/Users/leozinho.air/Desktop/Ironhack_DA/class_03/Lab 1 - customer analysis/lab-customer-analysis-round-1/files_for_lab/csv_files/file1.csv\")\n",
+    "\n",
+    "cus_data2 = pd.read_csv(r\"/Users/leozinho.air/Desktop/Ironhack_DA/class_03/Lab 1 - customer analysis/lab-customer-analysis-round-1/files_for_lab/csv_files/file2.csv\")\n",
+    "\n",
+    "cus_data3 = pd.read_csv(r\"/Users/leozinho.air/Desktop/Ironhack_DA/class_03/Lab 1 - customer analysis/lab-customer-analysis-round-1/files_for_lab/csv_files/file3.csv\")\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 349,
+   "id": "35c9e5a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(4008, 11)\n",
+      "(996, 11)\n",
+      "(7070, 11)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the DataFrame's shape.\n",
+    "\n",
+    "print(cus_data1.shape)\n",
+    "\n",
+    "print(cus_data2.shape)\n",
+    "\n",
+    "print(cus_data3.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 350,
+   "id": "29b4433c",
+   "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>education</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>SA25987</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>3479.137523</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>104</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>499.200000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>TB86706</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>2502.637401</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>3.468912</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ZL73902</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>3265.156348</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>F</td>\n",
+       "      <td>25820</td>\n",
+       "      <td>82</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>393.600000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>KX23516</td>\n",
+       "      <td>California</td>\n",
+       "      <td>4455.843406</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>121</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>699.615192</td>\n",
+       "      <td>SUV</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>FN77294</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7704.958480</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>M</td>\n",
+       "      <td>30366</td>\n",
+       "      <td>101</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>484.800000</td>\n",
+       "      <td>SUV</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>73</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>College</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>79</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>85</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>College</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>96</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>College</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>77</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7070 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer       state  customer_lifetime_value             education  \\\n",
+       "0     SA25987  Washington              3479.137523  High School or Below   \n",
+       "1     TB86706     Arizona              2502.637401                Master   \n",
+       "2     ZL73902      Nevada              3265.156348              Bachelor   \n",
+       "3     KX23516  California              4455.843406  High School or Below   \n",
+       "4     FN77294  California              7704.958480  High School or Below   \n",
+       "...       ...         ...                      ...                   ...   \n",
+       "7065  LA72316  California             23405.987980              Bachelor   \n",
+       "7066  PK87824  California              3096.511217               College   \n",
+       "7067  TD14365  California              8163.890428              Bachelor   \n",
+       "7068  UP19263  California              7524.442436               College   \n",
+       "7069  Y167826  California              2611.836866               College   \n",
+       "\n",
+       "     gender  income  monthly_premium_auto  number_of_open_complaints  \\\n",
+       "0         M       0                   104                          0   \n",
+       "1         M       0                    66                          0   \n",
+       "2         F   25820                    82                          0   \n",
+       "3         F       0                   121                          0   \n",
+       "4         M   30366                   101                          2   \n",
+       "...     ...     ...                   ...                        ...   \n",
+       "7065      M   71941                    73                          0   \n",
+       "7066      F   21604                    79                          0   \n",
+       "7067      M       0                    85                          3   \n",
+       "7068      M   21941                    96                          0   \n",
+       "7069      M       0                    77                          0   \n",
+       "\n",
+       "         policy_type  total_claim_amount  vehicle_class  \n",
+       "0      Personal Auto          499.200000   Two-Door Car  \n",
+       "1      Personal Auto            3.468912   Two-Door Car  \n",
+       "2      Personal Auto          393.600000  Four-Door Car  \n",
+       "3      Personal Auto          699.615192            SUV  \n",
+       "4      Personal Auto          484.800000            SUV  \n",
+       "...              ...                 ...            ...  \n",
+       "7065   Personal Auto          198.234764  Four-Door Car  \n",
+       "7066  Corporate Auto          379.200000  Four-Door Car  \n",
+       "7067  Corporate Auto          790.784983  Four-Door Car  \n",
+       "7068   Personal Auto          691.200000  Four-Door Car  \n",
+       "7069  Corporate Auto          369.600000   Two-Door Car  \n",
+       "\n",
+       "[7070 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 350,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Standardize header names.\n",
+    "\n",
+    "cols1 = []\n",
+    "\n",
+    "cols2 = []\n",
+    "\n",
+    "cols3 = []\n",
+    "\n",
+    "\n",
+    "for i in range(len(cus_data1.columns)):\n",
+    "    cols1.append(cus_data1.columns[i].lower().replace(' ', '_'))\n",
+    "\n",
+    "cus_data1.columns = cols1\n",
+    "\n",
+    "cus_data1\n",
+    "\n",
+    "for i in range(len(cus_data2.columns)):\n",
+    "    cols2.append(cus_data2.columns[i].lower().replace(' ', '_'))\n",
+    "\n",
+    "cus_data2.columns = cols2\n",
+    "\n",
+    "cus_data2\n",
+    "\n",
+    "for i in range(len(cus_data3.columns)):\n",
+    "    cols3.append(cus_data3.columns[i].lower().replace(' ', '_'))\n",
+    "\n",
+    "cus_data3.columns = cols3\n",
+    "\n",
+    "cus_data3\n",
+    "\n",
+    "    \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 351,
+   "id": "39a98573",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+      "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+      "       'policy_type', 'vehicle_class', 'total_claim_amount'],\n",
+      "      dtype='object')\n",
+      "Index(['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+      "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+      "       'policy_type', 'vehicle_class', 'total_claim_amount'],\n",
+      "      dtype='object')\n",
+      "Index(['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+      "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+      "       'policy_type', 'vehicle_class', 'total_claim_amount'],\n",
+      "      dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Rearrange the columns in the dataframe as needed\n",
+    "\n",
+    "# We use the columns of cus_data1 as the default columns for ours dataframes\n",
+    "\n",
+    "cus_data2 = cus_data2[['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+    "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+    "       'policy_type', 'vehicle_class', 'total_claim_amount']] # Changing the order of the columns\n",
+    "\n",
+    "cus_data2\n",
+    "\n",
+    "# Now i am going to do the same for cus_data3\n",
+    "\n",
+    "cus_data3['st'] = cus_data3['state']\n",
+    "cus_data3 = cus_data3.drop(columns ='state') # renaming the column 'state'\n",
+    "\n",
+    "cus_data3 # Thankfully renamed\n",
+    "\n",
+    "# Now let's order cus_data3\n",
+    "\n",
+    "desired_order = ['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+    "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+    "       'policy_type', 'vehicle_class', 'total_claim_amount']\n",
+    "cus_data3 = cus_data3[desired_order]\n",
+    "\n",
+    "# Checking if everything is ok\n",
+    "print(cus_data3.columns)\n",
+    "print(cus_data2.columns)\n",
+    "print(cus_data1.columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 352,
+   "id": "7aadaafc",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>education</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>6970</th>\n",
+       "      <td>NA56063</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>43019.01278</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>904.378268</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6971</th>\n",
+       "      <td>CA62597</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>7482.851041</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>978.257137</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6972</th>\n",
+       "      <td>ZO23305</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>4929.549699</td>\n",
+       "      <td>25632.0</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>351.270869</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6973</th>\n",
+       "      <td>UD20999</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>2537.667511</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>326.400000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6974</th>\n",
+       "      <td>FQ66351</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>5322.291688</td>\n",
+       "      <td>33681.0</td>\n",
+       "      <td>138.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>873.127345</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>23405.98798</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender education customer_lifetime_value   income  \\\n",
+       "6970  NA56063  California      M   College             43019.01278      0.0   \n",
+       "6971  CA62597  California      F  Bachelor             7482.851041      0.0   \n",
+       "6972  ZO23305  California      M  Bachelor             4929.549699  25632.0   \n",
+       "6973  UD20999  California      M    Master             2537.667511      0.0   \n",
+       "6974  FQ66351  California      F  Bachelor             5322.291688  33681.0   \n",
+       "...       ...         ...    ...       ...                     ...      ...   \n",
+       "7065  LA72316  California      M  Bachelor             23405.98798  71941.0   \n",
+       "7066  PK87824  California      F   College             3096.511217  21604.0   \n",
+       "7067  TD14365  California      M  Bachelor             8163.890428      0.0   \n",
+       "7068  UP19263  California      M   College             7524.442436  21941.0   \n",
+       "7069  Y167826  California      M   College             2611.836866      0.0   \n",
+       "\n",
+       "      monthly_premium_auto number_of_open_complaints     policy_type  \\\n",
+       "6970                 132.0                         0  Corporate Auto   \n",
+       "6971                 101.0                         0  Corporate Auto   \n",
+       "6972                  63.0                         0   Personal Auto   \n",
+       "6973                  68.0                         0  Corporate Auto   \n",
+       "6974                 138.0                         1   Personal Auto   \n",
+       "...                    ...                       ...             ...   \n",
+       "7065                  73.0                         0   Personal Auto   \n",
+       "7066                  79.0                         0  Corporate Auto   \n",
+       "7067                  85.0                         3  Corporate Auto   \n",
+       "7068                  96.0                         0   Personal Auto   \n",
+       "7069                  77.0                         0  Corporate Auto   \n",
+       "\n",
+       "      vehicle_class  total_claim_amount  \n",
+       "6970            SUV          904.378268  \n",
+       "6971            SUV          978.257137  \n",
+       "6972   Two-Door Car          351.270869  \n",
+       "6973  Four-Door Car          326.400000  \n",
+       "6974            SUV          873.127345  \n",
+       "...             ...                 ...  \n",
+       "7065  Four-Door Car          198.234764  \n",
+       "7066  Four-Door Car          379.200000  \n",
+       "7067  Four-Door Car          790.784983  \n",
+       "7068  Four-Door Car          691.200000  \n",
+       "7069   Two-Door Car          369.600000  \n",
+       "\n",
+       "[100 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 352,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Concatenate the three dataframes\n",
+    "\n",
+    "cus_data = pd.concat([cus_data1, cus_data2, cus_data3], axis = 0) # axis = 0 is not mandatory but is better putting it on\n",
+    "\n",
+    "cus_data.tail(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 353,
+   "id": "47da75af",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"\\n\\n'income','monthly_premium_auto','total_claim_amount ' are numerical, the other ones are object (strings or whatsoever).\\n\\ncustomer                      object = Id referring to the customer\\nst                            object = State in which the car was bought\\ngender                        object = gender of the buyer\\neducation                     object = education of the buyer\\ncustomer_lifetime_value       object = a metric that represents the total net profit a company can expect to generate from a customer throughout their entire relationship\\nincome                       float64 = annual income of the buyer\\nmonthly_premium_auto         float64 = monthly premium that the buyer has to pay\\nnumber_of_open_complaints     object = ...\\npolicy_type                   object = ...\\nvehicle_class                 object = ...\\ntotal_claim_amount           float64 = ...\\n\\n\""
+      ]
+     },
+     "execution_count": 353,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Which columns are numerical?\n",
+    "# Which columns are categorial?\n",
+    "\n",
+    "cus_data.dtypes\n",
+    "\n",
+    "\n",
+    "'''\n",
+    "\n",
+    "'income','monthly_premium_auto','total_claim_amount ' are numerical, the other ones are object (strings or whatsoever).\n",
+    "\n",
+    "customer                      object = Id referring to the customer\n",
+    "st                            object = State in which the car was bought\n",
+    "gender                        object = gender of the buyer\n",
+    "education                     object = education of the buyer\n",
+    "customer_lifetime_value       object = a metric that represents the total net profit a company can expect to generate from a customer throughout their entire relationship\n",
+    "income                       float64 = annual income of the buyer\n",
+    "monthly_premium_auto         float64 = monthly premium that the buyer has to pay\n",
+    "number_of_open_complaints     object = ...\n",
+    "policy_type                   object = ...\n",
+    "vehicle_class                 object = ...\n",
+    "total_claim_amount           float64 = ...\n",
+    "\n",
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 354,
+   "id": "ef630730",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>RB50392</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>2.704934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>697953.59%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1288743.17%</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>764586.18%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>536307.65%</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  customer          st gender customer_lifetime_value   income  \\\n",
+       "0  RB50392  Washington    NaN                     NaN      0.0   \n",
+       "1  QZ44356     Arizona      F              697953.59%      0.0   \n",
+       "2  AI49188      Nevada      F             1288743.17%  48767.0   \n",
+       "3  WW63253  California      M              764586.18%      0.0   \n",
+       "4  GA49547  Washington      M              536307.65%  36357.0   \n",
+       "\n",
+       "   monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "0                1000.0   Personal Auto  Four-Door Car            2.704934  \n",
+       "1                  94.0   Personal Auto  Four-Door Car         1131.464935  \n",
+       "2                 108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "3                 106.0  Corporate Auto            SUV          529.881344  \n",
+       "4                  68.0   Personal Auto  Four-Door Car           17.269323  "
+      ]
+     },
+     "execution_count": 354,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Data cleaning\n",
+    "\n",
+    "# Delete the column education and the number of open complaints from the dataframe\n",
+    "\n",
+    "cus_data = cus_data.drop(['education'], axis = 1)\n",
+    "\n",
+    "cus_data = cus_data.drop(['number_of_open_complaints'], axis = 1)\n",
+    "\n",
+    "cus_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b78633cc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 355,
+   "id": "331b02a9",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>6.979536e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1.288743e+08</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.645862e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.363076e+07</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>OC83172</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>8.256298e+07</td>\n",
+       "      <td>62902.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>159.383042</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>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.340599e+06</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>3.096511e+05</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>8.163890e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.524442e+05</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.611837e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9010 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender  customer_lifetime_value   income  \\\n",
+       "1     QZ44356     Arizona      F             6.979536e+07      0.0   \n",
+       "2     AI49188      Nevada      F             1.288743e+08  48767.0   \n",
+       "3     WW63253  California      M             7.645862e+07      0.0   \n",
+       "4     GA49547  Washington      M             5.363076e+07  36357.0   \n",
+       "5     OC83172      Oregon      F             8.256298e+07  62902.0   \n",
+       "...       ...         ...    ...                      ...      ...   \n",
+       "7065  LA72316  California      M             2.340599e+06  71941.0   \n",
+       "7066  PK87824  California      F             3.096511e+05  21604.0   \n",
+       "7067  TD14365  California      M             8.163890e+05      0.0   \n",
+       "7068  UP19263  California      M             7.524442e+05  21941.0   \n",
+       "7069  Y167826  California      M             2.611837e+05      0.0   \n",
+       "\n",
+       "      monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "1                     94.0   Personal Auto  Four-Door Car         1131.464935  \n",
+       "2                    108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "3                    106.0  Corporate Auto            SUV          529.881344  \n",
+       "4                     68.0   Personal Auto  Four-Door Car           17.269323  \n",
+       "5                     69.0   Personal Auto   Two-Door Car          159.383042  \n",
+       "...                    ...             ...            ...                 ...  \n",
+       "7065                  73.0   Personal Auto  Four-Door Car          198.234764  \n",
+       "7066                  79.0  Corporate Auto  Four-Door Car          379.200000  \n",
+       "7067                  85.0  Corporate Auto  Four-Door Car          790.784983  \n",
+       "7068                  96.0   Personal Auto  Four-Door Car          691.200000  \n",
+       "7069                  77.0  Corporate Auto   Two-Door Car          369.600000  \n",
+       "\n",
+       "[9010 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 355,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Correct the values in the column customer lifetime value. \n",
+    "# They are given as a percent, so multiply them by 100 and change `dtype` to `numerical` type\n",
+    "\n",
+    "cus_data = cus_data.dropna() # removing null values\n",
+    "\n",
+    "cus_data['customer_lifetime_value']  = cus_data['customer_lifetime_value'].astype(str) # On cus_data3 (third df) the dtype of the customer lifetime column was 'float', then before cutting out the '%' character i had to convert the column to 'str' dtype\n",
+    "\n",
+    "cus_data['customer_lifetime_value'] = cus_data['customer_lifetime_value'].str.replace('%','') # Excluding the '%' character from the colum so that i can convert all the column to float.\n",
+    "\n",
+    "cus_data['customer_lifetime_value'] = cus_data['customer_lifetime_value'].astype(float) # Converting the column to float dtype.\n",
+    "\n",
+    "cus_data['customer_lifetime_value'] = cus_data['customer_lifetime_value'].mul(100) # Multiplying the values by 100, the numbers are very large. ex -> 6.979536e+07 = 69,795,360\n",
+    "\n",
+    "\n",
+    "cus_data\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 356,
+   "id": "e1a37433",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>6.979536e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1.288743e+08</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.645862e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.363076e+07</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>OC83172</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>8.256298e+07</td>\n",
+       "      <td>62902.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>159.383042</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>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.340599e+06</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>3.096511e+05</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>8.163890e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.524442e+05</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.611837e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9007 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender  customer_lifetime_value   income  \\\n",
+       "1     QZ44356     Arizona      F             6.979536e+07      0.0   \n",
+       "2     AI49188      Nevada      F             1.288743e+08  48767.0   \n",
+       "3     WW63253  California      M             7.645862e+07      0.0   \n",
+       "4     GA49547  Washington      M             5.363076e+07  36357.0   \n",
+       "5     OC83172      Oregon      F             8.256298e+07  62902.0   \n",
+       "...       ...         ...    ...                      ...      ...   \n",
+       "7065  LA72316  California      M             2.340599e+06  71941.0   \n",
+       "7066  PK87824  California      F             3.096511e+05  21604.0   \n",
+       "7067  TD14365  California      M             8.163890e+05      0.0   \n",
+       "7068  UP19263  California      M             7.524442e+05  21941.0   \n",
+       "7069  Y167826  California      M             2.611837e+05      0.0   \n",
+       "\n",
+       "      monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "1                     94.0   Personal Auto  Four-Door Car         1131.464935  \n",
+       "2                    108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "3                    106.0  Corporate Auto            SUV          529.881344  \n",
+       "4                     68.0   Personal Auto  Four-Door Car           17.269323  \n",
+       "5                     69.0   Personal Auto   Two-Door Car          159.383042  \n",
+       "...                    ...             ...            ...                 ...  \n",
+       "7065                  73.0   Personal Auto  Four-Door Car          198.234764  \n",
+       "7066                  79.0  Corporate Auto  Four-Door Car          379.200000  \n",
+       "7067                  85.0  Corporate Auto  Four-Door Car          790.784983  \n",
+       "7068                  96.0   Personal Auto  Four-Door Car          691.200000  \n",
+       "7069                  77.0  Corporate Auto   Two-Door Car          369.600000  \n",
+       "\n",
+       "[9007 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 356,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check for duplicate rows in the data and remove if any.\n",
+    "\n",
+    "cus_data.duplicated()\n",
+    "\n",
+    "cus_data.drop_duplicates()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 357,
+   "id": "0135494b",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1.288743e+08</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.363076e+07</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>OC83172</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>8.256298e+07</td>\n",
+       "      <td>62902.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>159.383042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>XZ87318</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>5.380899e+07</td>\n",
+       "      <td>55350.0</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>321.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>DY87989</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.412750e+08</td>\n",
+       "      <td>14072.0</td>\n",
+       "      <td>71.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>511.200000</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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7063</th>\n",
+       "      <td>TF56202</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.032165e+05</td>\n",
+       "      <td>66367.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>307.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7064</th>\n",
+       "      <td>YM19146</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>4.100399e+05</td>\n",
+       "      <td>47761.0</td>\n",
+       "      <td>104.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>541.282007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.340599e+06</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>3.096511e+05</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.524442e+05</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6741 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender  customer_lifetime_value   income  \\\n",
+       "2     AI49188      Nevada      F             1.288743e+08  48767.0   \n",
+       "4     GA49547  Washington      M             5.363076e+07  36357.0   \n",
+       "5     OC83172      Oregon      F             8.256298e+07  62902.0   \n",
+       "6     XZ87318      Oregon      F             5.380899e+07  55350.0   \n",
+       "8     DY87989      Oregon      M             2.412750e+08  14072.0   \n",
+       "...       ...         ...    ...                      ...      ...   \n",
+       "7063  TF56202  California      M             5.032165e+05  66367.0   \n",
+       "7064  YM19146  California      F             4.100399e+05  47761.0   \n",
+       "7065  LA72316  California      M             2.340599e+06  71941.0   \n",
+       "7066  PK87824  California      F             3.096511e+05  21604.0   \n",
+       "7068  UP19263  California      M             7.524442e+05  21941.0   \n",
+       "\n",
+       "      monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "2                    108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "4                     68.0   Personal Auto  Four-Door Car           17.269323  \n",
+       "5                     69.0   Personal Auto   Two-Door Car          159.383042  \n",
+       "6                     67.0  Corporate Auto  Four-Door Car          321.600000  \n",
+       "8                     71.0  Corporate Auto  Four-Door Car          511.200000  \n",
+       "...                    ...             ...            ...                 ...  \n",
+       "7063                  64.0   Personal Auto   Two-Door Car          307.200000  \n",
+       "7064                 104.0   Personal Auto  Four-Door Car          541.282007  \n",
+       "7065                  73.0   Personal Auto  Four-Door Car          198.234764  \n",
+       "7066                  79.0  Corporate Auto  Four-Door Car          379.200000  \n",
+       "7068                  96.0   Personal Auto  Four-Door Car          691.200000  \n",
+       "\n",
+       "[6741 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 357,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter out the data for customers who have an income of 0 or less.\n",
+    "\n",
+    "cus_data = cus_data.loc[cus_data['income'] > 0]\n",
+    "\n",
+    "cus_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2c6f4495",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d155737",
+   "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/[lab_customer_analysis_round1] leonardo_pagliacci.ipynb b/[lab_customer_analysis_round1] leonardo_pagliacci.ipynb
new file mode 100644
index 0000000..cb4aab0
--- /dev/null
+++ b/[lab_customer_analysis_round1] leonardo_pagliacci.ipynb	
@@ -0,0 +1,1547 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 347,
+   "id": "958305e9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 348,
+   "id": "ff4186ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read the three files into python as dataframes\n",
+    "\n",
+    "cus_data1 = pd.read_csv(\"/Users/leozinho.air/Desktop/Ironhack_DA/class_03/Lab 1 - customer analysis/lab-customer-analysis-round-1/files_for_lab/csv_files/file1.csv\")\n",
+    "\n",
+    "cus_data2 = pd.read_csv(r\"/Users/leozinho.air/Desktop/Ironhack_DA/class_03/Lab 1 - customer analysis/lab-customer-analysis-round-1/files_for_lab/csv_files/file2.csv\")\n",
+    "\n",
+    "cus_data3 = pd.read_csv(r\"/Users/leozinho.air/Desktop/Ironhack_DA/class_03/Lab 1 - customer analysis/lab-customer-analysis-round-1/files_for_lab/csv_files/file3.csv\")\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 349,
+   "id": "35c9e5a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(4008, 11)\n",
+      "(996, 11)\n",
+      "(7070, 11)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show the DataFrame's shape.\n",
+    "\n",
+    "print(cus_data1.shape)\n",
+    "\n",
+    "print(cus_data2.shape)\n",
+    "\n",
+    "print(cus_data3.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 350,
+   "id": "29b4433c",
+   "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>education</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>SA25987</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>3479.137523</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>104</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>499.200000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>TB86706</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>2502.637401</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>3.468912</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>ZL73902</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>3265.156348</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>F</td>\n",
+       "      <td>25820</td>\n",
+       "      <td>82</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>393.600000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>KX23516</td>\n",
+       "      <td>California</td>\n",
+       "      <td>4455.843406</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>F</td>\n",
+       "      <td>0</td>\n",
+       "      <td>121</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>699.615192</td>\n",
+       "      <td>SUV</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>FN77294</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7704.958480</td>\n",
+       "      <td>High School or Below</td>\n",
+       "      <td>M</td>\n",
+       "      <td>30366</td>\n",
+       "      <td>101</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>484.800000</td>\n",
+       "      <td>SUV</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>23405.987980</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>M</td>\n",
+       "      <td>71941</td>\n",
+       "      <td>73</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>198.234764</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>College</td>\n",
+       "      <td>F</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>79</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>379.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>85</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>790.784983</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>College</td>\n",
+       "      <td>M</td>\n",
+       "      <td>21941</td>\n",
+       "      <td>96</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>691.200000</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>College</td>\n",
+       "      <td>M</td>\n",
+       "      <td>0</td>\n",
+       "      <td>77</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>369.600000</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7070 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer       state  customer_lifetime_value             education  \\\n",
+       "0     SA25987  Washington              3479.137523  High School or Below   \n",
+       "1     TB86706     Arizona              2502.637401                Master   \n",
+       "2     ZL73902      Nevada              3265.156348              Bachelor   \n",
+       "3     KX23516  California              4455.843406  High School or Below   \n",
+       "4     FN77294  California              7704.958480  High School or Below   \n",
+       "...       ...         ...                      ...                   ...   \n",
+       "7065  LA72316  California             23405.987980              Bachelor   \n",
+       "7066  PK87824  California              3096.511217               College   \n",
+       "7067  TD14365  California              8163.890428              Bachelor   \n",
+       "7068  UP19263  California              7524.442436               College   \n",
+       "7069  Y167826  California              2611.836866               College   \n",
+       "\n",
+       "     gender  income  monthly_premium_auto  number_of_open_complaints  \\\n",
+       "0         M       0                   104                          0   \n",
+       "1         M       0                    66                          0   \n",
+       "2         F   25820                    82                          0   \n",
+       "3         F       0                   121                          0   \n",
+       "4         M   30366                   101                          2   \n",
+       "...     ...     ...                   ...                        ...   \n",
+       "7065      M   71941                    73                          0   \n",
+       "7066      F   21604                    79                          0   \n",
+       "7067      M       0                    85                          3   \n",
+       "7068      M   21941                    96                          0   \n",
+       "7069      M       0                    77                          0   \n",
+       "\n",
+       "         policy_type  total_claim_amount  vehicle_class  \n",
+       "0      Personal Auto          499.200000   Two-Door Car  \n",
+       "1      Personal Auto            3.468912   Two-Door Car  \n",
+       "2      Personal Auto          393.600000  Four-Door Car  \n",
+       "3      Personal Auto          699.615192            SUV  \n",
+       "4      Personal Auto          484.800000            SUV  \n",
+       "...              ...                 ...            ...  \n",
+       "7065   Personal Auto          198.234764  Four-Door Car  \n",
+       "7066  Corporate Auto          379.200000  Four-Door Car  \n",
+       "7067  Corporate Auto          790.784983  Four-Door Car  \n",
+       "7068   Personal Auto          691.200000  Four-Door Car  \n",
+       "7069  Corporate Auto          369.600000   Two-Door Car  \n",
+       "\n",
+       "[7070 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 350,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Standardize header names.\n",
+    "\n",
+    "cols1 = []\n",
+    "\n",
+    "cols2 = []\n",
+    "\n",
+    "cols3 = []\n",
+    "\n",
+    "\n",
+    "for i in range(len(cus_data1.columns)):\n",
+    "    cols1.append(cus_data1.columns[i].lower().replace(' ', '_'))\n",
+    "\n",
+    "cus_data1.columns = cols1\n",
+    "\n",
+    "cus_data1\n",
+    "\n",
+    "for i in range(len(cus_data2.columns)):\n",
+    "    cols2.append(cus_data2.columns[i].lower().replace(' ', '_'))\n",
+    "\n",
+    "cus_data2.columns = cols2\n",
+    "\n",
+    "cus_data2\n",
+    "\n",
+    "for i in range(len(cus_data3.columns)):\n",
+    "    cols3.append(cus_data3.columns[i].lower().replace(' ', '_'))\n",
+    "\n",
+    "cus_data3.columns = cols3\n",
+    "\n",
+    "cus_data3\n",
+    "\n",
+    "    \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 351,
+   "id": "39a98573",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+      "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+      "       'policy_type', 'vehicle_class', 'total_claim_amount'],\n",
+      "      dtype='object')\n",
+      "Index(['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+      "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+      "       'policy_type', 'vehicle_class', 'total_claim_amount'],\n",
+      "      dtype='object')\n",
+      "Index(['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+      "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+      "       'policy_type', 'vehicle_class', 'total_claim_amount'],\n",
+      "      dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Rearrange the columns in the dataframe as needed\n",
+    "\n",
+    "# We use the columns of cus_data1 as the default columns for ours dataframes\n",
+    "\n",
+    "cus_data2 = cus_data2[['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+    "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+    "       'policy_type', 'vehicle_class', 'total_claim_amount']] # Changing the order of the columns\n",
+    "\n",
+    "cus_data2\n",
+    "\n",
+    "# Now i am going to do the same for cus_data3\n",
+    "\n",
+    "cus_data3['st'] = cus_data3['state']\n",
+    "cus_data3 = cus_data3.drop(columns ='state') # renaming the column 'state'\n",
+    "\n",
+    "cus_data3 # Thankfully renamed\n",
+    "\n",
+    "# Now let's order cus_data3\n",
+    "\n",
+    "desired_order = ['customer', 'st', 'gender', 'education', 'customer_lifetime_value',\n",
+    "       'income', 'monthly_premium_auto', 'number_of_open_complaints',\n",
+    "       'policy_type', 'vehicle_class', 'total_claim_amount']\n",
+    "cus_data3 = cus_data3[desired_order]\n",
+    "\n",
+    "# Checking if everything is ok\n",
+    "print(cus_data3.columns)\n",
+    "print(cus_data2.columns)\n",
+    "print(cus_data1.columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 352,
+   "id": "7aadaafc",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>education</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>number_of_open_complaints</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>6970</th>\n",
+       "      <td>NA56063</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>43019.01278</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>904.378268</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6971</th>\n",
+       "      <td>CA62597</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>7482.851041</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>978.257137</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6972</th>\n",
+       "      <td>ZO23305</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>4929.549699</td>\n",
+       "      <td>25632.0</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>351.270869</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6973</th>\n",
+       "      <td>UD20999</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Master</td>\n",
+       "      <td>2537.667511</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>326.400000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6974</th>\n",
+       "      <td>FQ66351</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>5322.291688</td>\n",
+       "      <td>33681.0</td>\n",
+       "      <td>138.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>873.127345</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>23405.98798</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>College</td>\n",
+       "      <td>3096.511217</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>Bachelor</td>\n",
+       "      <td>8163.890428</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>7524.442436</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>College</td>\n",
+       "      <td>2611.836866</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender education customer_lifetime_value   income  \\\n",
+       "6970  NA56063  California      M   College             43019.01278      0.0   \n",
+       "6971  CA62597  California      F  Bachelor             7482.851041      0.0   \n",
+       "6972  ZO23305  California      M  Bachelor             4929.549699  25632.0   \n",
+       "6973  UD20999  California      M    Master             2537.667511      0.0   \n",
+       "6974  FQ66351  California      F  Bachelor             5322.291688  33681.0   \n",
+       "...       ...         ...    ...       ...                     ...      ...   \n",
+       "7065  LA72316  California      M  Bachelor             23405.98798  71941.0   \n",
+       "7066  PK87824  California      F   College             3096.511217  21604.0   \n",
+       "7067  TD14365  California      M  Bachelor             8163.890428      0.0   \n",
+       "7068  UP19263  California      M   College             7524.442436  21941.0   \n",
+       "7069  Y167826  California      M   College             2611.836866      0.0   \n",
+       "\n",
+       "      monthly_premium_auto number_of_open_complaints     policy_type  \\\n",
+       "6970                 132.0                         0  Corporate Auto   \n",
+       "6971                 101.0                         0  Corporate Auto   \n",
+       "6972                  63.0                         0   Personal Auto   \n",
+       "6973                  68.0                         0  Corporate Auto   \n",
+       "6974                 138.0                         1   Personal Auto   \n",
+       "...                    ...                       ...             ...   \n",
+       "7065                  73.0                         0   Personal Auto   \n",
+       "7066                  79.0                         0  Corporate Auto   \n",
+       "7067                  85.0                         3  Corporate Auto   \n",
+       "7068                  96.0                         0   Personal Auto   \n",
+       "7069                  77.0                         0  Corporate Auto   \n",
+       "\n",
+       "      vehicle_class  total_claim_amount  \n",
+       "6970            SUV          904.378268  \n",
+       "6971            SUV          978.257137  \n",
+       "6972   Two-Door Car          351.270869  \n",
+       "6973  Four-Door Car          326.400000  \n",
+       "6974            SUV          873.127345  \n",
+       "...             ...                 ...  \n",
+       "7065  Four-Door Car          198.234764  \n",
+       "7066  Four-Door Car          379.200000  \n",
+       "7067  Four-Door Car          790.784983  \n",
+       "7068  Four-Door Car          691.200000  \n",
+       "7069   Two-Door Car          369.600000  \n",
+       "\n",
+       "[100 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 352,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Concatenate the three dataframes\n",
+    "\n",
+    "cus_data = pd.concat([cus_data1, cus_data2, cus_data3], axis = 0) # axis = 0 is not mandatory but is better putting it on\n",
+    "\n",
+    "cus_data.tail(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 353,
+   "id": "47da75af",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"\\n\\n'income','monthly_premium_auto','total_claim_amount ' are numerical, the other ones are object (strings or whatsoever).\\n\\ncustomer                      object = Id referring to the customer\\nst                            object = State in which the car was bought\\ngender                        object = gender of the buyer\\neducation                     object = education of the buyer\\ncustomer_lifetime_value       object = a metric that represents the total net profit a company can expect to generate from a customer throughout their entire relationship\\nincome                       float64 = annual income of the buyer\\nmonthly_premium_auto         float64 = monthly premium that the buyer has to pay\\nnumber_of_open_complaints     object = ...\\npolicy_type                   object = ...\\nvehicle_class                 object = ...\\ntotal_claim_amount           float64 = ...\\n\\n\""
+      ]
+     },
+     "execution_count": 353,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Which columns are numerical?\n",
+    "# Which columns are categorial?\n",
+    "\n",
+    "cus_data.dtypes\n",
+    "\n",
+    "\n",
+    "'''\n",
+    "\n",
+    "'income','monthly_premium_auto','total_claim_amount ' are numerical, the other ones are object (strings or whatsoever).\n",
+    "\n",
+    "customer                      object = Id referring to the customer\n",
+    "st                            object = State in which the car was bought\n",
+    "gender                        object = gender of the buyer\n",
+    "education                     object = education of the buyer\n",
+    "customer_lifetime_value       object = a metric that represents the total net profit a company can expect to generate from a customer throughout their entire relationship\n",
+    "income                       float64 = annual income of the buyer\n",
+    "monthly_premium_auto         float64 = monthly premium that the buyer has to pay\n",
+    "number_of_open_complaints     object = ...\n",
+    "policy_type                   object = ...\n",
+    "vehicle_class                 object = ...\n",
+    "total_claim_amount           float64 = ...\n",
+    "\n",
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 354,
+   "id": "ef630730",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>RB50392</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1000.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>2.704934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>697953.59%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1288743.17%</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>764586.18%</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>536307.65%</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  customer          st gender customer_lifetime_value   income  \\\n",
+       "0  RB50392  Washington    NaN                     NaN      0.0   \n",
+       "1  QZ44356     Arizona      F              697953.59%      0.0   \n",
+       "2  AI49188      Nevada      F             1288743.17%  48767.0   \n",
+       "3  WW63253  California      M              764586.18%      0.0   \n",
+       "4  GA49547  Washington      M              536307.65%  36357.0   \n",
+       "\n",
+       "   monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "0                1000.0   Personal Auto  Four-Door Car            2.704934  \n",
+       "1                  94.0   Personal Auto  Four-Door Car         1131.464935  \n",
+       "2                 108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "3                 106.0  Corporate Auto            SUV          529.881344  \n",
+       "4                  68.0   Personal Auto  Four-Door Car           17.269323  "
+      ]
+     },
+     "execution_count": 354,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Data cleaning\n",
+    "\n",
+    "# Delete the column education and the number of open complaints from the dataframe\n",
+    "\n",
+    "cus_data = cus_data.drop(['education'], axis = 1)\n",
+    "\n",
+    "cus_data = cus_data.drop(['number_of_open_complaints'], axis = 1)\n",
+    "\n",
+    "cus_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b78633cc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 355,
+   "id": "331b02a9",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>6.979536e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1.288743e+08</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.645862e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.363076e+07</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>OC83172</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>8.256298e+07</td>\n",
+       "      <td>62902.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>159.383042</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>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.340599e+06</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>3.096511e+05</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>8.163890e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.524442e+05</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.611837e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9010 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender  customer_lifetime_value   income  \\\n",
+       "1     QZ44356     Arizona      F             6.979536e+07      0.0   \n",
+       "2     AI49188      Nevada      F             1.288743e+08  48767.0   \n",
+       "3     WW63253  California      M             7.645862e+07      0.0   \n",
+       "4     GA49547  Washington      M             5.363076e+07  36357.0   \n",
+       "5     OC83172      Oregon      F             8.256298e+07  62902.0   \n",
+       "...       ...         ...    ...                      ...      ...   \n",
+       "7065  LA72316  California      M             2.340599e+06  71941.0   \n",
+       "7066  PK87824  California      F             3.096511e+05  21604.0   \n",
+       "7067  TD14365  California      M             8.163890e+05      0.0   \n",
+       "7068  UP19263  California      M             7.524442e+05  21941.0   \n",
+       "7069  Y167826  California      M             2.611837e+05      0.0   \n",
+       "\n",
+       "      monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "1                     94.0   Personal Auto  Four-Door Car         1131.464935  \n",
+       "2                    108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "3                    106.0  Corporate Auto            SUV          529.881344  \n",
+       "4                     68.0   Personal Auto  Four-Door Car           17.269323  \n",
+       "5                     69.0   Personal Auto   Two-Door Car          159.383042  \n",
+       "...                    ...             ...            ...                 ...  \n",
+       "7065                  73.0   Personal Auto  Four-Door Car          198.234764  \n",
+       "7066                  79.0  Corporate Auto  Four-Door Car          379.200000  \n",
+       "7067                  85.0  Corporate Auto  Four-Door Car          790.784983  \n",
+       "7068                  96.0   Personal Auto  Four-Door Car          691.200000  \n",
+       "7069                  77.0  Corporate Auto   Two-Door Car          369.600000  \n",
+       "\n",
+       "[9010 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 355,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Correct the values in the column customer lifetime value. \n",
+    "# They are given as a percent, so multiply them by 100 and change `dtype` to `numerical` type\n",
+    "\n",
+    "cus_data = cus_data.dropna() # removing null values\n",
+    "\n",
+    "cus_data['customer_lifetime_value']  = cus_data['customer_lifetime_value'].astype(str) # On cus_data3 (third df) the dtype of the customer lifetime column was 'float', then before cutting out the '%' character i had to convert the column to 'str' dtype\n",
+    "\n",
+    "cus_data['customer_lifetime_value'] = cus_data['customer_lifetime_value'].str.replace('%','') # Excluding the '%' character from the colum so that i can convert all the column to float.\n",
+    "\n",
+    "cus_data['customer_lifetime_value'] = cus_data['customer_lifetime_value'].astype(float) # Converting the column to float dtype.\n",
+    "\n",
+    "cus_data['customer_lifetime_value'] = cus_data['customer_lifetime_value'].mul(100) # Multiplying the values by 100, the numbers are very large. ex -> 6.979536e+07 = 69,795,360\n",
+    "\n",
+    "\n",
+    "cus_data\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 356,
+   "id": "e1a37433",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QZ44356</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>F</td>\n",
+       "      <td>6.979536e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>1131.464935</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1.288743e+08</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WW63253</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.645862e+07</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>106.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>SUV</td>\n",
+       "      <td>529.881344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.363076e+07</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>OC83172</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>8.256298e+07</td>\n",
+       "      <td>62902.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>159.383042</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>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.340599e+06</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>3.096511e+05</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7067</th>\n",
+       "      <td>TD14365</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>8.163890e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>790.784983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.524442e+05</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7069</th>\n",
+       "      <td>Y167826</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.611837e+05</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>369.600000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9007 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender  customer_lifetime_value   income  \\\n",
+       "1     QZ44356     Arizona      F             6.979536e+07      0.0   \n",
+       "2     AI49188      Nevada      F             1.288743e+08  48767.0   \n",
+       "3     WW63253  California      M             7.645862e+07      0.0   \n",
+       "4     GA49547  Washington      M             5.363076e+07  36357.0   \n",
+       "5     OC83172      Oregon      F             8.256298e+07  62902.0   \n",
+       "...       ...         ...    ...                      ...      ...   \n",
+       "7065  LA72316  California      M             2.340599e+06  71941.0   \n",
+       "7066  PK87824  California      F             3.096511e+05  21604.0   \n",
+       "7067  TD14365  California      M             8.163890e+05      0.0   \n",
+       "7068  UP19263  California      M             7.524442e+05  21941.0   \n",
+       "7069  Y167826  California      M             2.611837e+05      0.0   \n",
+       "\n",
+       "      monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "1                     94.0   Personal Auto  Four-Door Car         1131.464935  \n",
+       "2                    108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "3                    106.0  Corporate Auto            SUV          529.881344  \n",
+       "4                     68.0   Personal Auto  Four-Door Car           17.269323  \n",
+       "5                     69.0   Personal Auto   Two-Door Car          159.383042  \n",
+       "...                    ...             ...            ...                 ...  \n",
+       "7065                  73.0   Personal Auto  Four-Door Car          198.234764  \n",
+       "7066                  79.0  Corporate Auto  Four-Door Car          379.200000  \n",
+       "7067                  85.0  Corporate Auto  Four-Door Car          790.784983  \n",
+       "7068                  96.0   Personal Auto  Four-Door Car          691.200000  \n",
+       "7069                  77.0  Corporate Auto   Two-Door Car          369.600000  \n",
+       "\n",
+       "[9007 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 356,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check for duplicate rows in the data and remove if any.\n",
+    "\n",
+    "cus_data.duplicated()\n",
+    "\n",
+    "cus_data.drop_duplicates()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 357,
+   "id": "0135494b",
+   "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>st</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>customer_lifetime_value</th>\n",
+       "      <th>income</th>\n",
+       "      <th>monthly_premium_auto</th>\n",
+       "      <th>policy_type</th>\n",
+       "      <th>vehicle_class</th>\n",
+       "      <th>total_claim_amount</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AI49188</td>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>F</td>\n",
+       "      <td>1.288743e+08</td>\n",
+       "      <td>48767.0</td>\n",
+       "      <td>108.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>566.472247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GA49547</td>\n",
+       "      <td>Washington</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.363076e+07</td>\n",
+       "      <td>36357.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>17.269323</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>OC83172</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>8.256298e+07</td>\n",
+       "      <td>62902.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>159.383042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>XZ87318</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>F</td>\n",
+       "      <td>5.380899e+07</td>\n",
+       "      <td>55350.0</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>321.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>DY87989</td>\n",
+       "      <td>Oregon</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.412750e+08</td>\n",
+       "      <td>14072.0</td>\n",
+       "      <td>71.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>511.200000</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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7063</th>\n",
+       "      <td>TF56202</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>5.032165e+05</td>\n",
+       "      <td>66367.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Two-Door Car</td>\n",
+       "      <td>307.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7064</th>\n",
+       "      <td>YM19146</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>4.100399e+05</td>\n",
+       "      <td>47761.0</td>\n",
+       "      <td>104.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>541.282007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7065</th>\n",
+       "      <td>LA72316</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>2.340599e+06</td>\n",
+       "      <td>71941.0</td>\n",
+       "      <td>73.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>198.234764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7066</th>\n",
+       "      <td>PK87824</td>\n",
+       "      <td>California</td>\n",
+       "      <td>F</td>\n",
+       "      <td>3.096511e+05</td>\n",
+       "      <td>21604.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>Corporate Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>379.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7068</th>\n",
+       "      <td>UP19263</td>\n",
+       "      <td>California</td>\n",
+       "      <td>M</td>\n",
+       "      <td>7.524442e+05</td>\n",
+       "      <td>21941.0</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>Personal Auto</td>\n",
+       "      <td>Four-Door Car</td>\n",
+       "      <td>691.200000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6741 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     customer          st gender  customer_lifetime_value   income  \\\n",
+       "2     AI49188      Nevada      F             1.288743e+08  48767.0   \n",
+       "4     GA49547  Washington      M             5.363076e+07  36357.0   \n",
+       "5     OC83172      Oregon      F             8.256298e+07  62902.0   \n",
+       "6     XZ87318      Oregon      F             5.380899e+07  55350.0   \n",
+       "8     DY87989      Oregon      M             2.412750e+08  14072.0   \n",
+       "...       ...         ...    ...                      ...      ...   \n",
+       "7063  TF56202  California      M             5.032165e+05  66367.0   \n",
+       "7064  YM19146  California      F             4.100399e+05  47761.0   \n",
+       "7065  LA72316  California      M             2.340599e+06  71941.0   \n",
+       "7066  PK87824  California      F             3.096511e+05  21604.0   \n",
+       "7068  UP19263  California      M             7.524442e+05  21941.0   \n",
+       "\n",
+       "      monthly_premium_auto     policy_type  vehicle_class  total_claim_amount  \n",
+       "2                    108.0   Personal Auto   Two-Door Car          566.472247  \n",
+       "4                     68.0   Personal Auto  Four-Door Car           17.269323  \n",
+       "5                     69.0   Personal Auto   Two-Door Car          159.383042  \n",
+       "6                     67.0  Corporate Auto  Four-Door Car          321.600000  \n",
+       "8                     71.0  Corporate Auto  Four-Door Car          511.200000  \n",
+       "...                    ...             ...            ...                 ...  \n",
+       "7063                  64.0   Personal Auto   Two-Door Car          307.200000  \n",
+       "7064                 104.0   Personal Auto  Four-Door Car          541.282007  \n",
+       "7065                  73.0   Personal Auto  Four-Door Car          198.234764  \n",
+       "7066                  79.0  Corporate Auto  Four-Door Car          379.200000  \n",
+       "7068                  96.0   Personal Auto  Four-Door Car          691.200000  \n",
+       "\n",
+       "[6741 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 357,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filter out the data for customers who have an income of 0 or less.\n",
+    "\n",
+    "cus_data = cus_data.loc[cus_data['income'] > 0]\n",
+    "\n",
+    "cus_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2c6f4495",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d155737",
+   "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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