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--- a/.ipynb_checkpoints/Classification_Telco_customer_churn-checkpoint.ipynb
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@@ -1,2276 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Project Title: \n",
-    "Telecommunications Customer Churn Prediction Analysis"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Business Understanding"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 1. Introduction\n",
-    "This project aims to assist a telecom company in understanding their data and predicting customer churn. The company has provided access to three different datasets: the first dataset with 3000 records stored in a remote Microsoft SQL Server database, the second dataset with 2000 records stored on OneDrive, and the third dataset hosted on a GitHub repository.\n",
-    "\n",
-    "### 1.1. Objectives\n",
-    "Understand the data: Our first objective is to provide insights into the telecom company's data, including customer demographics, services availed, and payment details. This understanding will enable the company to make informed business decisions.\n",
-    "\n",
-    "Find the lifetime value of each customer: By analyzing the data, we aim to identify factors that influence the rate at which customers churn. Understanding customer behavior and identifying key predictors will help the telecom company estimate the lifetime value of each customer.\n",
-    "\n",
-    "Predict customer churn: The primary objective is to develop a predictive model that accurately determines whether a customer is likely to churn or not. We will employ machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., to build a model that effectively predicts customer churn.\n",
-    "\n",
-    "### 1.2. Methodology\n",
-    "To achieve our objectives, we will follow the CRISP-DM framework, which consists of the following steps:\n",
-    "\n",
-    "Data exploration: We will thoroughly explore the datasets to gain insights into the available variables, their distributions, and relationships. This step will provide us with an initial understanding of the data and help identify any data quality issues.\n",
-    "\n",
-    "Missing value computations: We will identify missing values in the datasets and decide on an appropriate strategy for handling them. This may involve imputing missing values or removing data points with missing values.\n",
-    "\n",
-    "Feature engineering: We will perform feature engineering to transform and create new variables that can potentially improve the predictive power of our models. This step may include encoding categorical variables, scaling numerical variables, or creating interaction terms.\n",
-    "\n",
-    "Model development: We will utilize various machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., to develop predictive models for customer churn. We will train the models on a subset of the data and evaluate their performance using appropriate metrics.\n",
-    "\n",
-    "Model evaluation and interpretation: We will evaluate the trained models using evaluation metrics such as accuracy, precision, recall, and F1-score. Additionally, we will interpret the models to understand the factors driving customer churn and their relative importance.\n",
-    "\n",
-    "Model optimization and hyperparameter tuning: We will fine-tune the models by optimizing their hyperparameters to improve their performance. This step may involve techniques like grid search or random search to find the optimal combination of hyperparameters.\n",
-    "\n",
-    "By following this methodology, we aim to provide valuable insights to the telecom company and develop a reliable predictive model for customer churn."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Load Datasets"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Installations"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Requirement already satisfied: pyodbc in c:\\users\\user\\anaconda3\\lib\\site-packages (4.0.34)\n",
-      "Note: you may need to restart the kernel to use updated packages.\n",
-      "Requirement already satisfied: openpyxl in c:\\users\\user\\anaconda3\\lib\\site-packages (3.0.10)\n",
-      "Requirement already satisfied: et_xmlfile in c:\\users\\user\\anaconda3\\lib\\site-packages (from openpyxl) (1.1.0)\n",
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "%pip install pyodbc\n",
-    "%pip install openpyxl"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load first dataset from SQL database"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Import necessary libraries\n",
-    "import pyodbc\n",
-    "import pandas as pd\n",
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Establish a connection\n",
-    "server = 'dap-projects-database.database.windows.net'\n",
-    "database = 'dapDB'\n",
-    "username = 'dataAnalyst_LP2'\n",
-    "password = 'A3g@3kR$2y'\n",
-    "\n",
-    "# Create the connection string using the ODBC driver format\n",
-    "conn_str = f'DRIVER={{ODBC Driver 17 for SQL Server}};SERVER={server};DATABASE={database};UID={username};PWD={password}'\n",
-    "\n",
-    "# Establish the connection using the connection string\n",
-    "conn = pyodbc.connect(conn_str)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Query the database to retrieve the data\n",
-    "query = 'SELECT TOP 3000 * FROM LP2_Telco_churn_first_3000'\n",
-    "df_db = pd.read_sql(query, conn)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Close connection\n",
-    "conn.close()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7590-VHVEG</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>29.850000</td>\n",
-       "      <td>29.850000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>5575-GNVDE</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>34</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>56.950001</td>\n",
-       "      <td>1889.500000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3668-QPYBK</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>53.849998</td>\n",
-       "      <td>108.150002</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>7795-CFOCW</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>45</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Bank transfer (automatic)</td>\n",
-       "      <td>42.299999</td>\n",
-       "      <td>1840.750000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>9237-HQITU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>70.699997</td>\n",
-       "      <td>151.649994</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID  gender  SeniorCitizen  Partner  Dependents  tenure  \\\n",
-       "0  7590-VHVEG  Female          False     True       False       1   \n",
-       "1  5575-GNVDE    Male          False    False       False      34   \n",
-       "2  3668-QPYBK    Male          False    False       False       2   \n",
-       "3  7795-CFOCW    Male          False    False       False      45   \n",
-       "4  9237-HQITU  Female          False    False       False       2   \n",
-       "\n",
-       "   PhoneService MultipleLines InternetService OnlineSecurity  ...  \\\n",
-       "0         False          None             DSL          False  ...   \n",
-       "1          True         False             DSL           True  ...   \n",
-       "2          True         False             DSL           True  ...   \n",
-       "3         False          None             DSL           True  ...   \n",
-       "4          True         False     Fiber optic          False  ...   \n",
-       "\n",
-       "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
-       "0            False       False       False           False  Month-to-month   \n",
-       "1             True       False       False           False        One year   \n",
-       "2            False       False       False           False  Month-to-month   \n",
-       "3             True        True       False           False        One year   \n",
-       "4            False       False       False           False  Month-to-month   \n",
-       "\n",
-       "  PaperlessBilling              PaymentMethod MonthlyCharges  TotalCharges  \\\n",
-       "0             True           Electronic check      29.850000     29.850000   \n",
-       "1            False               Mailed check      56.950001   1889.500000   \n",
-       "2             True               Mailed check      53.849998    108.150002   \n",
-       "3            False  Bank transfer (automatic)      42.299999   1840.750000   \n",
-       "4             True           Electronic check      70.699997    151.649994   \n",
-       "\n",
-       "   Churn  \n",
-       "0  False  \n",
-       "1  False  \n",
-       "2   True  \n",
-       "3  False  \n",
-       "4   True  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Display the dataframe\n",
-    "df_db.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load second dataset (excelfile)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>OnlineBackup</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7613-LLQFO</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>84.45</td>\n",
-       "      <td>1059.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>4568-TTZRT</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>20.40</td>\n",
-       "      <td>181.8</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>9513-DXHDA</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>81.70</td>\n",
-       "      <td>2212.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2640-PMGFL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>79.50</td>\n",
-       "      <td>2180.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3801-HMYNL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>89.15</td>\n",
-       "      <td>89.15</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  7613-LLQFO   Male              0      No         No      12          Yes   \n",
-       "1  4568-TTZRT   Male              0      No         No       9          Yes   \n",
-       "2  9513-DXHDA   Male              0      No         No      27          Yes   \n",
-       "3  2640-PMGFL   Male              0      No        Yes      27          Yes   \n",
-       "4  3801-HMYNL   Male              0     Yes        Yes       1          Yes   \n",
-       "\n",
-       "  MultipleLines InternetService       OnlineSecurity         OnlineBackup  \\\n",
-       "0           Yes     Fiber optic                   No                   No   \n",
-       "1            No              No  No internet service  No internet service   \n",
-       "2            No             DSL                  Yes                   No   \n",
-       "3           Yes     Fiber optic                   No                   No   \n",
-       "4            No     Fiber optic                   No                   No   \n",
-       "\n",
-       "      DeviceProtection          TechSupport          StreamingTV  \\\n",
-       "0                   No                   No                  Yes   \n",
-       "1  No internet service  No internet service  No internet service   \n",
-       "2                  Yes                  Yes                  Yes   \n",
-       "3                   No                  Yes                   No   \n",
-       "4                   No                   No                  Yes   \n",
-       "\n",
-       "       StreamingMovies        Contract PaperlessBilling     PaymentMethod  \\\n",
-       "0                   No  Month-to-month              Yes  Electronic check   \n",
-       "1  No internet service  Month-to-month               No      Mailed check   \n",
-       "2                  Yes        One year               No  Electronic check   \n",
-       "3                   No  Month-to-month              Yes  Electronic check   \n",
-       "4                  Yes  Month-to-month               No      Mailed check   \n",
-       "\n",
-       "   MonthlyCharges TotalCharges  \n",
-       "0           84.45      1059.55  \n",
-       "1           20.40        181.8  \n",
-       "2           81.70      2212.55  \n",
-       "3           79.50      2180.55  \n",
-       "4           89.15        89.15  "
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Read the excel file into a pandas dataframe\n",
-    "df_excel = pd.read_excel('Telco-churn-second-2000.xlsx')\n",
-    "\n",
-    "# Display the dataframe\n",
-    "df_excel.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load third dataset (csv file)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>5600-PDUJF</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>49.50</td>\n",
-       "      <td>312.7</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>8292-TYSPY</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>19</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>55.00</td>\n",
-       "      <td>1046.5</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0567-XRHCU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>69</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No phone service</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Two year</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>43.95</td>\n",
-       "      <td>2960.1</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1867-BDVFH</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>11</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>74.35</td>\n",
-       "      <td>834.2</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2067-QYTCF</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>64</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>111.15</td>\n",
-       "      <td>6953.4</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  5600-PDUJF    Male              0      No         No       6          Yes   \n",
-       "1  8292-TYSPY    Male              0      No         No      19          Yes   \n",
-       "2  0567-XRHCU  Female              0     Yes        Yes      69           No   \n",
-       "3  1867-BDVFH    Male              0     Yes        Yes      11          Yes   \n",
-       "4  2067-QYTCF  Female              0     Yes         No      64          Yes   \n",
-       "\n",
-       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
-       "0                No             DSL             No  ...               No   \n",
-       "1                No             DSL             No  ...              Yes   \n",
-       "2  No phone service             DSL            Yes  ...              Yes   \n",
-       "3               Yes     Fiber optic             No  ...               No   \n",
-       "4               Yes     Fiber optic             No  ...              Yes   \n",
-       "\n",
-       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
-       "0         Yes          No              No  Month-to-month              Yes   \n",
-       "1         Yes          No              No  Month-to-month              Yes   \n",
-       "2          No          No             Yes        Two year              Yes   \n",
-       "3          No          No              No  Month-to-month              Yes   \n",
-       "4         Yes         Yes             Yes  Month-to-month              Yes   \n",
-       "\n",
-       "             PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
-       "0  Credit card (automatic)          49.50         312.7    No  \n",
-       "1  Credit card (automatic)          55.00        1046.5   Yes  \n",
-       "2  Credit card (automatic)          43.95        2960.1    No  \n",
-       "3         Electronic check          74.35         834.2   Yes  \n",
-       "4         Electronic check         111.15        6953.4    No  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Read third dataset\n",
-    "df_csv = pd.read_csv('LP2_Telco-churn-last-2000.csv')\n",
-    "\n",
-    "# Display the dataframe\n",
-    "df_csv.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Questions and Hypothesis"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Hypothesis\n",
-    "\n",
-    "H0: The churn rate of customers in the telecom company is not significantly influenced by various factors related to their \n",
-    "demographics, services, and payment methods.\n",
-    "\n",
-    "H1: The churn rate of customers in the telecom company is influenced by various factors related to their demographics, services, and payment methods."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Questions\n",
-    "1. Is there a relationship between the monthly charges and the likelihood of churn?\n",
-    "2. Do customers who have internet service, specifically fiber optic, exhibit a higher churn rate compared to those with DSL or no internet service?\n",
-    "3. Does the availability of online security, online backup, device protection, and tech support impact the churn rate?\n",
-    "4. How does the churn rate vary based on the customers' gender?\n",
-    "5. Does the presence of a partner influence the likelihood of churn?\n",
-    "6. Is there a correlation between the tenure of customers and their churn rate?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Data Exploration"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Explore individual datasets "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Explore The Dataframe from the SQL Database(df_db)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 3000 entries, 0 to 2999\n",
-      "Data columns (total 21 columns):\n",
-      " #   Column            Non-Null Count  Dtype  \n",
-      "---  ------            --------------  -----  \n",
-      " 0   customerID        3000 non-null   object \n",
-      " 1   gender            3000 non-null   object \n",
-      " 2   SeniorCitizen     3000 non-null   bool   \n",
-      " 3   Partner           3000 non-null   bool   \n",
-      " 4   Dependents        3000 non-null   bool   \n",
-      " 5   tenure            3000 non-null   int64  \n",
-      " 6   PhoneService      3000 non-null   bool   \n",
-      " 7   MultipleLines     2731 non-null   object \n",
-      " 8   InternetService   3000 non-null   object \n",
-      " 9   OnlineSecurity    2349 non-null   object \n",
-      " 10  OnlineBackup      2349 non-null   object \n",
-      " 11  DeviceProtection  2349 non-null   object \n",
-      " 12  TechSupport       2349 non-null   object \n",
-      " 13  StreamingTV       2349 non-null   object \n",
-      " 14  StreamingMovies   2349 non-null   object \n",
-      " 15  Contract          3000 non-null   object \n",
-      " 16  PaperlessBilling  3000 non-null   bool   \n",
-      " 17  PaymentMethod     3000 non-null   object \n",
-      " 18  MonthlyCharges    3000 non-null   float64\n",
-      " 19  TotalCharges      2995 non-null   float64\n",
-      " 20  Churn             2999 non-null   object \n",
-      "dtypes: bool(5), float64(2), int64(1), object(13)\n",
-      "memory usage: 389.8+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Column information\n",
-    "df_db.info()"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "df_db has all 21 columns arranged as decribed in the readme file. The format for CustomerID in row 2999 is different from the rest. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(3000, 21)"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df_db.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Column: customerID - Unique Values: ['7590-VHVEG' '5575-GNVDE' '3668-QPYBK' ... '1891-FZYSA' '4770-UEZOX'\n",
-      " '1A1:U3001038-RQOST']\n",
-      "=============================================\n",
-      "Column: gender - Unique Values: ['Female' 'Male']\n",
-      "=============================================\n",
-      "Column: SeniorCitizen - Unique Values: [False  True]\n",
-      "=============================================\n",
-      "Column: Partner - Unique Values: [ True False]\n",
-      "=============================================\n",
-      "Column: Dependents - Unique Values: [False  True]\n",
-      "=============================================\n",
-      "Column: tenure - Unique Values: [ 1 34  2 45  8 22 10 28 62 13 16 58 49 25 69 52 71 21 12 30 47 72 17 27\n",
-      "  5 46 11 70 63 43 15 60 18 66  9  3 31 50 64 56  7 42 35 48 29 65 38 68\n",
-      " 32 55 37 36 41  6  4 33 67 23 57 61 14 20 53 40 59 24 44 19 54 51 26  0\n",
-      " 39]\n",
-      "=============================================\n",
-      "Column: PhoneService - Unique Values: [False  True]\n",
-      "=============================================\n",
-      "Column: MultipleLines - Unique Values: [None False True]\n",
-      "=============================================\n",
-      "Column: InternetService - Unique Values: ['DSL' 'Fiber optic' 'No']\n",
-      "=============================================\n",
-      "Column: OnlineSecurity - Unique Values: [False True None]\n",
-      "=============================================\n",
-      "Column: OnlineBackup - Unique Values: [True False None]\n",
-      "=============================================\n",
-      "Column: DeviceProtection - Unique Values: [False True None]\n",
-      "=============================================\n",
-      "Column: TechSupport - Unique Values: [False True None]\n",
-      "=============================================\n",
-      "Column: StreamingTV - Unique Values: [False True None]\n",
-      "=============================================\n",
-      "Column: StreamingMovies - Unique Values: [False True None]\n",
-      "=============================================\n",
-      "Column: Contract - Unique Values: ['Month-to-month' 'One year' 'Two year']\n",
-      "=============================================\n",
-      "Column: PaperlessBilling - Unique Values: [ True False]\n",
-      "=============================================\n",
-      "Column: PaymentMethod - Unique Values: ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
-      " 'Credit card (automatic)']\n",
-      "=============================================\n",
-      "Column: MonthlyCharges - Unique Values: [29.85000038 56.95000076 53.84999847 ... 33.90000153 34.\n",
-      " 38.59999847]\n",
-      "=============================================\n",
-      "Column: TotalCharges - Unique Values: [  29.85000038 1889.5         108.15000153 ... 6143.14990234  144.80000305\n",
-      "  414.95001221]\n",
-      "=============================================\n",
-      "Column: Churn - Unique Values: [False True None]\n",
-      "=============================================\n"
-     ]
-    }
-   ],
-   "source": [
-    "# check unique values of each column\n",
-    "for column in df_db.columns:\n",
-    "    print('Column: {} - Unique Values: {}'.format(column, df_db[column].unique()))\n",
-    "    print('==='*15)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "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>tenure</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>3000.000000</td>\n",
-       "      <td>3000.000000</td>\n",
-       "      <td>2995.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>32.527333</td>\n",
-       "      <td>65.347400</td>\n",
-       "      <td>2301.278315</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>24.637768</td>\n",
-       "      <td>30.137053</td>\n",
-       "      <td>2274.987884</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.400000</td>\n",
-       "      <td>18.799999</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>35.787499</td>\n",
-       "      <td>415.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>29.000000</td>\n",
-       "      <td>70.900002</td>\n",
-       "      <td>1404.650024</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>56.000000</td>\n",
-       "      <td>90.262501</td>\n",
-       "      <td>3868.725098</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>118.650002</td>\n",
-       "      <td>8564.750000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            tenure  MonthlyCharges  TotalCharges\n",
-       "count  3000.000000     3000.000000   2995.000000\n",
-       "mean     32.527333       65.347400   2301.278315\n",
-       "std      24.637768       30.137053   2274.987884\n",
-       "min       0.000000       18.400000     18.799999\n",
-       "25%       9.000000       35.787499    415.250000\n",
-       "50%      29.000000       70.900002   1404.650024\n",
-       "75%      56.000000       90.262501   3868.725098\n",
-       "max      72.000000      118.650002   8564.750000"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Summary statistics of df_db to get insights into the distribution and basic characteristics of the numerical variables\n",
-    "df_db.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "customerID            0\n",
-       "gender                0\n",
-       "SeniorCitizen         0\n",
-       "Partner               0\n",
-       "Dependents            0\n",
-       "tenure                0\n",
-       "PhoneService          0\n",
-       "MultipleLines       269\n",
-       "InternetService       0\n",
-       "OnlineSecurity      651\n",
-       "OnlineBackup        651\n",
-       "DeviceProtection    651\n",
-       "TechSupport         651\n",
-       "StreamingTV         651\n",
-       "StreamingMovies     651\n",
-       "Contract              0\n",
-       "PaperlessBilling      0\n",
-       "PaymentMethod         0\n",
-       "MonthlyCharges        0\n",
-       "TotalCharges          5\n",
-       "Churn                 1\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Handling missing values\n",
-    "df_db.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Explore df_excel"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>OnlineBackup</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7613-LLQFO</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>84.45</td>\n",
-       "      <td>1059.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>4568-TTZRT</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>20.40</td>\n",
-       "      <td>181.8</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>9513-DXHDA</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>81.70</td>\n",
-       "      <td>2212.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2640-PMGFL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>79.50</td>\n",
-       "      <td>2180.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3801-HMYNL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>89.15</td>\n",
-       "      <td>89.15</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  7613-LLQFO   Male              0      No         No      12          Yes   \n",
-       "1  4568-TTZRT   Male              0      No         No       9          Yes   \n",
-       "2  9513-DXHDA   Male              0      No         No      27          Yes   \n",
-       "3  2640-PMGFL   Male              0      No        Yes      27          Yes   \n",
-       "4  3801-HMYNL   Male              0     Yes        Yes       1          Yes   \n",
-       "\n",
-       "  MultipleLines InternetService       OnlineSecurity         OnlineBackup  \\\n",
-       "0           Yes     Fiber optic                   No                   No   \n",
-       "1            No              No  No internet service  No internet service   \n",
-       "2            No             DSL                  Yes                   No   \n",
-       "3           Yes     Fiber optic                   No                   No   \n",
-       "4            No     Fiber optic                   No                   No   \n",
-       "\n",
-       "      DeviceProtection          TechSupport          StreamingTV  \\\n",
-       "0                   No                   No                  Yes   \n",
-       "1  No internet service  No internet service  No internet service   \n",
-       "2                  Yes                  Yes                  Yes   \n",
-       "3                   No                  Yes                   No   \n",
-       "4                   No                   No                  Yes   \n",
-       "\n",
-       "       StreamingMovies        Contract PaperlessBilling     PaymentMethod  \\\n",
-       "0                   No  Month-to-month              Yes  Electronic check   \n",
-       "1  No internet service  Month-to-month               No      Mailed check   \n",
-       "2                  Yes        One year               No  Electronic check   \n",
-       "3                   No  Month-to-month              Yes  Electronic check   \n",
-       "4                  Yes  Month-to-month               No      Mailed check   \n",
-       "\n",
-       "   MonthlyCharges TotalCharges  \n",
-       "0           84.45      1059.55  \n",
-       "1           20.40        181.8  \n",
-       "2           81.70      2212.55  \n",
-       "3           79.50      2180.55  \n",
-       "4           89.15        89.15  "
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Call the dataset df_excel\n",
-    "df_excel.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 2000 entries, 0 to 1999\n",
-      "Data columns (total 20 columns):\n",
-      " #   Column            Non-Null Count  Dtype  \n",
-      "---  ------            --------------  -----  \n",
-      " 0   customerID        2000 non-null   object \n",
-      " 1   gender            2000 non-null   object \n",
-      " 2   SeniorCitizen     2000 non-null   int64  \n",
-      " 3   Partner           2000 non-null   object \n",
-      " 4   Dependents        2000 non-null   object \n",
-      " 5   tenure            2000 non-null   int64  \n",
-      " 6   PhoneService      2000 non-null   object \n",
-      " 7   MultipleLines     2000 non-null   object \n",
-      " 8   InternetService   2000 non-null   object \n",
-      " 9   OnlineSecurity    2000 non-null   object \n",
-      " 10  OnlineBackup      2000 non-null   object \n",
-      " 11  DeviceProtection  2000 non-null   object \n",
-      " 12  TechSupport       2000 non-null   object \n",
-      " 13  StreamingTV       2000 non-null   object \n",
-      " 14  StreamingMovies   2000 non-null   object \n",
-      " 15  Contract          2000 non-null   object \n",
-      " 16  PaperlessBilling  2000 non-null   object \n",
-      " 17  PaymentMethod     2000 non-null   object \n",
-      " 18  MonthlyCharges    2000 non-null   float64\n",
-      " 19  TotalCharges      2000 non-null   object \n",
-      "dtypes: float64(1), int64(2), object(17)\n",
-      "memory usage: 312.6+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Column information\n",
-    "df_excel.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Column: customerID - Unique Values: ['7613-LLQFO' '4568-TTZRT' '9513-DXHDA' ... '4816-JBHOV' '8920-NAVAY'\n",
-      " '1699-TLDLZ']\n",
-      "=============================================\n",
-      "Column: gender - Unique Values: ['Male' 'Female']\n",
-      "=============================================\n",
-      "Column: SeniorCitizen - Unique Values: [0 1]\n",
-      "=============================================\n",
-      "Column: Partner - Unique Values: ['No' 'Yes']\n",
-      "=============================================\n",
-      "Column: Dependents - Unique Values: ['No' 'Yes']\n",
-      "=============================================\n",
-      "Column: tenure - Unique Values: [12  9 27  1 24 14 32 11 38 54 29 44 59  3 18 67 22 33  5  2 72 16  8 23\n",
-      " 50 17 68 25 71 46 48 61 37 65 49 64 21 10  6 51 47 52 35 45  4 60 28 39\n",
-      " 30 55 58 26 43 56 36 13 70 69 41 15 19 31 34 66 40  7 53 63 42  0 57 62\n",
-      " 20]\n",
-      "=============================================\n",
-      "Column: PhoneService - Unique Values: ['Yes' 'No']\n",
-      "=============================================\n",
-      "Column: MultipleLines - Unique Values: ['Yes' 'No' 'No phone service']\n",
-      "=============================================\n",
-      "Column: InternetService - Unique Values: ['Fiber optic' 'No' 'DSL']\n",
-      "=============================================\n",
-      "Column: OnlineSecurity - Unique Values: ['No' 'No internet service' 'Yes']\n",
-      "=============================================\n",
-      "Column: OnlineBackup - Unique Values: ['No' 'No internet service' 'Yes']\n",
-      "=============================================\n",
-      "Column: DeviceProtection - Unique Values: ['No' 'No internet service' 'Yes']\n",
-      "=============================================\n",
-      "Column: TechSupport - Unique Values: ['No' 'No internet service' 'Yes']\n",
-      "=============================================\n",
-      "Column: StreamingTV - Unique Values: ['Yes' 'No internet service' 'No']\n",
-      "=============================================\n",
-      "Column: StreamingMovies - Unique Values: ['No' 'No internet service' 'Yes']\n",
-      "=============================================\n",
-      "Column: Contract - Unique Values: ['Month-to-month' 'One year' 'Two year']\n",
-      "=============================================\n",
-      "Column: PaperlessBilling - Unique Values: ['Yes' 'No']\n",
-      "=============================================\n",
-      "Column: PaymentMethod - Unique Values: ['Electronic check' 'Mailed check' 'Credit card (automatic)'\n",
-      " 'Bank transfer (automatic)']\n",
-      "=============================================\n",
-      "Column: MonthlyCharges - Unique Values: [ 84.45  20.4   81.7   79.5   89.15  20.3   74.95  74.4   20.    25.\n",
-      "  80.45  19.75  65.65  71.    89.2   86.75  55.3   61.5   25.1   55.15\n",
-      "  34.05  19.95  89.7   26.3   84.95  20.7   43.25  48.35  79.55  71.05\n",
-      "  19.45 110.8   84.5   69.3   49.35  20.35 105.6   64.45 108.6   49.9\n",
-      "  30.3   30.4   45.4  103.3   84.15  44.45  85.4   89.9   55.05 104.1\n",
-      " 106.6   75.2   70.5   19.6   55.85  24.05  38.1  106.4   34.25 100.05\n",
-      "  68.65  45.8   75.75  84.4   96.4   20.55  50.95  90.5   79.4   58.75\n",
-      "  59.45 105.7   56.25  53.3   85.55  24.3   77.85  59.9   23.95  20.15\n",
-      " 105.35  95.65  87.05  81.    82.45  53.5   20.5   54.4   58.6   84.8\n",
-      "  61.4   79.65  94.45  79.8   54.2   74.05  49.15  19.4  113.65 106.\n",
-      "  25.95  19.1  103.4  100.55  95.4   75.15 107.9   19.5   85.95  24.95\n",
-      "  59.4   69.95  82.85  19.    38.85  30.6   95.    78.45  74.3   51.05\n",
-      "  19.2   99.55  70.   109.1   45.3   29.85  76.45  95.1   19.8   72.8\n",
-      "  18.95  76.65  99.15 101.75  75.45  64.1   25.65  75.1   95.85  72.75\n",
-      "  19.85  19.05  44.95  49.55  94.85  46.25  19.35  69.6   90.7  101.4\n",
-      "  20.25  48.8   74.35  68.75 100.2   20.85  95.9   45.    81.5   25.5\n",
-      "  48.9   84.1   81.3   95.2   36.45  83.3   25.05  89.85  49.85  54.65\n",
-      "  29.35  19.15  55.55  80.55  69.5  104.3   79.6   55.25  88.05 117.6\n",
-      "  19.65  70.55  93.85  65.8   20.05  80.    35.4   80.25  50.45  20.45\n",
-      "  24.7   77.3   29.75  44.9   29.8   74.65  71.95  20.75  56.3  105.25\n",
-      "  94.2   19.55  53.65  29.9   19.7   43.7   49.45 106.55  20.1   39.7\n",
-      "  54.5   83.8  111.6   86.65 106.75  62.1  104.5  101.8  110.6   84.9\n",
-      "  93.2   24.4   85.    87.45  85.8   91.1   70.75  74.8   24.8  100.85\n",
-      " 101.35  68.25 105.1   79.15  57.2   94.8  102.5   69.2   95.45 100.95\n",
-      "  88.5   35.    64.    69.1   80.2   49.3   84.35 117.2  103.45  77.95\n",
-      " 109.95  94.75  25.2   19.9   44.8   80.05 107.35  47.85  70.8   29.5\n",
-      "  59.1   25.55  75.55  85.65  70.15  95.3   70.25  50.3   97.8   46.3\n",
-      " 106.3   75.35  89.4   88.    83.15  43.8   62.05  74.15  84.05  20.9\n",
-      " 105.9   99.5   44.15  53.9   85.45  85.05  44.1   90.2   50.85  59.2\n",
-      "  53.45  83.2   54.9   57.5  103.9   93.8   89.25  94.15  55.6   48.7\n",
-      "  19.25 104.9   54.85  19.3   79.85  75.5   73.75  96.05  68.4   20.65\n",
-      "  70.6  107.6   61.55  99.25  91.7  100.7   84.3   88.95  86.8   20.95\n",
-      "  50.7   53.4  101.9   59.5   87.8   41.9   83.    69.85 109.55  92.15\n",
-      "  97.    58.35  50.6   89.5   70.4   69.8   94.3   95.95 101.05 107.75\n",
-      "  54.6   71.3   94.7  104.15  90.55  60.8   98.8   98.15  35.35 103.15\n",
-      "  81.4   61.45  95.7  104.8   70.95  97.65  35.65  85.25  88.8   55.7\n",
-      "  85.2   91.15  83.85  45.9   91.4   91.5   51.3   21.1  104.75 106.15\n",
-      "  85.75 100.75  78.55  77.8   83.45  73.25  90.1   29.2   46.6   85.35\n",
-      "  54.   104.25  84.75  75.25  24.6   55.5   43.3  109.5   84.85 112.1\n",
-      "  95.05  50.35  74.6   74.2   69.   105.2  109.2   45.15 108.65  40.65\n",
-      "  55.35  90.05  68.05  96.2  102.1   23.4   92.2   43.9   80.5   89.8\n",
-      "  90.45  50.75  84.6   89.65  51.7   23.3   65.4   65.1   81.2   72.9\n",
-      "  74.5   60.3   75.    90.15  40.    99.45  69.05  59.7   86.25  45.65\n",
-      "  70.1   40.75  70.2   84.2   66.15  45.85  49.8  103.95 100.15  99.65\n",
-      "  73.7   50.05  60.25 105.75  87.3   54.25  85.3   50.    90.95  72.25\n",
-      "  96.1   25.15  71.25 113.8   24.55  50.15 100.5   74.45  81.9   69.7\n",
-      "  25.35  24.65  25.25  60.    24.1  109.9   35.5   87.55  88.4   50.8\n",
-      "  99.    96.55  59.75 111.5   24.25  30.55 101.   100.    98.05  71.15\n",
-      "  54.15  63.9   69.15  64.65 108.75  98.85  89.6   83.25  24.5   73.\n",
-      "  80.4   78.5  102.    48.95  18.25  54.55  89.05  96.6   77.15  35.05\n",
-      " 108.1   20.2   49.2   71.65 106.5   94.25  68.95  58.5   78.9   79.2\n",
-      " 109.45  29.15  76.05  24.45  66.5   89.35  73.6   82.65  49.    80.35\n",
-      "  25.45  55.8  110.9   77.75  26.2   79.05  80.85  98.4   56.35  50.4\n",
-      " 109.75  91.25  54.75  81.45  49.1  100.3   65.25  94.1   73.55 104.65\n",
-      "  44.55  54.45 105.    88.7   74.25  30.75 112.9   94.05  78.85  78.65\n",
-      "  74.75 105.65  96.5   70.85  73.9   45.45 109.65  65.   114.1   86.95\n",
-      " 105.45  25.4  102.55  24.    25.6   73.5   98.25 101.55 103.1   34.2\n",
-      "  43.75 111.95 100.65  55.95 116.05  45.75  82.    65.15  88.85 106.85\n",
-      "  80.15 109.25  56.1  118.6   24.15 115.5  111.3   80.6   20.8   35.2\n",
-      "  78.8   89.95  49.4  115.25  81.25  93.55  86.4   66.3   94.65  82.05\n",
-      "  72.1   34.7  109.4   40.25  42.9   44.    88.9   57.65 108.05 105.3\n",
-      " 102.6   73.85  61.35  57.55  29.25  84.55 111.75 107.7   63.7   24.75\n",
-      "  50.9   60.4   79.25 110.1   25.3   24.35  76.5   81.15  38.5   92.9\n",
-      "  93.5   84.7   66.   101.5   74.9   99.75  67.8   25.7   56.15  86.7\n",
-      "  50.55  54.35  45.35  59.    69.45  64.95  18.85 114.3   45.05  51.\n",
-      " 110.45  84.65  60.05  44.65  93.25  20.6   34.8   60.75  51.35  64.05\n",
-      "  94.6  100.25  98.9   97.7   40.3   46.2   24.9   65.7   63.35  50.1\n",
-      "  74.    38.9   65.45  98.7   99.35  95.8   67.5   78.15  26.1   78.05\n",
-      "  40.35  68.9   76.    82.3   29.45  59.15  44.75  90.8  106.7   67.95\n",
-      "  77.4   99.7   78.95  95.55  62.85  71.55  94.95  86.1   39.3   36.25\n",
-      "  23.9   98.6  103.65  99.9   39.85  60.5  103.85  24.85  89.    55.\n",
-      "  76.15 117.35  45.2   89.75  49.95  67.05  87.95  75.7   62.15 101.25\n",
-      " 115.15  86.55  28.6   56.4   73.3   98.65  33.6   79.9  104.05  70.05\n",
-      "  23.05  59.95  78.6  116.8   43.55  65.2  102.95  90.6  108.2   92.\n",
-      " 112.2   70.3   75.85  80.65  68.5  115.75  59.55  36.1   94.    61.15\n",
-      " 110.2  106.35  65.9   52.5   88.75  75.3   26.    99.4   73.15  66.4\n",
-      " 115.55 104.45  92.4   25.75  49.6   97.05 105.95  91.85  40.1  110.3\n",
-      "  85.15  60.95  46.    58.55  86.35  69.75  65.6   82.1   79.1   90.65\n",
-      " 110.    67.45  89.1   69.9   51.1   94.4   78.25  76.4   48.65  59.85\n",
-      "  80.3   91.8   18.8   64.75  89.45  85.6   54.1   80.9   90.85  48.75\n",
-      "  79.7  100.4   57.95  86.5   62.45  89.55  83.55  71.45  46.35  66.1\n",
-      "  75.4   70.45  21.05  69.35  40.55  75.65  60.6  101.15  98.   104.7\n",
-      "  93.9   86.45  98.5   78.2   88.45  69.55  83.75  98.1   53.35  69.4\n",
-      "  40.15  70.35  53.85 115.6   97.95  78.3   96.8   77.35  66.05  68.15\n",
-      "  92.45  45.55  93.4   88.15  79.35  79.75 105.15  79.3  105.5   92.7\n",
-      "  26.25  96.95 115.8   67.75  90.35  55.75 114.6   66.8  104.85  74.1\n",
-      " 118.75  85.9  101.3   21.2   24.2  102.8   99.95 115.85  35.1   99.1\n",
-      "  67.25  55.1  117.8   45.25  95.35 116.6   65.05  92.5   18.75  93.6\n",
-      " 104.4   70.7  108.95  26.45  86.2   51.2   75.8   36.15  61.2   99.85\n",
-      "  58.4   88.3  108.9  107.4  106.65 104.35  55.45  61.3   96.85 108.25\n",
-      " 105.05  66.9  110.7   38.25  54.95  79.    39.1  100.45  39.55  23.15\n",
-      "  72.45  60.1   91.55  35.8  113.15  53.95  99.3   51.55  78.75  54.7\n",
-      "  71.1  106.25 114.05 116.15  66.25  99.8   90.    54.05  97.25  83.05\n",
-      "  41.1   74.55  40.2   78.35 109.7   33.45  39.4   76.25  46.4   59.6\n",
-      " 108.5   58.95  63.05  64.4   83.9  117.45  59.05  76.55  62.5   29.4\n",
-      "  94.9  111.65 106.05 113.45  92.55  49.7   30.2   85.7   74.7  107.55\n",
-      "  23.85  76.1   39.2   39.15  59.8   49.75  35.75  60.15  84.   110.75\n",
-      "  76.35  18.9   98.35  91.65  44.35  47.95  63.6   53.    36.85 103.75\n",
-      "  56.75  59.65  45.5  106.45  30.05  44.7 ]\n",
-      "=============================================\n",
-      "Column: TotalCharges - Unique Values: [1059.55 181.8 2212.55 ... 552.95 7053.35 301.55]\n",
-      "=============================================\n"
-     ]
-    }
-   ],
-   "source": [
-    "# check unique values of each column\n",
-    "for column in df_excel.columns:\n",
-    "    print('Column: {} - Unique Values: {}'.format(column, df_excel[column].unique()))\n",
-    "    print('==='*15)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "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>SeniorCitizen</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>2000.000000</td>\n",
-       "      <td>2000.000000</td>\n",
-       "      <td>2000.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>0.161500</td>\n",
-       "      <td>31.853000</td>\n",
-       "      <td>63.933325</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>0.368084</td>\n",
-       "      <td>24.632677</td>\n",
-       "      <td>30.136858</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>8.000000</td>\n",
-       "      <td>34.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>27.000000</td>\n",
-       "      <td>69.800000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>55.000000</td>\n",
-       "      <td>89.275000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>118.750000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       SeniorCitizen       tenure  MonthlyCharges\n",
-       "count    2000.000000  2000.000000     2000.000000\n",
-       "mean        0.161500    31.853000       63.933325\n",
-       "std         0.368084    24.632677       30.136858\n",
-       "min         0.000000     0.000000       18.250000\n",
-       "25%         0.000000     8.000000       34.250000\n",
-       "50%         0.000000    27.000000       69.800000\n",
-       "75%         0.000000    55.000000       89.275000\n",
-       "max         1.000000    72.000000      118.750000"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Summary statistics of df_excel to get insights into the distribution and basic characteristics of the numerical variables\n",
-    "df_excel.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "customerID          0\n",
-       "gender              0\n",
-       "SeniorCitizen       0\n",
-       "Partner             0\n",
-       "Dependents          0\n",
-       "tenure              0\n",
-       "PhoneService        0\n",
-       "MultipleLines       0\n",
-       "InternetService     0\n",
-       "OnlineSecurity      0\n",
-       "OnlineBackup        0\n",
-       "DeviceProtection    0\n",
-       "TechSupport         0\n",
-       "StreamingTV         0\n",
-       "StreamingMovies     0\n",
-       "Contract            0\n",
-       "PaperlessBilling    0\n",
-       "PaymentMethod       0\n",
-       "MonthlyCharges      0\n",
-       "TotalCharges        0\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Handling missing values\n",
-    "df_excel.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "As expected, the test dataset does not have the \"Churn\" column."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Explore df_csv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>5600-PDUJF</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>49.50</td>\n",
-       "      <td>312.7</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>8292-TYSPY</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>19</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>55.00</td>\n",
-       "      <td>1046.5</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0567-XRHCU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>69</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No phone service</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Two year</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>43.95</td>\n",
-       "      <td>2960.1</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1867-BDVFH</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>11</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>74.35</td>\n",
-       "      <td>834.2</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2067-QYTCF</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>64</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>111.15</td>\n",
-       "      <td>6953.4</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  5600-PDUJF    Male              0      No         No       6          Yes   \n",
-       "1  8292-TYSPY    Male              0      No         No      19          Yes   \n",
-       "2  0567-XRHCU  Female              0     Yes        Yes      69           No   \n",
-       "3  1867-BDVFH    Male              0     Yes        Yes      11          Yes   \n",
-       "4  2067-QYTCF  Female              0     Yes         No      64          Yes   \n",
-       "\n",
-       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
-       "0                No             DSL             No  ...               No   \n",
-       "1                No             DSL             No  ...              Yes   \n",
-       "2  No phone service             DSL            Yes  ...              Yes   \n",
-       "3               Yes     Fiber optic             No  ...               No   \n",
-       "4               Yes     Fiber optic             No  ...              Yes   \n",
-       "\n",
-       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
-       "0         Yes          No              No  Month-to-month              Yes   \n",
-       "1         Yes          No              No  Month-to-month              Yes   \n",
-       "2          No          No             Yes        Two year              Yes   \n",
-       "3          No          No              No  Month-to-month              Yes   \n",
-       "4         Yes         Yes             Yes  Month-to-month              Yes   \n",
-       "\n",
-       "             PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
-       "0  Credit card (automatic)          49.50         312.7    No  \n",
-       "1  Credit card (automatic)          55.00        1046.5   Yes  \n",
-       "2  Credit card (automatic)          43.95        2960.1    No  \n",
-       "3         Electronic check          74.35         834.2   Yes  \n",
-       "4         Electronic check         111.15        6953.4    No  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Call the dataset df_csv\n",
-    "df_csv.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 2043 entries, 0 to 2042\n",
-      "Data columns (total 21 columns):\n",
-      " #   Column            Non-Null Count  Dtype  \n",
-      "---  ------            --------------  -----  \n",
-      " 0   customerID        2043 non-null   object \n",
-      " 1   gender            2043 non-null   object \n",
-      " 2   SeniorCitizen     2043 non-null   int64  \n",
-      " 3   Partner           2043 non-null   object \n",
-      " 4   Dependents        2043 non-null   object \n",
-      " 5   tenure            2043 non-null   int64  \n",
-      " 6   PhoneService      2043 non-null   object \n",
-      " 7   MultipleLines     2043 non-null   object \n",
-      " 8   InternetService   2043 non-null   object \n",
-      " 9   OnlineSecurity    2043 non-null   object \n",
-      " 10  OnlineBackup      2043 non-null   object \n",
-      " 11  DeviceProtection  2043 non-null   object \n",
-      " 12  TechSupport       2043 non-null   object \n",
-      " 13  StreamingTV       2043 non-null   object \n",
-      " 14  StreamingMovies   2043 non-null   object \n",
-      " 15  Contract          2043 non-null   object \n",
-      " 16  PaperlessBilling  2043 non-null   object \n",
-      " 17  PaymentMethod     2043 non-null   object \n",
-      " 18  MonthlyCharges    2043 non-null   float64\n",
-      " 19  TotalCharges      2043 non-null   object \n",
-      " 20  Churn             2043 non-null   object \n",
-      "dtypes: float64(1), int64(2), object(18)\n",
-      "memory usage: 335.3+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Column information\n",
-    "df_csv.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Column: customerID - Unique Values: ['5600-PDUJF' '8292-TYSPY' '0567-XRHCU' ... '4801-JZAZL' '8361-LTMKD'\n",
-      " '3186-AJIEK']\n",
-      "=============================================\n",
-      "Column: gender - Unique Values: ['Male' 'Female']\n",
-      "=============================================\n",
-      "Column: SeniorCitizen - Unique Values: [0 1]\n",
-      "=============================================\n",
-      "Column: Partner - Unique Values: ['No' 'Yes']\n",
-      "=============================================\n",
-      "Column: Dependents - Unique Values: ['No' 'Yes']\n",
-      "=============================================\n",
-      "Column: tenure - Unique Values: [ 6 19 69 11 64 39 15 25 66 61 43 12 23 71 34  5 41 72 14  1 10  7  9 48\n",
-      " 20 16  2 22 35 54 56 18 68 53 30 36 55 21 33 44  4 49 42 67 40 45 57  8\n",
-      " 65  3 17 28 52 47 50 46 29 27 13 24 62 26 60 51 70 59 38 37  0 58 31 32\n",
-      " 63]\n",
-      "=============================================\n",
-      "Column: PhoneService - Unique Values: ['Yes' 'No']\n",
-      "=============================================\n",
-      "Column: MultipleLines - Unique Values: ['No' 'No phone service' 'Yes']\n",
-      "=============================================\n",
-      "Column: InternetService - Unique Values: ['DSL' 'Fiber optic' 'No']\n",
-      "=============================================\n",
-      "Column: OnlineSecurity - Unique Values: ['No' 'Yes' 'No internet service']\n",
-      "=============================================\n",
-      "Column: OnlineBackup - Unique Values: ['No' 'Yes' 'No internet service']\n",
-      "=============================================\n",
-      "Column: DeviceProtection - Unique Values: ['No' 'Yes' 'No internet service']\n",
-      "=============================================\n",
-      "Column: TechSupport - Unique Values: ['Yes' 'No' 'No internet service']\n",
-      "=============================================\n",
-      "Column: StreamingTV - Unique Values: ['No' 'Yes' 'No internet service']\n",
-      "=============================================\n",
-      "Column: StreamingMovies - Unique Values: ['No' 'Yes' 'No internet service']\n",
-      "=============================================\n",
-      "Column: Contract - Unique Values: ['Month-to-month' 'Two year' 'One year']\n",
-      "=============================================\n",
-      "Column: PaperlessBilling - Unique Values: ['Yes' 'No']\n",
-      "=============================================\n",
-      "Column: PaymentMethod - Unique Values: ['Credit card (automatic)' 'Electronic check' 'Mailed check'\n",
-      " 'Bank transfer (automatic)']\n",
-      "=============================================\n",
-      "Column: MonthlyCharges - Unique Values: [ 49.5   55.    43.95 ...  78.7   60.65 103.2 ]\n",
-      "=============================================\n",
-      "Column: TotalCharges - Unique Values: ['312.7' '1046.5' '2960.1' ... '346.45' '306.6' '6844.5']\n",
-      "=============================================\n",
-      "Column: Churn - Unique Values: ['No' 'Yes']\n",
-      "=============================================\n"
-     ]
-    }
-   ],
-   "source": [
-    "# check unique values of each column\n",
-    "for column in df_csv.columns:\n",
-    "    print('Column: {} - Unique Values: {}'.format(column, df_csv[column].unique()))\n",
-    "    print('==='*15)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "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>SeniorCitizen</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>2043.000000</td>\n",
-       "      <td>2043.000000</td>\n",
-       "      <td>2043.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>0.168380</td>\n",
-       "      <td>32.649046</td>\n",
-       "      <td>64.712555</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>0.374295</td>\n",
-       "      <td>24.376248</td>\n",
-       "      <td>29.970010</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.550000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>35.825000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>30.000000</td>\n",
-       "      <td>70.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>55.000000</td>\n",
-       "      <td>89.625000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>118.350000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       SeniorCitizen       tenure  MonthlyCharges\n",
-       "count    2043.000000  2043.000000     2043.000000\n",
-       "mean        0.168380    32.649046       64.712555\n",
-       "std         0.374295    24.376248       29.970010\n",
-       "min         0.000000     0.000000       18.550000\n",
-       "25%         0.000000     9.000000       35.825000\n",
-       "50%         0.000000    30.000000       70.250000\n",
-       "75%         0.000000    55.000000       89.625000\n",
-       "max         1.000000    72.000000      118.350000"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Summary statistics of df_csv to get insights into the distribution and basic characteristics of the numerical variables\n",
-    "df_csv.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "customerID          0\n",
-       "gender              0\n",
-       "SeniorCitizen       0\n",
-       "Partner             0\n",
-       "Dependents          0\n",
-       "tenure              0\n",
-       "PhoneService        0\n",
-       "MultipleLines       0\n",
-       "InternetService     0\n",
-       "OnlineSecurity      0\n",
-       "OnlineBackup        0\n",
-       "DeviceProtection    0\n",
-       "TechSupport         0\n",
-       "StreamingTV         0\n",
-       "StreamingMovies     0\n",
-       "Contract            0\n",
-       "PaperlessBilling    0\n",
-       "PaymentMethod       0\n",
-       "MonthlyCharges      0\n",
-       "TotalCharges        0\n",
-       "Churn               0\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Handling missing values\n",
-    "df_csv.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "Observations:\n",
-    "Dataset df_db has missing values in a number of columns. \n",
-    "SeniorCitizen is supposed to be boolean type (0,1) in df_excel; but (yes, no) in df_db\n",
-    "Partner is supposed to be boolean type but is object in df_excel\n",
-    "Dependants is supposed to be boolean type but is object in df_excel\n",
-    "PhoneService is supposed to be boolean type but is object in df_excel\n",
-    "MultiplesLines is (None, True, or False) in df_db; but True or False in df_excel\n",
-    "OnlineSecurity is (True/False) in df_db; but Yes/No/No Internet in df_excel\n",
-    "DeviceProtection is (True/False) in df_db; but (yes/no) in df_excel\n",
-    "\n",
-    "TotalCharges is supposed to be float64 type but is object in df_excel"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/.ipynb_checkpoints/LP2_Classification_Telco_customer_churn-checkpoint.ipynb b/.ipynb_checkpoints/LP2_Classification_Telco_customer_churn-checkpoint.ipynb
deleted file mode 100644
index f537ed6..0000000
--- a/.ipynb_checkpoints/LP2_Classification_Telco_customer_churn-checkpoint.ipynb
+++ /dev/null
@@ -1,2326 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Business Understanding"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Business Understanding:\n",
-    "\n",
-    "The telecom company has provided access to three different datasets for a classification project. The first dataset consists of 3000 records and is stored in a remote database hosted on Microsoft SQL Server. The second dataset contains 2000 records and is stored on OneDrive. The third dataset is hosted on a GitHub repository.\n",
-    "\n",
-    "## Objectives of the project\n",
-    "\n",
-    "To assist the telecom company understand their data: The project aims to provide insights into the telecom company's data, including customer demographics, services availed, and payment details. This understanding will enable the company to make informed business decisions.\n",
-    "\n",
-    "Find the lifetime value of each customer: By analyzing the data, the project aims to identify factors that influence the rate at which customers churn. Understanding customer behavior and identifying key predictors will help the telecom company estimate the lifetime value of each customer.\n",
-    "\n",
-    "Predict customer churn: The project involves developing a predictive model to determine whether a customer is likely to churn or not. By using machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., the project aims to build a model that accurately predicts customer churn.\n",
-    "\n",
-    "## Methodology\n",
-    "\n",
-    "To achieve these objectives, the project will follow the CRISP-DM framework and involve the following steps:\n",
-    "\n",
-    "Data exploration: Explore the datasets to gain insights into the available variables, their distributions, and relationships. This step will provide an initial understanding of the data and help identify any data quality issues.\n",
-    "\n",
-    "Missing value computations: Identify missing values in the datasets and decide on an appropriate strategy for handling them, such as imputation or removal of missing data points.\n",
-    "\n",
-    "Feature engineering: Perform feature engineering to transform and create new variables that can potentially improve the predictive power of the models. This step may involve encoding categorical variables, scaling numerical variables, or creating interaction terms.\n",
-    "\n",
-    "Model development: Utilize machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., to develop predictive models for customer churn. Train the models on a subset of the data and evaluate their performance using appropriate metrics.\n",
-    "\n",
-    "Model evaluation and interpretation: Evaluate the trained models using evaluation metrics such as accuracy, precision, recall, and F1-score. Interpret the models to understand the factors driving customer churn and their relative importance.\n",
-    "\n",
-    "Model optimization and hyperparameter tuning: Fine-tune the models by optimizing their hyperparameters to improve their performance. This step may involve techniques like grid search or random search to find the optimal combination of hyperparameters."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Hypothesis\n",
-    "H0: The churn rate of customers in the telecom company is not significantly influenced by various factors related to their demographics, services, and payment methods.\n",
-    "H1: The churn rate of customers in the telecom company is influenced by various factors related to their demographics, services, and payment methods.\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Questions\n",
-    "1. Is there a relationship between the monthly charges and the likelihood of churn?\n",
-    "2. Do customers who have internet service, specifically fiber optic, exhibit a higher churn rate compared to those with DSL or no internet service?\n",
-    "3. Does the availability of online security, online backup, device protection, and tech support impact the churn rate?\n",
-    "4. How does the churn rate vary based on the customers' gender?\n",
-    "5. Does the presence of a partner influence the likelihood of churn?\n",
-    "6. Is there a correlation between the tenure of customers and their churn rate?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Load Datasets"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load first dataset from database"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Import necessary libraries\n",
-    "import pyodbc\n",
-    "import pandas as pd\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Establish a connection\n",
-    "server = 'dap-projects-database.database.windows.net'\n",
-    "database = 'dapDB'\n",
-    "username = 'dataAnalyst_LP2'\n",
-    "password = 'A3g@3kR$2y'\n",
-    "\n",
-    "conn_str = f'DRIVER={{ODBC Driver 17 for SQL Server}};SERVER={server};DATABASE={database};UID={username};PWD={password}'\n",
-    "conn = pyodbc.connect(conn_str)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\PSL-CUDJOE\\anaconda3\\lib\\site-packages\\pandas\\io\\sql.py:761: UserWarning: pandas only support SQLAlchemy connectable(engine/connection) ordatabase string URI or sqlite3 DBAPI2 connectionother DBAPI2 objects are not tested, please consider using SQLAlchemy\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Query the database to retrieve the data\n",
-    "query = 'SELECT TOP 3000 * FROM LP2_Telco_churn_first_3000'\n",
-    "df_db = pd.read_sql(query, conn)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Close connection\n",
-    "conn.close()\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7590-VHVEG</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>29.850000</td>\n",
-       "      <td>29.850000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>5575-GNVDE</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>34</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>56.950001</td>\n",
-       "      <td>1889.500000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3668-QPYBK</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>53.849998</td>\n",
-       "      <td>108.150002</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>7795-CFOCW</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>45</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Bank transfer (automatic)</td>\n",
-       "      <td>42.299999</td>\n",
-       "      <td>1840.750000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>9237-HQITU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>70.699997</td>\n",
-       "      <td>151.649994</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID  gender  SeniorCitizen  Partner  Dependents  tenure  \\\n",
-       "0  7590-VHVEG  Female          False     True       False       1   \n",
-       "1  5575-GNVDE    Male          False    False       False      34   \n",
-       "2  3668-QPYBK    Male          False    False       False       2   \n",
-       "3  7795-CFOCW    Male          False    False       False      45   \n",
-       "4  9237-HQITU  Female          False    False       False       2   \n",
-       "\n",
-       "   PhoneService MultipleLines InternetService OnlineSecurity  ...  \\\n",
-       "0         False          None             DSL          False  ...   \n",
-       "1          True         False             DSL           True  ...   \n",
-       "2          True         False             DSL           True  ...   \n",
-       "3         False          None             DSL           True  ...   \n",
-       "4          True         False     Fiber optic          False  ...   \n",
-       "\n",
-       "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
-       "0            False       False       False           False  Month-to-month   \n",
-       "1             True       False       False           False        One year   \n",
-       "2            False       False       False           False  Month-to-month   \n",
-       "3             True        True       False           False        One year   \n",
-       "4            False       False       False           False  Month-to-month   \n",
-       "\n",
-       "  PaperlessBilling              PaymentMethod MonthlyCharges  TotalCharges  \\\n",
-       "0             True           Electronic check      29.850000     29.850000   \n",
-       "1            False               Mailed check      56.950001   1889.500000   \n",
-       "2             True               Mailed check      53.849998    108.150002   \n",
-       "3            False  Bank transfer (automatic)      42.299999   1840.750000   \n",
-       "4             True           Electronic check      70.699997    151.649994   \n",
-       "\n",
-       "   Churn  \n",
-       "0  False  \n",
-       "1  False  \n",
-       "2   True  \n",
-       "3  False  \n",
-       "4   True  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df_db.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load second dataset (excelfile)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Read the excel file into a pandas dataframe\n",
-    "df_excel = pd.read_excel('Telco-churn-second-2000.xlsx')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>OnlineBackup</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7613-LLQFO</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>84.45</td>\n",
-       "      <td>1059.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>4568-TTZRT</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>20.40</td>\n",
-       "      <td>181.8</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>9513-DXHDA</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>81.70</td>\n",
-       "      <td>2212.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2640-PMGFL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>79.50</td>\n",
-       "      <td>2180.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3801-HMYNL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>89.15</td>\n",
-       "      <td>89.15</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  7613-LLQFO   Male              0      No         No      12          Yes   \n",
-       "1  4568-TTZRT   Male              0      No         No       9          Yes   \n",
-       "2  9513-DXHDA   Male              0      No         No      27          Yes   \n",
-       "3  2640-PMGFL   Male              0      No        Yes      27          Yes   \n",
-       "4  3801-HMYNL   Male              0     Yes        Yes       1          Yes   \n",
-       "\n",
-       "  MultipleLines InternetService       OnlineSecurity         OnlineBackup  \\\n",
-       "0           Yes     Fiber optic                   No                   No   \n",
-       "1            No              No  No internet service  No internet service   \n",
-       "2            No             DSL                  Yes                   No   \n",
-       "3           Yes     Fiber optic                   No                   No   \n",
-       "4            No     Fiber optic                   No                   No   \n",
-       "\n",
-       "      DeviceProtection          TechSupport          StreamingTV  \\\n",
-       "0                   No                   No                  Yes   \n",
-       "1  No internet service  No internet service  No internet service   \n",
-       "2                  Yes                  Yes                  Yes   \n",
-       "3                   No                  Yes                   No   \n",
-       "4                   No                   No                  Yes   \n",
-       "\n",
-       "       StreamingMovies        Contract PaperlessBilling     PaymentMethod  \\\n",
-       "0                   No  Month-to-month              Yes  Electronic check   \n",
-       "1  No internet service  Month-to-month               No      Mailed check   \n",
-       "2                  Yes        One year               No  Electronic check   \n",
-       "3                   No  Month-to-month              Yes  Electronic check   \n",
-       "4                  Yes  Month-to-month               No      Mailed check   \n",
-       "\n",
-       "   MonthlyCharges TotalCharges  \n",
-       "0           84.45      1059.55  \n",
-       "1           20.40        181.8  \n",
-       "2           81.70      2212.55  \n",
-       "3           79.50      2180.55  \n",
-       "4           89.15        89.15  "
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df_excel.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load third dataset (csv file)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Read third dataset\n",
-    "df_csv = pd.read_csv('LP2_Telco-churn-last-2000.csv')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>5600-PDUJF</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>49.50</td>\n",
-       "      <td>312.7</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>8292-TYSPY</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>19</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>55.00</td>\n",
-       "      <td>1046.5</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0567-XRHCU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>69</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No phone service</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Two year</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>43.95</td>\n",
-       "      <td>2960.1</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1867-BDVFH</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>11</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>74.35</td>\n",
-       "      <td>834.2</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2067-QYTCF</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>64</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>111.15</td>\n",
-       "      <td>6953.4</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  5600-PDUJF    Male              0      No         No       6          Yes   \n",
-       "1  8292-TYSPY    Male              0      No         No      19          Yes   \n",
-       "2  0567-XRHCU  Female              0     Yes        Yes      69           No   \n",
-       "3  1867-BDVFH    Male              0     Yes        Yes      11          Yes   \n",
-       "4  2067-QYTCF  Female              0     Yes         No      64          Yes   \n",
-       "\n",
-       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
-       "0                No             DSL             No  ...               No   \n",
-       "1                No             DSL             No  ...              Yes   \n",
-       "2  No phone service             DSL            Yes  ...              Yes   \n",
-       "3               Yes     Fiber optic             No  ...               No   \n",
-       "4               Yes     Fiber optic             No  ...              Yes   \n",
-       "\n",
-       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
-       "0         Yes          No              No  Month-to-month              Yes   \n",
-       "1         Yes          No              No  Month-to-month              Yes   \n",
-       "2          No          No             Yes        Two year              Yes   \n",
-       "3          No          No              No  Month-to-month              Yes   \n",
-       "4         Yes         Yes             Yes  Month-to-month              Yes   \n",
-       "\n",
-       "             PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
-       "0  Credit card (automatic)          49.50         312.7    No  \n",
-       "1  Credit card (automatic)          55.00        1046.5   Yes  \n",
-       "2  Credit card (automatic)          43.95        2960.1    No  \n",
-       "3         Electronic check          74.35         834.2   Yes  \n",
-       "4         Electronic check         111.15        6953.4    No  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df_csv.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Data Exploration"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Explore individual datasets "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Explore df_db\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7590-VHVEG</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>29.850000</td>\n",
-       "      <td>29.850000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>5575-GNVDE</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>34</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>56.950001</td>\n",
-       "      <td>1889.500000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3668-QPYBK</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>53.849998</td>\n",
-       "      <td>108.150002</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>7795-CFOCW</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>45</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Bank transfer (automatic)</td>\n",
-       "      <td>42.299999</td>\n",
-       "      <td>1840.750000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>9237-HQITU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>70.699997</td>\n",
-       "      <td>151.649994</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2995</th>\n",
-       "      <td>2209-XADXF</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1</td>\n",
-       "      <td>False</td>\n",
-       "      <td>None</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Bank transfer (automatic)</td>\n",
-       "      <td>25.250000</td>\n",
-       "      <td>25.250000</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2996</th>\n",
-       "      <td>6620-JDYNW</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>18</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>True</td>\n",
-       "      <td>...</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>60.599998</td>\n",
-       "      <td>1156.349976</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2997</th>\n",
-       "      <td>1891-FZYSA</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>69</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>89.949997</td>\n",
-       "      <td>6143.149902</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2998</th>\n",
-       "      <td>4770-UEZOX</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>False</td>\n",
-       "      <td>...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>74.750000</td>\n",
-       "      <td>144.800003</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2999</th>\n",
-       "      <td>1A1:U3001038-RQOST</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>False</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>19</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>No</td>\n",
-       "      <td>None</td>\n",
-       "      <td>...</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>None</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>False</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>20.600000</td>\n",
-       "      <td>414.950012</td>\n",
-       "      <td>False</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>3000 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "              customerID  gender  SeniorCitizen  Partner  Dependents  tenure  \\\n",
-       "0             7590-VHVEG  Female          False     True       False       1   \n",
-       "1             5575-GNVDE    Male          False    False       False      34   \n",
-       "2             3668-QPYBK    Male          False    False       False       2   \n",
-       "3             7795-CFOCW    Male          False    False       False      45   \n",
-       "4             9237-HQITU  Female          False    False       False       2   \n",
-       "...                  ...     ...            ...      ...         ...     ...   \n",
-       "2995          2209-XADXF  Female          False    False       False       1   \n",
-       "2996          6620-JDYNW  Female          False    False       False      18   \n",
-       "2997          1891-FZYSA    Male           True     True       False      69   \n",
-       "2998          4770-UEZOX    Male          False    False       False       2   \n",
-       "2999  1A1:U3001038-RQOST    Male          False     True        True      19   \n",
-       "\n",
-       "      PhoneService MultipleLines InternetService OnlineSecurity  ...  \\\n",
-       "0            False          None             DSL          False  ...   \n",
-       "1             True         False             DSL           True  ...   \n",
-       "2             True         False             DSL           True  ...   \n",
-       "3            False          None             DSL           True  ...   \n",
-       "4             True         False     Fiber optic          False  ...   \n",
-       "...            ...           ...             ...            ...  ...   \n",
-       "2995         False          None             DSL          False  ...   \n",
-       "2996          True          True             DSL           True  ...   \n",
-       "2997          True          True     Fiber optic          False  ...   \n",
-       "2998          True         False     Fiber optic          False  ...   \n",
-       "2999          True         False              No           None  ...   \n",
-       "\n",
-       "     DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
-       "0               False       False       False           False  Month-to-month   \n",
-       "1                True       False       False           False        One year   \n",
-       "2               False       False       False           False  Month-to-month   \n",
-       "3                True        True       False           False        One year   \n",
-       "4               False       False       False           False  Month-to-month   \n",
-       "...               ...         ...         ...             ...             ...   \n",
-       "2995            False       False       False           False  Month-to-month   \n",
-       "2996             True       False       False           False  Month-to-month   \n",
-       "2997            False       False        True           False  Month-to-month   \n",
-       "2998            False       False       False           False  Month-to-month   \n",
-       "2999             None        None        None            None  Month-to-month   \n",
-       "\n",
-       "     PaperlessBilling              PaymentMethod MonthlyCharges  TotalCharges  \\\n",
-       "0                True           Electronic check      29.850000     29.850000   \n",
-       "1               False               Mailed check      56.950001   1889.500000   \n",
-       "2                True               Mailed check      53.849998    108.150002   \n",
-       "3               False  Bank transfer (automatic)      42.299999   1840.750000   \n",
-       "4                True           Electronic check      70.699997    151.649994   \n",
-       "...               ...                        ...            ...           ...   \n",
-       "2995            False  Bank transfer (automatic)      25.250000     25.250000   \n",
-       "2996             True               Mailed check      60.599998   1156.349976   \n",
-       "2997             True           Electronic check      89.949997   6143.149902   \n",
-       "2998             True           Electronic check      74.750000    144.800003   \n",
-       "2999            False               Mailed check      20.600000    414.950012   \n",
-       "\n",
-       "      Churn  \n",
-       "0     False  \n",
-       "1     False  \n",
-       "2      True  \n",
-       "3     False  \n",
-       "4      True  \n",
-       "...     ...  \n",
-       "2995  False  \n",
-       "2996  False  \n",
-       "2997   True  \n",
-       "2998  False  \n",
-       "2999  False  \n",
-       "\n",
-       "[3000 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Call df_db\n",
-    "df_db"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 3000 entries, 0 to 2999\n",
-      "Data columns (total 21 columns):\n",
-      " #   Column            Non-Null Count  Dtype  \n",
-      "---  ------            --------------  -----  \n",
-      " 0   customerID        3000 non-null   object \n",
-      " 1   gender            3000 non-null   object \n",
-      " 2   SeniorCitizen     3000 non-null   bool   \n",
-      " 3   Partner           3000 non-null   bool   \n",
-      " 4   Dependents        3000 non-null   bool   \n",
-      " 5   tenure            3000 non-null   int64  \n",
-      " 6   PhoneService      3000 non-null   bool   \n",
-      " 7   MultipleLines     2731 non-null   object \n",
-      " 8   InternetService   3000 non-null   object \n",
-      " 9   OnlineSecurity    2349 non-null   object \n",
-      " 10  OnlineBackup      2349 non-null   object \n",
-      " 11  DeviceProtection  2349 non-null   object \n",
-      " 12  TechSupport       2349 non-null   object \n",
-      " 13  StreamingTV       2349 non-null   object \n",
-      " 14  StreamingMovies   2349 non-null   object \n",
-      " 15  Contract          3000 non-null   object \n",
-      " 16  PaperlessBilling  3000 non-null   bool   \n",
-      " 17  PaymentMethod     3000 non-null   object \n",
-      " 18  MonthlyCharges    3000 non-null   float64\n",
-      " 19  TotalCharges      2995 non-null   float64\n",
-      " 20  Churn             2999 non-null   object \n",
-      "dtypes: bool(5), float64(2), int64(1), object(13)\n",
-      "memory usage: 389.8+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Column information\n",
-    "df_db.info()"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "df_db has all 21 columns arranged as decribed in the readme file. The format for CustomerID in row 2999 is different from the rest. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "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>tenure</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>3000.000000</td>\n",
-       "      <td>3000.000000</td>\n",
-       "      <td>2995.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>32.527333</td>\n",
-       "      <td>65.347400</td>\n",
-       "      <td>2301.278315</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>24.637768</td>\n",
-       "      <td>30.137053</td>\n",
-       "      <td>2274.987884</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.400000</td>\n",
-       "      <td>18.799999</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>35.787499</td>\n",
-       "      <td>415.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>29.000000</td>\n",
-       "      <td>70.900002</td>\n",
-       "      <td>1404.650024</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>56.000000</td>\n",
-       "      <td>90.262501</td>\n",
-       "      <td>3868.725098</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>118.650002</td>\n",
-       "      <td>8564.750000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            tenure  MonthlyCharges  TotalCharges\n",
-       "count  3000.000000     3000.000000   2995.000000\n",
-       "mean     32.527333       65.347400   2301.278315\n",
-       "std      24.637768       30.137053   2274.987884\n",
-       "min       0.000000       18.400000     18.799999\n",
-       "25%       9.000000       35.787499    415.250000\n",
-       "50%      29.000000       70.900002   1404.650024\n",
-       "75%      56.000000       90.262501   3868.725098\n",
-       "max      72.000000      118.650002   8564.750000"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Summary statistics of df_db to get insights into the distribution and basic characteristics of the numerical variables\n",
-    "df_db.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "customerID            0\n",
-       "gender                0\n",
-       "SeniorCitizen         0\n",
-       "Partner               0\n",
-       "Dependents            0\n",
-       "tenure                0\n",
-       "PhoneService          0\n",
-       "MultipleLines       269\n",
-       "InternetService       0\n",
-       "OnlineSecurity      651\n",
-       "OnlineBackup        651\n",
-       "DeviceProtection    651\n",
-       "TechSupport         651\n",
-       "StreamingTV         651\n",
-       "StreamingMovies     651\n",
-       "Contract              0\n",
-       "PaperlessBilling      0\n",
-       "PaymentMethod         0\n",
-       "MonthlyCharges        0\n",
-       "TotalCharges          5\n",
-       "Churn                 1\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Handling missing values\n",
-    "df_db.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Explore df_excel"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>OnlineBackup</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7613-LLQFO</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>84.45</td>\n",
-       "      <td>1059.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>4568-TTZRT</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>No internet service</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>20.40</td>\n",
-       "      <td>181.8</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>9513-DXHDA</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>One year</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>81.70</td>\n",
-       "      <td>2212.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2640-PMGFL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>79.50</td>\n",
-       "      <td>2180.55</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3801-HMYNL</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Mailed check</td>\n",
-       "      <td>89.15</td>\n",
-       "      <td>89.15</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  7613-LLQFO   Male              0      No         No      12          Yes   \n",
-       "1  4568-TTZRT   Male              0      No         No       9          Yes   \n",
-       "2  9513-DXHDA   Male              0      No         No      27          Yes   \n",
-       "3  2640-PMGFL   Male              0      No        Yes      27          Yes   \n",
-       "4  3801-HMYNL   Male              0     Yes        Yes       1          Yes   \n",
-       "\n",
-       "  MultipleLines InternetService       OnlineSecurity         OnlineBackup  \\\n",
-       "0           Yes     Fiber optic                   No                   No   \n",
-       "1            No              No  No internet service  No internet service   \n",
-       "2            No             DSL                  Yes                   No   \n",
-       "3           Yes     Fiber optic                   No                   No   \n",
-       "4            No     Fiber optic                   No                   No   \n",
-       "\n",
-       "      DeviceProtection          TechSupport          StreamingTV  \\\n",
-       "0                   No                   No                  Yes   \n",
-       "1  No internet service  No internet service  No internet service   \n",
-       "2                  Yes                  Yes                  Yes   \n",
-       "3                   No                  Yes                   No   \n",
-       "4                   No                   No                  Yes   \n",
-       "\n",
-       "       StreamingMovies        Contract PaperlessBilling     PaymentMethod  \\\n",
-       "0                   No  Month-to-month              Yes  Electronic check   \n",
-       "1  No internet service  Month-to-month               No      Mailed check   \n",
-       "2                  Yes        One year               No  Electronic check   \n",
-       "3                   No  Month-to-month              Yes  Electronic check   \n",
-       "4                  Yes  Month-to-month               No      Mailed check   \n",
-       "\n",
-       "   MonthlyCharges TotalCharges  \n",
-       "0           84.45      1059.55  \n",
-       "1           20.40        181.8  \n",
-       "2           81.70      2212.55  \n",
-       "3           79.50      2180.55  \n",
-       "4           89.15        89.15  "
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Call the dataset df_excel\n",
-    "df_excel.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 2000 entries, 0 to 1999\n",
-      "Data columns (total 20 columns):\n",
-      " #   Column            Non-Null Count  Dtype  \n",
-      "---  ------            --------------  -----  \n",
-      " 0   customerID        2000 non-null   object \n",
-      " 1   gender            2000 non-null   object \n",
-      " 2   SeniorCitizen     2000 non-null   int64  \n",
-      " 3   Partner           2000 non-null   object \n",
-      " 4   Dependents        2000 non-null   object \n",
-      " 5   tenure            2000 non-null   int64  \n",
-      " 6   PhoneService      2000 non-null   object \n",
-      " 7   MultipleLines     2000 non-null   object \n",
-      " 8   InternetService   2000 non-null   object \n",
-      " 9   OnlineSecurity    2000 non-null   object \n",
-      " 10  OnlineBackup      2000 non-null   object \n",
-      " 11  DeviceProtection  2000 non-null   object \n",
-      " 12  TechSupport       2000 non-null   object \n",
-      " 13  StreamingTV       2000 non-null   object \n",
-      " 14  StreamingMovies   2000 non-null   object \n",
-      " 15  Contract          2000 non-null   object \n",
-      " 16  PaperlessBilling  2000 non-null   object \n",
-      " 17  PaymentMethod     2000 non-null   object \n",
-      " 18  MonthlyCharges    2000 non-null   float64\n",
-      " 19  TotalCharges      2000 non-null   object \n",
-      "dtypes: float64(1), int64(2), object(17)\n",
-      "memory usage: 312.6+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Column information\n",
-    "df_excel.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "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>SeniorCitizen</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>2000.000000</td>\n",
-       "      <td>2000.000000</td>\n",
-       "      <td>2000.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>0.161500</td>\n",
-       "      <td>31.853000</td>\n",
-       "      <td>63.933325</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>0.368084</td>\n",
-       "      <td>24.632677</td>\n",
-       "      <td>30.136858</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>8.000000</td>\n",
-       "      <td>34.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>27.000000</td>\n",
-       "      <td>69.800000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>55.000000</td>\n",
-       "      <td>89.275000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>118.750000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       SeniorCitizen       tenure  MonthlyCharges\n",
-       "count    2000.000000  2000.000000     2000.000000\n",
-       "mean        0.161500    31.853000       63.933325\n",
-       "std         0.368084    24.632677       30.136858\n",
-       "min         0.000000     0.000000       18.250000\n",
-       "25%         0.000000     8.000000       34.250000\n",
-       "50%         0.000000    27.000000       69.800000\n",
-       "75%         0.000000    55.000000       89.275000\n",
-       "max         1.000000    72.000000      118.750000"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Summary statistics of df_excel to get insights into the distribution and basic characteristics of the numerical variables\n",
-    "df_excel.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "customerID          0\n",
-       "gender              0\n",
-       "SeniorCitizen       0\n",
-       "Partner             0\n",
-       "Dependents          0\n",
-       "tenure              0\n",
-       "PhoneService        0\n",
-       "MultipleLines       0\n",
-       "InternetService     0\n",
-       "OnlineSecurity      0\n",
-       "OnlineBackup        0\n",
-       "DeviceProtection    0\n",
-       "TechSupport         0\n",
-       "StreamingTV         0\n",
-       "StreamingMovies     0\n",
-       "Contract            0\n",
-       "PaperlessBilling    0\n",
-       "PaymentMethod       0\n",
-       "MonthlyCharges      0\n",
-       "TotalCharges        0\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Handling missing values\n",
-    "df_excel.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "As expected, the test dataset does not have the \"Churn\" column."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Explore df_csv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "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>customerID</th>\n",
-       "      <th>gender</th>\n",
-       "      <th>SeniorCitizen</th>\n",
-       "      <th>Partner</th>\n",
-       "      <th>Dependents</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>PhoneService</th>\n",
-       "      <th>MultipleLines</th>\n",
-       "      <th>InternetService</th>\n",
-       "      <th>OnlineSecurity</th>\n",
-       "      <th>...</th>\n",
-       "      <th>DeviceProtection</th>\n",
-       "      <th>TechSupport</th>\n",
-       "      <th>StreamingTV</th>\n",
-       "      <th>StreamingMovies</th>\n",
-       "      <th>Contract</th>\n",
-       "      <th>PaperlessBilling</th>\n",
-       "      <th>PaymentMethod</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "      <th>TotalCharges</th>\n",
-       "      <th>Churn</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>5600-PDUJF</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>49.50</td>\n",
-       "      <td>312.7</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>8292-TYSPY</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>19</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>55.00</td>\n",
-       "      <td>1046.5</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0567-XRHCU</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>69</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No phone service</td>\n",
-       "      <td>DSL</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Two year</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Credit card (automatic)</td>\n",
-       "      <td>43.95</td>\n",
-       "      <td>2960.1</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1867-BDVFH</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>11</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>74.35</td>\n",
-       "      <td>834.2</td>\n",
-       "      <td>Yes</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2067-QYTCF</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>64</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Fiber optic</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Month-to-month</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Electronic check</td>\n",
-       "      <td>111.15</td>\n",
-       "      <td>6953.4</td>\n",
-       "      <td>No</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
-       "0  5600-PDUJF    Male              0      No         No       6          Yes   \n",
-       "1  8292-TYSPY    Male              0      No         No      19          Yes   \n",
-       "2  0567-XRHCU  Female              0     Yes        Yes      69           No   \n",
-       "3  1867-BDVFH    Male              0     Yes        Yes      11          Yes   \n",
-       "4  2067-QYTCF  Female              0     Yes         No      64          Yes   \n",
-       "\n",
-       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
-       "0                No             DSL             No  ...               No   \n",
-       "1                No             DSL             No  ...              Yes   \n",
-       "2  No phone service             DSL            Yes  ...              Yes   \n",
-       "3               Yes     Fiber optic             No  ...               No   \n",
-       "4               Yes     Fiber optic             No  ...              Yes   \n",
-       "\n",
-       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
-       "0         Yes          No              No  Month-to-month              Yes   \n",
-       "1         Yes          No              No  Month-to-month              Yes   \n",
-       "2          No          No             Yes        Two year              Yes   \n",
-       "3          No          No              No  Month-to-month              Yes   \n",
-       "4         Yes         Yes             Yes  Month-to-month              Yes   \n",
-       "\n",
-       "             PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
-       "0  Credit card (automatic)          49.50         312.7    No  \n",
-       "1  Credit card (automatic)          55.00        1046.5   Yes  \n",
-       "2  Credit card (automatic)          43.95        2960.1    No  \n",
-       "3         Electronic check          74.35         834.2   Yes  \n",
-       "4         Electronic check         111.15        6953.4    No  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Call the dataset df_csv\n",
-    "df_csv.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 2043 entries, 0 to 2042\n",
-      "Data columns (total 21 columns):\n",
-      " #   Column            Non-Null Count  Dtype  \n",
-      "---  ------            --------------  -----  \n",
-      " 0   customerID        2043 non-null   object \n",
-      " 1   gender            2043 non-null   object \n",
-      " 2   SeniorCitizen     2043 non-null   int64  \n",
-      " 3   Partner           2043 non-null   object \n",
-      " 4   Dependents        2043 non-null   object \n",
-      " 5   tenure            2043 non-null   int64  \n",
-      " 6   PhoneService      2043 non-null   object \n",
-      " 7   MultipleLines     2043 non-null   object \n",
-      " 8   InternetService   2043 non-null   object \n",
-      " 9   OnlineSecurity    2043 non-null   object \n",
-      " 10  OnlineBackup      2043 non-null   object \n",
-      " 11  DeviceProtection  2043 non-null   object \n",
-      " 12  TechSupport       2043 non-null   object \n",
-      " 13  StreamingTV       2043 non-null   object \n",
-      " 14  StreamingMovies   2043 non-null   object \n",
-      " 15  Contract          2043 non-null   object \n",
-      " 16  PaperlessBilling  2043 non-null   object \n",
-      " 17  PaymentMethod     2043 non-null   object \n",
-      " 18  MonthlyCharges    2043 non-null   float64\n",
-      " 19  TotalCharges      2043 non-null   object \n",
-      " 20  Churn             2043 non-null   object \n",
-      "dtypes: float64(1), int64(2), object(18)\n",
-      "memory usage: 335.3+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Column information\n",
-    "df_csv.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "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>SeniorCitizen</th>\n",
-       "      <th>tenure</th>\n",
-       "      <th>MonthlyCharges</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>2043.000000</td>\n",
-       "      <td>2043.000000</td>\n",
-       "      <td>2043.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>0.168380</td>\n",
-       "      <td>32.649046</td>\n",
-       "      <td>64.712555</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>0.374295</td>\n",
-       "      <td>24.376248</td>\n",
-       "      <td>29.970010</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>18.550000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>35.825000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>30.000000</td>\n",
-       "      <td>70.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>55.000000</td>\n",
-       "      <td>89.625000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>72.000000</td>\n",
-       "      <td>118.350000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       SeniorCitizen       tenure  MonthlyCharges\n",
-       "count    2043.000000  2043.000000     2043.000000\n",
-       "mean        0.168380    32.649046       64.712555\n",
-       "std         0.374295    24.376248       29.970010\n",
-       "min         0.000000     0.000000       18.550000\n",
-       "25%         0.000000     9.000000       35.825000\n",
-       "50%         0.000000    30.000000       70.250000\n",
-       "75%         0.000000    55.000000       89.625000\n",
-       "max         1.000000    72.000000      118.350000"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Summary statistics of df_csv to get insights into the distribution and basic characteristics of the numerical variables\n",
-    "df_csv.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "customerID          0\n",
-       "gender              0\n",
-       "SeniorCitizen       0\n",
-       "Partner             0\n",
-       "Dependents          0\n",
-       "tenure              0\n",
-       "PhoneService        0\n",
-       "MultipleLines       0\n",
-       "InternetService     0\n",
-       "OnlineSecurity      0\n",
-       "OnlineBackup        0\n",
-       "DeviceProtection    0\n",
-       "TechSupport         0\n",
-       "StreamingTV         0\n",
-       "StreamingMovies     0\n",
-       "Contract            0\n",
-       "PaperlessBilling    0\n",
-       "PaymentMethod       0\n",
-       "MonthlyCharges      0\n",
-       "TotalCharges        0\n",
-       "Churn               0\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Handling missing values\n",
-    "df_csv.isnull().sum()"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "Observations:\n",
-    "Dataset df_db has missing values in a number of columns. \n",
-    "SeniorCitizen is supposed to be boolean type (0,1) in df_excel; but (yes, no) in df_db\n",
-    "Partner is supposed to be boolean type but is object in df_excel\n",
-    "Dependants is supposed to be boolean type but is object in df_excel\n",
-    "PhoneService is supposed to be boolean type but is object in df_excel\n",
-    "MultiplesLines is (None, True, or False) in df_db; but True or False in df_excel\n",
-    "OnlineSecurity is (True/False) in df_db; but Yes/No/No Internet in df_excel\n",
-    "DeviceProtection is (True/False) in df_db; but (yes/no) in df_excel\n",
-    "\n",
-    "TotalCharges is supposed to be float64 type but is object in df_excel\n",
-    "\n",
-    " \n"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Classification_Telco_customer_churn.ipynb b/Classification_Telco_customer_churn.ipynb
index ffe1dfc..2f72ccb 100644
--- a/Classification_Telco_customer_churn.ipynb
+++ b/Classification_Telco_customer_churn.ipynb
@@ -1,5 +1,132 @@
 {
+<<<<<<< HEAD
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+<<<<<<< HEAD
+    "# Project Title: \n",
+    "Telecommunications Customer Churn Prediction Analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+=======
+>>>>>>> main
+    "# Business Understanding"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+<<<<<<< HEAD
+    "## 1. Introduction\n",
+    "This project aims to assist a telecom company in understanding their data and predicting customer churn. The company has provided access to three different datasets: the first dataset with 3000 records stored in a remote Microsoft SQL Server database, the second dataset with 2000 records stored on OneDrive, and the third dataset hosted on a GitHub repository.\n",
+    "\n",
+    "### 1.1. Objectives\n",
+    "Understand the data: Our first objective is to provide insights into the telecom company's data, including customer demographics, services availed, and payment details. This understanding will enable the company to make informed business decisions.\n",
+    "\n",
+    "Find the lifetime value of each customer: By analyzing the data, we aim to identify factors that influence the rate at which customers churn. Understanding customer behavior and identifying key predictors will help the telecom company estimate the lifetime value of each customer.\n",
+    "\n",
+    "Predict customer churn: The primary objective is to develop a predictive model that accurately determines whether a customer is likely to churn or not. We will employ machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., to build a model that effectively predicts customer churn.\n",
+    "\n",
+    "### 1.2. Methodology\n",
+    "To achieve our objectives, we will follow the CRISP-DM framework, which consists of the following steps:\n",
+    "\n",
+    "Data exploration: We will thoroughly explore the datasets to gain insights into the available variables, their distributions, and relationships. This step will provide us with an initial understanding of the data and help identify any data quality issues.\n",
+    "\n",
+    "Missing value computations: We will identify missing values in the datasets and decide on an appropriate strategy for handling them. This may involve imputing missing values or removing data points with missing values.\n",
+    "\n",
+    "Feature engineering: We will perform feature engineering to transform and create new variables that can potentially improve the predictive power of our models. This step may include encoding categorical variables, scaling numerical variables, or creating interaction terms.\n",
+    "\n",
+    "Model development: We will utilize various machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., to develop predictive models for customer churn. We will train the models on a subset of the data and evaluate their performance using appropriate metrics.\n",
+    "\n",
+    "Model evaluation and interpretation: We will evaluate the trained models using evaluation metrics such as accuracy, precision, recall, and F1-score. Additionally, we will interpret the models to understand the factors driving customer churn and their relative importance.\n",
+    "\n",
+    "Model optimization and hyperparameter tuning: We will fine-tune the models by optimizing their hyperparameters to improve their performance. This step may involve techniques like grid search or random search to find the optimal combination of hyperparameters.\n",
+    "\n",
+    "By following this methodology, we aim to provide valuable insights to the telecom company and develop a reliable predictive model for customer churn."
+=======
+    "## Business Understanding:\n",
+    "\n",
+    "The telecom company has provided access to three different datasets for a classification project. The first dataset consists of 3000 records and is stored in a remote database hosted on Microsoft SQL Server. The second dataset contains 2000 records and is stored on OneDrive. The third dataset is hosted on a GitHub repository.\n",
+    "\n",
+    "## Objectives of the project\n",
+    "\n",
+    "To assist the telecom company understand their data: The project aims to provide insights into the telecom company's data, including customer demographics, services availed, and payment details. This understanding will enable the company to make informed business decisions.\n",
+    "\n",
+    "Find the lifetime value of each customer: By analyzing the data, the project aims to identify factors that influence the rate at which customers churn. Understanding customer behavior and identifying key predictors will help the telecom company estimate the lifetime value of each customer.\n",
+    "\n",
+    "Predict customer churn: The project involves developing a predictive model to determine whether a customer is likely to churn or not. By using machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., the project aims to build a model that accurately predicts customer churn.\n",
+    "\n",
+    "## Methodology\n",
+    "\n",
+    "To achieve these objectives, the project will follow the CRISP-DM framework and involve the following steps:\n",
+    "\n",
+    "Data exploration: Explore the datasets to gain insights into the available variables, their distributions, and relationships. This step will provide an initial understanding of the data and help identify any data quality issues.\n",
+    "\n",
+    "Missing value computations: Identify missing values in the datasets and decide on an appropriate strategy for handling them, such as imputation or removal of missing data points.\n",
+    "\n",
+    "Feature engineering: Perform feature engineering to transform and create new variables that can potentially improve the predictive power of the models. This step may involve encoding categorical variables, scaling numerical variables, or creating interaction terms.\n",
+    "\n",
+    "Model development: Utilize machine learning algorithms such as logistic regression, decision trees, support vector machines, random forest, etc., to develop predictive models for customer churn. Train the models on a subset of the data and evaluate their performance using appropriate metrics.\n",
+    "\n",
+    "Model evaluation and interpretation: Evaluate the trained models using evaluation metrics such as accuracy, precision, recall, and F1-score. Interpret the models to understand the factors driving customer churn and their relative importance.\n",
+    "\n",
+    "Model optimization and hyperparameter tuning: Fine-tune the models by optimizing their hyperparameters to improve their performance. This step may involve techniques like grid search or random search to find the optimal combination of hyperparameters."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hypothesis\n",
+    "H0: The churn rate of customers in the telecom company is not significantly influenced by various factors related to their demographics, services, and payment methods.\n",
+    "H1: The churn rate of customers in the telecom company is influenced by various factors related to their demographics, services, and payment methods.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Questions\n",
+    "1. Is there a relationship between the monthly charges and the likelihood of churn?\n",
+    "2. Do customers who have internet service, specifically fiber optic, exhibit a higher churn rate compared to those with DSL or no internet service?\n",
+    "3. Does the availability of online security, online backup, device protection, and tech support impact the churn rate?\n",
+    "4. How does the churn rate vary based on the customers' gender?\n",
+    "5. Does the presence of a partner influence the likelihood of churn?\n",
+    "6. Is there a correlation between the tenure of customers and their churn rate?"
+>>>>>>> main
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Load Datasets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+<<<<<<< HEAD
+    "## Installations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+=======
   "cells": [
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     {
       "cell_type": "markdown",
       "metadata": {},
@@ -82,9 +209,26 @@
         "## Load first dataset from database"
       ]
     }
+<<<<<<< HEAD
+   ],
+   "source": [
+    "%pip install pyodbc\n",
+    "%pip install openpyxl"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load first dataset from SQL database"
+=======
+    "## Load first dataset from database"
+>>>>>>> main
+=======
   ]
 }
 
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {
@@ -95,9 +239,19 @@
    "source": [
     "# Import necessary libraries\n",
     "import pyodbc\n",
+<<<<<<< HEAD
+<<<<<<< HEAD
     "import pandas as pd\n",
     "import warnings\n",
     "warnings.filterwarnings(\"ignore\")"
+=======
+    "import pandas as pd\n"
+>>>>>>> main
+=======
+    "import pandas as pd\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\")"
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {
@@ -112,22 +266,56 @@
     "username = 'dataAnalyst_LP2'\n",
     "password = 'A3g@3kR$2y'\n",
     "\n",
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "# Create the connection string using the ODBC driver format\n",
     "conn_str = f'DRIVER={{ODBC Driver 17 for SQL Server}};SERVER={server};DATABASE={database};UID={username};PWD={password}'\n",
     "\n",
     "# Establish the connection using the connection string\n",
     "conn = pyodbc.connect(conn_str)"
+<<<<<<< HEAD
+=======
+    "conn_str = f'DRIVER={{ODBC Driver 17 for SQL Server}};SERVER={server};DATABASE={database};UID={username};PWD={password}'\n",
+    "conn = pyodbc.connect(conn_str)\n"
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "outputs": [],
    "source": [
     "# Query the database to retrieve the data\n",
     "query = 'SELECT TOP 3000 * FROM LP2_Telco_churn_first_3000'\n",
     "df_db = pd.read_sql(query, conn)"
+<<<<<<< HEAD
+=======
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\PSL-CUDJOE\\anaconda3\\lib\\site-packages\\pandas\\io\\sql.py:761: UserWarning: pandas only support SQLAlchemy connectable(engine/connection) ordatabase string URI or sqlite3 DBAPI2 connectionother DBAPI2 objects are not tested, please consider using SQLAlchemy\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Query the database to retrieve the data\n",
+    "query = 'SELECT TOP 3000 * FROM LP2_Telco_churn_first_3000'\n",
+    "df_db = pd.read_sql(query, conn)\n"
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {
@@ -137,7 +325,15 @@
    "outputs": [],
    "source": [
     "# Close connection\n",
+<<<<<<< HEAD
+<<<<<<< HEAD
+    "conn.close()"
+=======
+    "conn.close()\n"
+>>>>>>> main
+=======
     "conn.close()"
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {
@@ -360,7 +556,14 @@
     }
    ],
    "source": [
+<<<<<<< HEAD
+<<<<<<< HEAD
     "# Display the dataframe\n",
+=======
+>>>>>>> main
+=======
+    "# Display the dataframe\n",
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "df_db.head()"
    ]
   },
@@ -375,6 +578,22 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {},
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+   "outputs": [],
+   "source": [
+    "# Read the excel file into a pandas dataframe\n",
+    "df_excel = pd.read_excel('Telco-churn-second-2000.xlsx')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "outputs": [
     {
      "data": {
@@ -576,16 +795,33 @@
        "4           89.15        89.15  "
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
+     "execution_count": 7,
+=======
+     "execution_count": 8,
+>>>>>>> main
+=======
      "execution_count": 7,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "# Read the excel file into a pandas dataframe\n",
     "df_excel = pd.read_excel('Telco-churn-second-2000.xlsx')\n",
     "\n",
     "# Display the dataframe\n",
+<<<<<<< HEAD
+=======
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "df_excel.head()"
    ]
   },
@@ -598,7 +834,25 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
    "execution_count": 8,
+=======
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read third dataset\n",
+    "df_csv = pd.read_csv('LP2_Telco-churn-last-2000.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+>>>>>>> main
+=======
+   "execution_count": 8,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -803,16 +1057,33 @@
        "[5 rows x 21 columns]"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
      "execution_count": 8,
+=======
+     "execution_count": 10,
+>>>>>>> main
+=======
+     "execution_count": 8,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "# Read third dataset\n",
     "df_csv = pd.read_csv('LP2_Telco-churn-last-2000.csv')\n",
     "\n",
     "# Display the dataframe\n",
+<<<<<<< HEAD
+=======
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "df_csv.head()"
    ]
   },
@@ -820,6 +1091,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "# Questions and Hypothesis"
    ]
   },
@@ -852,6 +1127,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+<<<<<<< HEAD
+=======
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
     "# Data Exploration"
    ]
   },
@@ -866,15 +1146,432 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+<<<<<<< HEAD
+<<<<<<< HEAD
     "### Explore The Dataframe from the SQL Database(df_db)"
+=======
+    "### Explore df_db\n"
+>>>>>>> main
+=======
+    "### Explore The Dataframe from the SQL Database(df_db)"
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "execution_count": 9,
    "metadata": {
     "scrolled": false
    },
+<<<<<<< HEAD
+=======
+   "execution_count": 11,
+   "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>customerID</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>SeniorCitizen</th>\n",
+       "      <th>Partner</th>\n",
+       "      <th>Dependents</th>\n",
+       "      <th>tenure</th>\n",
+       "      <th>PhoneService</th>\n",
+       "      <th>MultipleLines</th>\n",
+       "      <th>InternetService</th>\n",
+       "      <th>OnlineSecurity</th>\n",
+       "      <th>...</th>\n",
+       "      <th>DeviceProtection</th>\n",
+       "      <th>TechSupport</th>\n",
+       "      <th>StreamingTV</th>\n",
+       "      <th>StreamingMovies</th>\n",
+       "      <th>Contract</th>\n",
+       "      <th>PaperlessBilling</th>\n",
+       "      <th>PaymentMethod</th>\n",
+       "      <th>MonthlyCharges</th>\n",
+       "      <th>TotalCharges</th>\n",
+       "      <th>Churn</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>7590-VHVEG</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>None</td>\n",
+       "      <td>DSL</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Electronic check</td>\n",
+       "      <td>29.850000</td>\n",
+       "      <td>29.850000</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>5575-GNVDE</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>34</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>DSL</td>\n",
+       "      <td>True</td>\n",
+       "      <td>...</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>One year</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Mailed check</td>\n",
+       "      <td>56.950001</td>\n",
+       "      <td>1889.500000</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3668-QPYBK</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>DSL</td>\n",
+       "      <td>True</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Mailed check</td>\n",
+       "      <td>53.849998</td>\n",
+       "      <td>108.150002</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>7795-CFOCW</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>45</td>\n",
+       "      <td>False</td>\n",
+       "      <td>None</td>\n",
+       "      <td>DSL</td>\n",
+       "      <td>True</td>\n",
+       "      <td>...</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>One year</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Bank transfer (automatic)</td>\n",
+       "      <td>42.299999</td>\n",
+       "      <td>1840.750000</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9237-HQITU</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Fiber optic</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Electronic check</td>\n",
+       "      <td>70.699997</td>\n",
+       "      <td>151.649994</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2995</th>\n",
+       "      <td>2209-XADXF</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>None</td>\n",
+       "      <td>DSL</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Bank transfer (automatic)</td>\n",
+       "      <td>25.250000</td>\n",
+       "      <td>25.250000</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2996</th>\n",
+       "      <td>6620-JDYNW</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>18</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>DSL</td>\n",
+       "      <td>True</td>\n",
+       "      <td>...</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Mailed check</td>\n",
+       "      <td>60.599998</td>\n",
+       "      <td>1156.349976</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2997</th>\n",
+       "      <td>1891-FZYSA</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>69</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Fiber optic</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Electronic check</td>\n",
+       "      <td>89.949997</td>\n",
+       "      <td>6143.149902</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2998</th>\n",
+       "      <td>4770-UEZOX</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Fiber optic</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Electronic check</td>\n",
+       "      <td>74.750000</td>\n",
+       "      <td>144.800003</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2999</th>\n",
+       "      <td>1A1:U3001038-RQOST</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>19</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>No</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Month-to-month</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Mailed check</td>\n",
+       "      <td>20.600000</td>\n",
+       "      <td>414.950012</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3000 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              customerID  gender  SeniorCitizen  Partner  Dependents  tenure  \\\n",
+       "0             7590-VHVEG  Female          False     True       False       1   \n",
+       "1             5575-GNVDE    Male          False    False       False      34   \n",
+       "2             3668-QPYBK    Male          False    False       False       2   \n",
+       "3             7795-CFOCW    Male          False    False       False      45   \n",
+       "4             9237-HQITU  Female          False    False       False       2   \n",
+       "...                  ...     ...            ...      ...         ...     ...   \n",
+       "2995          2209-XADXF  Female          False    False       False       1   \n",
+       "2996          6620-JDYNW  Female          False    False       False      18   \n",
+       "2997          1891-FZYSA    Male           True     True       False      69   \n",
+       "2998          4770-UEZOX    Male          False    False       False       2   \n",
+       "2999  1A1:U3001038-RQOST    Male          False     True        True      19   \n",
+       "\n",
+       "      PhoneService MultipleLines InternetService OnlineSecurity  ...  \\\n",
+       "0            False          None             DSL          False  ...   \n",
+       "1             True         False             DSL           True  ...   \n",
+       "2             True         False             DSL           True  ...   \n",
+       "3            False          None             DSL           True  ...   \n",
+       "4             True         False     Fiber optic          False  ...   \n",
+       "...            ...           ...             ...            ...  ...   \n",
+       "2995         False          None             DSL          False  ...   \n",
+       "2996          True          True             DSL           True  ...   \n",
+       "2997          True          True     Fiber optic          False  ...   \n",
+       "2998          True         False     Fiber optic          False  ...   \n",
+       "2999          True         False              No           None  ...   \n",
+       "\n",
+       "     DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
+       "0               False       False       False           False  Month-to-month   \n",
+       "1                True       False       False           False        One year   \n",
+       "2               False       False       False           False  Month-to-month   \n",
+       "3                True        True       False           False        One year   \n",
+       "4               False       False       False           False  Month-to-month   \n",
+       "...               ...         ...         ...             ...             ...   \n",
+       "2995            False       False       False           False  Month-to-month   \n",
+       "2996             True       False       False           False  Month-to-month   \n",
+       "2997            False       False        True           False  Month-to-month   \n",
+       "2998            False       False       False           False  Month-to-month   \n",
+       "2999             None        None        None            None  Month-to-month   \n",
+       "\n",
+       "     PaperlessBilling              PaymentMethod MonthlyCharges  TotalCharges  \\\n",
+       "0                True           Electronic check      29.850000     29.850000   \n",
+       "1               False               Mailed check      56.950001   1889.500000   \n",
+       "2                True               Mailed check      53.849998    108.150002   \n",
+       "3               False  Bank transfer (automatic)      42.299999   1840.750000   \n",
+       "4                True           Electronic check      70.699997    151.649994   \n",
+       "...               ...                        ...            ...           ...   \n",
+       "2995            False  Bank transfer (automatic)      25.250000     25.250000   \n",
+       "2996             True               Mailed check      60.599998   1156.349976   \n",
+       "2997             True           Electronic check      89.949997   6143.149902   \n",
+       "2998             True           Electronic check      74.750000    144.800003   \n",
+       "2999            False               Mailed check      20.600000    414.950012   \n",
+       "\n",
+       "      Churn  \n",
+       "0     False  \n",
+       "1     False  \n",
+       "2      True  \n",
+       "3     False  \n",
+       "4      True  \n",
+       "...     ...  \n",
+       "2995  False  \n",
+       "2996  False  \n",
+       "2997   True  \n",
+       "2998  False  \n",
+       "2999  False  \n",
+       "\n",
+       "[3000 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Call df_db\n",
+    "df_db"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "outputs": [
     {
      "name": "stdout",
@@ -925,6 +1622,10 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "execution_count": 10,
    "metadata": {},
    "outputs": [
@@ -1014,6 +1715,12 @@
   {
    "cell_type": "code",
    "execution_count": 12,
+<<<<<<< HEAD
+=======
+   "execution_count": 13,
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1107,7 +1814,15 @@
        "max      72.000000      118.650002   8564.750000"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
+     "execution_count": 12,
+=======
+     "execution_count": 13,
+>>>>>>> main
+=======
      "execution_count": 12,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1119,8 +1834,16 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+   "execution_count": 13,
+=======
+   "execution_count": 14,
+>>>>>>> main
+=======
    "execution_count": 13,
 
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1150,7 +1873,15 @@
        "dtype: int64"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
+     "execution_count": 13,
+=======
+     "execution_count": 14,
+>>>>>>> main
+=======
      "execution_count": 13,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1169,7 +1900,15 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+   "execution_count": 14,
+=======
+   "execution_count": 15,
+>>>>>>> main
+=======
    "execution_count": 14,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1372,7 +2111,15 @@
        "4           89.15        89.15  "
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
+     "execution_count": 14,
+=======
+     "execution_count": 15,
+>>>>>>> main
+=======
      "execution_count": 14,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1384,7 +2131,15 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
    "execution_count": 15,
+=======
+   "execution_count": 16,
+>>>>>>> main
+=======
+   "execution_count": 15,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1428,6 +2183,10 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "execution_count": 16,
    "metadata": {
     "scrolled": false
@@ -1593,7 +2352,13 @@
   {
    "cell_type": "code",
    "execution_count": 17,
+<<<<<<< HEAD
+=======
+   "execution_count": 18,
+>>>>>>> main
+=======
 
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1687,7 +2452,15 @@
        "max         1.000000    72.000000      118.750000"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
      "execution_count": 17,
+=======
+     "execution_count": 18,
+>>>>>>> main
+=======
+     "execution_count": 17,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1699,7 +2472,15 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+   "execution_count": 18,
+=======
+   "execution_count": 21,
+>>>>>>> main
+=======
    "execution_count": 18,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1728,7 +2509,15 @@
        "dtype: int64"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
      "execution_count": 18,
+=======
+     "execution_count": 21,
+>>>>>>> main
+=======
+     "execution_count": 18,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1754,7 +2543,15 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+   "execution_count": 19,
+=======
+   "execution_count": 17,
+>>>>>>> main
+=======
    "execution_count": 19,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -1959,7 +2756,15 @@
        "[5 rows x 21 columns]"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
      "execution_count": 19,
+=======
+     "execution_count": 17,
+>>>>>>> main
+=======
+     "execution_count": 19,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2016,6 +2821,10 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "execution_count": 21,
    "metadata": {},
    "outputs": [
@@ -2083,6 +2892,12 @@
   {
    "cell_type": "code",
    "execution_count": 22,
+<<<<<<< HEAD
+=======
+   "execution_count": 19,
+>>>>>>> main
+=======
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -2176,7 +2991,15 @@
        "max         1.000000    72.000000      118.350000"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
+     "execution_count": 22,
+=======
+     "execution_count": 19,
+>>>>>>> main
+=======
      "execution_count": 22,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2188,7 +3011,15 @@
   },
   {
    "cell_type": "code",
+<<<<<<< HEAD
+<<<<<<< HEAD
+   "execution_count": 23,
+=======
+   "execution_count": 22,
+>>>>>>> main
+=======
    "execution_count": 23,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    "metadata": {},
    "outputs": [
     {
@@ -2218,7 +3049,15 @@
        "dtype: int64"
       ]
      },
+<<<<<<< HEAD
+<<<<<<< HEAD
      "execution_count": 23,
+=======
+     "execution_count": 22,
+>>>>>>> main
+=======
+     "execution_count": 23,
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2242,7 +3081,17 @@
     "OnlineSecurity is (True/False) in df_db; but Yes/No/No Internet in df_excel\n",
     "DeviceProtection is (True/False) in df_db; but (yes/no) in df_excel\n",
     "\n",
+<<<<<<< HEAD
+<<<<<<< HEAD
+    "TotalCharges is supposed to be float64 type but is object in df_excel"
+=======
+    "TotalCharges is supposed to be float64 type but is object in df_excel\n",
+    "\n",
+    " \n"
+>>>>>>> main
+=======
     "TotalCharges is supposed to be float64 type but is object in df_excel"
+>>>>>>> a61f3e857c29edc0e2b7d8a2e93f52101a5dda44
    ]
   },
   {