Gmail Data Analysis Project

This is a data analysis project focused on Gmail account data (For privacy reasons i have not uploaded the data file which is used on this project for analysis) You can request your data from here. The aim of the project is to analyze the email habits of the account owner and uncover interesting insights about their communication patterns.

Table of Contents

• Introduction
• Project Scope
• Project Output
• Technologies Used
• Getting Started
• Usage
• Contributing

Introduction

This project analyzes the volume of incoming and outgoing emails, identifies the busiest days of the week, identifies frequent contacts for both sent and received emails, and identifies the most common topics in email conversations. The analysis is performed using Python libraries such as Pandas, Matplotlib, and Seaborn.

Project Scope

The project includes the following tasks:

• Data collection from the Gmail account
• Data cleaning and preparation
• Exploratory data analysis
• Visualization of the results
• Generation of insights

Project Output

The output of the project includes:

• Jupyter Notebook containing the code for data analysis.

Technologies Used

The following technologies were used in this project:

• Python
• Jupyter Notebook
• Pandas
• Numpy
• Matplotlib
• Seaborn

Getting Started

To get started with this project, you will need:

• Access to a Gmail account
• Python 3.x installed on your computer
• Jupyter Notebook installed on your computer

Usage

To use this project, you can:

• Clone the repository to your local machine
• Open the Jupyter Notebook file in a Jupyter Notebook environment
• Run the code cells to perform data analysis
• Explore the results and insights generated by the analysis

Contributing

Contributions to this project are welcome! If you find any bugs or issues, please open an issue on the GitHub repository.