E-Commerce Data Analysis and Visualization

This project involves analyzing and visualizing an e-commerce dataset to gain insights into product trends, customer behavior, and sales strategies.

Table of Contents

• Introduction
• Dataset
• Setup
• Data Preparation
• Exploratory Data Analysis (EDA)
• Visualizations
• License

Introduction

In the world of e-commerce, data is a powerful asset that can be leveraged to understand customer behavior, improve sales strategies, and enhance overall business performance. This project explores how to effectively utilize an e-commerce dataset to gain valuable insights into product trends, customer preferences, and market dynamics.

Dataset

The dataset used in this project is the "E-commerce product dataset," which contains information on 1000 products across different categories. The dataset includes attributes such as price, rating, number of reviews, stock quantity, discounts, sales, and date added to inventory.

Setup

To run the scripts in this project, you need to have Python and the required packages installed. You can install the necessary packages using pip:

pip install pandas matplotlib seaborn