E-Commerce User Behavior Analysis

This project explores an E-commerce dataset from Flipkart to understand product listings, pricing patterns, and category popularity. The goal is to perform Exploratory Data Analysis (EDA) and generate insights about which products and categories appear most frequently in the dataset. The analysis focuses on understanding product data such as product names, categories, pricing, and brand information, and visualizing trends using data visualization techniques.

Dataset Description

The dataset contains information about thousands of products listed on Flipkart. Each row represents a product listing with multiple attributes. Key attributes include: Product Name – Name of the product Product Category Tree – Category hierarchy of the product Retail Price – Original product price Discounted Price – Price after discount Brand – Brand name of the product Product Rating – Customer rating of the product Description – Product description and features Product Specifications – Detailed specifications of the product The dataset contains around 20,000 product listings, making it suitable for data analysis and visualization.

Key Insights

The dataset contains a large number of products across multiple categories. Some product categories appear significantly more often than others. Prices vary widely across different products and categories. Certain products appear multiple times in the dataset, indicating high listing frequency.