UserTrackAI

This repository contains an exploratory data analysis (EDA) of user behavior, product data, and session activity in an e-commerce environment.

📊 Project Overview

The goal of this project is to understand how users interact with an online store by analyzing three main datasets:

• user.csv — demographic and basic info of users
• product.csv — product metadata and category info
• session.csv — user browsing and session activity

The project includes:

• Data cleaning and preprocessing
• Exploratory visualizations (matplotlib, seaborn, folium)
• Encoding and feature transformation
• Geospatial analysis using geopandas and folium

🧰 Technologies Used

• Python 3.x
• Jupyter Notebook
• pandas, numpy
• matplotlib, seaborn
• scikit-learn
• geopandas, folium

📍 Highlights

• Distribution and uniqueness of product, session, and user data
• Detection of missing values and basic data imputation
• Label encoding for categorical features
• Initial steps toward segmentation and predictive modeling
• Mapping user behavior geographically using Folium