joyce767/Nigeria-E-commerce-Data-Analysis

Data wrangling and Visualizations using Pandas, NumPy, Matplotlib, Plotly. # E-Commerce Data Analysis Project ## Overview This project explores and analyzes a Nigerian e-commerce dataset using Python libraries such as **Pandas**, **NumPy**, **Matplotlib**,**Seaborn**, and **Plotly** The analysis focuses on understanding customer behavior, sales trends, and revenue insights to derive actionable business conclusions. ## Tools & Libraries - Python - Pandas - NumPy - Matplotlib - Seaborn - Google Colab ## Objectives - Clean and preprocess raw e-commerce data. - Perform exploratory data analysis (EDA) to uncover insights. - Visualize customer and sales trends. - Identify factors influencing purchase frequency and total revenue. ## Key Insights - Revenue distribution by category and region. - Customer purchase frequency patterns. - Peak order periods and product performance. ## Results The visualizations and insights from this analysis can guide marketing, pricing, and inventory decisions for e-commerce platforms. ## How to Use 1. Download the `.ipynb` notebook from this repository. 2. Open it in **Google Colab** or **Jupyter Notebook**. 3. Run all cells to reproduce the results. ## Author **Joy Olamide** --- © 2025 Joy Olamide. All rights reserved.