📦 E-Commerce Database Analysis Using SQL & Python

This project performs data analysis on an E-commerce database using MySQL, Python, and Pandas. A Jupyter Notebook (Ecommerce Python+SQL Project) is used to execute SQL queries directly from Python and analyze the results.

🎯 Project Objectives

• Connect Python to a MySQL E-commerce database
• Run SQL queries from Jupyter Notebook
• Analyze customers, orders, sales, and product category performance
• Visualize insights using Matplotlib & Seaborn

🧰 Tech Stack: Languages:

• Python
• SQL Libraries Used:
• mysql-connector-python
• pandas
• matplotlib
• seaborn
• numpy

Database: MySQL (Localhost)

🗄️ Database Tables Used From the notebook, the database contains

• customers
• orders
• products
• order_items
• order_payments
• sellers
• geolocation

🔧 Project Workflow

1️⃣ Connect Python to MySQL The notebook uses:

db = mysql.connector.connect( host='localhost', user='root', password='your_password', database='Ecommerce' ) cur = db.cursor()

• Enables running SQL queries directly from Python.

2️⃣ Execute SQL Queries

• The notebook contains multiple business-focused SQL queries including:

✔ 1. List all unique customer cities

• SELECT DISTINCT customer_city FROM customers;

✔ 2. Count number of orders placed in 2017

• SELECT COUNT(order_id) FROM orders WHERE YEAR(order_purchase_timestamp) = 2017;

✔ 3. Total sales by product category SELECT UPPER(products.product_category) AS category, SUM(order_items.price) AS sales FROM order_items JOIN products ON order_items.product_id = products.product_id GROUP BY category;

• Results are loaded into Pandas DataFrames for further analysis.

3️⃣ Data Visualization Visualizations created using:

• import matplotlib.pyplot as plt
• import seaborn as sns

Examples:

• Bar chart of sales by category
• Distribution plots of sales
• Geographic insights (cities, states)

📊 Sample Analysis Performed ✔ Customer locations ✔ Order volume trends ✔ Sales by product category ✔ Seller performance ✔ Payment type distribution

▶️ How to Run the Project

1️⃣ Install dependencies

• pip install -r requirements.txt

2️⃣ Start MySQL server locally

• Ensure the Ecommerce database is imported.

3️⃣ Run the notebook

• jupyter notebook Ecommerce Python+SQL Project

🧾 Requirements

• mysql-connector-python
• pandas
• matplotlib
• seaborn
• numpy

👨‍💻 Developed By -- Ayush Data Analysis | SQL | Python | Machine Learning

• 🔗GitHub: https://github.com/ayush13-0
• 🔗LinkedIn: https://www.linkedin.com/in/ayush130

📜 License

• This project is licensed under the MIT License.