📊 Sales Data Analysis Project

overview

This project analyzes a retail sales dataset to identify patterns, trends, and key business insights using data analysis and visualization techniques.

🔷 Tools & Technologies

• Python
• Pandas
• Matplotlib
• Seaborn
• Jupiter Notebook -visual studio code

🔷 Dataset

The dataset contains information about:

• Order Date
• Region
• Category & Sub-Category
• Sales and Customer Segment

🔷 Key Insights

• West region generates the highest total sales
• Technology category contributes the most revenue
• Sales data is highly right-skewed (many small, few large transactions)
• Significant outliers exist across categories
• Monthly sales show fluctuating trends over time
• Certain sub-categories dominate overall sales

🔷 Visualizations

• 📊 Region-wise Sales (Bar Chart)
• 📈 Monthly Sales Trend (Line Chart)
• 📦 Category-wise Distribution (Boxplot)
• 📉 Sales Distribution (Histogram + KDE)

IMAGES

category_box

distribution_sales

monthly_sales

region_sales

project structure

SALES_PROJECT/ |- Sample -Superstore.csv |--analysis.ipynb |--images/ |--analysis.py |--Readme.md