Sales Data Analysis

Overview

This project analyzes a retail sales dataset using Python, Pandas, and Matplotlib. It performs data cleaning, statistical analysis, and data visualization to identify sales trends and generate useful business insights.

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Dataset

File: superstore_dataset2011-2015.csv

The dataset contains retail sales records used for analysis and visualization.

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Features

• Load sales data from a CSV file
• Display the first five records
• Display dataset information
• Generate descriptive statistics
• Check for missing values
• Calculate total sales
• Analyze sales by category
• Display the top 10 products by sales
• Plot monthly sales trends
• Visualize sales by region
• Perform correlation analysis
• Generate a final sales report

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Technologies Used

• Python
• Pandas
• Matplotlib

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Project Structure

SalesDataAnalysis/
│
├── analysis.py
├── superstore_dataset2011-2015.csv
├── README.md
└── LICENSE

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Installation

Clone the repository

git clone https://github.com/taqdeesfatima-ds/SalesDataAnalysis.git

Move to the project directory

cd SalesDataAnalysis

Install the required libraries

pip install pandas matplotlib

Run the project

python analysis.py

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Output

The program generates:

• Dataset Overview
• Sales Statistics
• Monthly Sales Trend
• Sales by Region
• Correlation Analysis
• Final Sales Report

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Screenshots

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Future Improvements

• Add interactive dashboards
• Export reports to Excel or PDF
• Build a Streamlit web application
• Add filtering options by region and category
• Support multiple datasets

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Author

Taqdees Fatima

Python Developer | Python Trainee & Intern

BS Data Science Student

Email: taqdeesf5@gmail.com

GitHub: https://github.com/taqdeesfatima-ds

LinkedIn: https://linkedin.com/in/taqdees-fatima-aa9b68260

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License

This project is licensed under the MIT License.