portfolio

Sales Analytics Dashboard

A comprehensive data analytics project that analyzes sales data and creates interactive visualizations using Python, pandas, matplotlib, and seaborn.

Features

• Data Analysis: Comprehensive sales data analysis with statistical insights
• Visualizations: Interactive charts and graphs including:
  • Sales trends over time
  • Product performance analysis
  • Regional sales distribution
  • Customer segmentation
• Export Reports: Generate PDF and HTML reports
• Data Cleaning: Automated data preprocessing and validation

Technologies Used

• Python 3.8+
• pandas - Data manipulation and analysis
• matplotlib - Data visualization
• seaborn - Statistical data visualization
• numpy - Numerical computing
• jupyter - Interactive notebooks

Installation

pip install -r requirements.txt

Usage

Run the main analysis:

python main.py

Open Jupyter Notebook for interactive analysis:

jupyter notebook analysis.ipynb

Project Structure

• main.py - Main analysis script
• analysis.ipynb - Interactive Jupyter notebook
• data/ - Sample sales data
• reports/ - Generated reports and visualizations
• src/ - Source code modules
  • data_loader.py - Data loading and preprocessing
  • analyzer.py - Analysis functions
  • visualizer.py - Visualization functions

Sample Insights

The dashboard provides insights such as:

• Top performing products and regions
• Seasonal sales trends
• Customer buying patterns
• Revenue forecasts
• Product correlation analysis

Future Enhancements

• Real-time data integration
• Machine learning predictions
• Interactive web dashboard with Plotly Dash
• Database integration