📊 Data Visualization Dashboard

A Streamlit web application for exploring, visualizing, and analyzing datasets, with options to clean data and download reports as PDF or CSV.

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Features

1. Upload Data

   • Upload CSV or Excel files.
   • Automatically stores the dataset in the app session.

2. Data Summary

   • View number of rows & columns.
   • Descriptive statistics for all columns.
   • Check missing values.
   • Quick data cleaning: drop missing values or duplicates.

3. Visualization

   • Generate charts:

     • Line, Bar, Scatter, Pie, Histogram, Box, Heatmap, Pairplot.

   • Option to use interactive Plotly charts or static Seaborn/Matplotlib charts.

   • Select axes and columns dynamically.

4. Advanced Analysis

   • Correlation heatmap for numeric columns.
   • Value counts for any column.

5. Download Report

   • Generate PDF report with:

     • Dataset overview, missing values, descriptive stats, and a sample chart.

   • Download cleaned CSV dataset.

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Installation

1. Clone the repository

git clone <your-repo-url>
cd <your-repo-folder>

2. Create a virtual environment (optional but recommended)

python -m venv venv
source venv/bin/activate   # Linux/macOS
venv\Scripts\activate      # Windows

3. Install dependencies

pip install streamlit pandas matplotlib seaborn plotly fpdf openpyxl

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Usage

1. Run the Streamlit app:

streamlit run app.py

2. Use the sidebar menu to navigate:

   • Upload your dataset.
   • View data summary & clean data.
   • Generate visualizations.
   • Perform advanced analysis.
   • Download PDF/CSV report.

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Supported File Formats

• CSV (.csv)
• Excel (.xlsx)

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Screenshots

Dependencies

• Python 3.7+
• Streamlit
• Pandas
• Matplotlib
• Seaborn
• Plotly
• FPDF

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Notes

• For large datasets, visualizations like pairplots may take time to render.
• PDF generation may truncate long text in tables.

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License

This project is open-source and free to use.