📊 ChartMaker - Offline CSV to Chart Converter

A portable, offline application to create beautiful charts from CSV files using Plotly. Works on Windows, macOS, and Linux with Docker.

✨ Features

• 📈 Multiple Chart Types: Bar, Line, Scatter, Pie, and Area charts
• 🎨 Customizable Styling:
  • Multiple color palettes
  • Custom backgrounds (White, Black, Transparent)
  • Adjustable text colors and labels
• 💾 Export Options: PNG, JPEG, SVG, and PDF formats
• 📦 Batch Processing: Export all charts at once
• 🌐 Bilingual: English and Portuguese (PT) interface
• 🔒 Offline: Works completely offline after initial setup
• 🐳 Docker-based: No Python installation required

🚀 Quick Start

Prerequisites

• Docker Desktop installed and running
• Any modern web browser

Installation & Running

On Linux (Ubuntu, Debian, Mint, etc.)

1. Clone or download this repository

   git clone https://github.com/brunurb/plotly-chart-maker-offline.git
   cd plotly-chart-maker-offline

2. Make the run script executable

   chmod +x run.sh

3. Run the application

   ./run.sh

4. Access the app

   • Your browser will open automatically to http://localhost:8501
   • Or manually navigate to http://localhost:8501

On Windows

1. Download and extract this repository

2. Double-click run.bat

3. Access the app at http://localhost:8501 (opens automatically)

On macOS

1. Clone or download this repository

   git clone https://github.com/brunurb/plotly-chart-maker-offline.git
   cd plotly-chart-maker-offline

2. Make executable and run

   chmod +x run.sh
   ./run.sh

3. Access at http://localhost:8501

📖 How to Use

1. Upload CSV files - Click "Choose CSV files" and select one or more files
2. Choose chart type - Bar, Line, Scatter, Pie, or Area
3. Select color palette - Preview and choose from available palettes
4. Customize appearance - Toggle labels, values, and styling options
5. Select export format - PNG, JPEG, SVG, or PDF
6. Preview - Click "Preview Charts" to see your visualizations
7. Export - Use "Export All Charts" for batch download or export individually

📂 CSV File Format

Your CSV files should have:

• Header row with column names
• First column: Categories/labels (e.g., location names)
• Remaining columns: Numeric data to plot

Example:

concelhos,Sim,Não,Ns/Nr
Lisboa,45,30,25
Porto,50,35,15
Faro,40,40,20

🎨 Export Formats

• PNG: Best for presentations and documents (raster image)
• JPEG: Compressed raster image
• SVG: Best for scaling and editing (vector image)
• PDF: Best for printing and reports

📁 Output

Exported charts are saved in the output_charts folder in the same directory as the application.

🛠️ Technical Details

Built With

• Streamlit - Web application framework
• Plotly - Interactive charting library
• Pandas - Data manipulation
• Kaleido - Static image export
• Docker - Containerization

Architecture

The application runs in a Docker container with:

• Python 3.8
• All required dependencies pre-installed
• Persistent volume for chart exports
• Port mapping to localhost:8501

System Requirements

• RAM: 2GB minimum
• Disk Space: ~500MB for Docker image
• OS: Linux, Windows 7+, or macOS 10.14+
• Docker: Version 20.10 or higher

🔧 Troubleshooting

Docker is not running

# Linux
sudo systemctl start docker

# Or start Docker Desktop on Windows/Mac

Port 8501 already in use

Edit run.sh or run.bat and change the port:

# Change this line:
docker run -p 8502:8501 ...
# Then access at http://localhost:8502

Permission denied on Linux

# Make script executable
chmod +x run.sh

# Or run Docker without sudo (add user to docker group)
sudo usermod -aG docker $USER
# Then log out and log back in

Charts not exporting

• Check the output_charts folder is created
• Ensure Docker has permission to write to the directory
• Try running Docker with elevated permissions

Browser doesn't open automatically

Manually navigate to: http://localhost:8501

🌐 Online Version

For an online version that works without installation, visit: plotly-chart-maker-bbb.streamlit.app

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.

👤 Author

Bruno

• GitHub: @brunurb

🙏 Acknowledgments

• Built with Streamlit
• Charts powered by Plotly
• Containerized with Docker

📸 Screenshots

---

⭐ If you find this project useful, please consider giving it a star!