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glnnlhmn/PSF-Survey-Data-Playground

PSF Survey Data Playground

Welcome to the PSF Survey Data Playground! This repository, PSF-Survey-Data-Playground, contains data from the annual PSF survey. It is designed to be a comprehensive resource for data cleaning and exploration.

We encourage you to create your own notebooks and scripts to analyze and visualize the data. Whether you're a beginner or an experienced data scientist, this playground is the perfect place to experiment, learn, and share your insights.

Our goal is to foster a collaborative learning environment. By contributing your work, you help others understand different approaches and techniques. We believe in the power of community and the importance of sharing knowledge.

When you document your process, please aim to teach others. Explain your steps clearly and provide insights into your thought process. Even small contributions can make a big difference in helping others learn.

Remember, the primary goal of this project is to learn and grow together. So, dive in, experiment, and don't hesitate to share your findings. Let's make data science accessible and enjoyable for everyone!

Features

Feature Description
PSF_DATA_PIPELINE This feature is the entire data cleaning process, from loading raw data to producing clean, analyzable data.

Setup Instructions

For detailed setup instructions, please refer to the Setup Guide.

How to Contribute

We welcome contributions to the PSF Survey Data Playground! If you would like to contribute, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bugfix.
  3. Make your changes.
  4. Commit your changes with a descriptive commit message.
  5. Push your changes to your fork.
  6. Open a pull request to the main repository.

For more detailed guidelines, please refer to our Contributing Guide.

Acknowledgements

We would like to extend our heartfelt thanks to JetBrains for making the raw data available. Your commitment to providing valuable resources is greatly appreciated.

Additionally, we are grateful to the Python Software Foundation for conducting their annual survey. Your efforts in gathering and sharing insights about the Python community are invaluable.

License

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

About

This repo contains data from the annual PSF survey, perfect for practicing data cleaning and exploration. Features: Data Cleaning: Hone your skills with real-world data. Data Exploration: Discover trends and insights. Storytelling: Example stories for data presentation.

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