We welcome contributions to improve this guide! Here's how you can help:
If you find any errors or have suggestions for new packages to include:
- Open an issue in the issue tracker.
- Provide a clear and descriptive title.
- Include as much detail as possible about the suggestion or problem.
To make changes directly:
-
Fork the Repository: Click the "Fork" button at the top right of the repository page.
-
Clone Your Fork: Clone the forked repository to your local machine.
git clone https://github.com/yourusername/python-packages-for-applied-economists.git
Replace
yourusername
with your GitHub username. -
Create a New Branch: It's good practice to create a new branch for your changes.
git checkout -b feature/your-feature-name
-
Make Your Changes:
- Edit the
GUIDE.md
file or other relevant files as needed. - Follow the existing structure and format of the guide.
- Ensure all links are valid and point to the correct resources.
- Use proper Markdown formatting.
- Edit the
-
Commit Your Changes:
git commit -am "Add detailed description of your changes"
-
Push to Your Fork:
git push origin feature/your-feature-name
-
Submit a Pull Request: Go to your fork on GitHub and click the "Compare & pull request" button.
- Provide a clear and descriptive title for your pull request.
- In the pull request description, explain what changes you've made and why they should be included.
- Consistency: Maintain consistency with the existing style and formatting of the guide.
- Clarity: Be clear and concise in your descriptions and explanations.
- Accuracy: Verify the accuracy of the information you provide, including package names, installation commands, and links.
- Formatting: Use Markdown formatting properly, including headings, lists, code blocks, and links.
- Language: Use proper spelling and grammar.
- If you have any questions or need assistance, feel free to open an issue in the issue tracker.
Thank you for your interest in improving this guide! Your contributions help make this resource more valuable for the community of applied economists using Python.