This repo was copied from pandas_cookbook. Do have a look at the original.
There are several chapters that guide you through how to use pandas in the cookbook folder. It will be your job to create a cookbook for polars.
- Fork this repo.
- Clone the forked repo and open it in VS Code.
- Create a virtual environment from the environment.yml:
- Select this environment as your interpreter in VS Code.
Refactor the "Pandas cookbook" repository into a "Polars cookbook," showcasing common functionalities of the Polars library.
A common task as a data scientist is refactoring code. Refactoring code involves improving its readability, efficiency, or adapting it to use different libraries. This exercise focuses on rewriting Pandas code using Polars, a relatively new data manipulation library.
By completing this assignment, you'll create a valuable "Polars cookbook" on your GitHub profile that demonstrates common data manipulation tasks using the Polars library.
Polars is quickly gaining popularity because of its nice syntax and speed.
- Fork the repository from the Cambridge-FDS workspace: https://github.com/cambridge-FDS/pandas_to_polars_cookbook
- Divide the chapters among team members, ensuring each person is responsible for at least one chapter of the cookbook.
- Rewrite each Pandas implementation using Polars. Note that sometimes this might not be directly possible. Particularly plotting is harder with a Polars data frame at the moment.
- Create a separate Pull Request (PR) for each change implemented.
- Have team members review each other's PRs to ensure everyone gains exposure to various Pandas and Polars functionalities across all chapters.
- Keep Pull Requests concise and focused on specific changes.
- Each team member should provide PR reviews to maximise learning opportunities.
- After forking the repo, team members can clone it directly from their teammate's GitHub page.
For an introduction to Polars, refer to this tutorial: https://calmcode.io/course/polars/introduction