Have you ever wished for a simple and approachable way to learn and experiment with math and dataframe operations? Rustframe is a new educational project that aims to provide just that. This lightweight toolkit offers straightforward implementations of common dataframe, matrix, mathematical, and statistical operations, making it ideal for quick numeric experiments or learning.
The project’s goal is to provide a clean API with high test coverage, making it perfect for educational purposes. Rustframe is not meant to compete with heavyweights like polars or ndarray, but rather to offer a more approachable alternative.
The toolkit includes a range of features, such as matrix operations, dataframes, compute modules, and random utilities. It also includes a growing collection of demos showcasing broader functionality, including simple ML models. Each module includes unit tests that double as usage examples, and the documentation is enriched with inline code and doctests.
The project is still evolving, and the creator is looking for feedback, code reviews, and contributions. If you’re interested in learning more or getting involved, be sure to check out the GitHub repository, Crates.io page, and homepage.