Awesome GitHub RepositoriesData Processing Libraries

Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e

This library is a data processing framework for the JVM that provides a type-safe environment for manipulating structured tabular data. It functions as a comprehensive toolset for performing complex data transformations, aggregations, and statistical analysis, while leveraging compile-time schema validation to ensure structural integrity across data pipelines. The project distinguishes itself through its deep integration with interactive notebook environments and its use of compile-time code generation. By automatically deriving and enforcing schemas from raw inputs, it generates type-safe ac