Make awesome display tables using Python
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Updated
Sep 9, 2025 - Python
Make awesome display tables using Python
Python package to read and write sas, spss and stata files into/from pandas and polars data frames. It is a wrapper for the C library readstat.
Scripts and datasets for the O'Reilly book Python Polars: The Definitive Guide
VS Code extension to transform table from clipboard to R, Python, Julia, JS or MD dataframe
New Polars implementation of the classic featurewiz MRMR algorithm. Created by Ram Seshadri. Collaborators welcome.
Polars extension for fzf-style fuzzy matching
Material (notebooks and data) for the hands-on workshop "Polars: The Turbo Boost for Dataframes" at data2day 2023 by BettercallPaul.
Pizzly, financial market analysis combining technical indicators with LLMs, featuring real-time data processing and AI-powered market insights ⚡️
PyIndicators is a powerful and user-friendly Python library for financial technical analysis indicators, metrics and helper functions for pandas and polars dataframes. Written entirely in Python, it requires no external dependencies, ensuring seamless integration and ease of use.
Building a poor man's data lake: Exploring the Power of Polars and Delta Lake
Polars Plugin for List-type Columns
Python library providing a Polars DataFrame interface for easy and intuitive access to the Bloomberg API
Dimensionality Reduction, Animated
Osiris is a Python library designed for efficient data conversion and management, primarily transforming data into Cairo programs
A Polars plugin for JSON schema inference from string columns using genson-rs.
Learn data collection by putting a couple of things into consideration
Log LAMMPS Reader is a high-performance Rust library and Python extension for reading LAMMPS log files and converting them into DataFrames using the Polars library. This project leverages PyO3 to create a Python module that interfaces with Rust code, ensuring both speed and efficiency.
Sumeh — Unified Data Quality Framework Sumeh is a unified data quality validation framework supporting multiple backends (PySpark, Dask, Polars, DuckDB, Pandas) with centralized rule configuration.
Explore MVG Rad bike sharing ride data
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