The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON

The open-source tool for building high-quality datasets and computer vision models

A light-weight, flexible, and expressive statistical data testing library

Jupyter notebook and datasets from the pandas video series

General Assembly's 2015 Data Science course in Washington, DC

🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark

simple tools for data cleaning in R

The JavaScript data transformation and analysis toolkit inspired by Pandas and LINQ.

Prepping tables for machine learning

An open-source educational chat model from ICALK, East China Normal University. 开源中英教育对话大模型。(通用基座模型，GPU部署，数据清理) 致敬: LLaMA, MOSS, BELLE, Ziya, vLLM

Schema-Inspector is a simple JavaScript object sanitization and validation module.

Easy to use Python library of customized functions for cleaning and analyzing data.

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

Professional data validation for the R environment

Deal with bad samples in your dataset dynamically, use Transforms as Filters, and more!

🗣️ A book and repo to get you started programming voice computing applications in Python (10 chapters and 200+ scripts).

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

Data Science Feature Engineering and Selection Tutorials

A domain-specific probabilistic programming language for scalable Bayesian data cleaning