1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
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Updated
Jun 11, 2024 - Python
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Always know what to expect from your data.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
The open-source tool for building high-quality datasets and computer vision models
The Open Source Feature Store for Machine Learning
Compare tables within or across databases
⚡ Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
Automatically find issues in image datasets and practice data-centric computer vision.
Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
Code review for data in dbt
The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.
FeatHub - A stream-batch unified feature store for real-time machine learning
The Lakehouse Engine is a configuration driven Spark framework, written in Python, serving as a scalable and distributed engine for several lakehouse algorithms, data flows and utilities for Data Products.
数据治理、数据质量检核/监控平台(Django+jQuery+MySQL)
Great Expectations Airflow operator
Possibly the fastest DataFrame-agnostic quality check library in town.
re_data - fix data issues before your users & CEO would discover them 😊
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
Swiple enables you to easily observe, understand, validate and improve the quality of your data
Define, govern, and model event data for warehouse-first product analytics.
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