Topics / #data-cleaning

Data-cleaning projects on GitHub

Tools that detect dataset errors and clean training data.

As of , the most-starred Data-cleaning projects on GitHub are great_expectations (11.9K stars), cleanlab (11.7K stars) and fiftyone (11.2K stars). GitHub.Locker tracks 5 Data-cleaning repositories with 45.3K stars combined. The fastest-growing on October 16 was fiftyone, with +3 stars in a day.

5Projects
45.3KStars in total
+8Stars in a day
Browse in the catalog →github.com/topics/data-cleaning ↗

Hot right now

Most stars gained in a day · Oct 16

+3

fiftyone

voxel51/fiftyone · ★ 11.2K

FiftyOne is an open-source tool for building high-quality datasets and computer vision models: you use it to visualize and label your visual data, evaluate models, and find and fix data quality issues.

+2

great_expectations

fivetran/great_expectations · ★ 11.9K

GX Core (Great Expectations) is a Python framework for testing, validating, and documenting the quality of your data. Its core concept is the 'Expectation' — an expressive unit test for your data, built from the collective experience of thousands of data quality deployments.

+2

cleanlab

cleanlab/cleanlab · ★ 11.7K

Cleanlab is an open-source Python library that automatically finds issues in ML datasets — label errors, outliers, duplicates — using your existing models, so that fixing the data trains better models.

+1

huashu-excel

alchaincyf/huashu-excel · ★ 439

This is a Skill for AI coding agents that handles the entire Excel/data-analysis workflow: it profiles a messy spreadsheet, cleans it, aligns with the user on what to actually analyze, runs the analysis, reconciles the numbers against the sheet's own totals, and only then delivers a report.

The all-time top

5 projects · by stars

  1. #1 · fivetran/great_expectations

    great_expectations

    GX Core (Great Expectations) is a Python framework for testing, validating, and documenting the quality of your data. Its core concept is the 'Expectation' — an expressive unit test for your data, built from the collective experience of thousands of data quality deployments.

    11.9K
  2. #2 · cleanlab/cleanlab

    cleanlab

    Cleanlab is an open-source Python library that automatically finds issues in ML datasets — label errors, outliers, duplicates — using your existing models, so that fixing the data trains better models.

    11.7K
  3. #3 · voxel51/fiftyone

    fiftyone

    FiftyOne is an open-source tool for building high-quality datasets and computer vision models: you use it to visualize and label your visual data, evaluate models, and find and fix data quality issues.

    11.2K
  1. 4

    miller

    10Kjohnkerl/miller · Go

    Miller is a command-line toolkit like awk, sed, cut, join, and sort, but built for name-indexed data such as CSV, TSV, JSON, and JSON Lines: you address fields by name instead of counting column positions.

  2. 5

    huashu-excel

    439alchaincyf/huashu-excel · Python

    This is a Skill for AI coding agents that handles the entire Excel/data-analysis workflow: it profiles a messy spreadsheet, cleans it, aligns with the user on what to actually analyze, runs the analysis, reconciles the numbers against the sheet's own totals, and only then delivers a report.

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