# pyjanitor-devs/pyjanitor

Clean APIs for data cleaning. Python implementation of R package Janitor

Repository: https://github.com/pyjanitor-devs/pyjanitor
Canonical: https://ross.abutalabs.com/products/pyjanitor
Homepage: https://pyjanitor-devs.github.io/pyjanitor
Language: Python
License: MIT
License Family: permissive
Topics: pandas, dataframe, data, cleaning-data, data-engineering, pydata, hacktoberfest
Last push: 2026-08-26T15:18:58+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 98, longevity 100
- inputs: {"age_days": 3104, "days_push": 7, "days_rel": 16, "gap_med": 4, "n_releases_24m": 26}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1498, forks 195 (observed 2026-08-28T04:04:54.066864+00:00)

## What it is
pyjanitor is a Python library providing clean, readable APIs for data cleaning on pandas DataFrames, inspired by the R package janitor. It extends pandas with method-chaining functions for common preprocessing tasks like dropping empty rows, renaming columns, and filtering.

## Use cases
- clean messy pandas dataframes
- remove empty rows and columns from data
- rename dataframe columns consistently
- chain data preprocessing steps readably
- port R janitor workflows to Python
- prepare raw data for analysis

## When to choose
- you use pandas and want expressive, chainable data-cleaning functions
- you want a dplyr/janitor-style API in Python

## When to avoid
- you work outside the pandas ecosystem
- you need heavy-duty distributed data processing like Spark

## Facets
- artifact type: library
- maturity: active
- function: data-science, etl
- domain: data-science
- platform: python
- tags: pandas, dataframe, data-cleaning, method-chaining, data-preprocessing, data-engineering

## Member repositories
- pyjanitor-devs/pyjanitor (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:54.066864+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:33:05.678598+00:00, confidence not recorded.
  - readme: https://github.com/pyjanitor-devs/pyjanitor (fetched 2026-08-28T04:04:54.066864+00:00, sha cb3e107da3bb)
  - homepage: https://pyjanitor-devs.github.io/pyjanitor (fetched 2026-08-29T11:38:18.578967+00:00, sha d3c8e925057c)
  - registry_pypi: https://pypi.org/pypi/pyjanitor/json (fetched 2026-08-29T11:38:18.581762+00:00, sha af8977b759de)
- Data as of 2026-08-30T08:39:29.467469+00:00.