Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:46 UTC

pyjanitor-devs / pyjanitor

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

PythonMIT★ 1,499 stars⑂ 191 forkssince Mar 2018View on GitHub ↗

#pandas #dataframe #data #cleaning-data #data-engineering #pydata #hacktoberfest

pyjanitor-devs/pyjanitor holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Vitality (88/100) and lowest on Security (67/100). It was last updated 1 day ago. 2 contributors account for most of its recent work.

overall / 100

Exceptional

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met

Excellent80-92Strong across the board; minor gaps

Good65-79Healthy; gaps are limited and manageable

Moderate50-64Acceptable with notable gaps; review recommended

Weak35-49Material weaknesses across several areas

At Risk20-34Significant weaknesses; adoption warrants caution

Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 79 is calibrated to 93 on the published index scale (record calibration 2026-08-02).

Ownership

pyjanitor-devsOrganization

21 followers5 public repossince Jul 2019

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish	Tags
PyPI	pyjanitor	0.32.23	-	90	127 days ago	pandas data-cleaning data-science janitor

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

88Excellent · 21% of overall

Development activity

87Excellent

How it's scored

36/36	Push recency — last push 1 days ago
22.8/36	Commit cadence — 33/52 weeks with commits
18/18	Commit volume — 267 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 16 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	267
human_commit_share	0.88
days_since_last_push	1
active_weeks_last_year	33

Release discipline

90Excellent

How it's scored

27/27	Ships releases — 38 releases published
27/36	Release recency — latest release 127 days ago
27/27	Release cadence — a release every ~6.5 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	38
latest_release_tag	v0.32.23
releases_from_tags	no
days_since_latest_release	127
mean_days_between_releases	6.5

Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

77Good · 17% of overall

Popularity & adoption

77Good

How it's scored

51.5/60	Stars — 1,499 stars
19/25	Forks — 191 forks
6.4/15	Watchers — 15 watchers

Inputs used

forks	191
stars	1,499
watchers	15
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

77Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (MIT)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	0
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	—
has_pull_request_template	yes

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

77Good · 23% of overall

Maintainer resilience (bus factor)

61Moderate

How it's scored

25.2/54	Bus factor — 2 contributor(s) cover half of all commits
11.9/22.5	Commit distribution — top contributor authored 47% of commits
13.5/13.5	Contributor breadth — 97 contributors
10/10	OpenSSF Scorecard: Contributors — project has 16 contributing companies or organizations

Inputs used

bus_factor	2
contributors_sampled	97
top_contributor_share	0.473

Issue & PR responsiveness

81Excellent

How it's scored

35.1/42	Issue resolution — 84% of issues closed
27.1/30	PR acceptance — 899/995 decided PRs merged
13/13	Newcomer PR acceptance — 3/3 first-time contributors' PRs merged in 30d
6/15	OpenSSF Scorecard: Code-Review — Found 8/17 approved changesets -- score normalized to 4

Inputs used

merged_prs	899
open_issues	100
closed_issues	509
prs_merged_7d	3
prs_decided_7d	3
prs_merged_30d	3
prs_decided_30d	3
issue_closed_ratio	0.836
closed_unmerged_prs	96
first_time_authors_30d	3
first_time_prs_merged_30d	3
first_time_prs_decided_30d	3

Ownership & stewardship

72Good

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain — verified-domain status not read for this organization
9.7/25	Owner reach — 21 followers of pyjanitor-devs
17.7/25	Track record — 5 public repos, account ~7 yr old

Inputs used

followers	21
owner_type	Organization
is_verified	—
owner_login	pyjanitor-devs
public_repos	5
account_age_days	2,572

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 127 days ago
20/20	Version history — 90 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	pyjanitor
ecosystems	pypi
any_deprecated	no
min_days_since_publish	127

Engineering Quality

Are baseline engineering and documentation practices in place?

85Excellent · 19% of overall

Engineering practices

92Excellent

How it's scored

24/24	CI workflows — 3 workflow(s)
24/24	Tests present
16/16	Linter config
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
18/20	OpenSSF Scorecard: CI-Tests — 18 out of 20 merged PRs checked by a CI test -- score normalized to 9

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

75Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://pyjanitor-devs.github.io/pyjanitor
10/10	Repository description
10/10	Topics — 7 topics
10/10	Wiki

Inputs used

topics	pandas, dataframe, data, cleaning-data, data-engineering, pydata, hacktoberfest
has_wiki	yes
homepage	https://pyjanitor-devs.github.io/pyjanitor
docs_site	https://pyjanitor-devs.github.io/pyjanitor
has_readme	yes
has_docs_dir	no
has_description	yes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

67Good · 16% of overall

Security posture

59Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2.2/2.5	CI-Tests — 18 out of 20 merged PRs checked by a CI test -- score normalized to 9
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3/7.5	Code-Review — Found 8/17 approved changesets -- score normalized to 4
2.5/2.5	Contributors — project has 16 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 16 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	5.9

Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	11
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:pyjanitor@0.32.23 runtime dependency closure — what installing the published package pulls in — 11 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

73Good · 4% of overall

Agent context & guidance

61Moderate

How it's scored

45/45	Agent instructions — AGENTS.md
0/15	Machine-readable docs (llms.txt)
15.8/40	Legible commit history — 26 of 88 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.295
agent_instruction_files	AGENTS.md
agent_instruction_max_bytes	15,321

Verify loop (build / test / typecheck)

79Good

How it's scored

18/18	One-command bootstrap — Makefile
22/22	Automated tests
11/11	Lint / format config
0/11	Static type checking
10/10	Reproducible environment — devcontainer, Dockerfile
10/10	Demonstrated agent practice — 6 of the last 100 commits agent-authored or agent-credited
8/8	Automated maintenance — 12 of the last 100 commits are automated dependency updates
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
has_dockerfile	yes
typed_language	no
bootstrap_files	Makefile
has_devcontainer	yes
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.06
toolchain_manifests	—
dependency_bot_commit_share	0.12

Code legibility for models

54Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
54.1/55	Manageable file sizes — 5/297 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	191,621
source_files_sampled	297
oversized_source_files	5

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — examples, notebooks

Inputs used

example_dirs	examples, notebooks
has_mcp_signal	no
api_schema_files	—
interfaces_expected_of	—

Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

1,499GitHub stars

97contributors

267commits, last 12 months

1days since last push

38releases

2bus factor

100open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 191 ⇿

0Stars

191Forks

38Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Major 0Minor 11Patch 27

Each point covers 8 days.

OpenSSF Scorecard 5.9 / 10

5.9aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-13 03:45 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
9	CI-Tests	18 out of 20 merged PRs checked by a CI test -- score normalized to 9
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
4	Code-Review	Found 8/17 approved changesets -- score normalized to 4
10	Contributors	project has 16 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	16 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
10	Vulnerabilities	0 existing vulnerabilities detected

Direct dependencies 6

Registry	Package	Version constraint	Manifest
PyPI	pandas	`>=3.0.0`	pyproject.toml
PyPI	natsort	`>=8.4.0,<9`	pyproject.toml
PyPI	pandas-flavor	`>=0.8.1,<0.9`	pyproject.toml
PyPI	multipledispatch	`—`	pyproject.toml
PyPI	scipy	`—`	pyproject.toml
PyPI	janitor-rs	`>=0.6.1,<0.7`	pyproject.toml

All dependencies 141

Full resolved dependency set from the GitHub dependency graph: 11 direct and 130 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	janitor-rs	`—`	direct
PyPI	janitor-rs	`0.5.0`	direct
PyPI	multipledispatch	`0.6.0`	direct
PyPI	natsort	`—`	direct
PyPI	natsort	`8.1.0`	direct
PyPI	pandas	`—`	direct
PyPI	pandas	`1.4.1`	direct
PyPI	pandas-flavor	`—`	direct
PyPI	pandas-flavor	`0.7.0`	direct
PyPI	pandas-flavor	`0.8.1`	direct
PyPI	scipy	`1.10.0`	direct
PyPI	asttokens	`2.0.5`	indirect
PyPI	asttokens	`2.2.1`	indirect
PyPI	attrs	`21.4.0`	indirect
PyPI	backcall	`0.2.0`	indirect
PyPI	biopython	`1.79`	indirect
PyPI	biopython	`1.80`	indirect
PyPI	black	`—`	indirect
PyPI	black	`24.3.0`	indirect
PyPI	certifi	`2024.7.4`	indirect
PyPI	cfgv	`3.3.1`	indirect
PyPI	charset-normalizer	`3.0.1`	indirect
PyPI	click	`8.0.4`	indirect
PyPI	click	`8.1.3`	indirect
PyPI	colorama	`0.4.4`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coverage	`6.3.2`	indirect
PyPI	darglint	`1.8.1`	indirect
PyPI	decorator	`5.1.1`	indirect
PyPI	distlib	`0.3.9`	indirect
PyPI	execnet	`1.9.0`	indirect
PyPI	executing	`0.8.3`	indirect
PyPI	executing	`1.2.0`	indirect
PyPI	filelock	`3.16.1`	indirect
PyPI	flake8	`4.0.1`	indirect
PyPI	ghp-import	`2.0.2`	indirect
PyPI	ghp-import	`2.1.0`	indirect
PyPI	griffe	`0.25.4`	indirect
PyPI	hypothesis	`—`	indirect
PyPI	hypothesis	`6.39.3`	indirect
PyPI	identify	`2.4.11`	indirect
PyPI	idna	`3.15`	indirect
PyPI	importlib-metadata	`4.11.2`	indirect
PyPI	importlib-metadata	`7.0.1`	indirect
PyPI	iniconfig	`1.1.1`	indirect
PyPI	interrogate	`1.5.0`	indirect
PyPI	ipython	`—`	indirect
PyPI	ipython	`8.10.0`	indirect
PyPI	isort	`—`	indirect
PyPI	isort	`5.10.1`	indirect
PyPI	jedi	`0.18.1`	indirect
PyPI	jedi	`0.18.2`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	markdown	`3.3.6`	indirect
PyPI	markdown	`3.3.7`	indirect
PyPI	markupsafe	`2.1.0`	indirect
PyPI	markupsafe	`2.1.2`	indirect
PyPI	matplotlib-inline	`0.1.3`	indirect
PyPI	matplotlib-inline	`0.1.6`	indirect
PyPI	mccabe	`0.6.1`	indirect
PyPI	mergedeep	`1.3.4`	indirect
PyPI	mkdocs	`1.2.3`	indirect
PyPI	mkdocs	`1.4.2`	indirect
PyPI	mkdocs-autorefs	`0.4.1`	indirect
PyPI	mkdocs-material	`8.2.5`	indirect
PyPI	mkdocs-material	`9.0.8`	indirect
PyPI	mkdocs-material-extensions	`1.0.3`	indirect
PyPI	mkdocs-material-extensions	`1.1.1`	indirect
PyPI	mkdocstrings	`—`	indirect
PyPI	mkdocstrings	`0.20.0`	indirect
PyPI	mkdocstrings-python	`0.8.3`	indirect
PyPI	mpmath	`1.3.0`	indirect
PyPI	mypy-extensions	`0.4.3`	indirect
PyPI	nodeenv	`1.6.0`	indirect
PyPI	numpy	`1.22.3`	indirect
PyPI	numpy	`1.24.1`	indirect
PyPI	packaging	`21.3`	indirect
PyPI	packaging	`23.0`	indirect
PyPI	packaging	`24.0`	indirect
PyPI	pandas-vet	`0.2.3`	indirect
PyPI	parso	`0.8.3`	indirect
PyPI	pathspec	`0.9.0`	indirect
PyPI	pep517	`0.12.0`	indirect
PyPI	pexpect	`4.8.0`	indirect
PyPI	pickleshare	`0.7.5`	indirect
PyPI	pip-tools	`6.5.1`	indirect
PyPI	platformdirs	`4.3.6`	indirect
PyPI	pluggy	`1.0.0`	indirect
PyPI	polars	`0.20.31`	indirect
PyPI	polars	`1.1.0`	indirect
PyPI	pre-commit	`2.17.0`	indirect
PyPI	prompt-toolkit	`3.0.36`	indirect
PyPI	prompt-toolkit	`3.0.39`	indirect
PyPI	ptyprocess	`0.7.0`	indirect
PyPI	pure-eval	`0.2.2`	indirect
PyPI	py	`—`	indirect
PyPI	py	`1.11.0`	indirect
PyPI	py4j	`0.10.9.7`	indirect
PyPI	pycodestyle	`2.8.0`	indirect
PyPI	pyflakes	`2.4.0`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pymdown-extensions	`10.0`	indirect
PyPI	pyparsing	`3.0.7`	indirect
PyPI	pyspark	`3.4.4`	indirect
PyPI	pytest	`—`	indirect
PyPI	pytest	`7.0.1`	indirect
PyPI	pytest-cov	`3.0.0`	indirect
PyPI	pytest-forked	`1.4.0`	indirect
PyPI	pytest-xdist	`2.5.0`	indirect
PyPI	python-dateutil	`2.8.2`	indirect
PyPI	pytz	`2021.3`	indirect
PyPI	pyyaml	`6.0`	indirect
PyPI	pyyaml-env-tag	`0.1`	indirect
PyPI	regex	`2022.10.31`	indirect
PyPI	requests	`2.32.4`	indirect
PyPI	setuptools	`—`	indirect
PyPI	six	`1.16.0`	indirect
PyPI	sortedcontainers	`2.4.0`	indirect
PyPI	stack-data	`0.2.0`	indirect
PyPI	stack-data	`0.6.2`	indirect
PyPI	sympy	`1.10`	indirect
PyPI	sympy	`1.11.1`	indirect
PyPI	tabulate	`0.8.9`	indirect
PyPI	toml	`0.10.2`	indirect
PyPI	tomli	`2.0.1`	indirect
PyPI	tqdm	`4.66.3`	indirect
PyPI	traitlets	`5.1.1`	indirect
PyPI	traitlets	`5.8.1`	indirect
PyPI	typing-extensions	`4.15.0`	indirect
PyPI	unyt	`2.8.0`	indirect
PyPI	unyt	`2.9.3`	indirect
PyPI	unyt	`3.0.4`	indirect
PyPI	urllib3	`2.6.3`	indirect
PyPI	virtualenv	`20.36.1`	indirect
PyPI	watchdog	`2.1.6`	indirect
PyPI	watchdog	`2.2.1`	indirect
PyPI	wcwidth	`0.2.5`	indirect
PyPI	wcwidth	`0.2.6`	indirect
PyPI	wheel	`0.46.2`	indirect
PyPI	xarray	`2022.3.0`	indirect
PyPI	zipp	`3.19.1`	indirect

Dependency advisories 0

Installing pypi:pyjanitor@0.32.23 pulls in 11 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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