Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 22:17 UTC

mwaskom / seaborn

Statistical data visualization in Python

PythonBSD-3-Clause★ 14,008 stars⑂ 2,126 forkssince Jun 2012View on GitHub ↗

mwaskom/seaborn holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Vitality (44/100). It was last updated 52 days ago. A single contributor accounts for most of its recent work.

83
overall / 100
Excellent

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.

83
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)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

Michael WaskomPersonal account
3,463 followers58 public repossince Jun 2010@modal-labs

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIseaborn0.13.235,437,48836945 days ago

Metrics by category

Vitality

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

44Weak · 21% of overall
How it's scored
18/36Push recencylast push 52 days ago
2.1/36Commit cadence3/52 weeks with commits
11.5/18Commit volume18 commits in the last year
10/10OpenSSF Scorecard: Maintained15 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year18
human_commit_share0.95
days_since_last_push52
active_weeks_last_year3
How it's scored
27/27Ships releases37 releases published
0/36Release recencylatest release 945 days ago
19.8/27Release cadencea release every ~62.3 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count37
latest_release_tagv0.13.2
releases_from_tagsno
days_since_latest_release945
mean_days_between_releases62.3

Community & Adoption

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

89Excellent · 17% of overall
How it's scored
60/60Stars14,008 stars
25/25Forks2,126 forks
13.3/15Watchers250 watchers
Inputs used
forks2,126
stars14,008
watchers250
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads35,437,488 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesseaborn
dependents
ecosystemspypi
total_downloads
monthly_downloads35,437,488
unverified_packages_excluded
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

60Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
3.2/22.5Commit distributiontop contributor authored 86% of commits
13.5/13.5Contributor breadth99 contributors
10/10OpenSSF Scorecard: Contributorsproject has 58 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled99
top_contributor_share0.86
How it's scored
39.2/42Issue resolution93% of issues closed
22.3/30PR acceptance863/1,160 decided PRs merged
0/13Newcomer PR acceptance0/2 first-time contributors' PRs merged in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 10/30 approved changesets -- score normalized to 3
Inputs used
merged_prs863
open_issues175
closed_issues2,484
prs_merged_7d0
prs_decided_7d1
prs_merged_30d0
prs_decided_30d2
issue_closed_ratio0.934
closed_unmerged_prs297
first_time_authors_30d2
first_time_prs_merged_30d0
first_time_prs_decided_30d2
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
25/25Owner reach3,463 followers of mwaskom
24.9/25Track record58 public repos, account ~16 yr old
Inputs used
followers3,463
owner_typeUser
is_verified
owner_loginmwaskom
public_repos58
account_age_days5,905
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 945 days ago
20/20Version history36 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesseaborn
ecosystemspypi
any_deprecatedno
min_days_since_publish945

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests15 out of 28 merged PRs checked by a CI test -- score normalized to 5
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://seaborn.pydata.org
10/10Repository description
10/10Topics5 topics
10/10Wiki
Inputs used
topicspython, data-visualization, data-science, matplotlib, pandas
has_wikiyes
homepagehttps://seaborn.pydata.org
docs_sitehttps://seaborn.pydata.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

74Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
1.2/2.5CI-Tests15 out of 28 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-ReviewFound 10/30 approved changesets -- score normalized to 3
2.5/2.5Contributorsproject has 58 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained15 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
5/5Pinned-Dependenciesall dependencies are pinned
2/5SASTSAST tool is not run on all commits -- score normalized to 4
5/5Security-Policysecurity policy file detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.8
Excluded from scoring (no data or not applicable): Packaging. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages12
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:seaborn@0.13.2 runtime dependency closure — what installing the published package pulls in — 12 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.

62Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history77 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.811
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, doc/Makefile, doc/_docstrings/Makefile, doc/_tutorial/Makefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance5 of the last 100 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependenciesall dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, doc/Makefile, doc/_docstrings/Makefile, doc/_tutorial/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.05
How it's scored
0/45Type-checkable codePython without a type-check config
51/55Manageable file sizes11/152 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes122,179
source_files_sampled152
oversized_source_files11
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
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

14,008GitHub stars
99contributors
18commits, last 12 months
52days since last push
37releases
1bus factor
175open 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 ★ / 2,126 ⇿
0Stars
2,126Forks
19Releases

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

1,0001,2001,4001,6001,8002,0002,2002,126282020-062023-072026-08
Major 0Minor 3Patch 6

Each point covers 6 days.

OpenSSF Scorecard 6.8 / 10
6.8aggregate

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 · 2026-08-27 22:17 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
5CI-Tests15 out of 28 merged PRs checked by a CI test -- score normalized to 5
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 10/30 approved changesets -- score normalized to 3
10Contributorsproject has 58 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained15 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
10Pinned-Dependenciesall dependencies are pinned
4SASTSAST tool is not run on all commits -- score normalized to 4
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPInumpy>=2.0pyproject.toml
PyPIpandas>=2.2pyproject.toml
PyPImatplotlib>=3.9pyproject.toml
All dependencies 25

Full resolved dependency set from the GitHub dependency graph: 3 direct and 22 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImatplotlibdirect
PyPInumpydirect
PyPIpandasdirect
PyPIflit3.12.0indirect
PyPIflit-coreindirect
PyPIipykernel7.3.0indirect
PyPIjupyterlab4.6.1indirect
PyPInbconvert7.17.1indirect
PyPInumpydoc1.6.0indirect
PyPIpandas-stubs3.0.3.260530indirect
PyPIpre-commit4.6.0indirect
PyPIpydata-sphinx-theme0.19.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-xdist3.8.0indirect
PyPIpyyaml6.0.3indirect
PyPIruff0.15.20indirect
PyPIscipyindirect
PyPIscipy-stubs1.18.0.0indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-copybutton0.5.2indirect
PyPIsphinx-design0.7.0indirect
PyPIsphinx-issues5.0.1indirect
PyPIstatsmodelsindirect
PyPIty0.0.56indirect
Dependency advisories 0

Installing pypi:seaborn@0.13.2 pulls in 12 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.

The message is kept through sign-in.

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 v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.