Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 18:06 UTC

DistrictDataLabs / yellowbrick

Visual analysis and diagnostic tools to facilitate machine learning model selection.

PythonApache-2.0★ 4,404 stars⑂ 569 forkssince May 2016View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

DistrictDataLabs/yellowbrick holds a health index of 34 out of 100, placing it in the At Risk band. It scores highest on Community & Adoption (86/100) and lowest on Vitality (18/100). It was last updated 574 days ago. 2 contributors account for most of its recent work.

34
overall / 100
At Risk

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.

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)
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 60 is calibrated to 65 on the published index scale (record calibration 2026-08-02).

Ownership

District Data LabsOrganization
67 followers76 public repossince Mar 2014

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

Metrics by category

Vitality

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

18Critical · 21% of overall
How it's scored
0/36Push recency — last push 574 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push574
active_weeks_last_year0
How it's scored
27/27Ships releases — 24 releases published
0/36Release recency — latest release 1,488 days ago
12.6/27Release cadence — a release every ~143.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count24
latest_release_tagv1.5
releases_from_tagsno
days_since_latest_release1,488
mean_days_between_releases143.6
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?

86Excellent · 17% of overall
How it's scored
59.1/60Stars — 4,404 stars
23/25Forks — 569 forks
11.2/15Watchers — 103 watchers
Inputs used
forks569
stars4,404
watchers103
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, codecov.io, github.com, readthedocs.org, shields.io
has_pull_request_templateyes

Sustainability & Governance

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

71Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13/22.5Commit distribution — top contributor authored 42% of commits
13.5/13.5Contributor breadth — 100 contributors
10/10OpenSSF Scorecard: Contributors — project has 14 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled100
top_contributor_share0.423
How it's scored
36.4/42Issue resolution — 87% of issues closed
23.8/30PR acceptance — 483/609 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
13.5/15OpenSSF Scorecard: Code-Review — Found 27/30 approved changesets -- score normalized to 9
Inputs used
merged_prs483
open_issues94
closed_issues608
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.866
closed_unmerged_prs126
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
13.2/25Owner reach — 67 followers of DistrictDataLabs
25/25Track record — 76 public repos, account ~12 yr old
Inputs used
followers67
owner_typeOrganization
is_verifiedno
owner_loginDistrictDataLabs
public_repos76
account_age_days4,554

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — setup.cfg ([flake8])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 27 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://www.scikit-yb.org/
10/10Repository description
10/10Topics — 10 topics
0/10Wiki
Inputs used
topicsmachine-learning, visual-analysis, model-selection, visualization, scikit-learn, visualizer, matplotlib, python, estimator, anaconda
has_wikino
homepagehttp://www.scikit-yb.org/
docs_sitehttp://www.scikit-yb.org/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

51Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — 0 out of 27 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6.8/7.5Code-Review — Found 27/30 approved changesets -- score normalized to 9
2.5/2.5Contributors — project has 14 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
3.5/5SAST — SAST tool detected but not run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 47 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.9
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories89
affected_packages4
assessed_packages13
unassessed_packages11
affected_by_severitycritical 1, moderate 2, unknown 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 13 resolved dependencies against OSV. 11 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

56Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 82 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.82
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — setup.cfg ([flake8])
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/199 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes44,210
source_files_sampled199
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, 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

4,404GitHub stars
100contributors
0commits, last 12 months
574days since last push
24releases
2bus factor
94open 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 ★ / 569 ⇿
0Stars
569Forks
24Releases

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.

0100200300400500600557262016-052021-072026-08
Major 0Minor 0Patch 7

Each point covers 10 days.

OpenSSF Scorecard 3.9 / 10
3.9aggregate

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 · 2026-09-17 18:04 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
0CI-Tests0 out of 27 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
9Code-ReviewFound 27/30 approved changesets -- score normalized to 9
10Contributorsproject has 14 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
7SASTSAST tool detected but not run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities47 existing vulnerabilities detected
All dependencies 24

Full resolved dependency set from the GitHub dependency graph: 0 direct and 24 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcoverage5.5indirect
PyPIcycler—indirect
PyPIcycler0.10.0indirect
PyPImatplotlib—indirect
PyPImatplotlib3.4.2indirect
PyPInltk3.6.7indirect
PyPInumba0.55.2indirect
PyPInumpy—indirect
PyPInumpy1.22.0indirect
PyPInumpydoc—indirect
PyPIpandas—indirect
PyPIpandas1.3.0indirect
PyPIpytest6.2.4indirect
PyPIpytest-cov2.12.1indirect
PyPIpytest-flakes4.0.3indirect
PyPIpytest-spec—indirect
PyPIscikit-learn—indirect
PyPIscikit-learn1.0.2indirect
PyPIscipy—indirect
PyPIscipy1.8.0indirect
PyPIsphinx—indirect
PyPIsphinx-rtd-theme—indirect
PyPIumap-learn—indirect
PyPIumap-learn0.5.3indirect
Dependency advisories 4

This repository publishes no package the index resolves, so its own dependency graph was assessed — 13 packages, which also include development and test pins that never ship: 4 carry known advisories, of which 0 are direct. 11 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
nltk3.6.7indirectcritical843.10.3
pytest6.2.4indirectmoderate29.0.3
scikit-learn1.0.2indirectmoderate21.5.0
scipy1.8.0indirectunknown11.10.0

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 statistics.