pandas-dev/pandas
Grade a repo

91

/ 100

GradeB

Well engineered. The main gaps are linting and a reproducible setup.

Top 28% of 5,156 graded repos

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Documentation93
Engineering69
Health100
Python49,388BSD-3-Clausetoday

Top fixes

Highest-impact changes first, ranked by point weight

9 to address
  1. 1
    Tests18pt

    Wire your tests to a documented command (e.g. a test script in your build config) so the suite is reproducible.

  2. 2
    CI/CD14pt

    Add a lint step to catch style issues automatically.

  3. 3
    CI/CD14pt

    Add `tsc --noEmit`, `mypy`, or `cargo check` to catch type errors before they merge.

  4. 4
    Install and run instructions9pt

    Add a .env.example listing all required environment variables so contributors know what to set up.

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

93

Contributing guide5pt72

CONTRIBUTING guide found.

Install and run instructions9pt90

README documents how to install the project.

README12pt100

README is present.

License6pt100

Licensed under BSD-3-Clause.

Engineering

69

Linting and formatting5pt0

No linter or formatter config found.

→ Add a linter config such as .eslintrc.json, .prettierrc, ruff.toml, or .golangci.yml to enforce consistent code style.

Reproducibility6pt22

No dependency lockfile found (−70 pts).

→ Commit the lockfile for this project's package manager so installs produce the same dependency versions everywhere.

Tests18pt80

Test files detected (pandas/conftest.py).

CI/CD14pt85

CI is configured (.github/workflows/code-checks.yml).

Issue and PR templates6pt100

Issue or PR templates present.

Project health

100

Dependency manifest6pt100

Dependency manifest found (pyproject.toml).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Housekeeping3pt100

.gitignore present.

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • 459 / 1026
    Commits (30d / 90d)
  • 20,218
    Forks
  • 122
    Releaseslatest 11y ago

Community

  • 87% - Good
    Community health
  • 5 bus factor
    authors own >50% of commits
  • 49,388
    Watchers

Responsiveness

  • 65d 18h
    Median issue response
  • 17h
    Median PR merge time
  • 2,921
    Open issues
Repository files27 root entries
  • .github
    Good: CI is configured (.github/workflows/code-checks.yml).
    Good: Dependabot configured for github-actions.
    Good: Issue or PR templates present.
  • asv_bench
  • ci
  • doc
    Good: CONTRIBUTING guide found.
    Issue: CONTRIBUTING guide contents could not be read (−28 pts vs a readable file).Fix: Move the file to the repo root or docs/CONTRIBUTING.md so its setup, style, test, and PR sections can be graded.
  • LICENSES
  • pandas
    Good: Test files detected (pandas/conftest.py).
  • scripts
  • subprojects
  • web
  • .gitattributes
  • .gitignore
    Good: .gitignore present.
  • .pre-commit-config.yaml
  • AGENTS.md
  • AUTHORS.md
  • CITATION.cff
  • codecov.yml
  • environment.yml
    Good: Environment pinned via environment.yml.
  • generate_pxi.py
  • generate_version.py
  • LICENSE
    Good: Licensed under BSD-3-Clause.
  • meson.build
  • pixi.lock
  • pixi.toml
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • pyright_reportGeneralTypeIssues.json
  • README.md
    Good: README is present.
    Good: README is well structured with multiple sections.
    Good: README includes screenshots or visuals. Great for first impressions.
    Good: README has code examples.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • requirements-dev.txt
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