GitStar

pandasOrganization

pandas

@pandas-dev • Powerful data manipulation tools for Python. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.

Portfolio concentration

100%

Top three share

Shows whether the organization is driven by one breakout repo or several visible projects.

Breadth

15 repos

Visible snapshot

4 repositories updated in the last 90 days.

Leading language

Python

Portfolio mix

Python (8), Unknown (4), Jupyter Notebook (1)

Average size

3.3K

Stars per repository

Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.

Updated: 2026-03-31(28d ago)GitHub API fallback15 repositories

Portfolio Shape

100%

of the visible star count comes from this organization's top three repositories.

Average Repository Size

3.3K

stars per repository in this same snapshot.

Current Mix

Python

is the most common language here, with 4 repositories updated in the last 90 days.

Why this rank

This organization stands out because one flagship repo drives 99% of its visible star count.

Flagship share 99%Breakout repo: pandas

Organization pages work best when you separate portfolio breadth from flagship concentration. In pandas's case, the visible top three repositories account for about 100% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.

The dominant language mix here is Python (8), Unknown (4), Jupyter Notebook (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.

Source: GitHub API fallback. This is the same cache-first snapshot used by the organization ranking list, so the summary view and the detail view should stay aligned.

Top Repositories

#RepositoryLanguage⭐ Stars
1pandas-dev/pandas

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

Python48.6K
2pandas-dev/pandas-stubs

Public type stubs for pandas

Python314
3pandas-dev/pandas-governance

Project governance documents for the pandas Project

36
4pandas-dev/pandas-msgpack

Pandas Msgpack

Python24
5pandas-dev/pandas-dev-flaker

flake8 plugin used for pandas development

Python10
6pandas-dev/pandas-user-surveysJupyter Notebook10
7pandas-dev/pandas-blog

Source for https://dev.pandas.io/pandas-blog

Python8
8pandas-dev/pandas-release

Infrastructure for making a pandas release

Python8
9pandas-dev/pandas-compat

API compatibility for pandas downstream

Python7
10pandas-dev/asv-runner

https://pandas-dev.github.io/asv-runner/

Python3
11pandas-dev/pandas-benchmarks

Environment to run the pandas benchmarks suite

2
12pandas-dev/pandas-jupyterlite

Assets and CI for the pandas interactive terminal

1
13pandas-dev/pandas-dev.github.ioHTML0
14pandas-dev/github-doc-previewer

Service to preview documentation from GitHub artifacts

Rust0
15pandas-dev/project-management0

Next step after the organization read

Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.

Learn and methodology

Keep trust-building context reachable, but behind the first data read instead of ahead of it.

How to Read This Snapshot

Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.

For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.