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Data sourced from GitHub API

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  3. pandas-dev
  4. pandas
PythonVisible projectFresh activityAdopted in packagesPartial snapshot

pandas-dev/pandas

Rank not captured·Top 100·All-time stars·◐Cached ranking snapshot·Updated Aug 15, 2026

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

Compare closest alternativesOpen GitHub

First read

Strong enough to justify a deeper source review

pandas-dev/pandas looks visible enough to matter, active enough to trust for a next pass, and adopted enough to merit checking maintainers, releases, and real integration cost in the source repository.

Visible

49.5K public stars in the current GitStar snapshot.

Recognizable in the ecosystem

Active

Last commit Aug 15, 2026.

Fresh activity

Adopted

pypi gives the strongest production-style signal.

7.1M/week

Confidence

One or more key signals are partial, so GitStar keeps the interpretation conservative.

Partial snapshot

Snapshot facts

  • 49.5K stars
  • 20.3K forks
  • Last commit Aug 15, 2026
  • pypi 7.1M/week

Compare lens

lukasmasuch/best-of-ml-python and ray-project/ray are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.

Signal trail

Trajectory

Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.

Daily momentum
Recent momentum is not captured
Weekly momentum
Recent momentum is not captured
Monthly momentum
Recent momentum is not captured
Last commit
Aug 15, 2026

Package reality

GitStar found pypi:pandas. Package traffic can help separate visible repositories from dependencies that are quietly used in real workflows.

Hype vs Reality
Balanced
Package mapping
pypi · pandas
Cross-links
Standalone repo read

Validation note

GitStar can summarize public signals for pandas-dev/pandas, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.

PyPI: 7.1M/week
Package signal

Install & Package Signals

📐 How this feeds Hype vs Reality

GitStar uses the strongest linked package signal below when it reads Hype vs Reality for this repository.

Balanced
Recent attention and package usage are moving in the same direction.
PyPI package

pandas

7.1M downloads/week
pip install pandas
Open pypi
alignmentdata-analysisdata-scienceflexiblepandaspython
🦕Living Fossil🏭Factory Floor
🛡️ Editorial Context

GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.

Why this rank

This repository stands out because it combines package adoption and fresh update.

Package adoptionFresh updateStable visibility
📈 Momentum & Adoption Signals
Approximate star trajectory

Reconstructed from current stars and cached daily/weekly/monthly deltas.

Now: 49.5K
30d ago7d ago1d agoNow
Daily momentum
No signal
Weekly momentum
No signal
Monthly momentum
No signal
Signal mix (log-scaled for readability)
Current stars49.5K
Weekly package downloads7.1M
🧭 Hype vs Reality
Balanced

Recent attention and package usage are moving in the same direction.

This usually means the project has both mindshare and a measurable production footprint, which makes it a stronger validation candidate.

Status
Balanced
Package footprint
PyPI · 7.1M/week
Method note
Balanced means GitStar sees both meaningful package adoption and enough current star velocity or scale to avoid reading the repo as purely niche. Compare it against other Python repos before treating stars as a moat.
📐 Read the Hype vs Reality heuristic
Related alternative

lukasmasuch/best-of-ml-python

Shares the libraries category footprint with pandas-dev/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

ray-project/ray

Shares the libraries category footprint with pandas-dev/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

explosion/spaCy

Shares the libraries category footprint with pandas-dev/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

akfamily/akshare

Shares the libraries category footprint with pandas-dev/pandas, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Research links

Cross-links

Compare against related repos

GitStar picked best-of-ml-python + ray as the closest next comparison from the related repository set.

Open compare presetCompare with best-of-ml-pythonCompare with ray
Repo utility

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GitHub Repositorypandas-dev/pandasPyPI PackagepandasExport Ranking DataDownload CSV

Wider nearby ecosystem

Compare with best-of-ml-pythonCompare with ray
Unknown
23.7K stars
lukasmasuch/best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Python
43.5K stars
ray-project/ray

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Python
33.8K stars
explosion/spaCy

💫 Industrial-strength Natural Language Processing (NLP) in Python

Python
22K stars
akfamily/akshare

AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

Unknown
16.6K stars
bharathgs/Awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Python
1.7K stars
prettytable/prettytable

Display tabular data in a visually appealing ASCII table format

Next step after the validation read

Move into a compare preset, organization view, or the heuristic notes once this first fold tells you whether the repo looks visible, active, adopted, and credible enough to keep researching.
Compare the closest alternativesView the organizationRead the heuristic

Learn and methodology

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

About This Page

This page provides a quick overview of pandas-dev/pandas based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.

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