GStars
    pandas-dev

    pandas-dev/pandas

    #114 this week

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

    backend
    alignment
    data-analysis
    data-science
    flexible
    pandas
    Python
    BSD-3-Clause
    50.6K stars
    20.7K forks
    1.1K GitHub watchers
    Updated Nov 11, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    Ranks #14 among Backend repositories ranked this week; #114 of 163 repositories with measured growth this week (top 70%).

    4 releases in the last 90 days, the latest 6 days ago, with 413 contributors on GitHub.

    The biggest single-day gain in the last year, +127 stars on Jun 28, coincided with release v3.0.4.

    Use Cases & Benefits

    • Provides fast, flexible Python data structures and tools for practical data analysis and manipulation with labeled relational data.
    • Offers powerful, intuitive handling of missing data, automatic data alignment, and versatile group-by operations unmatched by other libraries.
    • Use for cleaning and transforming large datasets with missing or irregular data in data science projects.
    • Use for performing complex time series analysis including date shifting, frequency conversion, and moving window statistics.
    • Use for merging, reshaping, and pivoting diverse data sources like CSV, Excel, SQL databases, and HDF5 files efficiently.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    BSD 3-Clause

    Permissive: commercial use, modification and redistribution are allowed with attribution.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open-source data analysis/manipulation tool available in any language. It is already well on its way towards this goal.

    Excerpt from the pandas-dev/pandas README on GitHub (BSD-3-Clause license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Nov 8: +22Nov 9: +20Nov 10: +16Nov 11: +16

    +1,074 stars over 86 days across 11 snapshot days; best day +22 on Nov 8.

    Forks

    20.7K+472

    Open issues

    1.9K-934

    Compared with peers in Backend

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

    View category →
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