Topics / #dataframe

Dataframe projects on GitHub

DataFrame libraries for fast columnar data processing.

As of , the most-starred Dataframe projects on GitHub are pandas (50.1K stars), spark (44.2K stars) and polars (40.1K stars). GitHub.Locker tracks 7 Dataframe repositories with 201.9K stars combined. The fastest-growing on October 16 was pandas, with +15 stars in a day.

7Projects
201.9KStars in total
+37Stars in a day
Browse in the catalog →github.com/topics/dataframe ↗

Hot right now

Most stars gained in a day · Oct 16

+15

pandas

pandas-dev/pandas · ★ 50.1K

pandas is a Python library providing fast, flexible data structures (Series and DataFrame) for working with labeled/relational data, aiming to be the fundamental building block for practical data analysis in Python.

+10

spark

apache/spark · ★ 44.2K

Apache Spark is a unified analytics engine for large-scale data processing, offering high-level APIs in Scala, Java, Python, and R on top of an optimized execution engine.

+7

polars

pola-rs/polars · ★ 40.1K

Polars is an extremely fast analytical query engine for DataFrames, written in Rust and designed to be fast, easy to use and expressive.

+3

pandas-ai

sinaptik-ai/pandas-ai · ★ 23.9K

PandasAI is a Python library that lets you ask questions about your data (SQL, CSV, parquet, dataframes) in plain natural language, powered by LLMs.

The all-time top

7 projects · by stars

  1. #1 · pandas-dev/pandas

    pandas

    pandas is a Python library providing fast, flexible data structures (Series and DataFrame) for working with labeled/relational data, aiming to be the fundamental building block for practical data analysis in Python.

    50.1K
  2. #2 · apache/spark

    spark

    Apache Spark is a unified analytics engine for large-scale data processing, offering high-level APIs in Scala, Java, Python, and R on top of an optimized execution engine.

    44.2K
  3. #3 · pola-rs/polars

    polars

    Polars is an extremely fast analytical query engine for DataFrames, written in Rust and designed to be fast, easy to use and expressive.

    40.1K
  1. 4

    pandas-ai

    23.9Ksinaptik-ai/pandas-ai · Python

    PandasAI is a Python library that lets you ask questions about your data (SQL, CSV, parquet, dataframes) in plain natural language, powered by LLMs.

  2. 5

    arrow

    17.2Kapache/arrow · C++

    Apache Arrow is a universal columnar format plus a multi-language toolbox for fast data interchange and in-memory analytics — technologies that let data systems store, process, and move tabular data efficiently.

  3. 6

    pygwalker

    16KKanaries/pygwalker · Python

    PyGWalker is a Python library that turns your pandas dataframe into an interactive UI for visual analysis, so you can explore and chart data with drag-and-drop right inside Jupyter Notebook.

  4. 7

    modin

    10.4Kmodin-project/modin · Python

    Modin is a drop-in replacement for pandas: you keep the same API and syntax, but your workflows run on all of your CPU cores instead of a single thread. Change one import line and your existing pandas code just runs faster.

Often tagged together