Pandas
pandas
Judgement: Adopt
Universal Python DataFrame; you don't choose it, you encounter it.
The original Python DataFrame library. Whatever else a Python data practitioner uses, they almost certainly know pandas — which makes its API a de-facto interface that other libraries (Polars, Modin, cuDF) deliberately mimic.
Pandas 2.x added Arrow-backed columns, narrowing the gap with newer engines while preserving the familiar API.
Why it counts as a standard
The pandas Python API is the de-facto DataFrame interface other libraries deliberately mimic — Modin, cuDF, Dask, and many wrappers expose pandas-compatible surfaces precisely because users already know it. The API shape, not the implementation, is what makes pandas a standard reference.
At a glance
- Category
- Processing
- Governance
- NumFOCUS (open source)
- Status
- Stable; the de-facto Python DataFrame API
- First released
- 2008
Links
Related standards
Other standards in Processing.
- dbt — data build tool
- Spark — Apache Spark
- SQL DML — SQL Data Manipulation Language
- Beam — Apache Beam
- Ibis
- XSLT — Extensible Stylesheet Language Transformations
See Pandas in context
Open the interactive Data Landscape to compare Pandas against every other open standard, or grab the raw JSON. Spotted something wrong? Open an issue.