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dataframe-api-compat

Implementation of the DataFrame Standard for pandas and Polars

With conditionsPyPI Information AnalysisReleased Apr 2024122.1K downloads / mopermissive licensePure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — dataframe_api_compat-0.2.7-py3-none-any.whl
v0.2.7 · released 2024-04-26 · Python >=3.8 · 1 runtime deps: packaging

Yes, if you need to write dataframe code that works across multiple libraries or want to avoid lock-in to a single implementation. The low install friction and permissive license make it a safe addition. However, maintenance is dormant (no commits since April 2024), so verify that the standard implementation covers your actual use cases and that the libraries you target are fully compliant before committing to it in production.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.8 or later; the underlying dataframe libraries (pandas, Polars, etc.) must implement the Python Dataframe API Standard.
  • Low friction: pure Python wheel under 50 kB with only packaging as a runtime dependency.
  • Dormant maintenance since April 2024 (840 days), though the repository remains active and unarchived.

License · maintenance · safety

permissive license (permissive) — MIT license (permissive) means you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.

last release 2024-04-26 (840 days) · last repo commit 2024-04-26 · 41 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 122,128 downloads/mo, #11,959 on PyPI

Verify before relying

pip install dataframe-api-compat

import dataframe_api_compat
# Use standard DataFrame API methods across pandas, Polars, or other compliant libraries
  • How complete is the standard implementation coverage across different dataframe libraries in practice.
  • Whether dormant status (no commits since April 2024) signals incomplete standard support or stable maturity.
Same gist for agents: .md · .json

What it is and what it does

Dataframe API Compat is a thin abstraction layer that sits between your code and dataframe libraries like pandas and Polars, allowing you to write dataframe operations using the Python Dataframe API Standard. Instead of learning library-specific syntax, you write against a common interface that any compliant dataframe library can implement. The package itself is intentionally minimal—under 50 kB, pure Python, with only packaging as a dependency—making it easy to add to any project without bloat.

The main use case is writing library-agnostic dataframe code: you can prototype with pandas, switch to Polars for performance, or support multiple backends without rewriting your logic. It's designed for teams or libraries that want to avoid lock-in to a single dataframe implementation while still using standard, predictable operations.

Use it for

  • Write dataframe transformation code that works with both pandas and Polars without conditional imports or adapter code.
  • Build a library or tool that accepts dataframes from multiple sources and processes them with a single code path.
  • Prototype analysis with pandas, then swap to Polars for production performance without refactoring your dataframe calls.
  • Support multiple dataframe backends in a data pipeline without maintaining separate code branches for each.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you need to write dataframe code that works across multiple libraries or want to avoid lock-in to a single implementation.

The low install friction and permissive license make it a safe addition. However, maintenance is dormant (no commits since April 2024), so verify that the standard implementation covers your actual use cases and that the libraries you target are fully compliant before committing to it in production.

Install

dataframe-api-compat on PyPI

Before you install

Low friction: pure Python wheel under 50 kB with only packaging as a runtime dependency. Dormant maintenance since April 2024 (840 days), though the repository remains active and unarchived.

Requires Python 3.8 or later; the underlying dataframe libraries (pandas, Polars, etc.) must implement the Python Dataframe API Standard.

License in practice

MIT license (permissive) means you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.

Quickstart

pip install dataframe-api-compat

import dataframe_api_compat
# Use standard DataFrame API methods across pandas, Polars, or other compliant libraries

Verify before relying

  • How complete is the standard implementation coverage across different dataframe libraries in practice.
  • Whether dormant status (no commits since April 2024) signals incomplete standard support or stable maturity.

Package facts

Licensepermissive license permissive
Python supportSupports the current Python release >=3.8
Install frictionLow. Pure-Python wheel
Runtime dependencies
1 package
packaging
MaintenanceDormant 840 days since the last release
Last repo commit
First released
Downloads122,128 / month, #11,959 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3

Evidence: dataframe_api_compat-0.2.7-py3-none-any.whl

Tags

Capabilities
dataframe api standard compatibilitypandas polars interop layerwrite once run anywhere dataframesdataframe abstraction layercross-dataframe library supportdataframe api wrapperunified dataframe interface
Topics
dataframe-abstractioncross-library-compat

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See also narwhals · datacompy · modin · array-api-compat · percentify · polars-runtime-compat · itables · array-api-strict · fastf1 · bigframes