akimbo

For when your data won't fit in your dataframe

Akimbo provides fast vectorized processing of nested, ragged data in dataframes, using the .ak accessor.

numpy-like API for slicing and accessing data deep in nested structures
apply any function, ufunc or aggregation at any level
use with different backends: pandas, polars, dask-dataframe and cuDF exactly the same way (more backends may come in the future)
CPU and GPU processing and support for numba-jit
attach object-like behaviours to your record (sub)structures

See the quick start in the documentation for an introduction to akimbo.

Acknowledgements

Support for this work was provided by NSF grant OAC-2103945.

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for akimbo 2025.3.0
File	Size	Uploaded
akimbo-2025.3.0.tar.gz	25.4 kB	Mar 28, 2025	Details

Table of built distributions (wheels) for akimbo 2025.3.0
File	Interpreter	ABI	Platform	Reset
akimbo-2025.3.0-py3-none-any.whl 32.2 kB Mar 28, 2025	Python 3	none	any	Details

Total release size: 57.6 kB

Download URL	akimbo-2025.3.0.tar.gz
Size	25.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`fcb18e715ed875395b2c1a86891bca3be488bee05338b93dede3b974b472d602`
BLAKE2b-256 checksum How to use checksums	`aa1cdd2c7837f57333af8ab2580736db4b03730a591122b64d5ceaa7bdd061cc`
Upload date	Mar 28, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Download URL	akimbo-2025.3.0-py3-none-any.whl
Size	32.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`f861263da65d18ead901f1fcabfb22f8e4c954b987eae27421429f3970070960`
BLAKE2b-256 checksum How to use checksums	`0c50a1b9cf348612a531629542712acf2f13a56954315acf66ec9b92dc4598af`
Upload date	Mar 28, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.12.9`