xarray-einstats
Stats, linear algebra and einops for xarray
Installation
To install, run
(.venv) $ pip install xarray-einstats
See the docs for more extensive install instructions.
Overview
As stated in their website:
xarray makes working with multi-dimensional labeled arrays simple, efficient and fun!
The code is often more verbose, but it is generally because it is clearer and thus less error prone and more intuitive. Here are some examples of such trade-off where we believe the increased clarity is worth the extra characters:
| numpy | xarray |
|---|---|
a[2, 5] |
da.sel(drug="paracetamol", subject=5) |
a.mean(axis=(0, 1)) |
da.mean(dim=("chain", "draw")) |
a.reshape((-1, 10)) |
da.stack(sample=("chain", "draw")) |
a.transpose(2, 0, 1) |
da.transpose("drug", "chain", "draw") |
In some other cases however, using xarray can result in overly verbose code
that often also becomes less clear. xarray_einstats provides wrappers
around some numpy and scipy functions (mostly numpy.linalg and scipy.stats)
and around einops with an api and features adapted to xarray.
Continue at the getting started page.
Contributing
xarray-einstats is in active development and all types of contributions are welcome! See the contributing guide for details on how to contribute.
Relevant links
- Documentation: https://einstats.python.arviz.org/en/latest/
- Contributing guide: https://einstats.python.arviz.org/en/latest/contributing/overview.html
- ArviZ project website: https://www.arviz.org
Similar projects
Here we list some similar projects we know of. Note that all of them are complementary and don't overlap:
Cite xarray-einstats
If you use this software, please cite it using the following template and the version
specific DOI provided by Zenodo. Click on the badge to go to the Zenodo page
and select the DOI corresponding to the version you used
- Oriol Abril-Pla. (2022). arviz-devs/xarray-einstats
<version>. Zenodo.<version_doi>
or in bibtex format:
@software{xarray_einstats2022,
author = {Abril-Pla, Oriol},
title = {{xarray-einstats}},
year = 2022,
url = {https://github.com/arviz-devs/xarray-einstats}
publisher = {Zenodo},
version = {<version>},
doi = {<version_doi>},
}
1 maintainer
Metadata
1 maintainer
Release files for xarray-einstats 0.11.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| xarray_einstats-0.11.0.tar.gz | 34.3 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| xarray_einstats-0.11.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 74.1 kB
Release files / xarray_einstats-0.11.0.tar.gz
| Download URL | xarray_einstats-0.11.0.tar.gz |
|---|---|
| Size | 34.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
69f48a60f62151d40c49fd6d9a6dc0b970aecef2813a33209e4dcde897fca48b
|
|
BLAKE2b-256 checksum How to use checksums |
6f70adb14007ee636eadd2a404802f7bb340c6f123ea81cfca152ebd4b6e2660
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 20, 2026.
Transparency logRelease files / xarray_einstats-0.11.0-py3-none-any.whl
| Download URL | xarray_einstats-0.11.0-py3-none-any.whl |
|---|---|
| Size | 39.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9dc8372aeb5db233054ddde4e57cbbcd1eee6c2e1b6bbe85863881c09b4421b3
|
|
BLAKE2b-256 checksum How to use checksums |
307b34a9ce89f7a1e78423ca5a66492341c4f7daf6d0e9668af427fc2a7bc099
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 20, 2026.
Transparency logSecurity for xarray-einstats 0.11.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for xarray_einstats-0.11.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 20, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
