Science Score: 77.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
56 of 559 committers (10.0%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (7.5%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
N-D labeled arrays and datasets in Python
Basic Info
- Host: GitHub
- Owner: pydata
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://xarray.dev
- Size: 48.2 MB
Statistics
- Stars: 3,946
- Watchers: 105
- Forks: 1,169
- Open Issues: 1,292
- Releases: 108
Topics
Metadata Files
README.md
xarray: N-D labeled arrays and datasets
xarray (pronounced "ex-array", formerly known as xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun!
Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.
Xarray was inspired by and borrows heavily from pandas, the popular data analysis package focused on labelled tabular data. It is particularly tailored to working with netCDF files, which were the source of xarray\'s data model, and integrates tightly with dask for parallel computing.
Why xarray?
Multi-dimensional (a.k.a. N-dimensional, ND) arrays (sometimes called "tensors") are an essential part of computational science. They are encountered in a wide range of fields, including physics, astronomy, geoscience, bioinformatics, engineering, finance, and deep learning. In Python, NumPy provides the fundamental data structure and API for working with raw ND arrays. However, real-world datasets are usually more than just raw numbers; they have labels which encode information about how the array values map to locations in space, time, etc.
Xarray doesn\'t just keep track of labels on arrays -- it uses them to provide a powerful and concise interface. For example:
- Apply operations over dimensions by name:
x.sum('time'). - Select values by label instead of integer location:
x.loc['2014-01-01']orx.sel(time='2014-01-01'). - Mathematical operations (e.g.,
x - y) vectorize across multiple dimensions (array broadcasting) based on dimension names, not shape. - Flexible split-apply-combine operations with groupby:
x.groupby('time.dayofyear').mean(). - Database like alignment based on coordinate labels that smoothly
handles missing values:
x, y = xr.align(x, y, join='outer'). - Keep track of arbitrary metadata in the form of a Python dictionary:
x.attrs.
Documentation
Learn more about xarray in its official documentation at https://docs.xarray.dev/.
Try out an interactive Jupyter notebook.
Contributing
You can find information about contributing to xarray at our Contributing page.
Get in touch
- Ask usage questions ("How do I?") on GitHub Discussions.
- Report bugs, suggest features or view the source code on GitHub.
- For less well defined questions or ideas, or to announce other projects of interest to xarray users, use the mailing list.
NumFOCUS
Xarray is a fiscally sponsored project of NumFOCUS, a nonprofit dedicated to supporting the open source scientific computing community. If you like Xarray and want to support our mission, please consider making a donation to support our efforts.
History
Xarray is an evolution of an internal tool developed at The Climate Corporation. It was originally written by Climate Corp researchers Stephan Hoyer, Alex Kleeman and Eugene Brevdo and was released as open source in May 2014. The project was renamed from "xray" in January 2016. Xarray became a fiscally sponsored project of NumFOCUS in August 2018.
Contributors
Thanks to our many contributors!
License
Copyright 2014-2024, xarray Developers
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Xarray bundles portions of pandas, NumPy and Seaborn, all of which are available under a "3-clause BSD" license:
- pandas:
setup.py,xarray/util/print_versions.py - NumPy:
xarray/core/npcompat.py - Seaborn:
_determine_cmap_paramsinxarray/core/plot/utils.py
Xarray also bundles portions of CPython, which is available under the
"Python Software Foundation License" in xarray/core/pycompat.py.
Xarray uses icons from the icomoon package (free version), which is available under the "CC BY 4.0" license.
The full text of these licenses are included in the licenses directory.
Owner
- Name: Python for Data
- Login: pydata
- Kind: organization
- Website: http://groups.google.com/forum/?fromgroups#!forum/pydata
- Repositories: 28
- Profile: https://github.com/pydata
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Hoyer"
given-names: "Stephan"
orcid: "https://orcid.org/0000-0002-5207-0380"
- family-names: "Roos"
given-names: "Maximilian"
- family-names: "Joseph"
given-names: "Hamman"
orcid: "https://orcid.org/0000-0001-7479-8439"
- family-names: "Magin"
given-names: "Justus"
orcid: "https://orcid.org/0000-0002-4254-8002"
- family-names: "Cherian"
given-names: "Deepak"
orcid: "https://orcid.org/0000-0002-6861-8734"
- family-names: "Fitzgerald"
given-names: "Clark"
orcid: "https://orcid.org/0000-0003-3446-6389"
- family-names: "Hauser"
given-names: "Mathias"
orcid: "https://orcid.org/0000-0002-0057-4878"
- family-names: "Fujii"
given-names: "Keisuke"
orcid: "https://orcid.org/0000-0003-0390-9984"
- family-names: "Maussion"
given-names: "Fabien"
orcid: "https://orcid.org/0000-0002-3211-506X"
- family-names: "Imperiale"
given-names: "Guido"
- family-names: "Clark"
given-names: "Spencer"
orcid: "https://orcid.org/0000-0001-5595-7895"
- family-names: "Kleeman"
given-names: "Alex"
- family-names: "Nicholas"
given-names: "Thomas"
orcid: "https://orcid.org/0000-0002-2176-0530"
- family-names: "Kluyver"
given-names: "Thomas"
orcid: "https://orcid.org/0000-0003-4020-6364"
- family-names: "Westling"
given-names: "Jimmy"
- family-names: "Munroe"
given-names: "James"
orcid: "https://orcid.org/0000-0001-9098-6309"
- family-names: "Amici"
given-names: "Alessandro"
orcid: "https://orcid.org/0000-0002-1778-4505"
- family-names: "Barghini"
given-names: "Aureliana"
- family-names: "Banihirwe"
given-names: "Anderson"
orcid: "https://orcid.org/0000-0001-6583-571X"
- family-names: "Bell"
given-names: "Ray"
orcid: "https://orcid.org/0000-0003-2623-0587"
- family-names: "Hatfield-Dodds"
given-names: "Zac"
orcid: "https://orcid.org/0000-0002-8646-8362"
- family-names: "Abernathey"
given-names: "Ryan"
orcid: "https://orcid.org/0000-0001-5999-4917"
- family-names: "Bovy"
given-names: "Benoît"
- family-names: "Omotani"
given-names: "John"
orcid: "https://orcid.org/0000-0002-3156-8227"
- family-names: "Mühlbauer"
given-names: "Kai"
orcid: "https://orcid.org/0000-0001-6599-1034"
- family-names: "Roszko"
given-names: "Maximilian K."
orcid: "https://orcid.org/0000-0001-9424-2526"
- family-names: "Wolfram"
given-names: "Phillip J."
orcid: "https://orcid.org/0000-0001-5971-4241"
- family-names: "Henderson"
given-names: "Scott"
orcid: "https://orcid.org/0000-0003-0624-4965"
- family-names: "Awowale"
given-names: "Eniola Olufunke"
- family-names: "Scheick"
given-names: "Jessica"
orcid: "https://orcid.org/0000-0002-3421-4459"
- family-names: "Savoie"
given-names: "Matthew"
orcid: "https://orcid.org/0000-0002-8881-2550"
- family-names: "Littlejohns"
given-names: "Owen"
title: "xarray"
abstract: "N-D labeled arrays and datasets in Python."
license: Apache-2.0
doi: 10.5281/zenodo.598201
url: "https://xarray.dev/"
repository-code: "https://github.com/pydata/xarray"
preferred-citation:
type: article
authors:
- family-names: "Hoyer"
given-names: "Stephan"
orcid: "https://orcid.org/0000-0002-5207-0380"
- family-names: "Joseph"
given-names: "Hamman"
orcid: "https://orcid.org/0000-0001-7479-8439"
doi: "10.5334/jors.148"
journal: "Journal of Open Research Software"
month: 4
title: "xarray: N-D labeled Arrays and Datasets in Python"
volume: 5
issue: 1
year: 2017
GitHub Events
Total
- Create event: 39
- Release event: 7
- Issues event: 611
- Watch event: 323
- Delete event: 27
- Issue comment event: 2,657
- Push event: 416
- Pull request event: 916
- Pull request review event: 1,615
- Pull request review comment event: 1,466
- Fork event: 125
Last Year
- Create event: 39
- Release event: 7
- Issues event: 611
- Watch event: 323
- Delete event: 27
- Issue comment event: 2,657
- Push event: 416
- Pull request event: 916
- Pull request review event: 1,615
- Pull request review comment event: 1,466
- Fork event: 125
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Stephan Hoyer | s****r@c****m | 1,262 |
| Deepak Cherian | d****n | 408 |
| Maximilian Roos | 5****y | 391 |
| keewis | k****s | 311 |
| Thomas Nicholas | t****s@c****u | 307 |
| Illviljan | 1****n | 170 |
| Mathias Hauser | m****e | 131 |
| Joe Hamman | j****n@u****u | 114 |
| Spencer Clark | s****k@g****m | 101 |
| dependabot[bot] | 4****] | 100 |
| pre-commit-ci[bot] | 6****] | 98 |
| Clark Fitzgerald | c****g@g****m | 88 |
| Kai Mühlbauer | k****r@u****e | 79 |
| Mick | m****s@g****m | 70 |
| Keisuke Fujii | f****p@g****m | 69 |
| crusaderky | c****y@g****m | 69 |
| Joe Hamman | j****1@u****u | 67 |
| Fabien Maussion | f****n@u****t | 67 |
| Dimitri Papadopoulos Orfanos | 3****s | 65 |
| Clark Fitzgerald | c****d@c****m | 61 |
| Anderson Banihirwe | a****e@u****u | 60 |
| Benoit Bovy | b****y@g****m | 58 |
| Thomas Kluyver | t****l@g****m | 45 |
| alexamici | a****i@b****u | 28 |
| Ray Bell | r****0@g****m | 26 |
| James Munroe | j****e@m****a | 25 |
| Alex Kleeman | k****n@c****m | 24 |
| aurghs | 3****s | 24 |
| github-actions[bot] | 4****] | 20 |
| Mark Harfouche | m****e@g****m | 20 |
| and 529 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 1,632
- Total pull requests: 2,486
- Average time to close issues: over 1 year
- Average time to close pull requests: about 1 month
- Total issue authors: 762
- Total pull request authors: 265
- Average comments per issue: 4.14
- Average comments per pull request: 2.56
- Merged pull requests: 1,821
- Bot issues: 28
- Bot pull requests: 117
Past Year
- Issues: 479
- Pull requests: 1,157
- Average time to close issues: 13 days
- Average time to close pull requests: 6 days
- Issue authors: 248
- Pull request authors: 121
- Average comments per issue: 1.74
- Average comments per pull request: 1.81
- Merged pull requests: 839
- Bot issues: 18
- Bot pull requests: 55
Top Authors
Issue Authors
- dcherian (103)
- TomNicholas (97)
- max-sixty (60)
- shoyer (52)
- github-actions[bot] (27)
- mathause (23)
- benbovy (19)
- rabernat (16)
- kmuehlbauer (15)
- keewis (15)
- Illviljan (14)
- jhamman (13)
- hmaarrfk (12)
- flamingbear (11)
- eni-awowale (10)
Pull Request Authors
- dcherian (339)
- max-sixty (219)
- TomNicholas (136)
- keewis (136)
- kmuehlbauer (129)
- Illviljan (126)
- DimitriPapadopoulos (106)
- shoyer (98)
- dependabot[bot] (69)
- benbovy (66)
- mathause (59)
- pre-commit-ci[bot] (48)
- spencerkclark (44)
- andersy005 (41)
- hmaarrfk (34)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 7
-
Total downloads:
- pypi 10,092,275 last-month
- Total docker downloads: 19,430,565
-
Total dependent packages: 1,732
(may contain duplicates) -
Total dependent repositories: 10,016
(may contain duplicates) - Total versions: 271
- Total maintainers: 5
pypi.org: xarray
N-D labeled arrays and datasets in Python
- Documentation: https://docs.xarray.dev
- License: apache-2.0
-
Latest release: 2025.9.0
published 6 months ago
Rankings
Maintainers (4)
conda-forge.org: xarray
- Homepage: https://github.com/pydata/xarray
- License: Apache-2.0
-
Latest release: 2022.11.0
published over 3 years ago
Rankings
spack.io: py-xarray
N-D labeled arrays and datasets in Python
- Homepage: https://github.com/pydata/xarray
- License: []
-
Latest release: 2025.7.1
published 6 months ago
Rankings
Maintainers (1)
pypi.org: xray
N-D labeled arrays and datasets in Python
- Homepage: https://github.com/pydata/xarray
- Documentation: https://xray.readthedocs.io/
- License: Apache
-
Latest release: 0.7.0
published about 10 years ago
Rankings
Maintainers (1)
proxy.golang.org: github.com/pydata/xarray
- Documentation: https://pkg.go.dev/github.com/pydata/xarray#section-documentation
- License: apache-2.0
-
Latest release: v2024.11.0+incompatible
published about 1 year ago
Rankings
anaconda.org: xarray
xarray (formerly xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun! xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy_-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures. xarray was inspired by and borrows heavily from pandas_, the popular data analysis package focused on labelled tabular data. It is particularly tailored to working with netCDF_ files, which were the source of xarray's data model, and integrates tightly with dask_ for parallel computing.
- Homepage: https://xarray.dev
- License: Apache-2.0
-
Latest release: 2025.4.0
published 9 months ago
Rankings
pypi.org: xarray-map
Plot xarrays lat-lon datasets using folium
- Homepage: https://github.com/pydata/xarray
- Documentation: https://xarray-map.readthedocs.io/
- License: Apache-2.0
-
Latest release: 0.0.2
published almost 3 years ago
Rankings
Dependencies
- actions/checkout v3 composite
- actions/upload-artifact v3 composite
- mamba-org/provision-with-micromamba v14 composite
- actions/checkout v3 composite
- codecov/codecov-action v3.1.1 composite
- mamba-org/provision-with-micromamba v14 composite
- xarray-contrib/ci-trigger v1 composite
- actions/checkout v3 composite
- actions/upload-artifact v3 composite
- codecov/codecov-action v3.1.1 composite
- mamba-org/provision-with-micromamba v14 composite
- xarray-contrib/ci-trigger v1 composite
- EnricoMi/publish-unit-test-result-action v2 composite
- actions/checkout v3 composite
- actions/download-artifact v3 composite
- actions/setup-python v4 composite
- actions/upload-artifact v3 composite
- pypa/gh-action-pypi-publish v1.6.4 composite
- actions/checkout v3 composite
- mamba-org/provision-with-micromamba v14 composite
- xarray-contrib/ci-trigger v1 composite
- xarray-contrib/issue-from-pytest-log v1 composite
- WyriHaximus/github-action-get-previous-tag v1 composite
- actions/checkout v3 composite
- actions/upload-artifact v3 composite
- mamba-org/setup-micromamba v1 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- scientific-python/upload-nightly-action main composite
- boto3
- bottleneck
- cartopy
- cfgrib
- cftime
- coveralls
- dask
- dask_labextension
- distributed
- h5netcdf
- h5py
- hdf5
- iris
- lxml
- matplotlib
- nc-time-axis
- netcdf4
- numba
- numbagg
- numpy
- packaging
- pandas
- pint >=0.22
- pip
- pooch
- pydap
- pynio
- python 3.10.*
- rasterio
- scipy
- seaborn
- setuptools
- sparse
- toolz
- xarray
- zarr
- aiobotocore
- boto3
- bottleneck
- cartopy
- cftime
- dask-core
- distributed
- flox
- fsspec !=2021.7.0
- h5netcdf
- h5py
- hdf5
- hypothesis
- iris
- lxml
- matplotlib-base
- nc-time-axis
- netcdf4
- numba
- numbagg
- numexpr
- numpy
- opt_einsum
- packaging
- pandas
- pint >=0.22
- pip
- pooch
- pre-commit
- pydap
- pytest
- pytest-cov
- pytest-env
- pytest-timeout
- pytest-xdist
- rasterio
- scipy
- seaborn
- sparse
- toolz
- typing_extensions
- zarr