xarray (formerly xray) is an open source project and Python package that aims to bring the labeled data power of pandas to the physical sciences, by providing N-dimensional variants of the core pandas data structures.
Our goal is to provide a pandas-like and pandas-compatible toolkit for
analytics on multi-dimensional arrays, rather than the tabular data for which
pandas excels. Our approach adopts the Common Data Model for self-
describing scientific data in widespread use in the Earth sciences:
xarray.Dataset is an in-memory representation of a netCDF file.
Note
xray is now xarray! See :ref:`the v0.7.0 release notes<whats-new.0.7.0>` for more details. The preferred URL for these docs is now http://xarray.pydata.org.
.. toctree:: :maxdepth: 1 whats-new why-xarray faq examples installing data-structures indexing computation groupby reshaping combining time-series pandas io dask plotting api internals
- Stephan Hoyer and Joe Hamman's Journal of Open Research Software paper describing the xarray project.
- The UW eScience Institute's Geohackweek tutorial on xarray for geospatial data scientists.
- Stephan Hoyer's SciPy2015 talk introducing xarray to a general audience.
- Stephan Hoyer's 2015 Unidata Users Workshop talk and tutorial (with answers) introducing xarray to users familiar with netCDF.
- Nicolas Fauchereau's tutorial on xarray for netCDF users.
- Ask usage questions on StackOverflow.
- Report bugs, suggest features or view the source code on GitHub.
- For less well defined questions or ideas, use the mailing list.
- You can also try our chatroom on Gitter.
xarray is available under the open source Apache License.
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.