N-D labeled arrays and datasets in Python¶
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 the v0.7.0 release notes for more details. The preferred URL for these docs is now http://xarray.pydata.org.
Documentation¶
- What’s New
- Overview: Why xarray?
- Frequently Asked Questions
- Examples
- Installation
- Data Structures
- Indexing and selecting data
- Computation
- GroupBy: split-apply-combine
- Reshaping and reorganizing data
- Combining data
- Time series data
- Working with pandas
- Serialization and IO
- Out of core computation with dask
- Plotting
- API reference
- xarray Internals
See also¶
- 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.
Get in touch¶
- 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.
License¶
xarray is available under the open source Apache License.
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.