I'm pleased to announce the release of the latest major version of xarray, v0.9.
xarray is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays. Its approach combines an API inspired by pandas with the Common Data Model for self-described scientific data. This release includes five months worth of enhancements and bug fixes from 24 contributors, including some significant enhancements to the data model that are not fully backwards compatible. Highlights include: - Coordinates are now optional in the xarray data model, even for dimensions. - Changes to caching, lazy loading and pickling to improve xarray’s experience for parallel computing. - Improvements for accessing and manipulating pandas.MultiIndex levels. - Many new methods and functions, including quantile(), cumsum(), cumprod(), combine_firstset_index(), reset_index(), reorder_levels(), full_like(), zeros_like(), ones_like(), open_dataarray(), compute(), Dataset.info(), testing.assert_equal(), testing.assert_identical(), and testing.assert_allclose(). For more details, read the full release notes: http://xarray.pydata.org/en/latest/whats-new.html You can install xarray with pip or conda: pip install xarray conda install -c conda-forge xarray Best, Stephan
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