I'm pleased to announce the release of the latest major version of xarray,

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
- 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

For more details, read the full release notes:

You can install xarray with pip or conda:
pip install xarray
conda install -c conda-forge xarray

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