This release brings improvements to plotting of categorical data, the ability to specify how attributes are combined in xarray operations, a new high-level
unify_chunks function, as well as various deprecations, bug fixes, and minor improvements.
This release is intended as a small patch release to be compatible with the new 2021.5.0 dask.distributed release. It also includes a new
drop_duplicates method, some documentation improvements, the beginnings of our internal Index refactoring, and some bug fixes.
This release brings a few important performance improvements, a wide range of usability upgrades, lots of bug fixes, and some new features. These include a plugin API to add backend engines, a new theme for the documentation, curve fitting methods, and several new plotting functions.
This release brings a few important performance improvements, a wide range of usability upgrades, lots of bug fixes, and some new features. These include better
cftime support, a new quiver plot, better
unstack performance, more efficient memory use in rolling operations, and some python packaging improvements. We also have a few documentation improvements (and more planned!).
This release brings the ability to write to limited regions of
zarr files, open zarr files with
open_mfdataset, increased support for propagating
attrs using the
keep_attrs flag, as well as numerous bugfixes and documentation improvements.
This patch release fixes an incompatibility with a recent pandas change, which was causing an issue indexing with a
datetime64. It also includes improvements to
corr methods and bug fixes. Our documentation has a number of improvements, including fixing all doctests and confirming their accuracy on every commit.
This release adds
xarray.corr for covariance & correlation respectively; the
idxmin methods, the
polyfit method &
xarray.polyval for fitting polynomials, as well as a number of documentation improvements, other features, and bug fixes. Many thanks to all 44 contributors who contributed to this release.
This release brings many new features such as
weighted methods for weighted array reductions, a new jupyter repr by default, and the start of units integration with pint. There's also the usual batch of usability improvements, documentation additions, and bug fixes.