Releases: pydata/xarray
v0.18.1
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.
v0.18.0
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.
v0.17.0
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!).
v0.16.2
This release brings the ability to write to limited regions of zarr files, open zarr files with open_dataset and open_mfdataset, increased support for propagating attrs using the keep_attrs flag, as well as numerous bugfixes and documentation improvements.
v0.16.1
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 rolling, to_dataframe, cov & corr methods and bug fixes. Our documentation has a number of improvements, including fixing all doctests and confirming their accuracy on every commit.
v0.16.0
This release adds xarray.cov & xarray.corr for covariance & correlation respectively; the idxmax & 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.
v0.15.1
732b6cd
max-sixty
Maximilian Roos
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.
