v0.8.0rc1

v0.8.0rc1

v0.7.2

Version 0.7.2

v0.7.1

Version 0.7.1

v0.7.0

Version 0.7.0

v0.6.1

This release contains a number of bug and compatibility fixes, as well as enhancements to plotting, indexing and writing files to disk.

Note that the minimum required version of dask for use with xray is now version 0.6.

• Faceted plotting through FacetGrid and the plot() method. See Faceting for more details and examples.
• sel() and reindex() now support the tolerance argument for controlling nearest-neighbor selection (GH629). This feature requires pandas v0.17 or newer.
• New encoding argument in to_netcdf() for writing netCDF files with compression, as described in the new documentation section on Writing encoded data.
• Add real and imag attributes to Dataset and DataArray (GH553).
• More informative error message with from_dataframe() if the frame has duplicate columns.
• xray now uses deterministic names for dask arrays it creates or opens from disk. This allows xray users to take advantage of dask’s nascent support for caching intermediate computation results. See GH555 for an example.
• Compatibility with Python 3.5 (GH583).
• Compatibility with pandas 0.17 (GH569).
• Compatability with numpy 1.10 (GH618).

See the What's New page for more information. Please report any issues here.

You an install the latest version of xray via conda:

conda install xray

or via pip:

pip install xray

v0.5.1

This minor release fixes a few bugs and an inconsistency with pandas. It also adds the pipe method, copied from pandas.

For more details, see the release notes.

v0.5

Highlights of this release:

• Support for parallel computation on arrays that don't fit in memory using dask.array (see http://continuum.io/blog/xray-dask for more details)
• Support for multi-file datasets
• assign and fillna methods, based on the pandas methods of the same name.
• to_array and to_dataset methods for easier conversion between xray Dataset and DataArray objects.
• Label based indexing with nearest neighbor lookups

For more details, see the release notes.

v0.4.1

The release contains bug fixes and several new features. All changes should be fully backwards compatible.

Highlights include:

• Documentation sections on Time series data and Combining multiple files.
• resample method for resampling to a new temporal resolution like pandas
• first and last methods on groupby objects
• swap_dims method for swapping dimensions
• Fixed a critical bug with the scipy netCDF backend

For more details, see the release notes

v0.4

This is a major release that includes a number of new features and bug fixes, including several changes from existing behavior.

Highlights include:

• Automatic alignment of index labels in arithmetic and when combining arrays or datasets.
• Aggregations like mean now skip missing values by default.
• Relaxed equality rules in concat and merge for variables with equal value(s) but different shapes.
• New drop method for dropping variables or index labels.
• Support for reindexing with a fill method like pandas.

For more details, see the release notes.

v0.4 release candidate

This is a release candidate for v0.4. This version of xray includes some major changes, so I wanted it to get some testing before its official release.

For a list of changes, please read the release notes from the development version of the documentation:
http://xray.readthedocs.org/en/latest/whats-new.html

To test it out, use:

pip install https://github.com/xray/xray/archive/v0.4rc1.zip