The minor release includes a number of bug-fixes and backwards compatible enhancements.

For full details, see the release notes: http://xarray.pydata.org/en/latest/whats-new.html

The minor release includes a number of bug-fixes and enhancements, along with one possibly backwards incompatible change (when applying NumPy ufunc methods to xarray objects).

For full details, see the release notes.

The minor release includes a number of bug-fixes and backwards compatible enhancements. For full details, see the release notes.

This is a major release that includes bug fixes, new features and a few backwards incompatible changes. Highlights include:

• Indexing now supports broadcasting over dimensions, similar to NumPy's vectorized indexing (but better!).
• resample has a new groupby-like API like pandas.
• xarray.apply_ufunc facilitates wrapping and parallelizing functions written for NumPy arrays.
• Performance improvements, particularly for dask and open_mfdataset.

For more details, see the release notes: http://xarray.pydata.org/en/latest/whats-new.html

This release includes a number of backwards compatible enhancements and bug fixes.

Enhancements - New sortby() method to Dataset and DataArray that enable sorting along dimensions (GH967). See the docs for examples. By Chun-Wei Yuan and Kyle Heuton. - Add .dt accessor to DataArrays for computing datetime-like properties for the values they contain, similar to pandas.Series (GH358). By Daniel Rothenberg. - Renamed internal dask arrays created by open_dataset to match new dask conventions (GH1343). By Ryan Abernathey. - as_variable() is now part of the public API (GH1303). By Benoit Bovy. - align() now supports join='exact', which raises an error instead of aligning when indexes to be aligned are not equal. By Stephan Hoyer. - New function open_rasterio() for opening raster files with the rasterio library. See the docs for details. By Joe Hamman, Nic Wayand and Fabien Maussion

Bug fixes - Fix error from repeated indexing of datasets loaded from disk (GH1374). By Stephan Hoyer. - Fix a bug where .isel_points wrongly assigns unselected coordinate to data_vars. By Keisuke Fujii. - Tutorial datasets are now checked against a reference MD5 sum to confirm successful download (GH1392). By Matthew Gidden. - DataArray.chunk() now accepts dask specific kwargs like Dataset.chunk() does. By Fabien Maussion. - Support for engine='pydap' with recent releases of Pydap (3.2.2+), including on Python 3 (GH1174).

Documentation - A new gallery allows to add interactive examples to the documentation. By Fabien Maussion.

Testing - Fix test suite failure caused by changes to pandas.cut function (GH1386). By Ryan Abernathey. - Enhanced tests suite by use of @network decorator, which is controlled via --run-network-tests command line argument to py.test (GH1393). By Matthew Gidden.

Remove an inadvertently introduced print statement.

Enhancements - Add .persist() method to Datasets and DataArrays to enable persisting data in distributed memory (GH1344). By Matthew Rocklin. - New expand_dims() method for DataArray and Dataset (GH1326). By Keisuke Fujii.

Bug fixes - Fix .where() with drop=True when arguments do not have indexes (GH1350). This bug, introduced in v0.9, resulted in xarray producing incorrect results in some cases. By Stephan Hoyer. - Fixed writing to file-like objects with to_netcdf() (GH1320). Stephan Hoyer. - Fixed explicitly setting engine='scipy' with to_netcdf when not providing a path (GH1321). Stephan Hoyer. - Fixed open_dataarray does not pass properly its parameters to open_dataset (GH1359). Stephan Hoyer. - Ensure test suite works when runs from an installed version of xarray (GH1336). Use @pytest.mark.slow instead of a custom flag to mark slow tests. By Stephan Hoyer

The minor release includes bug-fixes and backwards compatible enhancements.

Enhancements

• .rolling() on Dataset is now supported (GH859). By Keisuke Fujii.
• When bottleneck version 1.1 or later is installed, use bottleneck for rolling var, argmin, argmax, and rank computations. Also, rolling median now accepts a min_periods argument (GH1276). By Joe Hamman.
• When .plot() is called on a 2D DataArray and only one dimension is specified with x= or y=, the other dimension is now guessed (GH1291). By Vincent Noel.
• Added new method assign_attrs() to DataArray and Dataset, a chained-method compatible implementation of the dict.update method on attrs (GH1281). By Henry S. Harrison.
• Added new autoclose=True argument to open_mfdataset() to explicitly close opened files when not in use to prevent occurrence of an OS Error related to too many open files (GH1198). Note, the default is autoclose=False, which is consistent with previous xarray behavior. By Phillip J. Wolfram.
• The repr() of Dataset and DataArray attributes uses a similar format to coordinates and variables, with vertically aligned entries truncated to fit on a single line (GH1319). Hopefully this will stop people writing data.attrs = {} and discarding metadata in notebooks for the sake of cleaner output. The full metadata is still available as data.attrs. By Zac Hatfield-Dodds.
• Enhanced tests suite by use of @slow and @flaky decorators, which are controlled via --run-flaky and --skip-slow command line arguments to py.test (GH1336). By Stephan Hoyer and Phillip J. Wolfram.

Bug fixes

• Rolling operations now keep preserve original dimension order (GH1125). By Keisuke Fujii.
• Fixed sel with method='nearest' on Python 2.7 and 64-bit Windows (GH1140). Stephan Hoyer.
• Fixed where with drop='True' for empty masks (GH1341). By Stephan Hoyer and Phillip J. Wolfram.

Renamed the "Unindexed dimensions" section in the Dataset and DataArray repr (added in v0.9.0) to "Dimensions without coordinates".

This major release includes five months worth of enhancements and bug fixes from 24 contributors, including some significant changes 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_first set_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, see what's new.

This release includes a number of bug fixes and minor enhancements.

Breaking changes

• broadcast() and concat() now auto-align inputs, using join=outer. Previously, these functions raised ValueError for non-aligned inputs. By Guido Imperiale.

Enhancements

• New documentation on Transitioning from pandas.Panel to xarray. By Maximilian Roos.
• New Dataset and DataArray methods to_dict() and from_dict() to allow easy conversion between dictionaries and xarray objects (#432). See dictionary IO for more details. By Julia Signell.
• Added exclude and indexes optional parameters to align(), and exclude optional parameter to broadcast(). - By Guido Imperiale.
• Better error message when assigning variables without dimensions (#971). By Stephan Hoyer.
• Better error message when reindex/align fails due to duplicate index values (#956). By Stephan Hoyer.

Bug fixes

• Ensure xarray works with h5netcdf v0.3.0 for arrays with dtype=str (#953). By Stephan Hoyer.
• Dataset.dir() (i.e. the method python calls to get autocomplete options) failed if one of the dataset’s keys was not a string (#852). By Maximilian Roos.
• Dataset constructor can now take arbitrary objects as values (#647). By Maximilian Roos. Clarified copy argument for reindex() and align(), which now consistently always return new xarray objects (#927).
• Fix open_mfdataset with engine='pynio' (#936). By Stephan Hoyer. groupby_bins sorted bin labels as strings (#952). By Stephan Hoyer.
• Fix bug introduced by v0.8.0 that broke assignment to datasets when both the left and right side have the same non-unique index values (#956).

Bug fixes

• Fix bug in v0.8.0 that broke assignment to Datasets with non-unique indexes (#943). By Stephan Hoyer.

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.

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.

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

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.

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

This release focused on bug-fixes, speedups and resolving some niggling inconsistencies.

There are a few cases where the behavior of xray differs from the previous version. However, I expect that in almost all cases your code will continue to run unmodified.

xray now requires pandas v0.15.0 or later. This was necessary for supporting TimedeltaIndex without too many painful hacks.

Backwards incompatible changes: - Arrays of datetime.datetime objects are now automatically cast to datetime64[ns] arrays when stored in an xray object, using machinery borrowed from pandas:

``` In [1]: from datetime import datetime

In [2]: xray.Dataset({'t': [datetime(2000, 1, 1)]}) Out[2]: <xray.Dataset> Dimensions: (t: 1) Coordinates: * t (t) datetime64[ns] 2000-01-01 Variables: empty `` - xray now has support (including serialization to netCDF) forpandas.TimedeltaIndex.datetime.timedeltaobjects are thus accordingly cast totimedelta64[ns]objects when appropriate. - Masked arrays are now properly coerced to useNaN` as a sentinel value.

Enhancements: - Due to popular demand, we have added experimental attribute style access as a shortcut for dataset variables, coordinates and attributes:

``` In [3]: ds = xray.Dataset({'tmin': ([], 25, {'units': 'celcius'})})

In [4]: ds.tmin.units Out[4]: 'celcius' ```

Tab-completion for these variables should work in editors such as IPython. However, setting variables or attributes in this fashion is not yet supported because there are some unresolved ambiguities. - You can now use a dictionary for indexing with labeled dimensions. This provides a safe way to do assignment with labeled dimensions:

``` In [5]: array = xray.DataArray(np.zeros(5), dims=['x'])

In [6]: array[dict(x=slice(3))] = 1

In [7]: array Out[7]: <xray.DataArray (x: 5)> array([ 1., 1., 1., 0., 0.]) Coordinates: * x (x) int64 0 1 2 3 4 `` - Non-index coordinates can now be faithfully written to and restored from netCDF files. This is done according to CF conventions when possible by using thecoordinatesattribute on a data variable. When not possible, xray defines a globalcoordinatesattribute. - Preliminary support for convertingxray.DataArrayobjects to and from CDATcdms2` variables. - We sped up any operation that involves creating a new Dataset or DataArray (e.g., indexing, aggregation, arithmetic) by a factor of 30 to 50%. The full speed up requires cyordereddict to be installed.

Bug fixes: - Fix for to_dataframe() with 0d string/object coordinates - Fix for to_netcdf with 0d string variable - Fix writing datetime64 arrays to netcdf if NaT is present - Fix align silently upcasts data arrays when NaNs are inserted

This is mostly a bug-fix release to make xray compatible with the latest release of pandas (v0.15).

We added several features to better support working with missing values and exporting xray objects to pandas. We also reorganized the internal API for serializing and deserializing datasets, but this change should be almost entirely transparent to users.

Other than breaking the experimental DataStore API, there should be no backwards incompatible changes.

New features: - Added count and dropna methods, copied from pandas, for working with missing values. - Added DataArray.to_pandas for converting a data array into the pandas object with the same dimensionality (1D to Series, 2D to DataFrame, etc.). - Support for reading gzipped netCDF3 files. - Reduced memory usage when writing netCDF files. - 'missing_value' is now supported as an alias for the '_FillValue' attribute on netCDF variables. - Trivial indexes, equivalent to range(n) where n is the length of the dimension, are no longer written to disk.

Bug fixes: - Compatibility fixes for pandas v0.15. - Fixes for display and indexing of NaT (not-a-time). - Fix slicing by label was an argument is a data array. - Test data is now shipped with the source distribution. - Ensure order does not matter when doing arithmetic with scalar data arrays. - Order of dimensions preserved with DataArray.to_dataframe.

New features: - Revamped coordinates: "coordinates" now refer to all arrays that are not used to index a dimension. Coordinates are intended to allow for keeping track of arrays of metadata that describe the grid on which the points in "variable" arrays lie. They are preserved (when unambiguous) even though mathematical operations. - Dataset math xray.Dataset objects now support all arithmetic operations directly. Dataset-array operations map across all dataset variables; dataset-dataset operations act on each pair of variables with the same name. - GroupBy math: This provides a convenient shortcut for normalizing by the average value of a group. - The dataset __repr__ method has been entirely overhauled; dataset objects now show their values when printed. - You can now index a dataset with a list of variables to return a new dataset: ds[['foo', 'bar']].

Backwards incompatible changes: - Dataset.__eq__ and Dataset.__ne__ are now element-wise operations instead of comparing all values to obtain a single boolean. Use the method Dataset.equals instead.

Deprecations: - Dataset.noncoords is deprecated: use Dataset.vars instead. - Dataset.select_vars deprecated: index a Dataset with a list of variable names instead. - DataArray.select_vars and DataArray.drop_vars deprecated: use DataArray.reset_coords instead.

This is major release that includes some new features and quite a few bug fixes. Here are the highlights: - There is now a direct constructor for DataArray objects, which makes it possible to create a DataArray without using a Dataset. This is highlighted in the refreshed tutorial. - You can perform aggregation operations like mean directly on xray.Dataset objects, thanks to Joe Hamman. These aggregation methods also worked on grouped datasets. - xray now works on Python 2.6, thanks to Anna Kuznetsova. - A number of methods and attributes were given more sensible (usually shorter) names: labeled -> sel, indexed -> isel, select -> select_vars, unselect -> drop_vars, dimensions -> dims, coordinates -> coords, attributes -> attrs. - New Dataset.load_data and Dataset.close methods for datasets facilitate lower level of control of data loaded from disk.

xray 0.1.1 is a bug-fix release that includes changes that should be almost entirely backwards compatible with v0.1: - Python 3 support (#53) - Required numpy version relaxed to 1.7 (#129) - Return numpy.datetime64 arrays for non-standard calendars (#126) - Support for opening datasets associated with NetCDF4 groups (#127) - Bug-fixes for concatenating datetime arrays (#134)

Special thanks to new contributors Thomas Kluyver, Joe Hamman and Alistair Miles.

Initial release