issues

It would be nice to have a generic .pad() method to xarray objects based on numpy.pad and dask.array.pad.

In particular,pad with mode='wrap' could solve several use-cases related to periodic boundary conditions: https://github.com/pydata/xarray/issues/1005 , https://github.com/pydata/xarray/issues/2007. For example, ds.pad(longitude=(0, 1), mode='wrap') to add an extra point with periodic boundary conditions along the longitude dimension.

It probably makes sense to linearly extrapolate coordinates along padded dimensions, as long as they are regularly spaced. This might use heuristics and/or a keyword argument.

I don't have a plans to work on this in the near term. It could be a good project of moderate complexity for a new contributor.

Clean-ups we should definitely do: - [x] remove deprecated options from xarray.concat (deprecated back in July 2015!): https://github.com/pydata/xarray/blob/79dc7dc461c7540cc0b84a98543c6f7796c05268/xarray/core/concat.py#L114-L144 (edit by @max-sixty ) - [x] argument order in DataArray.to_dataset (also from July 2015) https://github.com/pydata/xarray/blob/41fecd8658ba50ddda0a52e04c21cec5e53415ac/xarray/core/dataarray.py#L491 (edit by @max-sixty ) - [x] remove the warning back reindex with variables with different dimensions (from 2017). This could either be replaced by replacing dimensions like sel or by simply raising an error for now and leaving replacing dimensions for later: https://github.com/pydata/xarray/pull/1639): https://github.com/pydata/xarray/blob/79dc7dc461c7540cc0b84a98543c6f7796c05268/xarray/core/alignment.py#L389-L398 (edit by @max-sixty ) - [x] remove xarray.broadcast_array, deprecated back in 2016 in https://github.com/pydata/xarray/commit/52ee95f8ae6b9631ac381b5b889de47e41f2440e (edit by @max-sixty ) - [x] remove Variable.expand_dims (deprecated back in August 2017), whose implementation actually looks like it's already broken: https://github.com/pydata/xarray/blob/41fecd8658ba50ddda0a52e04c21cec5e53415ac/xarray/core/variable.py#L1232-L1237 (edit by @max-sixty ) - [x] stop supporting a list of colors in the cmap argument (dating back to at least v0.7.0): https://github.com/pydata/xarray/blob/d089df385e737f71067309ff7abae15994d581ec/xarray/plot/utils.py#L737-L745 (edit by @max-sixty ) - [x] push the removal of the compat and encoding arguments from Dataset/DataArray back to 0.14. These were only deprecated 7 months ago in https://github.com/pydata/xarray/pull/2703. (edit by @max-sixty )

Clean-ups to consider: - [x] switch the default reduction dimension of groupby and resample? (https://github.com/pydata/xarray/pull/2366) This has been giving a FutureWarning since v0.11.0, released back in November 2018. We could also potentially push this back to 0.14, but these warnings are a little annoying... - [x] deprecate auto_combine (#2616) only since 29 June 2019, so that should be pushed.

Includes silencing two warnings that show up in xarray's public API:

1. Dataset.update(Dataset) #2161
2. .equals() with scalar timedelta64/datetime64 arrays containing NaT:

``` In [1]: import numpy as np

In [2]: import xarray as xr

In [3]: array = xr.DataArray([np.datetime64('NaT')])

In [4]: array[0].equals(array[0]) /Users/shoyer/dev/xarray/xarray/core/duck_array_ops.py:148: FutureWarning: In the future, 'NAT == x' and 'x == NAT' will always be False. flag_array = (arr1 == arr2) Out[16]: True ```

Fixes #2161

• [x] Tests added (for all bug fixes or enhancements)
• [x] Tests passed (for all non-documentation changes)
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)

I'm particularly interested in projects that we should highlight in our docs and other publications, either as evidence of the impact of xarray or because other xarray users would find it useful to know about them. We could put together an "Xarray ecosystem" docs page like pandas.

What I have so far falls into three categories:

Tools for analyzing global climate model output with xarray: - xgcm: for analyzing general circulation model output data - oocgcm: analysis of large gridded geophysical dataset - mpas_xarray: wrapper to allow input of mpas data into xarray - marc_analysis: Analysis package for CESM/MARC experiments and output

Other weather/climate specific tools: - windspharm: wind spherical harmonics - eofs: empirical orthogonal functions - infinite-diff: xarray-based finite-differencing - aospy: Climate data analysis, database, and visualization

Non-climate: - Datashader: visualization for large data - cesium: machine learning for time series analysis - ptsa: EEG Time Series Analysis - pyGDX: GDX file data access - pycalphad: Computational Thermodynamics in Python

align now supports join='exact', which raises xarray.AlignmentError instead of aligning when indexes to be aligned are not equal.

This is useful for asserting that objects are identical instead of aligning in xarray operations.

For example:

ds1 = xarray.Dataset(coords={'x': [0, 1]})
ds2 = xarray.Dataset(coords={'x': [1, 2]})
xarray.merge([ds1, ds2], join='exact')
# AlignmentError: indexes along dimension 'x' are not equal

• [x] tests added / passed
• [x] passes git diff upstream/master | flake8 --diff
• [x] whatsnew entry