• [x] Closes #1444, closes #1436
• [x] Tests added / passed
• [x] Passes git diff master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

xref https://github.com/pydata/xarray/issues/974#issuecomment-313977794

• [x] Closes #1257
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API

This is a very bare bones addition of the asv benchmarking tool to xarray. I have added four very rudimentary benchmarks in the dataset_io.py module.

Usage of asv is pretty straightforward but I'll outline the steps for those who want to try this out: cd xarray conda install asv -c conda-forge asv run # this will install some conda environments in ./.asv/envs asv publish # this collates the results asv preview # this will launch a web server so you can visually compare the tests

Before I go any further, I want to get some input from @pydata/xarray on what we want to see in this PR. In previous projects, I have found designing tests after the fact can end up being fairly arbitrary and I want to avoid that if at all possible. I'm guessing that we will want to focus our efforts for now on I/O and dask related performance but how we do that is up for discussion.

cc @shoyer, @rabernat, @MaximilianR, @Zac-HD

• [x] Closes #1512
• [x] Tests passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Explicitly deprecated old pandas (< 0.18) and old numpy (< 1.11) supports. Some backported functions in npcompat are removed because numpy == 1.11 already has them.

• [x] xref #986
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

This PR adds a new module level function xr.show_versions() and a new Github Issue Template to help with debugging user issues. Hopefully, we stop having to ask "what version of dask are you using?" Functionality is copied from pandas.

• [x] Closes #1093
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Working towards on a solution for #1462

Just some stub code for the moment.

Dask dataframes don't appear to support MultiIndex so not sure what to do about that.

apply_ufunc() does not meet all our needs for wrapping unlabeled array routines with xarray (see #1618 for a proposal for apply_raw()), but it should be useful for many advanced users and isn't doing much in its current state as non-public API. So I'd like to make it public for the xarray 0.10 release.

• [x] Closes #770
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API
• [x] Turn the example from #1517 into a separate docs page of some sort, and link to it from computation.rst and dask.rst.

@MaximilianR @rabernat @jhamman Review from any of you would be appreciated here!

• [x] Closes #1521
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

This is a work-in-progress to resolve #1269.

• [x] Basic functionality
• [x] Cleanly deprecate old API
• [x] New test cases
• [x] Documentation / examples
• [x] "What's new"

Openly welcome feedback/critiques on how I approached this. Subclassing Data{Array/set}GroupBy may not be the best way, but it would be easy enough to re-write the necessary helper functions (just apply(), I think) so that we do not need to inherit form them directly. Additional issues I'm working to resolve:

• [x] I tried make sure that calls using the old API won't break by refactoring the old logic to _resample_immediately(). This may not be the best approach!
• [x] Similarly, I copied all the original test cases and added the suffix ..._old_api; these could trivially be placed into their related test cases for the new API.
• [x] BUG: keep_attrs is ignored when you call it on methods chained to Dataset.resample(). Oddly enough, if I hard-code keep_attrs=True inside reduce_array() in DatasetResample::reduce it works just fine. I haven't figured out where the kwarg is getting lost.
• [x] BUG: Some of the test cases (for instance, test_resample_old_vs_new_api) fail because the resampling by calling self.groupby_cls ends up not working - it crashes because the group sizes that get computed are not what it expects. Occurs with both new and old API

• [x] Fixes #1522
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Stop dataset data vars and non-index dataset/dataarray coords from being loaded by repr() and getattr(). The latter is particularly acute when working in Jupyter, which does a dozen or so getattr() when printing an object.

• [x] Closes #1120
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Make the filename argument to NetCDF4DataStore polymorphic so that a Dataset can be passed in.

• [x] Closes #1459
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

1459 discussed adding an alternate constructor (i.e. a class method) to NetCDF4DataStore to allow this, which would be my preferred approach rather than making a filename polymorphic (via isinstance). Unfortunately, alternate constructors only work by taking one set of parameters (or setting defaults) and then passing them to the original constructor. Given that, there's no way to make an alternate constructor without also making the original constructor somehow aware of this functionality--or breaking backwards-compatibility. I'm open to suggestions to the contrary.

Example usage: ```python

a.where(a.x + a.y < 5, -1) <xarray.DataArray (x: 5, y: 5)> array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, -1], [10, 11, 12, -1, -1], [15, 16, -1, -1, -1], [20, -1, -1, -1, -1]]) Dimensions without coordinates: x, y ` - [x] Closes #576 - [x] Tests added / passed - [x] Passesgit diff upstream/master | flake8 --diff` - [x] Fully documented, includingwhats-new.rstfor all changes andapi.rst` for new API

CC @MaximilianR

• [x] Closes #1477
• [x] Tests added / passed
• [x] passes git diff upstream/master | flake8 --diff
• [x] added whats-new.rst entry.

This is a temporary work around for https://github.com/pandas-dev/pandas/issues/16896, which was introduced by pandas 0.20.3

We can safely revert it after the next pandas release.

• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

~~This still probably should have a regression test.~~ Done

• [x] Closes #1444
• [x] Tests added / passed
• [x] Passes git diff upstream/master | flake8 --diff
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

Solves this error:

TypeError: 'NotImplementedType' object is not callable

Adds the 'res', 'is_tiled', and 'transform' attributes to xarray's rasterio backend.

• [X] Closes #1456
• [X] Tests added / passed
• [X] Passes git diff upstream/master | flake8 --diff
• [X] Fully documented, including whats-new.rst for all changes and api.rst for new API

EDIT: fixed typo; 'tiled' attribute name updated to 'is_tiled'

Rasterio uses edge-based coordinates, which is a different convention from how xarray treats coordinates (based on description here: http://xarray.pydata.org/en/stable/plotting.html#coordinates). This PR centers them, offsetting by half of the resolution.

• [X] Tests added / passed
• [X] Passes git diff upstream/master | flake8 --diff ~- [ ] Closes #xxxx~
• [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

CCing @fmaussion since he may be interested.

I've spotted this wrong error message. In my opinion this is too small to justify an entry in whats-new.rst.