id,node_id,number,state,locked,title,user,body,created_at,updated_at,closed_at,merged_at,merge_commit_sha,assignee,milestone,draft,head,base,author_association,auto_merge,repo,url,merged_by
251611039,MDExOlB1bGxSZXF1ZXN0MjUxNjExMDM5,2757,closed,0,Allow expand_dims() method to support inserting/broadcasting dimensions with size>1,10720577,"This pull request enhances the `expand_dims` method for both `Dataset` and `DataArray` objects to support inserting/broadcasting dimensions with size > 1. It corresponds to this issue https://github.com/pydata/xarray/issues/2710.

## Changes:
1. dataset.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions
3. dataarray.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions
5. Add alternative option to passing a dict to the dim argument, which is now an optional kwarg, passing in each new dimension as its own kwarg
7. Add expand_dims enhancement from issue 2710 to whats-new.rst

## Included:
 - [ ] Tests added
 - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API

## What's new:
All of the old functionality is still there, so it shouldn't break anyone's existing code that uses it. 

You can now pass a dim as a dict, where the keys are the new dimensions and the values are either integers (giving the length of the new dimensions) or iterables (giving the coordinates of the new dimensions).
```
import numpy as np
import xarray as xr

>>> original = xr.Dataset({'x': ('a', np.random.randn(3)),
                                  'y': (['b', 'a'], np.random.randn(4, 3))},
                                  coords={'a': np.linspace(0, 1, 3),
                                                'b': np.linspace(0, 1, 4),
                                                'c': np.linspace(0, 1, 5)},
                                  attrs={'key': 'entry'})
>>> original
<xarray.Dataset>
Dimensions:  (a: 3, b: 4, c: 5)
Coordinates:
  * a        (a) float64 0.0 0.5 1.0
  * b        (b) float64 0.0 0.3333 0.6667 1.0
  * c        (c) float64 0.0 0.25 0.5 0.75 1.0
Data variables:
    x        (a) float64 -1.556 0.2178 0.6319
    y        (b, a) float64 0.5273 0.6652 0.3418 1.858 ... -0.3519 0.8088 0.8753
Attributes:
    key:      entry
>>> original.expand_dims({""d"": 4, ""e"": [""l"", ""m"", ""n""]})
<xarray.Dataset>
Dimensions:  (a: 3, b: 4, c: 5, d: 4, e: 3)
Coordinates:
  * e        (e) <U1 'l' 'm' 'n'
  * a        (a) float64 0.0 0.5 1.0
  * b        (b) float64 0.0 0.3333 0.6667 1.0
  * c        (c) float64 0.0 0.25 0.5 0.75 1.0
Dimensions without coordinates: d
Data variables:
    x        (d, e, a) float64 -1.556 0.2178 0.6319 ... -1.556 0.2178 0.6319
    y        (d, e, b, a) float64 0.5273 0.6652 0.3418 ... -0.3519 0.8088 0.8753
Attributes:
    key:      entry
```
Or, equivalently, you can pass the new dimensions as kwargs instead of a dictionary.
```
original.expand_dims(d=4, e=[""l"", ""m"", ""n""])
```",2019-02-08T21:59:36Z,2019-03-26T02:42:11Z,2019-03-26T02:41:48Z,2019-03-26T02:41:48Z,16a2c03bb23757a92f3f9b8e74c4d489e892e6d6,,,0,cac434e45781f39643f5b42eb96fd4c1f82fe8ed,164d20abb6ffc35eb3f314ce7fb5b9600cf9de3f,CONTRIBUTOR,,13221727,https://github.com/pydata/xarray/pull/2757,
274547973,MDExOlB1bGxSZXF1ZXN0Mjc0NTQ3OTcz,2930,closed,0,Bugfix/coords not deep copy,10720577,"This pull request fixes a bug that prevented making a complete deep copy of a `DataArray` or `Dataset`, because the `coords` weren't being deep copied. It took a small fix in the `IndexVariable.copy` method. This method now allows both deep and shallow copies of coords to be made.

This pull request corresponds to this issue https://github.com/pydata/xarray/issues/1463.

 - [x] Tests added
 - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API
",2019-04-29T22:43:10Z,2023-01-20T10:58:37Z,2019-05-02T22:46:36Z,,e2e3317ba115598235c4920e8deeae6f6f06552d,,,0,3d964985c28a76fc829cb843a4dac6d52b6aa97d,6d93a95d05bdbfc33fff24064f67d29dd891ab58,CONTRIBUTOR,,13221727,https://github.com/pydata/xarray/pull/2930,
275547871,MDExOlB1bGxSZXF1ZXN0Mjc1NTQ3ODcx,2936,closed,0,"BUGFIX: deep-copy wasn't copying coords, bug fixed within IndexVariable",10720577,"This pull request fixes a bug that prevented making a complete deep copy of a `DataArray` or `Dataset`, because the `coords` weren't being deep copied. It took a small fix in the `IndexVariable.copy method`. This method now allows both deep and shallow copies of `coords` to be made.

This pull request corresponds to this issue https://github.com/pydata/xarray/issues/1463.
 - [x] Tests added
 - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API
",2019-05-02T22:58:40Z,2019-05-09T22:31:02Z,2019-05-08T14:44:25Z,2019-05-08T14:44:25Z,c04234d4892641e1da89e47c7164cdcf5e4777a4,,,0,1db167329596995bab739682e10773d64a66b31a,5aaa6547cd14a713f89dfc7c22643d86fce87916,CONTRIBUTOR,,13221727,https://github.com/pydata/xarray/pull/2936,
277517546,MDExOlB1bGxSZXF1ZXN0Mjc3NTE3NTQ2,2953,closed,0,Mark test for copying coords of dataarray and dataset with xfail,10720577,"Mark test for copying coords of dataarray and dataset with `xfail`. It looks like the test fails for the shallow copy, and apparently only on Windows for some reason. In Windows coords seem to be immutable unless it's one dataarray deep copied from another (which is why only the deep=False test fails). So I decided to just mark the tests as xfail for now (but I'd be happy to create an issue and look into it more in the future).

<!-- Feel free to remove check-list items aren't relevant to your change -->
",2019-05-09T19:25:40Z,2019-05-09T22:17:56Z,2019-05-09T22:17:53Z,2019-05-09T22:17:53Z,698293e6cdff8be94464af00e8b8f171e8fd1557,,,0,f43abfcc524ff20a0a6aee029118f1a42511b8ed,ab3972294860447f9515c7b7b0a04838db061496,CONTRIBUTOR,,13221727,https://github.com/pydata/xarray/pull/2953,