issues: 514077742

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
514077742 MDU6SXNzdWU1MTQwNzc3NDI= 3458 Keep index dimension when selecting only a single coord 13770365 open 0     6 2019-10-29T17:02:29Z 2021-03-02T06:48:08Z   NONE      

MCVE Code Sample

```python

Your code here

import numpy as np import xarray as xr

data = np.zeros((10, 4)) example_xr = xr.DataArray(data, coords=[range(10), ["idx0", "idx1", "idx2", "dim3"]], dims=["rows", "cols"])

desired behavior

subset = example_xr[:, 1:2] subset.shape

inclusive indexing means both idx1 and idx2 kept

subset_named1 = example_xr.loc[:, "idx1":"idx2"] subset_named1.shape

slicing behavior means that 2nd dimension is dropped

subset_named2 = example_xr.loc[:, "idx1"] subset_named2.shape ```

Expected Output

I'd like to be able to use named .loc indexing to select only a single named coord from one dimension, but not have that dimension collapse when subsetting.

Problem Description

I looked, but wasn't able to find anything in the documentation about how to perform this same action using named coords. It works with integer-based slicing.

Output of xr.show_versions()

# Paste the output here xr.show_versions() here 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/3458/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     13221727 issue

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