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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
1325761961 I_kwDOAMm_X85PBYWp 6867 The Dataset.rename_dims creates a new dimension without coordinates ZhaJiMan 54382968 closed 0     2 2022-08-02T12:11:41Z 2022-09-28T17:48:14Z 2022-09-28T17:48:09Z NONE      

What is your issue?

The documentation says Dataset.rename_dims will returns a new object with renamed dimensions only. In my work I am intended to rename the longitude and latitude dimensions: ds = ds.rename_dims(longitude='lon', latitude='lat'). But it turned out that a new dimension lon was created with values from 0 to its length minus 1. Is this result the expected behaviour of rename_dims, or I misused this method?

A simple case below:

```Python import numpy as np import xarray as xr

da = xr.DataArray([1, 2, 3], coords=[('space', list('abc'))]) ds = xr.Dataset({'x': da}) ```

The information of ds in repl is

<xarray.Dataset> Dimensions: (space: 3) Coordinates: * space (space) <U1 'a' 'b' 'c' Data variables: x (space) int32 1 2 3

But after ds = ds.rename_dims(space='label')

<xarray.Dataset> Dimensions: (label: 3) Coordinates: space (label) <U1 'a' 'b' 'c' Dimensions without coordinates: label Data variables: x (label) int32 1 2 3

space became a non-coordinate dimension, and label was created as a new dimension without coordinates.

Environment: numpy : 1.22.3 pandas : 1.4.2 xarray : 2022.3.0

 
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   completed xarray 13221727 issue

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