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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:
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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