Description
What happened?
In 2025.4.0 and on the current master, trying to export to netCDF a dataset created from a dataframe with categorical index raises the error:
TypeError: Cannot interpret 'CategoricalDtype(categories=['C1', 'C2'], ordered=True, categories_dtype=object)' as a data type
What did you expect to happen?
In 2025.3.1 and before, it was possible to export such a dataset (although the categorical index might be lost in the process).
Minimal Complete Verifiable Example
import pandas as pd
import xarray as xr
df = pd.DataFrame([{"ind": "C1", "val": 1.0}, {"ind": "C2", "val": 2.0}]).set_index("ind")
df.index = df.index.astype(pd.CategoricalDtype(categories=["C1", "C2"], ordered=True))
ds = df.to_xarray()
ds.to_netcdf("foo.nc")MVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
- Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
Anything else we need to know?
Might be related to #10301.
Arguably, the new behavior is better than silently converting to another type. But then, the changelog of 2025.4.0 might need a bit more information on how to update your code for this new behavior.
(Cross-ref: capytaine/capytaine#683)
Environment
xarray: 2025.4.1.dev16+gc8affb3c
pandas: 2.2.3
numpy: 2.2.5
scipy: 1.15.2
netCDF4: 1.7.2
pydap: None
h5netcdf: None
h5py: 3.13.0
zarr: None
cftime: 1.6.4.post1
nc_time_axis: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.10.0
cartopy: None
seaborn: None
numbagg: None
fsspec: 2025.3.2
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: None
pip: 25.0.1
conda: None
pytest: 8.3.4
mypy: None
IPython: 8.32.0
sphinx: 8.1.3
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