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unable to stack on IntervalIndex
What happened?
Previously, in v2025.03.1 datasets were able to be stacked upon IntervalIndex dimensions. This is no longer the case. I now receive the following error:
TypeError: Cannot interpret 'interval[datetime64[ns], left]' as a data type
What did you expect to happen?
I expected to be able to stack on IntervalIndex dimensions as this was previous behavior.
Minimal Complete Verifiable Example
import numpy as np
import pandas as pd
import xarray as xr
t0 = pd.Timestamp('2024-01-01 00:00:00')
t1 = pd.Timestamp('2024-01-07 00:00:00')
dt = pd.Timedelta('1d')
t = pd.interval_range(start=t0, end=t1+dt, freq=dt, closed='left')
xmin = -112.15
xmax = -111.75
ymin = 40.45
ymax = 40.95
dx = dy = 0.05
x = np.arange(xmin, xmax + dx, dx)
y = np.arange(ymin, ymax + dy, dy)
ds = xr.Dataset(
{
'data': (['time', 'y', 'x'], np.random.rand(len(t), len(y), len(x))),
},
coords={
'time': t,
'y': y,
'x': x,
}
)
ds.stack(state=('time', 'y', 'x'))
MVCE confirmation
- [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [x] Complete example — the example is self-contained, including all data and the text of any traceback.
- [x] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- [x] New issue — a search of GitHub Issues suggests this is not a duplicate.
- [x] Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
>>> ds.stack(state=('time', 'y', 'x'))
Traceback (most recent call last):
File "<python-input-3>", line 1, in <module>
ds.stack(state=('time', 'y', 'x'))
~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/dataset.py", line 2313, in __repr__
return formatting.dataset_repr(self)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/reprlib.py", line 21, in wrapper
result = user_function(self)
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/formatting.py", line 752, in dataset_repr
summary.append(coords_repr(ds.coords, col_width=col_width, max_rows=max_rows))
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/formatting.py", line 441, in coords_repr
return _mapping_repr(
coords,
...<5 lines>...
max_rows=max_rows,
)
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/formatting.py", line 415, in _mapping_repr
summarizer(k, v, col_width, **summarizer_kwargs[k])
~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/formatting.py", line 351, in summarize_variable
values_str = inline_variable_array_repr(variable, values_width)
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/formatting.py", line 305, in inline_variable_array_repr
return var._data._repr_inline_(max_width)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/indexing.py", line 2057, in _repr_inline_
return format_array_flat(self._get_array_subset(), max_width)
~~~~~~~~~~~~~~~~~~~~~~^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/indexing.py", line 2049, in _get_array_subset
return np.asarray(subset)
~~~~~~~~~~^^^^^^^^
File "/uufs/chpc.utah.edu/common/home/u6036966/software/python/miniforge3/envs/xarray_interval/lib/python3.13/site-packages/xarray/core/indexing.py", line 1983, in __array__
return np.asarray(
~~~~~~~~~~^
self.array.get_level_values(self.level).values, dtype=dtype
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
TypeError: Cannot interpret 'interval[datetime64[ns], left]' as a data type
Anything else we need to know?
This seems similar to #10312
Environment
INSTALLED VERSIONS
commit: None python: 3.13.5 | packaged by conda-forge | (main, Jun 16 2025, 08:27:50) [GCC 13.3.0] python-bits: 64 OS: Linux OS-release: 4.18.0-553.44.1.el8_10.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: None libnetcdf: None
xarray: 2025.6.1 pandas: 2.3.0 numpy: 2.3.0 scipy: None netCDF4: None pydap: None h5netcdf: None h5py: None zarr: None cftime: None nc_time_axis: None iris: None bottleneck: None dask: None distributed: None matplotlib: None cartopy: None seaborn: None numbagg: None fsspec: None cupy: None pint: None sparse: None flox: None numpy_groupies: None setuptools: None pip: 25.1.1 conda: None pytest: None mypy: None IPython: None sphinx: None
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Hi @jmineau thanks for the detailed bug report!
Are you still experiencing this issue, i just tried to replicate it with the latest xarray and could not get the error