Description
What happened?
xr.concat removes datetime information and can't concatenate the arrays because they don't have compatible types anymore.
What did you expect to happen?
Succesful concatenation with the same type.
Minimal Complete Verifiable Example
import numpy as np
import xarray as xr
from datetime import datetime
month = np.arange(1, 13, 1)
data = np.sin(2 * np.pi * month / 12.0)
darray = xr.DataArray(data, dims=["time"])
darray.coords["time"] = np.array([datetime(2017, m, 1) for m in month])
darray_nan = np.nan * darray.isel(**{"time": -1})
darray = xr.concat([darray, darray_nan], dim="time")Relevant log output
Traceback (most recent call last):
File "<ipython-input-15-31040255a336>", line 2, in <module>
darray = xr.concat([darray, darray_nan], dim="time")
File "c:\users\j.w\documents\github\xarray\xarray\core\concat.py", line 244, in concat
return f(
File "c:\users\j.w\documents\github\xarray\xarray\core\concat.py", line 642, in _dataarray_concat
ds = _dataset_concat(
File "c:\users\j.w\documents\github\xarray\xarray\core\concat.py", line 555, in _dataset_concat
combined_idx = indexes[0].concat(indexes, dim, positions)
File "c:\users\j.w\documents\github\xarray\xarray\core\indexes.py", line 318, in concat
coord_dtype = np.result_type(*[idx.coord_dtype for idx in indexes])
File "<__array_function__ internals>", line 5, in result_type
TypeError: The DType <class 'numpy.dtype[datetime64]'> could not be promoted by <class 'numpy.dtype[int64]'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtype[datetime64]'>, <class 'numpy.dtype[int64]'>)Anything else we need to know?
Similar to #6384.
Happens around here:
Line 535 in 728b648
Environment
INSTALLED VERSIONS
commit: None
python: 3.9.6 | packaged by conda-forge | (default, Jul 11 2021, 03:37:25) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: ('Swedish_Sweden', '1252')
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.16.3.dev99+gc19467fb
pandas: 1.3.1
numpy: 1.21.5
scipy: 1.7.1
netCDF4: 1.5.6
pydap: installed
h5netcdf: 0.11.0
h5py: 2.10.0
Nio: None
zarr: 2.8.3
cftime: 1.5.0
nc_time_axis: 1.3.1
PseudoNetCDF: installed
rasterio: 1.2.6
cfgrib: None
iris: 3.0.4
bottleneck: 1.3.2
dask: 2021.10.0
distributed: 2021.10.0
matplotlib: 3.4.3
cartopy: 0.19.0.post1
seaborn: 0.11.1
numbagg: 0.2.1
fsspec: 2021.11.1
cupy: None
pint: 0.17
sparse: 0.12.0
setuptools: 49.6.0.post20210108
pip: 21.2.4
conda: None
pytest: 6.2.4
IPython: 7.31.0
sphinx: 4.3.2