xr.concat changes dtype

[volkerjaenisch]

Code Sample, a copy-pastable example if possible

>>> dataset_a.wind_quality_flag.dtype
dtype('int64')

>>> dataset_b.wind_quality_flag.dtype
dtype('int64')

>>> result = xr.concat((dataset_a, dataset_b), dim='time')
>>> result.wind_quality_flag.dtype
dtype('float64')

>>> dataset_a.wind_quality_flag
<xarray.DataArray 'wind_quality_flag' (time: 1, altitude: 13)>
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
Coordinates:
  * time      (time) datetime64[ns] 2018-12-27T11:30:00
  * altitude  (altitude) float64 210.0 245.0 281.0 ... 1.141e+03 1.177e+03
>>> dataset_b.wind_quality_flag
<xarray.DataArray 'wind_quality_flag' (time: 1, altitude: 10)>
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
Coordinates:
  * time      (time) datetime64[ns] 2018-12-27T01:20:00
  * altitude  (altitude) float64 210.0 245.0 281.0 ... 1.213e+03 1.249e+03
>>> result.wind_quality_flag
<xarray.DataArray 'wind_quality_flag' (time: 2, altitude: 17)>
array([[ 0.,  0.,  0.,  0.,  0.,  0., nan, nan,  0.,  0.,  0.,  0.,  0.,  0.,
         0., nan, nan],
       [ 0.,  0.,  0., nan, nan, nan,  0.,  0., nan, nan, nan, nan,  0.,  0.,
         0.,  0.,  0.]])
Coordinates:
  * altitude  (altitude) float64 210.0 245.0 281.0 ... 1.213e+03 1.249e+03
  * time      (time) datetime64[ns] 2018-12-27T11:30:00 2018-12-27T01:20:00

Problem description

Using xr.concat to combine two datasets along the time axis. Dtype of variable wind_quality_flag changes from int64 to float. I suppose that this behavior has to do with NaN not available in int64 and the Datasets are not completely overlapping in the altitude dimension.

How can this conversion be avoided?

Expected Output

Combined Dataset with original datatype preserved.

Output of xr.show_versions()

>>> xr.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.5.3 (default, Sep 27 2018, 17:25:39)
[GCC 6.3.0 20170516]
python-bits: 64
OS: Linux
OS-release: 4.9.0-8-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: de_DE.UTF-8
libhdf5: 1.10.2
libnetcdf: 4.4.1.1

xarray: 0.11.3
pandas: 0.24.1
numpy: 1.16.1
scipy: None
netCDF4: 1.4.2
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.0.2.1
PseudonetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
cyordereddict: None
dask: None
distributed: None
matplotlib: 3.0.2
cartopy: None
seaborn: None
setuptools: 40.6.2
pip: 18.1
conda: None
pytest: None
IPython: None
sphinx: None

[shoyer]

I suppose that this behavior has to do with NaN not available in int64 and the Datasets are not completely overlapping in the altitude dimension.

This is correct.

Alternatively, you could pre-align your data to have the same coordinate labels. Someone could pretty easily add a fill_value to xarray.align(), but this hasn't been done yet: #2876