xarray cannot directly convert an xarray.Dataset into a numpy array

Question

I'm experiencing an error that I cannot seem to resolve when attempting to convert from a Dataset to array when using xarray. I'm encountering this because I'm attempting to add a time dimension to a netcdf file (open netcdf, add a timestamp that is the same across all data, save out netcdf).

import xarray as xr
import pandas as pd

scriptpath = os.path.dirname(os.path.abspath(__file__))

outputfile = scriptpath + '\\20210629_deadgrass.aus.nc'

times= pd.to_datetime(str(yesterday.strftime('%Y%m%d')))
time_da = xr.Dataset({"time": times})

arr = xr.open_dataset(outputfile)
ds = arr.to_array()
dst = ds.expand_dims(time=time_da) #errors here

The error I'm receiving is

Exception has occurred: TypeError
cannot directly convert an xarray.Dataset into a numpy array. Instead, create an xarray.DataArray first, either with indexing on the Dataset or by invoking the `to_array()` method.
  File "Z:\UpdateAussieGRASS.py", line 101, in <module>
    dst = ds.expand_dims(time=time_da)

I can't seem to work out what I'm doing wrong with to_array() in the second last line. Examples of to_array() are here. Autogenerated documentation is here.

Kraigolas · Accepted Answer · 2021-06-30 02:50:33Z

3

ds is already an xarray.DataArray. The error occurs on this line:

dst = ds.expand_dims(time=time_da) #errors here

Because while ds is a DataArray, time_da is not. This should work:

dst = ds.expand_dims(time=time_da.to_array())

answered Jun 30, 2021 at 2:50

Kraigolas

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2 Comments

anakaine Over a year ago

Thank you. So, I've moved on to a different problem with that line using your modification.

Exception has occurred: ValueError at least one array or dtype is required   File "Z:\UpdateAussieGRASS.py", line 104, in <module>     dst = ds.expand_dims(time=time_da.to_array())

. Shouldn't an array be present since we just did a to_array?

denis Over a year ago

@anakaine, is that still an error ? @Kraigolas, is there doc on what to_array actually does / how it works / pitfalls (a soft question) ? Thanks

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