I want to replace values in a variable in an xarray dataset with None. I tried this approach but it did not work:
da[da['var'] == -9999.]['var'] = None
I get this error: *** TypeError: unhashable type: 'numpy.ndarray'
Is there something like numpy replace that I could use here? da
is xarray dataset. here is what da
looks like:
<xarray.Dataset>
Dimensions: (band: 1, time: 3, x: 4258, y: 2334)
Coordinates:
* band (band) int32 1
* y (y) float64 4.406e+06 4.406e+06 4.406e+06 4.406e+06 4.406e+06 ...
* x (x) float64 1.125e+05 1.126e+05 1.127e+05 1.128e+05 1.129e+05 ...
* time (time) datetime64[ns] 2005-12-31 2006-12-31 2007-12-31
Data variables:
var (time, band, y, x) float32 dask.array<shape=(3, 1, 2334, 4258), chunksize=(1, 1, 2334, 4258)>
Here is what da.var looks like:
<xarray.DataArray 'var' (time: 3, band: 1, y: 2334, x: 4258)>
dask.array<shape=(3, 1, 2334, 4258), dtype=float32, chunksize=(1, 1, 2334, 4258)>
Coordinates:
* band (band) int32 1
* y (y) float64 4.406e+06 4.406e+06 4.406e+06 4.406e+06 4.406e+06 ...
* x (x) float64 1.125e+05 1.126e+05 1.127e+05 1.128e+05 1.129e+05 ...
* time (time) datetime64[ns] 2005-12-31 2006-12-31 2007-12-31
Attributes:
transform: (90.0, 0.0, 112500.0, 0.0, -90.0, 4406400.0, 0.0, 0.0, 1.0)
crs: +ellps=GRS80 +no_defs +proj=utm +towgs84=0,0,0,0,0,0,0 +unit...
res: (90.0, 90.0)
is_tiled: 1
nodatavals: (-9999.0,)
The standard way to do this is using where
: http://xarray.pydata.org/en/latest/indexing.html#masking-with-where
# Note that I'm going to use `ds` instead of the OP's `da`
# replace all values equal to -9999 with np.nan
ds_masked = ds.where(ds['var'] != -9999.)
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