问题
I have Netcdf file loaded in an xarray dataset and I want to make daily climatologies without the leap day that is, without 29th Feb included in it. I'm trying the Dataset.drop method by the syntax is not so intuitive for me. Here is the Dataset
print(ds)
>><xarray.Dataset>
Dimensions: (lat: 1, lev: 1, lon: 720, time: 27133)
Coordinates:
* lon (lon) float32 -180.0 -179.5 -179.0 ... 178.5 179.0 179.5
* lev (lev) float32 1.0
* time (time) datetime64[ns] 2000-01-02T18:00:00 ... 2018-07-30
Dimensions without coordinates: lat
Data variables:
Var1 (time, lev, lon) float32 ...
Var2 (time, lat, lon) float64 ...
Var3 (time, lat, lon) float64 ...
I tried
ds_N_R.drop(['Var1', 'Var2', 'Var3'], time='2000-02-29')
>>TypeError: drop() got an unexpected keyword argument 'time'
##another approach
ds_N_R.sel(time='2000-02-29').drop(['Var1', 'Var2', 'Var3'])
## gives not the result I intended
<xarray.Dataset>
Dimensions: (lev: 1, lon: 720, time: 4)
Coordinates:
* lon (lon) float32 -180.0 -179.5 -179.0 -178.5 ... 178.5 179.0 179.5
* lev (lev) float32 1.0
* time (time) datetime64[ns] 2000-02-29 ... 2000-02-29T18:00:00
Data variables:
*empty*
How do I proceed here? It would be great to know if there is a direct method through which I can calculate daily climatologies considering only 365 days of a year but I would also like to know how to remove data from a particular time step when required.
回答1:
The right way to use drop() here would be:
ds_N_R.drop([np.datetime64('2000-02-29')], dim='time')
But I think this could actually be more cleanly done with an indexing operation, e.g.,
ds_N_R.sel(time=~((ds_N_R.time.dt.month == 2) & (ds_N_R.time.dt.day == 29)))
来源：https://stackoverflow.com/questions/53376113/removing-leap-day-from-leap-years-in-xarray-dataset