Regridding coordinates with Python-Xarray

Question

I've a NetCDF file in which the variables are stored in 0 to 360-degrees longitude. I would like to convert it to -180 to 180 degrees. This should be a rather straightforward task but for some reason I can't seem to make some of the examples given in the tutorial work out.

ds = xr.open_dataset(file_)   
>ds
<xarray.Dataset>
Dimensions:  (lev: 1, lon: 720, time: 1460)
Coordinates:
* lon      (lon) float64 0.0 0.5 1.0 1.5 2.0 2.5 ... -2.5 -2.0 -1.5 -1.0 -0.5
* lev      (lev) float32 1.0
* time     (time) datetime64[ns] 2001-01-01 ... 2001-12-31T18:00:00
Data variables:
 V        (time, lev, lon) float32 13.281297 11.417505 ... -19.312767

I try using the help of Dataset.assign_coord

ds.V.assign_coords(lon=((ds.V.lon + 180) % 360 - 180)) 
#gives me a new array with lon -180 to 180
ds['V'] = ds.V.assign_coords(lon=((ds.V.lon + 180) % 360 - 180))
# didn't modify the V for some reason?

So, assign_coords worked but setting the variable back to Dataset doesn't work. After many tries, I figured to directly modify the coordinates "lon" because they're linked to the Datavariable "V" via dictionary.

ds.coords['lon'] = (ds.coords['lon'] + 180) % 360 - 180
#solves the problem!

Second Problem I encountered is in sorting my data variable according to the above-modified longitudes. I tried

 ds['V'] = ds.V.sortby(ds.lon)
 >ds.V 

 # the array is not sorted according to -180 to 180 values

But when I sort the dataset and assign it, it works.

ds = ds.sortby(ds.lon) # now my dataset is sorted to -180 to 180 degrees lon

It would be very helpful for my understanding of xarrays if someone can point out why my first approach for both problems are not working?

Answer 1

I apologise for the one-liner but this is exactly how I have solved this issue: d = d.assign_coords(longitude=(((d.longitude + 180) % 360) - 180)).sortby('longitude') you should work at Dataset level and not at DataArray.