Masking a NetCDF file using a shapefile of points with rioxarray

Question

I took the proposed solution from this question (How to mask NetCDF time series data from a shapefile in Python?) and tried to implement it. However, whenever I apply this solution it seems to set all of my values to NaNs and doesn't mask. Anyone know what's going on here? All of the data details below.

#load in precipitation data
data=xr.open_dataset('/Volumes/Ext HDD 1/Python_data/ERA_precip/data/SA_last10yrs_oct1_nov11/adaptor.mars.internal-1605293227.6880476-7726-17-60b7b292-7985-46a5-ac6e-d3ad5469e87a.nc')

I perform some calculations and up with this percent of normal dataarray that only contains latitude and longitude. It looks like this (pon):

Now, I have a shapefile, which is a list of points in southern Brazil. It looks like this and contains about 2500 points (south_bra_shape):

0       POINT (-50.70833 -26.20833)
1       POINT (-50.79167 -26.20833)
2       POINT (-50.79167 -26.12500)
3       POINT (-54.20833 -25.20833)
4       POINT (-50.95833 -26.20833)

Then I try the solution offered by the previous post:

pon.rio.set_spatial_dims(x_dim="longitude", y_dim="latitude", inplace=True)
pon.rio.write_crs("epsg:32663", inplace=True)
south_bra_shape=gpd.read_file('/Users/eli.turaskyriskpulse.com/Documents/shapefiles/brazil/SC_RGDS_PAR_brazil_soybeans/SC_RGDS_PAR_brazil_soybeans.shp',crs="epsg:32663")
clipped=pon.rio.clip(south_bra_shape.geometry.apply(mapping), south_bra_shape.crs, drop=False)

However, here is the result of clipped:

I do not understand what is happening here or what I am doing wrong.

Answer 1

Convex Hull in GeoPandas

Here is what I think you want to do:

clipped = pon.rio.clip(
    [mapping(south_bra_shape.geometry.unary_union.convex_hull)],
    south_bra_shape.crs,
    drop=False,
)

Answer 2

I found a solution that is similar to what I posted in my original question.

#load in the list of points into a GeoDataFrame
south_bra_shape=gpd.read_file('/file/to/path/shapefile.shp')

#set the CRS for the xarray data
pon.rio.write_crs("epsg:32663", inplace=True)

#clip the data
pon.rio.clip(south_bra_shape.geometry.apply(mapping), south_bra_shape.crs)

That's it!