A package to aggregate gridded data in :pyxarray to polygons in :pygeopandas using area-weighting from the relative area overlaps between pixels and polygons.
The simplest code run, involving raster data in an :pyxarray :pyDataset ds and polygons in a :pygeopandas :pyGeoDataFrame gpd, is:
import xagg as xa
# Get overlap between pixels and polygons
weightmap = xa.pixel_overlaps(ds,gdf)
# Aggregate data in [ds] onto polygons
aggregated = xa.aggregate(ds,weightmap):pyaggregated can then be turned into an :pyxarray :pyDataset, a :pygeopandas :pyGeoDataFrame, or directly exported to a CSV (for use in, e.g., STATA), NetCDF, or Shapefile.
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