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I played with assign(), ls(), and mget() to accomplish something that I believe will improve your workflow. First I use ls() to get a list of all environment variables that start with "p": names_poly <- ls(pattern='^p.') I used combn() to find all the unique combinations of polygons combos <- combn(names_poly,2) I looped over combos using get() ...


Depending on whether you want a mean or a spatially weighted mean there are a couple things you can do using the rgeos and raster packages library(rgeos) proj4string(grid) <- proj4string(nuts) # I assumed these were the same projection? First find out which grid cells intersect your NUTS polygons grid_nuts <- gIntersects(grid,nuts,byid = TRUE) ...

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