Geopandas spatial join result and dissolve by geometry

Question

For my process I make a spatial join between a polygon grid and points :

join = gpd.sjoin(rotate_grid, gdf, op='contains')

It's look like this.

the result is a grid where each square of my grid is multiplied by as many points that are contained.

My goal is to have only one square and mean of a particular column, NdviM. First I just tried to dissolve square without mean calcul with

dissol = join.dissolve(by='geometry')

But it returns me KeyError: 'geometry'

Somebody knows how to do this ?

Answer 1

Pandas and geopandas allows you to group by attributes and aggregate them:

# we'll make a string column for the wKT geom
gdf['WKT'] = gdf['geometry'].apply(lambda x: str(x))

grouped_gdf = gdf.groupby('WKT').mean().reset_index()
result_gdf  = grouped_gdf[['WKT', 'your_column']]

# then rebuild geometry from WKT
from shapely.wkt import loads

result_gdf['geometry'] = result_gdf['WKT'].apply(lambda x: loads(x))
result_gdf = geopandas.GeoDataFrame(result_gdf)