I have a shapefile of Phoenix, AZ of size 172mb which I am loading in to the Jupyter notebook. It's a extremely slow process to read the file in. I am running the notebook on locally and the files are stored locally as well. When I read CSV or other data files, it's fairly quick, no issues at all.
%%timeit # Read shape file px_shp = '~/data/map/City_Parcels.shp' geodata = gpd.read_file(px_shp) geodata.dtypes . . . 44.9 s ± 11.5 s per loop (mean ± std. dev. of 7 runs, 1 loop each) # Filter for Phoenix, Mesa, Tempe, Scottsdale and Chandler df_geodata =geodata[geodata['CITY'].isin(['PHOENIX','MESA','SCOTTSDALE','TEMPE'])] df_geodata.plot()