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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
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.
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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()

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