b001_09.py

b001_09.py

# -- about 17 seconds --
gdf_commuters_workplace = gpd.GeoDataFrame(df_commuter.copy(), geometry=gpd.points_from_xy(df_commuter.workplace_lng, df_commuter.workplace_lat))

# -- about 120 seconds: points in polygon 
mask_points_in_city = gdf_commuters_workplace.intersects(gdf.geometry.iloc[0])
mask_points_in_london = gdf_commuters_workplace.intersects(gdf.geometry.iloc[1])
num_total_rows = len(gdf_commuters_workplace)
num_rows_in_city = len(mask_points_in_city[mask_points_in_city == True])
num_rows_in_london = len(mask_points_in_london[mask_points_in_london == True])
print(f"Number of rows for offices in the city {num_rows_in_city} ({100 * num_rows_in_city / num_total_rows} %)")
print(f"Number of rows for offices in london {num_rows_in_london} ({100 * num_rows_in_london / num_total_rows} %)")

mask_union = mask_points_in_city | mask_points_in_london
num_rows_in_union = mask_union.sum()
print(f"Number of offices in the union of London and the City {num_rows_in_union} ({100 * num_rows_in_union / num_total_rows} %)")

# Sanity check
assert num_rows_in_union == num_rows_in_city + num_rows_in_london

df_commuter_london_office = df_commuter[mask_union]
df_commuter_london_office.reset_index(inplace=True, drop=True)
try:
    from kepler_config import config_map_3
except ImportError:
    config_map_3 = config

# Use the config_3 in kepler_config.py in the repo to reproduce the same image
map_3 = KeplerGl(data={'london':gdf_epsg.copy(),  "commuters": df_commuter_london_office.copy()}, config=config_map_3, height=800)
display(map_3)