Clipped heatmapsΒΆ

../_images/nyc-collision-factors.png

Python source code: [download source: nyc-collision-factors.py]

import geoplot.crs as gcrs
import geoplot as gplt
import pandas as pd
import geopandas as gpd
from shapely.geometry import Point
import matplotlib.pyplot as plt
import shapely


# Load the data.
boroughs = gpd.read_file("../../data/nyc_boroughs/boroughs.geojson", driver='GeoJSON')
collisions = pd.read_csv("../../data/nyc_collisions/NYPD_Motor_Vehicle_Collisions_2016.csv", index_col=0)

def pointify(srs):
    lat, long = srs['LATITUDE'], srs['LONGITUDE']
    if pd.isnull(lat) or pd.isnull(long):
        return shapely.geometry.Point(0, 0)
    else:
        return shapely.geometry.Point(long, lat)

collisions = gpd.GeoDataFrame(collisions.head(100000), geometry=collisions.head(100000).apply(pointify, axis='columns'))
collisions = collisions[collisions.geometry.map(lambda srs: not (srs.x == 0))]


# Plot the data.
fig = plt.figure(figsize=(10,5))

ax1 = plt.subplot(121, projection=gcrs.AlbersEqualArea(central_latitude=40.7128, central_longitude=-74.0059))

gplt.kdeplot(collisions[collisions["CONTRIBUTING FACTOR VEHICLE 1"] == 'Failure to Yield Right-of-Way'],
             projection=gcrs.AlbersEqualArea(), shade=True, clip=boroughs.geometry, shade_lowest=False, ax=ax1)
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax1)
plt.title("Failure to Yield Right-of-Way Crashes, 2016")

ax2 = plt.subplot(122, projection=gcrs.AlbersEqualArea(central_latitude=40.7128, central_longitude=-74.0059))

gplt.kdeplot(collisions[collisions["CONTRIBUTING FACTOR VEHICLE 1"] == 'Lost Consciousness'],
             projection=gcrs.AlbersEqualArea(), shade=True, clip=boroughs.geometry, shade_lowest=False, ax=ax2)
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax2)
plt.title("Loss of Consciousness Crashes, 2016")


plt.savefig("nyc-collision-factors.png", bbox_inches='tight', pad_inches=0.1)