7.Top State : CA

According to a 2017 study from the U.S. Census Bureau, California state's local governments consist of 57 counties, 482 cities, towns, and villages, and 2,894 special districts

From this data, it has been found that the average duration of the incidents in CA is ~37 minutes.

Summary -

1. Contra Costa FPD is the most engaged agency
2. Highest reported incidents occurred on Sunday
3. After the end of covid-19 lockdown, the number of emergency incidents was higher and peaked at last month - November
4. Most reported emergencies have taken place in Los Angeles
5. Fire Truck Engine 51 (E51) was the most frequent emergency code

Top emergency code descriptions refer to Fire Emergency -

• E51 Fire Engine
• E57 responding to a emergency
• Here is an E53 Fire Truck -

Apart from the medical emergency, top incidents of California includes fire, alarm, and traffic collision

California is susceptible to an impressive array of natural hazards, including earthquakes, fires, flooding, and mudslides.

Here is a good article on this -

4 REASONS CALIFORNIA IS MORE SUSCEPTIBLE TO NATURAL DISASTERS THAN OTHER STATES

Incidents Distribution

Geoplot

Color Coded Cities

Script

ca_city['color']=ca_city['count'].apply(lambda count:"Black" if count>=1500 else
                                         "green" if count>=1200 and count<1500 else
                                         "Orange" if count>=800 and count<1200 else
                                         "darkblue" if count>=500 and count<800 else
                                         "red" if count>=300 and count<500 else
                                         "lightblue" if count>=100 and count<300 else
                                         "brown" if count>=10 and count<100 else
                                         "violet" if count>=5 and count<10 else
                                         "grey")
ca_city['size']=ca_city['count'].apply(lambda count:10 if count>=1500 else
                                         8 if count>=1200 and count<1500 else
                                         7 if count>=800 and count<1200 else
                                         6 if count>=500 and count<800 else
                                         5 if count>=300 and count<500 else
                                         4 if count>=100 and count<300 else
                                         3 if count>=10 and count<100 else
                                         2 if count>=5 and count<10 else
                                         1)

geometry2 = geopandas.points_from_xy(ca_city.longitude, ca_city.latitude)
geo_df2 = geopandas.GeoDataFrame(ca_city[['city','count','longitude', 'latitude']], geometry=geometry2)


url = (
    "https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
)

state_geo = f"{url}/us-states.json"

geoJSON_df = geopandas.read_file(state_geo)
geoJSON_CA = geoJSON_df.loc[geoJSON_df.id == 'CA']


map_CA = folium.Map(location = [38, -115], zoom_start = 6)

# https://stackoverflow.com/a/61129097/11105356
folium.GeoJson(geoJSON_CA.geometry,
               name='California').add_to(map_CA)


for lat,lon,area,color,count,size in zip(ca_city['latitude'],ca_city['longitude'],ca_city['city'],ca_city['color'],ca_city['count'],ca_city['size']):
     folium.CircleMarker([lat, lon],
                            popup=folium.Popup(f"{area}, {count}", parse_html=True),
                            radius=size*5,
                            color='b',
                            fill=True,
                            fill_opacity=0.7,
                            fill_color=color,
                           ).add_to(map_CA)
map_CA

With Heat Map

Script

heat_data = [[point.xy[1][0], point.xy[0][0]] for point in geo_df2.geometry ]

## heat_data
HeatMap(heat_data).add_to(map_CA)

map_CA

With Marker

Script

map_CA_c = folium.Map(location = [38, -115], zoom_start = 6)

# https://stackoverflow.com/a/61129097/11105356
folium.GeoJson(geoJSON_CA.geometry,
               name='California').add_to(map_CA_c)

for i in range(0, len(ca_city)):
  folium.Marker(
    location = [ca_city.iloc[i]['latitude'], ca_city.iloc[i]['longitude']],
    popup = folium.Popup(f"{ca_city.iloc[i]['city']}\n{ca_city.iloc[i]['count']}", parse_html=True),
    icon=folium.features.CustomIcon('https://i.postimg.cc/JhmnMQXj/sos.png', icon_size=(24, 31))
  ).add_to(map_CA_c)

# # heat_data
HeatMap(heat_data).add_to(map_CA_c)

map_CA_c

Insights

1. Southern and central California are two most active region
2. Most of the incidents have taken place in Los Angelos and San Francisco, both are highly active city (PulsePoint is based in the San Francisco Bay Area)