#!/usr/bin/env python
# -*- coding: utf-8 -*-
import folium
import pandas as pd

# define the polygons
states_geojson = r'us-states.json'

# statistic data to connect to our polygons
state_unemployment = r'../www/html/US_Unemployment_Oct2012.csv'

# read the csv statistic data
state_data = pd.read_csv(state_unemployment)

# Let Folium determine the scale
map = folium.Map(location=[48, -102], zoom_start=3, tiles="Stamen Toner")

# create the leaflet map settings
map.geo_json(geo_path=states_geojson, data=state_data,
             columns=['State', 'Unemployment'],
             threshold_scale=[5, 6, 7, 8, 9, 10],
             key_on='feature.id',
             fill_color='YlGn', fill_opacity=0.7, line_opacity=0.2,
             legend_name='Unemployment Rate (%)')

# output the final map file
map.create_map(path='../www/html/ch10-01_folium_map.html')
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import folium
import pandas as pd

# define the polygons
states_geojson = r'us-states.json'

# statistic data to connect to our polygons
state_unemployment = r'../www/html/US_Unemployment_Oct2012.csv'

# read the csv statistic data
state_data = pd.read_csv(state_unemployment)

# Let Folium determine the scale
map = folium.Map(location=[48, -102], zoom_start=3, tiles="Stamen Toner")

# create the leaflet map settings
map.geo_json(geo_path=states_geojson, data=state_data,
             columns=['State', 'Unemployment'],
             threshold_scale=[5, 6, 7, 8, 9, 10],
             key_on='feature.id',
             fill_color='YlGn', fill_opacity=0.7, line_opacity=0.2,
             legend_name='Unemployment Rate (%)')

# output the final map file
map.create_map(path='../www/html/ch10-01_folium_map.html')
#!/usr/bin/env python # -*- coding: utf-8 -*- # define the polygons # statistic data to connect to our polygons # read the csv statistic data # Let Folium determine the scale # create the leaflet map settings # output the final map file