In [1]:
import os
import folium
print(folium.__version__)
GeoPandas is a project to add support for geographic data to pandas objects. (See https://github.com/geopandas/geopandas)
It provides (among other cool things) a GeoDataFrame object that represents a Feature collection.
When you have one, you may be willing to use it on a folium map. Here's the simplest way to do so.
In this example, we'll use the same file as GeoPandas demo ; it's containing the boroughs of New York City.
In [2]:
import geopandas
nybb = os.path.join('data', 'nybb.shp')
boros = geopandas.GeoDataFrame.from_file(nybb)
boros
Out[2]:
To create a map with these features, simply put them in a GeoJson:
In [3]:
m = folium.Map([40.7, -74], zoom_start=10, tiles='cartodbpositron')
folium.GeoJson(boros).add_to(m)
m.save(os.path.join('results', 'geopandas_0.html'))
m
Out[3]:
Quite easy.
Well, you can also take advantage of your GeoDataFrame structure to set the style of the data. For this, just create a column style containing each feature's style in a dictionnary.
In [4]:
boros['style'] = [
{'fillColor': '#ff0000', 'weight': 2, 'color': 'black'},
{'fillColor': '#00ff00', 'weight': 2, 'color': 'black'},
{'fillColor': '#0000ff', 'weight': 2, 'color': 'black'},
{'fillColor': '#ffff00', 'weight': 2, 'color': 'black'},
{'fillColor': '#00ffff', 'weight': 2, 'color': 'black'},
]
boros
Out[4]:
In [5]:
m = folium.Map([40.7, -74], zoom_start=10, tiles='cartodbpositron')
folium.GeoJson(boros).add_to(m)
m.save(os.path.join('results', 'geopandas_1.html'))
m
Out[5]: