de Bici Las Condes a Folium

bikemapper.py

import folium
import pandas as pd

URL = 'https://www.bicilascondes.cl/availability_map/getJsonObject'
COLORS = ['red',  'darkred', 'lightred', 'yellow', 
	  'darkgreen', 'lightgreen', 'green']	# low is bad->red, high is good->green

bike_data = pd.read_json(URL)
bikemap = folium.Map(bike_data[['lat','lon']].mean().tolist(), # data centroid
					 tiles = 'Stamen Terrain', zoom_start = 15)	
for station_id, station_data in bike_data.iterrows():
	station_html = folium.Html('<b>%s</b>' %(pd.DataFrame(station_data).to_html()), 
								script=True)
	station_color = COLORS[int(station_data.bikes/len(COLORS))]       # not quite right
	bikemap.add_child(folium.Marker([station_data.lat,station_data.lon],
					  popup = folium.Popup(station_html),
					  icon=folium.Icon(color=station_color)  
					))
bikemap.save('mapa_blc.html')

COLORS should be from a matplotlib.colormap:
https://matplotlib.org/examples/color/colormaps_reference.html

the map above shows the availability of bikes (slots can be inferred), red is bad, green is good! A lot more than the code above has been used to produce, for instance, the lines showing good neighbours for bad stations.

folium has colormaps!
http://nbviewer.jupyter.org/github/python-visualization/folium/blob/master/examples/Colormaps.ipynb