Contents

Geo Overview

Jupyter notebooks provide a natural home for embedded, interactive maps although we can also use embdded code to generate a wide range of static maps too.

A wide range of Python packages exist that support the creation and embedding of interactive maps built from third party mapping services such as OpenStreetMap (OSM).

Packages can also work with tiles served from a personally hosted map tile server.

ipyleaflet

The ipyleaflet package supports the creation of embedded, interactive maps as an ipywidget using the leaflet.js Javascript package.

import ipyleaflet as lflt

m = lflt.Map(center=[52.0250, -0.7084], zoom=14)
m

folium

The folium package supports the creation and embedding of interactive maps using leaflet.js although in this case the embedded map is not wrapped as an ipywidget.

import folium

m = folium.Map(location=[52.0250, -0.7084], zoom_start=14)
m
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Adding Markers

Adding one or more markers to a map is relatively straightforward:

m = folium.Map(location=[52.0250, -0.7084], zoom_start=14, tiles='Stamen Toner')

folium.Marker([52.0250, -0.7084],
              popup='Open University, Walton Hall').add_to(m)
m
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Adding Boundaries

Boundaries represented using a .geojson file can be rendered as an overlayed map layer.

import os
m = folium.Map( location=[52.0250, -0.7084], zoom_start=9 )

#Path to geojson file
mk = os.path.join('boundaries', 'mk.json')

#Add geojson layer to map
folium.GeoJson( mk, name='geojson' ).add_to(m)

m
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Choropleth Maps

We can easily create a choropleth map from a tabular dataset that shares keys with a shapefile.

import pandas as pd

turnout=pd.read_csv('data/iw_turnout.csv')
turnout.head()
Electoral Division Candidate Electorate NoOnRoll turnout
0 Arreton and Newchurch Total votes cast 1286 3070 0.418893
1 Binstead and Fishbourne Total votes cast 1160 2766 0.419378
2 Brading, St Helens and Bembridge Total votes cast 4640 6189 0.749717
3 Carisbrooke Total votes cast 883 2632 0.335486
4 Central Wight Total votes cast 1339 2904 0.461088

Various tools exist that allow us to read and process geojson files in a convenient way.

For example, use fiona to read in a geojson file, parse the extent of the shape file and find the mid-point:

import fiona

with fiona.open('boundaries/iw.json') as fi:
    latlong = [(fi.bounds[1]+fi.bounds[3])/2,
               (fi.bounds[0]+fi.bounds[2])/2]

Center the map on that mid-point and add a choropleth layer:

m = folium.Map(location=latlong )

folium.Choropleth(
   geo_data='boundaries/iw.json',
    data=turnout,
    columns=['Electoral Division', 'turnout'],
    key_on='feature.properties.WD13NM',
    fill_color='PuBuGn', fill_opacity=0.7
).add_to(m)

m
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