Overview¶
In this lesson, we will continue to learn how to manipulate and analyse spatial data using Geopandas, Shapely and other relevant Python packages. First, we will learn how to geocode addresses, i.e. convert addresses into coodrinates. Next, we will focus on spatial queries and we will learn how to join data based on spatial information. Finally, we will conduct nearest neighbor analysis between a set of points.
Learning goals¶
After this weeks’ lesson you should be able to:
Geocode data, i.e. transform addresses into coordinates
Conduct point-in-polygon queries
Make spatial joins
Conduct nearest neighbour analysis (finding the closest point).
Sources¶
Lesson materials are partly based on documentation of Geopandas, geopy, Pandas, Shapely, and Lawhead, J. (2013), Chapters I and V.
Lesson videos¶
Lesson 3.1 - Geocoding
Vuokko Heikinheimo, University of Helsinki @ AutoGIS channel on Youtube.
Lesson 3.2 - Point in polygon, spatial join, nearest neighbor analysis
Vuokko Heikinheimo, University of Helsinki @ AutoGIS channel on Youtube.
Lesson 3.3 - Intro to exercise 3
Vuokko Heikinheimo, University of Helsinki @ AutoGIS channel on Youtube.