09-03, 09:00–10:30 (UTC), Track4 (Chillida)
This tutorial is an introduction to geospatial data analysis, with a focus on tabular vector data using GeoPandas. It will show how GeoPandas and related libraries can improve your GIS workflow and fit nicely in the traditional PyData stack.
This tutorial is an introduction to geospatial data analysis in Python, with a focus on tabular vector data using GeoPandas. The content focuses on introducing the participants to the different libraries to work with geospatial data and will cover munging geo-data and exploring relations over space. This includes importing data in different formats (e.g. shapefile, GeoJSON), visualizing, combining and tidying them up for analysis, and will use libraries such as pandas, geopandas, shapely, pyproj, matplotlib, cartopy, ... The tutorial will cover the following topics, each of them using Jupyter notebooks and hands-on exercises with real-world data:
1. Introduction to vector data and GeoPandas
2. Visualizing geospatial data
3. Spatial relationships and operations
4. Spatial joins and overlays
Materials of previous versions of this tutorial: https://github.com/jorisvandenbossche/geopandas-tutorial
Introduction to geospatial data analysis with GeoPandas and the PyData stack
Python Skill Level –basic
Domain Expertise –none
Domains –none of the above
I am a core contributor to Pandas and maintainer of GeoPandas. I have given several tutorials at international conferences and a course on python for data analysis for PhD students at Ghent University. I did a PhD at Ghent University and VITO in air quality research, worked at the Paris-Saclay Center for Data Science, and, currently I am a freelance software developer and teacher.