Introduction to Geospatial Data Analysis with Python

This tutorial is an introduction to geospatial data analysis in Python, with a focus on tabular vector data. It is the first part in a series of two tutorials; this part 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`, `PySAL`, or `rasterio`. The second part will built upon this and focus on more more advanced geographic data science and statistical methods to gain insight from the data. No previous experience with those geospatial python libraries is needed, but basic familiarity with geospatial data and concepts (shapefiles, vector vs raster data) and pandas will be helpful.

Serge  ReySpeaker: Serge Rey, University of California, Riverside
 Speaker: Dani Arribas-Bel, University of Liverpool
 Speaker: Joris Van den Bossche, Université Paris-Saclay Center for Data Science
 Speaker: Levi Wolf, University of Bristol