Python is an extremely popular general-purpose programming language. It is used in a wide range of settings and for various purposes, including for spatial data processing and analysis. The aim of this tutorial is to give an introduction to methods of working with spatial data using Python. The tutorial was split into two parts, introducing two central Python packages: geopandas---For working with vector layers rasterio---For working with rasters The tutorial demonstrated typical basic workflows of processing spatial data: data input, processing, geo-computation, and exporting of the results. We used realistic datasets, such as GTFS public transport data and remote sensing products. By the end of the tutorial, the participants were able to: Import spatial data from files Subset and process the data Graphically display the data Perform spatial calculations (such as calculating distances, or applying raster algebra operators) Export the results To follow along and reproduce the results on your own computer, the prerequisite is to be able to run Python code in a Jupyter Notebook interface, linked to a Python environment with the two above-mentioned packages installed. Instructions were sent in advance.