Introduction to Python

This course will introduce the participants to the nascent field of Geographic Data Science using the industry standard, the Python programming language. We will cover the key steps involved in solving practical problems with spatial data: design, manipulation, exploration, and modelling. These topics will be explored from a “hands-on” perspective using a modern Python stack (e.g. geopandas, seaborn, scikit-learn, PySAL), and examples from real-world spatial and tabular data.

We will start with an overview of the main ways to access and read spatial data formats such as shapefiles or GeoJSON from disparate sources. Then we will move on to techniques to visualise (e.g. choropleths) and summarise your data, including exploratory spatial data analysis techniques. From there we will cover traditional as well as explicitly spatial unsupervised learning (clustering). The course is intended to provide practical support to researchers and practitioners by introducing them to useful strategies to learn more from their spatial data. There will be time for self-directed learning using data from the CDRC data store.
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