Handling GPS Data with Python

Explore the intricacies of handling GPS data with Python in this comprehensive conference talk from EuroPython 2016. Dive into various libraries for reading and writing GPS tracks in the GPS Exchange Format, and learn how to add missing elevation information. Discover techniques for visualizing tracks on OpenStreetMap data using interactive plots in Jupyter notebooks. Gain insights into common GPS algorithms such as Douglas-Peucker and Kalman filters, with clear explanations of their concepts and implementations. Follow along as the speaker demonstrates practical examples using Jupyter notebooks, making it easier to experiment and learn. Whether you're new to working with GPS data in Python or looking to expand your knowledge, this 42-minute talk provides valuable tools and techniques to enhance your geospatial data processing skills.