Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence

From a bestselling geospatial author and data analyst, a bold framework for accessing the power of Python and integrating insights from emergent datasets into agency around evolving questions about our built environment.

Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Large Language Models are helpful with contextual basic programming but your task is to query the edges of ecology, economics, sustainability, infrastructure, social change, climate change, and the world writ large. The human element is tasked with stewardship of finite resources against exponential demands— perhaps it is why we evolved. In this no nonsense skill building book across a wide array of open source libraries, platforms and tools, let's work toward asking better questions.

This book helps you: Explore geospatial integration with Python Understand the importance of applying spatial relationships in data science Select and apply data layering of both raster and vector graphics Apply location data to leverage spatial analytics Design informative and accurate maps Automate geographic data with Python scripts Explore Python packages for additional functionality Work with atypical data types such as polygons, shape files, and projections Understand the graphical syntax of spatial data science to stimulate curiosity