This book equips you with the tools, methods, and theoretical knowledge to tackle modern data science challenges in geographic contexts. In today’s world of abundant and fast-paced data, new opportunities arise to explore the impact of geography on daily life. “Geographic Data Science with Python” introduces a novel approach to analysis, combining geographical and computational reasoning to uncover hidden insights within data.

Key Features:

  • Highlights the robust data science capabilities of Python.
  • Offers replicable examples for readers to adapt, extend, and enhance.
  • Delivers essential knowledge for geographic data scientists.

Unlike other textbooks, this resource presents concepts through a geographic lens, focusing on spatial data, mapping, and spatial statistics. It explores geographic concepts such as clusters and outliers in a unique way.

Targeted at data scientists, GIScientists, and geographers, this book is invaluable for its innovative presentation of geospatial data, methods, tools, and practices in this emerging field.

Authored by Sergio Rey, a leading figure behind the Python package PySAL and a professor at San Diego State University.

For more resources and insights into data science and geography, visit ThinkJava.net.

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Last Update: September 25, 2024

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