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

McClain, Bonny P.

Softcover

ISBN 10: 109810479X ISBN 13: 9781098104795

Publisher: O'Reilly Media, 2022

Synopsis

In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.

Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python.

This book helps you:

• 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

About this title

About the Author

Bonny is a geospatial analyst, self described human geographer, social anthropologist and sought after speaker on topics including the built infrastructure, climate change, sustainability, and what we should be learning about the integration of ecology, economics, and the limits of our planetary boundary.
 
Bonny brings audiences along while exploring geographic properties that capture complex interactions, dynamic shifts in ecosystem balance and how activities influence eco-geomorphic conceptual frameworks across a wide variety of environments.
 
The ability to apply advanced spatial data analytics, including data engineering and geo-enrichment, to social demographic discussions targets judgments about structural determinants, racial equity, and elements of intersectionality to illuminate the confluence of metrics contributing to the chaos in our current world order.


Bonny is the author of the books Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence (publisher, O'Reilly Media) and Geospatial Analysis with SQL: A hands on guide to performing geospatial analysis by unlocking the syntax of spatial SQL published by Packt Press. Current projects include a new book in progress with Locate Press, Geospatial Data Science & the Art of Storytelling.

From the Back Cover

Learning how too unpack the syntax of Python opens a door to access a wide variety of data packages.


The ability to quickly create a jupyter notebook, run Python in the console, or an integrated development platform allows expansion of your data science perspective and skill set to include earth observation and location intelligence.

From the Inside Flap

Tobler's first law of geography states, "Everything is related to everything else, but near things are more related than distant things." But if you look at Tobler's second law, "Phenomena external to a geographic area of interest affect what goes on inside it," you can see why a geographer and data analyst brings the science of location into data stories and large-scale research projects.


With this practical book, geospatial professionals, data scientists, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis.


Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. This book is for curious, eager professionals or citizen scientists hoping to explore geospatial integration with Python.
You will learn how to:

• Apply spatial relationships to data questions
• Work with both raster and vector graphics
• Design informative maps using open source tools and publicly available datasets
• Automate geographic data with Python scripts
• Understand the graphical syntax of spatial data science to
  stimulate curiosity

Edition details

• Publisher: O'Reilly Media
• Publication date: 2022
• Language: English
• ISBN 10: 109810479X
• ISBN 13: 9781098104795
• Binding: Paperback
• Edition number: 1
• Number of pages: 279