Geocomputation with Python - Dorman, Michael; Graser, Anita; Nowosad, Jakub; - Prospero Internet Bookshop

 
Product details:

ISBN13:9781032460659
ISBN10:1032460652
Binding:Paperback
No. of pages:344 pages
Size:234x156 mm
Language:English
Illustrations: 13 Illustrations, black & white; 133 Illustrations, color; 13 Line drawings, black & white; 133 Line drawings, color; 21 Tables, black & white
700
Category:

Geocomputation with Python

 
Edition number: 1
Publisher: Chapman and Hall
Date of Publication:
 
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GBP 55.99
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Short description:

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as many examples covering a range of GIS operations.

Long description:

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.


Key features:



  • Showcases the integration of vector and raster datasets operations.

  • Provides explanation of each line of code in the book to minimize surprises.

  • Includes example datasets and meaningful operations to illustrate the applied nature of geographic research.


Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.


The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.

Table of Contents:

Preface  1. Geographic data in Python  2. Attribute data operations  3. Spatial data operations  4. Geometry operations  5. Raster-vector interactions  6. Reprojecting geographic data  7. Geographic data I/O  8. Making maps with Python  References