New Release: Python Maps for Geospatial Visualization
We are thrilled to announce the release of Python Maps: Geospatial Visualization with Python, an exciting new book by Adam Symington, the founder of the PythonMaps project.
Launch price is $5 off for the month of January
About the Book
This book is a comprehensive guide to leveraging Python’s powerful libraries for geospatial data processing, analysis, and visualization. Whether you’re a GIS professional, data analyst, or a Python enthusiast looking to dive into geospatial data, this book provides the tools and techniques you need to succeed.
218 pages, full color$35 $30 launch price for January
What’s Inside?
- Part 1: Getting Started
Learn the basics of GIS and Python’s geospatial libraries, focusing on key data types like points, lines, polygons, and rasters. Start creating simple visualizations to explore your data. - Part 2: Core GIS Concepts
Dive into workflows like raster masking, geospatial joins, and data projections, building a strong foundation for advanced analyses. - Part 3: Advanced Mapping and Visualization
Master techniques like converting rasters to vectors, generating contours, and creating publication-ready maps.
Why This Book?
Authored by an expert with years of experience in open-source geospatial tools, this book offers practical examples and clear explanations that make complex topics accessible. It’s ideal for both beginners and seasoned GIS professionals.
Key Features:
- Comprehensive Coverage of Python’s Geospatial Libraries
Learn how to effectively use libraries like Pandas for data manipulation, GeoPandas for geospatial data integration, and Shapely for geometric operations. Discover how these tools fit into the geospatial analysis pipeline. - Advanced Visualization Techniques
Master data visualization with Matplotlib and Cartopy, creating insightful maps and visualizations. Explore techniques for plotting complex spatial patterns and presenting geospatial data effectively. - Hands-On with Raster and Vector Data
Work with raster data using Rasterio and its extended functionality with RioXarray. Dive into vector data processing with GDAL and explore efficient workflows for spatial data transformation. - Tools for Real-World Applications
Utilize specialized libraries like OverPy for querying OpenStreetMap data, EarthPy for environmental dataset analysis, and Affine for handling affine transformations in spatial data. - Built for Performance and Scalability
Harness the power of NumPy for numerical computations, enabling batch processing of raster data and spatial datasets. Scale your analyses with tools like Dask, ensuring efficient handling of large geospatial datasets.
Get Your Copy Today!
Don’t miss the chance to elevate your geospatial visualization skills with this must-have resource. Order your copy now and join the growing community of mapping enthusiasts!
Available in PDF eBook format from Locate Press. Paperback version is coming soon.
