Over time, Python has become the programming language of choice for spatial analysis, resulting in many packages that read, convert, analyze, and visualize spatial data. With so many packages available, it made sense to create a reference book for students and experienced professionals containing essential geospatial Python libraries for Python 3.
This book also comes at an exciting moment: new technology is transforming how people work with geospatial data – IoT, machine learning, and data science are areas where geospatial data is used constantly. This explains the inclusion of new Python libraries, such as CARTOframes and MapboxGL, and Jupyter is included as well, to explore these new trends. At the same time, web and cloud-based ...
