Book Image

Applied Geospatial Data Science with Python

By : David S. Jordan
3 (1)
Book Image

Applied Geospatial Data Science with Python

3 (1)
By: David S. Jordan

Overview of this book

Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python. Throughout this book, you’ll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You’ll learn how to read, process, and manipulate spatial data effectively. With data in hand, you’ll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you’ll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries. By the end of the book, you’ll be able to tackle random data, find meaningful correlations, and make geospatial data models.
Table of Contents (17 chapters)
Part 1:The Essentials of Geospatial Data Science
Free Chapter
Chapter 1: Introducing Geographic Information Systems and Geospatial Data Science
Part 2: Exploratory Spatial Data Analysis
Part 3: Geospatial Modeling Case Studies

Packages for producing production-quality spatial visualizations

In this section, we’ll introduce you to five packages that will enable you to produce spatial visualizations, namely static and interactive maps, which will take your resulting analytical deliverable to the next level. The packages we’ll be discussing are ipyLeaflet, folium, geoplot, geoviews, and datashader.


ipyLeaflet is a Python package that enables you to create interactive mapping widgets within the Jupyter Notebook IDE. At its core, ipyLeaflet is a connection between the Python IDE and the open sourced, JavaScript-based Leaflet visualization package.

To begin exposing you to the power of ipyLeaflet, let’s work through creating an interactive map of the attractions in Washington, DC. First, you’ll need to import a number of modules from ipyleaflet and a handful of other packages, such as GeoPandas, for working with spatial data. To do that, you’ll execute the...