Lesson 1. Customize your Maps in Python using Matplotlib: GIS in Python

Customize Plots of Spatial Vector Data in Python - Scientists guide to plotting data in python textbook course module

Welcome to the first lesson in the Customize Plots of Spatial Vector Data in Python module. When making maps, you often want to create legends, customize colors, adjust zoom levels, or even make interactive maps. Learn how to customize maps created using vector data in Python with matplotlib, geopandas, and folium.

Chapter Three - Customize Vector Plots

In this chapter, you will learn how to create and customize vector plots in Python using geopandas, matplotlib, and folium.

Learning Objectives

After completing this chapter, you will be able to:

  • Create a map containing multiple vector datasets, colored by unique attributes in Python.
  • Add a custom legend to a map in Python with unique colors.
  • Visually “clip” or zoom in to a particular spatial extent in a plot.
  • Create interactive plots of vector data using folium in Python and Jupyter Notebook.

What You Need

You need Python and Jupyer Notebook to complete this chapter. You should also have an earth-analytics directory setup on your computer with a data subdirectory within it. You should have completed the lesson on Setting Up the Earth Analytics Python Conda Environment..

You will need a computer with internet access to complete this lesson and the spatial-vector-lidar dataset.

Download Spatial Lidar Teaching Data Subset data

or using the earthpy package: et.data.get_data("spatial-vector-lidar")

Leave a Comment