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Visualizing Geospatial Data in Python

IntermediateSkill Level
4.7+
311 reviews
Updated 06/2025
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.
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PythonData Visualization4 hr14 videos51 Exercises4,250 XP22,750Statement of Accomplishment

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Course Description

One of the most important tasks of a data scientist is to understand the relationships between their data's physical location and their geographical context. In this course you'll be learning to make attractive visualizations of geospatial data with the GeoPandas package. You will learn to spatially join datasets, linking data to context. Finally you will learn to overlay geospatial data to maps to add even more spatial cues to your work. You will use several datasets from the City of Nashville's open data portal to find out where the chickens are in Nashville, which neighborhood has the most public art, and more!

Prerequisites

Introduction to Data Visualization with MatplotlibData Manipulation with pandas
1

Building 2-Layer Maps : Combining Polygons and Scatterplots

In this chapter, you will learn how to create a two-layer map by first plotting regions from a shapefile and then plotting location points as a scatterplot.
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2

Creating and Joining GeoDataFrames

3

GeoSeries and Folium

First you will learn to get information about the geometries in your data with three different GeoSeries attributes and methods. Then you will learn to create a street map layer using folium.
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4

Creating a Choropleth Building Permit Density in Nashville

Visualizing Geospatial Data in Python
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FAQs

What Python library is the focus of this geospatial visualization course?

GeoPandas is the primary library. You will use it alongside pandas and Matplotlib to create attractive visualizations of geospatial data including maps and spatial overlays.

What datasets from Nashville are used in this course?

You will use datasets from Nashville's open data portal to map chicken locations, identify which neighborhoods have the most public art, and explore other city data.

Does this course teach spatial joins?

Yes. You will learn to spatially join datasets, linking your data to its geographical context, and practice creating and joining GeoDataFrames from GeoJSON and shapefiles.

What types of maps will I create in this course?

You will create two-layer maps combining polygon regions from shapefiles with scatterplot location points, and overlay geospatial data onto maps to add spatial context.

Will I learn about coordinate reference systems and projections?

Yes. The second chapter covers projections and coordinate reference systems, which are essential for ensuring your geospatial data displays accurately on maps.

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