Visualizing Geospatial Data in Python
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.
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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!
- 1
Building 2-layer maps : combining polygons and scatterplots
FreeIn 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. - 2
Creating and joining GeoDataFrames
You'll work with GeoJSON to create polygonal plots, learn about projections and coordinate reference systems, and get practice spatially joining data in this chapter. - 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. - 4
Creating a choropleth building permit density in Nashville
In this chapter, you will learn about a special map called a choropleth. Then you will learn and practice building choropleths using two different packages: geopandas and folium.
In the following tracks
Data Visualization
Greg Wilson
Adrián Soto
Mary van Valkenburg
Data Science Program Manager at Nashville Software School
Mary van Valkenburg is a lead instructor and program manager for the Analytics and Data Science Program at Nashville Software School, a non-profit that helps adults develop skills and launch careers in software development and data science. She holds a Masters in Data Science from Lipscomb University. Mary enjoys the thrill of discovery that comes with exploring and analyzing data, and as an instructor seeks to facilitate that sense of discovery by others.
What do other learners have to say?
“I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.”
Devon Edwards Joseph
Lloyds Banking Group
“DataCamp is the top resource I recommend for learning data science.”
Louis Maiden
Harvard Business School
“DataCamp is by far my favorite website to learn from.”
Ronald Bowers
Decision Science Analytics, USAA
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