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Ben Bolstad has completed

Visualizing Geospatial Data in Python

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4 hours
4,250 XP
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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!
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  1. 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.

    Play Chapter Now
    50 xp
    Plotting a scatterplot from longitude and latitude
    50 xp
    Styling a scatterplot
    100 xp
    Extracting longitude and latitude
    100 xp
    Plotting chicken locations
    100 xp
    Geometries and shapefiles
    50 xp
    Creating a GeoDataFrame & examining the geometry
    100 xp
    Plotting shapefile polygons
    100 xp
    Scatterplots over polygons
    50 xp
    50 xp
    Plotting points over polygons - part 1
    100 xp
    Plotting points over polygons - part 2
    100 xp

In the following tracks

Data Visualization


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Greg Wilson
Collaborator's avatar
Adrián Soto
Mary van Valkenburg HeadshotMary van Valkenburg

Data Science Program Manager at Nashville Software School

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