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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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4 Stunden14 Videos51 Übungen19.662 LernendeTrophyLeistungsnachweis

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Kursbeschreibung

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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In den folgenden Tracks

Datenvisualisierung mit Python

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  1. 1

    Building 2-Layer Maps : Combining Polygons and Scatterplots

    Kostenlos

    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.

    Kapitel Jetzt Abspielen
    Introduction
    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
    Geometry
    50 xp
    Plotting points over polygons - part 1
    100 xp
    Plotting points over polygons - part 2
    100 xp
  2. 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.

    Kapitel Jetzt Abspielen
    GeoJSON and plotting with geopandas
    50 xp
    Working with GeoJSON
    50 xp
    Colormaps
    100 xp
    Map Nashville neighborhoods
    100 xp
    Projections and coordinate reference systems
    50 xp
    Changing coordinate reference systems
    100 xp
    Construct a GeoDataFrame from a DataFrame
    100 xp
    Spatial joins
    50 xp
    Spatial join practice
    100 xp
    Finding the neighborhood with the most public art
    100 xp
    Aggregating points within polygons
    100 xp
    Plotting the Urban Residents neighborhood and art
    100 xp
  3. 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.

    Kapitel Jetzt Abspielen
    GeoSeries attributes and methods I
    50 xp
    Find the area of the Urban Residents neighborhood
    100 xp
    GeoSeries attributes and methods II
    50 xp
    The center of the Urban Residents neighborhood
    100 xp
    Prepare to calculate distances
    100 xp
    Art distances from neighborhood center
    100 xp
    Street maps with folium
    50 xp
    Create a folium location from the urban centroid
    100 xp
    Create a folium map of downtown Nashville
    100 xp
    Folium street map of the downtown neighborhood
    100 xp
    Creating markers and popups in folium
    50 xp
    Adding markers for the public art
    100 xp
    Troubleshooting data issues
    100 xp
    A map of downtown art
    100 xp
  4. 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.

    Kapitel Jetzt Abspielen
    What is a choropleth?
    50 xp
    Finding counts from a spatial join
    100 xp
    Council district areas and permit counts
    100 xp
    Calculating a normalized metric
    100 xp
    Choropleths with geopandas
    50 xp
    Geopandas choropleths
    100 xp
    Area in km squared, geometry in decimal degrees
    100 xp
    Spatially joining and getting counts
    100 xp
    Building a polished Geopandas choropleth
    100 xp
    Choropleths with folium
    50 xp
    Folium choropleth
    100 xp
    Folium choropleth with markers and popups
    100 xp
    Closing thoughts
    50 xp
Für Unternehmen

Trainierst du 2 oder mehr?

Verschaffen Sie Ihrem Team Zugriff auf die vollständige DataCamp-Plattform, einschließlich aller Funktionen.

In den folgenden Tracks

Datenvisualisierung mit Python

Gehe zu Track

Datensätze

Building permits issued in Nashville in 2017Council district GIS dataNashville neighborhoods GIS dataPublic artworks in NashvilleSchool district GIS dataSchools in Nashville

Mitwirkende

Collaborator's avatar
Greg Wilson
Collaborator's avatar
Adrián Soto

Voraussetzungen

Introduction to Data Visualization with MatplotlibData Manipulation with pandas
Mary van Valkenburg HeadshotMary van Valkenburg

Data Science Program Manager at Nashville Software School

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