1. Apprendre
    2. /
  2. Cours
    3. /
  3. Visualizing Geospatial Data in Python
  • 1

    Building 2-Layer Maps : Combining Polygons and Scatterplots

    Gratuit

    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.

  • 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.

Initializing

Exercice

Spatially joining and getting counts

You will continue preparing your dataset for plotting a geopandas choropleth by creating a GeoDataFrame of the building permits spatially joined to the council districts. After that, you will be able to get counts of the building permits issued in each council district.

Instructions

100 XP
  • Create permits_geo from permits, the council_districts.crs, and the geometry in permits.
  • Spatially join permits_geo and the council_districts to get building permits within each council district. Call this permits_by_district.
  • Count permits in each district, permit_counts, by chaining groupby() and size() methods.
  • Create counts_df from permit_counts. Reset the index, and name the columns district and bldg_permits.