课程

Visualizing Geospatial Data in Python

中级技能水平

更新时间 2025年6月

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

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PythonData Visualization4 小时14 视频51 练习4,250 经验值22,747成就声明

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课程描述

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!

先决条件

Introduction to Data Visualization with Matplotlib Data 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.

Introduction

50 经验值

Plotting a scatterplot from longitude and latitude

50 经验值

Styling a scatterplot

100 经验值

Extracting longitude and latitude

100 经验值

Plotting chicken locations

100 经验值

Geometries and shapefiles

50 经验值

Creating a GeoDataFrame & examining the geometry

100 经验值

Plotting shapefile polygons

100 经验值

Scatterplots over polygons

50 经验值

50 经验值

Plotting points over polygons - part 1

100 经验值

Plotting points over polygons - part 2

100 经验值

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.

GeoJSON and plotting with geopandas

50 经验值

Working with GeoJSON

50 经验值

100 经验值

Map Nashville neighborhoods

100 经验值

Projections and coordinate reference systems

50 经验值

Changing coordinate reference systems

100 经验值

Construct a GeoDataFrame from a DataFrame

100 经验值

Spatial joins

50 经验值

Spatial join practice

100 经验值

Finding the neighborhood with the most public art

100 经验值

Aggregating points within polygons

100 经验值

Plotting the Urban Residents neighborhood and art

100 经验值

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.

GeoSeries attributes and methods I

50 经验值

Find the area of the Urban Residents neighborhood

100 经验值

GeoSeries attributes and methods II

50 经验值

The center of the Urban Residents neighborhood

100 经验值

Prepare to calculate distances

100 经验值

Art distances from neighborhood center

100 经验值

Street maps with folium

50 经验值

Create a folium location from the urban centroid

100 经验值

Create a folium map of downtown Nashville

100 经验值

Folium street map of the downtown neighborhood

100 经验值

Creating markers and popups in folium

50 经验值

Adding markers for the public art

100 经验值

Troubleshooting data issues

100 经验值

A map of downtown art

100 经验值

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.

What is a choropleth?

50 经验值

Finding counts from a spatial join

100 经验值

Council district areas and permit counts

100 经验值

Calculating a normalized metric

100 经验值

Choropleths with geopandas

50 经验值

Geopandas choropleths

100 经验值

Area in km squared, geometry in decimal degrees

100 经验值

Spatially joining and getting counts

100 经验值

Building a polished Geopandas choropleth

100 经验值

Choropleths with folium

50 经验值

Folium choropleth

100 经验值

Folium choropleth with markers and popups

100 经验值

Closing thoughts

50 经验值

Visualizing Geospatial Data in Python

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