Analyzing US Census Data in R

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

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4 Hours17 Videos59 Exercises3,330 Learners
5050 XP

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Course Description

Analysts across industries rely on data from the United States Census Bureau in their work. In this course, students will learn how to work with Census tabular and spatial data in the R environment. The course focuses on the tidycensus package for acquiring data from the decennial US Census and American Community survey in a tidyverse-friendly format, and the tigris package for accessing Census geographic data within R. By the end of this course, students will be able to rapidly visualize and explore demographic data from the Census Bureau using ggplot2 and other tidyverse tools, and make maps of Census demographic data with only a few lines of R code.

  1. 1

    Census data in R with tidycensus


    In this chapter, students will learn the basics of working with Census data in R with tidycensus. They will acquire data using tidycensus functions, search for data, and make a basic plot.

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    Census data in R: an overview
    50 xp
    Obtain and set your Census API key
    100 xp
    Getting Census data with tidycensus
    100 xp
    Basic tidycensus functionality
    50 xp
    Understanding tidycensus options
    100 xp
    Tidy and wide data in tidycensus
    100 xp
    Searching for data with tidycensus
    50 xp
    Loading variables in tidycensus
    100 xp
    Exploring variables with tidyverse tools
    100 xp
    Visualizing Census data with ggplot2
    50 xp
    Comparing geographies with ggplot2 visualizations
    100 xp
    Customizing ggplot2 visualizations of ACS data
    100 xp


Chester IsmayBecca Robins


Introduction to the TidyverseSpatial Analysis with sf and raster in R
Kyle Walker Headshot

Kyle Walker

Geography professor at TCU and spatial data science consultant

I work as a geography professor at TCU and as a spatial data science consultant. My research focuses on demographic change and migration in US cities and suburbs; demographic data visualization; and tools for open data science. I'm also the author of the tidycensus, tigris, and idbr R packages for working with US Census Bureau data.
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