Analyzing Us Census Data: Methods, Maps, and Models in R

Census data are widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions. Until recently, projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare, map, and present data products. This book introduces readers to tools in the R programming language for accessing and analyzing Census data, helping analysts manage these types of projects in a single computing environment.

Chapters in this book cover the following key topics:

- Rapidly acquiring data from the decennial US Census and American Community Survey using R, then analyzing these datasets using tidyverse tools;

- Visualizing US Census data with a wide range of methods including charts in ggplot2 as well as both static and interactive maps;

- Using R as a geographic information system (GIS) to manage, analyze, and model spatial demographic data from the US Census;

- Working with and modeling individual-level microdata from the American Community Survey's PUMS datasets;

- Applying these tools and workflows to the analysis of historical Census data, other US government datasets, and international Census data from countries like Canada, Brazil, Kenya, and Mexico.

Kyle Walker is an associate professor of geography at Texas Christian University, director of TCU's Center for Urban Studies, and a spatial data science consultant. His research focuses on demographic trends in the United States, demographic data visualization, and software tools for open spatial data science. He is the lead author of a number of R packages including tigris, tidycensus, and mapboxapi.