In the past, working with US Census data in its various forms
required gathering the data from numerous locations and using multiple
software packages for processing, analyzing, and visualization.
Fortunately, recent improvements in census data delivery systems have
made it far easier to acquire the data, greatly reducing the startup
costs for people interested in working with the data. Additionally, new
tools such as the tidycensus library in the R programming
language offer a streamlined environment for interacting with census
data products.
This one-day workshop will provide a hands-on, guided introduction to
working with US Census data using tidycensus in R. The
course will focus on using geographically-referenced demographic and
socioeconomic data from the decennial census and American Community
Survey (ACS). Participants will learn how to acquire data, perform basic
data preprocessing tasks (e.g., subset, query, join), create basic
visualizations (e.g., maps, plots, and graphs), and perform basic
spatial and statistical analysis (e.g., correlation). Some experience
with coding (particularly in R) is strongly recommended.
Participants are required to register for a Census API Key.
Prior to the course, participants are required to have a working version of R (I suggest using RStudio as well). The following packages must be installed to run the code provided:
In RStudio, the package installer can be accessed via the Tools menu. In the GUI-based version of R, the package installer can be accessed via the Packages & Data menu.
This page was last updated on February 26, 2024