R Census Data Wrangling and Mapping

March 15, 2022, 12:00pm to 3:00pm

Trying to register, but not affiliated with the UCB campus? If you are from Berkeley Lab (LBL), UCSF, or CZ Biohub, please register via our partner portals here

If you are from the UCB campus there's no more waitlist! But after registering above, please do fill out the affiliations form if you have not done so at least once before: https://dlab.berkeley.edu/affiliations

Location: Remote via Zoom. Link will be sent on the morning of the event.

Date & Time: This workshop runs from Tuesday, March 15 from 12pm-3pm

Start Time: D-Lab workshops start 10 minutes after the scheduled start time (“Berkeley Time”). We will admit all participants from the waiting room at that time.


Since 1790, the US Census has been THE source of data about American people, providing valuable insights to social scientists and humanists. Mapping these data by census geographies adds more value by allowing researchers to explore spatial trends and outliers. This workshop will introduce three key packages for streamlining census data workflows in R: tigris, tidycensus and tmap. Participants will learn how to download census tabular data for one or more geographic aggregation units or years, download the associated census geographic data and then join these data for analysis and mapping.

Specifically, we will:

  • Describe the primary Census data products
  • Introduce the R tidycensus package for working with Census Data
  • Use that packages to fetch decennial and ACS census data
  • Use those packages to fetch census geographic boundary files
  • Make maps of census data, symbolizing the color of those maps by the data values

Prerequisites: D-Lab R Fundamentals: Parts 1-4 or equivalent knowledge. Basic knowledge of census data and geospatial data will be very helpful.

Workshop materials:https://github.com/dlab-berkeley/Census-Data-in-R

Software Requirements:Installation Instructions for R and RStudio

Feedback: After completing the workshop, please provide us feedback using this form

Questions? Email: dlab-frontdesk@berkeley.edu