Slides and code for Census data workshops given at the University of Michigan in 2023
This repository contains materials for a series of workshops on using Census data in R and Python given for the University of Michigan’s Social Science Data Analysis Network in February of 2023.
Workshop slides are available from the links below:
February 8, 2023: Working with the 2021 American Community Survey with R and tidycensus
February 15, 2023: Mapping and spatial analysis with ACS data in R
February 22, 2023: Spatial Census data and mapping in Python
Users new to R and RStudio should use the pre-built Posit Cloud environment available at https://posit.cloud/content/5377428.
Advanced users familiar with R and RStudio should clone the repository to their computers with the command git clone https://github.com/walkerke/umich-workshop-2023.git. They should then install the following R packages, if not already installed:
pkgs <- c("tidycensus", "tidyverse", "mapview", "plotly", "ggiraph",
"survey", "srvyr", "mapedit", "mapboxapi",
"leafsync", "spdep", "segregation")
install.packages(pkgs)
Experienced users should re-install tidycensus to get the latest updates and ensure that all code used in the workshop will run.
Other packages used will be picked up as dependencies of these packages on installation.
A Census API key is recommended to access the Census API. Participants can sign up for a key at https://api.census.gov/data/key_signup.html (it generally takes just a few minutes).
Users newer to Python should use the hosted Colab notebooks. Access them from these links:
Advanced users can clone the repository and build a conda environment using the environment.yml file in the python folder. Then, they should activate the ssdan-python environment.
conda env create -f environment.yml
conda activate ssdan-python