The goal of ppmf is to convert Census Privacy Protected Microdata Files into somewhat wider data aggregated to a geographic level.
You can install the development version from GitHub with:
# install.packages("devtools") devtools::install_github("christopherkenny/ppmf")
Load the package:
Download and read data with:
path <- download_ppmf(dsn = 'filename.csv', dir = 'some/directory', version = '19') al <- read_ppmf(state = 'AL', path = path)
Version ‘19’ reflects the 19.61 finalized parameters used again for the 2020 Census.
For future use, I recommend storing the path to the data for future sessions using:
Then the path can be recovered with:
path19 <- Sys.getenv('ppmf19')
Once you’ve read in what you want, you can aggregate it to the right level:
And aggregated data can use the GEOID to merge with shapefiles:
For users with the newest package version, there is an added dependency on
censable, which allows for an easier workflow. If you’ve used the
add_pmmf*_path() workflow suggested, you don’t even need to supply the paths!
This will not just read the
ppmf data, it will merge it with 2010 Census populations (by major race/ethnicity grouping) and add the corresponding geometries.
al <- read_merge_ppmf('AL', level = 'block', versions = '19')