produce tables from xlsx data dictionary
process_datadict(path, quiet = TRUE, simplify_names = TRUE)character(1) path to xlsx file with data dictionary in several sheets
logical(1) if TRUE (default) suppress messages about column names from read_xlsx
logical(1) if TRUE (default) remove inessential elements of sheet names
list of data.frames
Original xlsx file retrieved from https://data.cdc.gov/api/views/unsk-b7fc/files/bfb13090-4148-4f48-9d5a-e1d1c2fb93b3?download=true&filename=DataDictionary_v36_12082022.xlsx in early 2023.
pa = system.file("cdc/VACCDataDictionary_v36_12082022.xlsx", package="teachCovidData")
pd = process_datadict(pa)
names(pd)
#> [1] "0. Notes" "1. Vaccinations US Jurisdiction"
#> [3] "2. Vaccinations US Trends" "3. Vaccinations US Demograp"
#> [5] "4. Age Sex Trends" "5. Vaccinations US County"
#> [7] "6. CaseTrends AgeGp" "7. Booster Dose Eligibility"
#> [9] "8. Primary and Booster Chart" "9. Jurisdiction Abbreviations"
head(pd[[1]])
#> CDC COVID-19 Vaccine Administration and Distribution data
#> 1 Recent as of 11/17/2022 @ 8:00 AM ET
#> 2 Historical data available for download:
#> 3 COVID-19 Vaccinations in the United States, Jurisdiction
#> 4 COVID-19 Vaccination Trends in the United States, National and Jurisdictional
#> 5 COVID-19 Vaccination Age and Sex Trends in the United States, National and Jurisdictional
#> 6 COVID-19 Vaccinations in the United States, County level
#> ...2 ...3
#> 1 <NA> <NA>
#> 2 <NA> Associated CDC COVID Data Tracker Site:
#> 3 → Vaccinations in the United States
#> 4 → Vaccination Trends
#> 5 → Vaccination Demographic Trends
#> 6 → Vaccinations by County