# get census data
# need to define/operationalize topics of interest, such as race, poverty,
# other metrics of evaluation
#' Get Census Variables
#'
#'
#' @param region One of a predefined region (see description)
#' @param variables A vector of at least length 1 containg acceptable categories (see description) and or dataset variables
#' @param year 4 digit numeric year to obtain data from
#' @param output One of \code{tibble} or \code{sf}
#'
ead_census <- function(region, variables, year, class){
# NSE Implementation
# Build API Call
# Get Data
if(race %in% variables){
vars <- append(vars, c("B02001_01", "B02001_02"))
}
# Parse and return data...
if(race %in% variables){
.data <- dplyr::mutate(race = B02001_02E/B02002_01E) %>% dplyr::select(-B02001_01E, -B02001_02E, -B02001_01M, -B02001_02M)
} # should I include margin of error?
# optionally convert to sf
if (output == "sf"){
out <- dplyr::filter(out, !is.na(lon) & !is.na(lat))
out <- sf::st_as_sf(out, coords = c("lon", "lat"), crs = 4326)
}
# return result
return(out)
}
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