#' Return the householder count per income bracket and per age group for the
#' given the geographical names (i.e., zip codes, state codes, state names,
#' city names, county names) and the observation year period.
#'
#' @param geo_names required, vector of string(s) of geographical names.
#' @param location_type optional, string indicating the location type of the
#' geographical names. If the location_type is blank then the function will
#' try to guess the location type based on the input geo_names. NA by default.
#' @param start_year optional, integer indicating the start year of observation.
#' 2011 by default.
#' @param end_year optional, integer indicating the end year of observation.
#' 2018 by default.
#' @param year optional, integer indicating a single year of observation.
#' This parameter overrides the start_year and end_year parameters when
#' it is not NA, such that start_year=year and end_year=year. NA by default.
#' @return A named list with each list item is a data frame containing the
#' household income observations of each region per income bracket. The data
#' frame is identified by the observation year and age group.
#'
#' @export
#' @examples
#' zips <- c("94035","94039","94040","94041","94042","94043")
#'
#' # Count the householders per income and age group in the specified ZIP codes
#' count_household_income_by_age(zips)
#'
#' # Count the householders from 2012 to 2015
#' count_household_income_by_age(zips, start_year=2012, end_year=2015)
#'
#' # Count the householders in 2012
#' count_household_income_by_age(zips, year=2012)
#'
#' # Count the householders in the state of California
#' count_household_income_by_age(c("California")) # State name
#' count_household_income_by_age(c("CA")) # State code
#' count_household_income_by_age(c("06")) # 2-digit state FIPS code
count_household_income_by_age <- function(geo_names,
location_type=c(NA, "zip", "city", "county", "state"),
start_year=2011, end_year=2018, year=NA) {
location_type <- match.arg(location_type)
geo_map <- .create_geo_dcid_map(geo_names, location_type)
statvar_map <- list()
for (age_group in CENSUS_HOUSEHOLDER_AGE_GROUPS) {
statvar_map[[age_group]] <-
sapply(CENSUS_INCOME_BRACKETS,
function(x) paste0("Count_Household_HouseholderAge", age_group, "_IncomeOf", x),
simplify = FALSE, USE.NAMES = TRUE)
}
return (.get_statistical_data(geo_map, statvar_map, start_year, end_year, year))
}
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