R/acs_data.R
In sdaza/acsr: Wrapped functions to manage data from the US Census American Community Survey (ACS)
Defines functions
acsdata
Documented in
acsdata
#' @title Create a list containing ACS data files (\code{\link{acs}}).
#' @description Because downloading the data to compute a proportion, ratio or
#' aggregation can be slow, the \code{acsdata} function creates an object that
#' can be used with the \code{\link{sumacs}} function. Before using this
#' function remember to define a key using the \code{\link{acs}} command
#' \code{api.key.install(key="*")}.
#' @param formula A character or vector of characters containing formulas using
#' ACS/Census variables. + - operators can be included. / defines a division.
#' @param level A character or vector of characters specifying the geographic
#' level of the data. It may be necessary to specificy values to the
#' corresponding levels. For instance, when \code{level = "county"}, you have
#' to specify a state (e.g., \code{state = "WI"}, the default state in this
#' package). You can also use a wildcard method (\code{state = "*"}) to
#' include all the states. Below, you can see the required combinations of
#' different summary levels.
#'
#' \cr 010 us \cr 020 region \cr 030 division \cr 040 state \cr 050 state,
#' county \cr 060 state, county, county.subdivision \cr 140 state, county,
#' tract \cr 150 state, county, tract, block.group \cr 160 state, place \cr
#' 250 american.indian.area \cr 320 state, msa \cr 340 state, csa \cr 350
#' necta \cr 400 urban.area \cr 500 state, congressional.district \cr 610
#' state, state.legislative.district.upper \cr 620 state,
#' state.legislative.district.lower \cr 795 state, puma \cr 860 zip.code \cr
#' 950 state, school.district.elementary \cr 960 state,
#' school.district.secondary \cr 970 state, school.district.unified \cr
#'
#' @param combine Whether the geographies are to be combined. If \code{combine = TRUE},
#' lists should be used when specifying geographic levels (the corresponding level
#' for the level specified). If the rest geographic levels has one element,
#' the function will assume that level is equal for all the sub-levels.
#' For example, if \code{state = "WI"}, and several counties were specified,
#' the function assumes that all the counties are from WI.
#' @param combine.name Label for the aggregate geography when combining levels.
#' The default value is \code{aggregate}.
#' @param dataset A string or vector of strings specifying the data set to be used: acs, sf1 or sf1.
#' The default value is "acs".
#' @param endyear An integer or vector of integers (defaults to 2014) indicating the latest year of
#' the data in the survey or Census year.
#' @param span An integer indicating the span (in years) of the desired ACS data
#' (should be 1, 3,or 5), defaults to 5.
#' @param print.levels Boolean that print levels generated by the \code{geo.make} function.
#' @return Returns a list of ACS objects for different levels to be used with
#' the \code{\link{sumacs}} function.
#' @note Depending on the quality of the internet connection, number of
#' variables and levels, getting the ACS data can be slow especially for the
#' levels "county.subdivision", "block.group", and "tract" (it might take more
#' than 30 minutes).
#' @examples
#' api.key.install(key="*")
#' # get variables from formula
#' acsdata("(b16004_004 + b16004_026 + b16004_048 / b16004_001)", level = "county")
#'
#' # get variables directly
#' acsdata(c("b16004_004", "b16004_026"), level = "county")
#'
#' # combine levels
#' acsdata("(b16004_004 + b16004_026 + b16004_048 / b16004_001)",
#' level = c("block.group"), state = list("WI"),
#' county = list(1, 141),
#' tract = list(950100, 11700),
#' block.group = list(1:2, 1:2), combine = TRUE)
acsdata <- function(formula, level = "state", dataset = "acs", endyear = 2014, span = 5,
us = "*",
region = "*",
division = "*",
state = "WI",
county = "*",
county.subdivision ="*",
place ="*",
tract = "*",
block.group = "*",
msa = "*",
csa = "*",
necta = "*",
urban.area = "*",
congressional.district = "*",
state.legislative.district.upper = "*",
state.legislative.district.lower = "*",
puma = "*",
zip.code = "*",
american.indian.area = "*",
school.district.elementary = "*",
school.district.secondary = "*",
school.district.unified = "*",
combine = FALSE,
combine.name = "aggregate",
print.levels = TRUE
) {
lnames <- c("us","region","division","state","county","county.subdivision","place",
"tract","block.group","msa","csa","necta","urban.area",
"congressional.district","state.legislative.district.upper",
"state.legislative.district.lower","puma","zip.code",
"american.indian.area","school.district.elementary",
"school.district.secondary","school.district.unified")
# short loop to levels
for (i in seq_along(level)) {
if ( !level[i] %in% lnames ) { stop("Some levels were not found, please check!")}
}
# get variables
variables <- acsr::getvars(formula)
variables_aux <- variables[1] # just to speed auxiliary data extraction when downloading directly doesn't
nvars <- length(variables)
nlevels <- length(level)
#print (paste0(". . . . . . ACS/Census variables : ", nvars))
#print (paste0(". . . . . . Levels : ", nlevels))
ldata <- list()
# start level loop
if ( combine == FALSE ) {
for (tlev in seq_along(level) ) {
# first get the data, this could be slow, specially for county subdivision and block group
if (level[tlev] == "us") {
print (". . . . . . Getting us data")
ldata[["us"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(us = us),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["us"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "region") {
print (". . . . . . Getting region data")
ldata[["region"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(region = region),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["region"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "division") {
print (". . . . . . Getting division data")
ldata[["division"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(division = division),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["division"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "american.indian.area") {
print (". . . . . . Getting american indian area data")
ldata[["american.indian.area"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(american.indian.area = american.indian.area),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["american.indian.area"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "state") {
print (". . . . . . Getting state data")
ldata[["state"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(state = state),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["state"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "county") {
print (". . . . . . Getting county data")
ldata[["county"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(state = state, county = county),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span, one.zero = TRUE))
if (length(ldata[["county"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "county.subdivision") {
# I didn't need an auxiliary procedure to get the data
print (". . . . . . Getting county subdivision data")
ldata[["county.subdivision"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, county = county, county.subdivision = county.subdivision),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["county.subdivision"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "place") {
print (". . . . . . Getting place data")
ldata[["place"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, place = place),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["place"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "tract") {
print (". . . . . . Getting tract data")
ldata[["tract"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, county = county, tract = tract),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["tract"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "block.group") {
print (". . . . . . Getting block group data")
# auxiliary procedure to get the data
if (!any(county == "*")) {
ldata[["block.group"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(state= state, county = county, tract = tract, block.group = block.group),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
}
else {
county.data <- suppressWarnings( acs::acs.fetch( acs::geo.make(state= state, county = "*", ),
variable = variables_aux,
dataset = dataset,
endyear = endyear,
span = span))
ncounty <- as.numeric(geography(county.data)$county)
ldata[["block.group"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state = state, county = ncounty, tract = tract, block.group = block.group),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
}
if (length(ldata[["block.group"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "msa") {
print (". . . . . . Getting msa data")
ldata[["msa"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state = state, msa = msa),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["msa"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "csa") {
print (". . . . . . Getting csa data")
ldata[["csa"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state = state, csa = csa),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["csa"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "necta") {
print (". . . . . . Getting necta data")
ldata[["necta"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(necta = necta),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["necta"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "urban.area") {
print (". . . . . . Getting urban area data")
ldata[["urban.area"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(urban.area = urban.area),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["urban.area"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "congressional.district") {
print (". . . . . . Getting congressional district data")
ldata[["congressional.district"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, congressional.district = congressional.district),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["congressional.district"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "state.legislative.district.upper") {
print (". . . . . . Getting state legislative district upper data")
ldata[["state.legislative.district.upper"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, state.legislative.district.upper = state.legislative.district.upper),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["state.legislative.district.upper"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "state.legislative.district.lower") {
print (". . . . . . Getting state legislative district lower data")
ldata[["state.legislative.district.lower"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, state.legislative.district.lower = state.legislative.district.lower),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["state.legislative.district.lower"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "puma") {
print (". . . . . . Getting puma data")
ldata[["puma"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, puma = puma),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["puma"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "zip.code") {
print (". . . . . . Getting zip code data")
ldata[["zip.code"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(zip.code = zip.code),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["zip.code"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "school.district.elementary") {
print (". . . . . . Getting school district elementary data")
ldata[["school.district.elementary"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state= state, school.district.elementary = school.district.elementary),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span, one.zero = TRUE) )
if (length(ldata[["school.district.elementary"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "school.district.secondary") {
print (". . . . . . Getting school district secondary data")
ldata[["school.district.secondary"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state= state, school.district.secondary = school.district.secondary),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["school.district.secondary"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "school.district.unified") {
print (". . . . . . Getting school district unified data")
ldata[["school.district.unified"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, school.district.unified = school.district.unified),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["school.district.unified"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
} # end level loop
}
if ( combine == TRUE ) {
print (". . . . . . Getting combined data")
t.geo <- acsr::combine.make.geo(
level = level,
combine.name = combine.name,
print.levels = print.levels,
region = region,
division = division,
state = state,
county = county,
county.subdivision = county.subdivision,
place = place,
tract = tract,
block.group = block.group,
msa = msa,
csa = csa,
necta = necta,
urban.area = urban.area,
congressional.district = congressional.district,
state.legislative.district.upper = state.legislative.district.upper,
state.legislative.district.lower = state.legislative.district.lower,
puma = puma,
zip.code = zip.code,
american.indian.area = american.indian.area,
school.district.elementary = school.district.elementary,
school.district.secondary = school.district.secondary,
school.district.unified = school.district.unified)
ldata <- acs::acs.fetch( t.geo, variable = variables, dataset = dataset, endyear = endyear, span = span, one.zero = TRUE)
}
return(ldata)
}
sdaza/acsr documentation built on June 18, 2020, 6:53 p.m.
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Defines functions acsdata
Documented in acsdata
#' @title Create a list containing ACS data files (\code{\link{acs}}).
#' @description Because downloading the data to compute a proportion, ratio or
#' aggregation can be slow, the \code{acsdata} function creates an object that
#' can be used with the \code{\link{sumacs}} function. Before using this
#' function remember to define a key using the \code{\link{acs}} command
#' \code{api.key.install(key="*")}.
#' @param formula A character or vector of characters containing formulas using
#' ACS/Census variables. + - operators can be included. / defines a division.
#' @param level A character or vector of characters specifying the geographic
#' level of the data. It may be necessary to specificy values to the
#' corresponding levels. For instance, when \code{level = "county"}, you have
#' to specify a state (e.g., \code{state = "WI"}, the default state in this
#' package). You can also use a wildcard method (\code{state = "*"}) to
#' include all the states. Below, you can see the required combinations of
#' different summary levels.
#'
#' \cr 010 us \cr 020 region \cr 030 division \cr 040 state \cr 050 state,
#' county \cr 060 state, county, county.subdivision \cr 140 state, county,
#' tract \cr 150 state, county, tract, block.group \cr 160 state, place \cr
#' 250 american.indian.area \cr 320 state, msa \cr 340 state, csa \cr 350
#' necta \cr 400 urban.area \cr 500 state, congressional.district \cr 610
#' state, state.legislative.district.upper \cr 620 state,
#' state.legislative.district.lower \cr 795 state, puma \cr 860 zip.code \cr
#' 950 state, school.district.elementary \cr 960 state,
#' school.district.secondary \cr 970 state, school.district.unified \cr
#'
#' @param combine Whether the geographies are to be combined. If \code{combine = TRUE},
#' lists should be used when specifying geographic levels (the corresponding level
#' for the level specified). If the rest geographic levels has one element,
#' the function will assume that level is equal for all the sub-levels.
#' For example, if \code{state = "WI"}, and several counties were specified,
#' the function assumes that all the counties are from WI.
#' @param combine.name Label for the aggregate geography when combining levels.
#' The default value is \code{aggregate}.
#' @param dataset A string or vector of strings specifying the data set to be used: acs, sf1 or sf1.
#' The default value is "acs".
#' @param endyear An integer or vector of integers (defaults to 2014) indicating the latest year of
#' the data in the survey or Census year.
#' @param span An integer indicating the span (in years) of the desired ACS data
#' (should be 1, 3,or 5), defaults to 5.
#' @param print.levels Boolean that print levels generated by the \code{geo.make} function.
#' @return Returns a list of ACS objects for different levels to be used with
#' the \code{\link{sumacs}} function.
#' @note Depending on the quality of the internet connection, number of
#' variables and levels, getting the ACS data can be slow especially for the
#' levels "county.subdivision", "block.group", and "tract" (it might take more
#' than 30 minutes).
#' @examples
#' api.key.install(key="*")
#' # get variables from formula
#' acsdata("(b16004_004 + b16004_026 + b16004_048 / b16004_001)", level = "county")
#'
#' # get variables directly
#' acsdata(c("b16004_004", "b16004_026"), level = "county")
#'
#' # combine levels
#' acsdata("(b16004_004 + b16004_026 + b16004_048 / b16004_001)",
#' level = c("block.group"), state = list("WI"),
#' county = list(1, 141),
#' tract = list(950100, 11700),
#' block.group = list(1:2, 1:2), combine = TRUE)
acsdata <- function(formula, level = "state", dataset = "acs", endyear = 2014, span = 5,
us = "*",
region = "*",
division = "*",
state = "WI",
county = "*",
county.subdivision ="*",
place ="*",
tract = "*",
block.group = "*",
msa = "*",
csa = "*",
necta = "*",
urban.area = "*",
congressional.district = "*",
state.legislative.district.upper = "*",
state.legislative.district.lower = "*",
puma = "*",
zip.code = "*",
american.indian.area = "*",
school.district.elementary = "*",
school.district.secondary = "*",
school.district.unified = "*",
combine = FALSE,
combine.name = "aggregate",
print.levels = TRUE
) {
lnames <- c("us","region","division","state","county","county.subdivision","place",
"tract","block.group","msa","csa","necta","urban.area",
"congressional.district","state.legislative.district.upper",
"state.legislative.district.lower","puma","zip.code",
"american.indian.area","school.district.elementary",
"school.district.secondary","school.district.unified")
# short loop to levels
for (i in seq_along(level)) {
if ( !level[i] %in% lnames ) { stop("Some levels were not found, please check!")}
}
# get variables
variables <- acsr::getvars(formula)
variables_aux <- variables[1] # just to speed auxiliary data extraction when downloading directly doesn't
nvars <- length(variables)
nlevels <- length(level)
#print (paste0(". . . . . . ACS/Census variables : ", nvars))
#print (paste0(". . . . . . Levels : ", nlevels))
ldata <- list()
# start level loop
if ( combine == FALSE ) {
for (tlev in seq_along(level) ) {
# first get the data, this could be slow, specially for county subdivision and block group
if (level[tlev] == "us") {
print (". . . . . . Getting us data")
ldata[["us"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(us = us),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["us"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "region") {
print (". . . . . . Getting region data")
ldata[["region"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(region = region),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["region"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "division") {
print (". . . . . . Getting division data")
ldata[["division"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(division = division),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["division"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "american.indian.area") {
print (". . . . . . Getting american indian area data")
ldata[["american.indian.area"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(american.indian.area = american.indian.area),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["american.indian.area"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "state") {
print (". . . . . . Getting state data")
ldata[["state"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(state = state),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
if (length(ldata[["state"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "county") {
print (". . . . . . Getting county data")
ldata[["county"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(state = state, county = county),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span, one.zero = TRUE))
if (length(ldata[["county"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "county.subdivision") {
# I didn't need an auxiliary procedure to get the data
print (". . . . . . Getting county subdivision data")
ldata[["county.subdivision"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, county = county, county.subdivision = county.subdivision),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["county.subdivision"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "place") {
print (". . . . . . Getting place data")
ldata[["place"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, place = place),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["place"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "tract") {
print (". . . . . . Getting tract data")
ldata[["tract"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, county = county, tract = tract),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["tract"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "block.group") {
print (". . . . . . Getting block group data")
# auxiliary procedure to get the data
if (!any(county == "*")) {
ldata[["block.group"]] <- suppressWarnings(acs::acs.fetch( acs::geo.make(state= state, county = county, tract = tract, block.group = block.group),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE))
}
else {
county.data <- suppressWarnings( acs::acs.fetch( acs::geo.make(state= state, county = "*", ),
variable = variables_aux,
dataset = dataset,
endyear = endyear,
span = span))
ncounty <- as.numeric(geography(county.data)$county)
ldata[["block.group"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state = state, county = ncounty, tract = tract, block.group = block.group),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
}
if (length(ldata[["block.group"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "msa") {
print (". . . . . . Getting msa data")
ldata[["msa"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state = state, msa = msa),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["msa"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "csa") {
print (". . . . . . Getting csa data")
ldata[["csa"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state = state, csa = csa),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["csa"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "necta") {
print (". . . . . . Getting necta data")
ldata[["necta"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(necta = necta),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["necta"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "urban.area") {
print (". . . . . . Getting urban area data")
ldata[["urban.area"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(urban.area = urban.area),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["urban.area"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "congressional.district") {
print (". . . . . . Getting congressional district data")
ldata[["congressional.district"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, congressional.district = congressional.district),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["congressional.district"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "state.legislative.district.upper") {
print (". . . . . . Getting state legislative district upper data")
ldata[["state.legislative.district.upper"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, state.legislative.district.upper = state.legislative.district.upper),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["state.legislative.district.upper"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "state.legislative.district.lower") {
print (". . . . . . Getting state legislative district lower data")
ldata[["state.legislative.district.lower"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, state.legislative.district.lower = state.legislative.district.lower),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["state.legislative.district.lower"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "puma") {
print (". . . . . . Getting puma data")
ldata[["puma"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, puma = puma),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["puma"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "zip.code") {
print (". . . . . . Getting zip code data")
ldata[["zip.code"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(zip.code = zip.code),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["zip.code"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "school.district.elementary") {
print (". . . . . . Getting school district elementary data")
ldata[["school.district.elementary"]] <- suppressWarnings ( acs::acs.fetch( acs::geo.make(state= state, school.district.elementary = school.district.elementary),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span, one.zero = TRUE) )
if (length(ldata[["school.district.elementary"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "school.district.secondary") {
print (". . . . . . Getting school district secondary data")
ldata[["school.district.secondary"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state= state, school.district.secondary = school.district.secondary),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["school.district.secondary"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
else if (level[tlev] == "school.district.unified") {
print (". . . . . . Getting school district unified data")
ldata[["school.district.unified"]] <- suppressWarnings( acs::acs.fetch( acs::geo.make(state = state, school.district.unified = school.district.unified),
variable = variables,
dataset = dataset,
endyear = endyear,
span = span,
one.zero = TRUE) )
if (length(ldata[["school.district.unified"]]@acs.colnames) != length(variables)) {
stop("Not all the ACS/Census variables were found, check variable names in your formulas!")
}
}
} # end level loop
}
if ( combine == TRUE ) {
print (". . . . . . Getting combined data")
t.geo <- acsr::combine.make.geo(
level = level,
combine.name = combine.name,
print.levels = print.levels,
region = region,
division = division,
state = state,
county = county,
county.subdivision = county.subdivision,
place = place,
tract = tract,
block.group = block.group,
msa = msa,
csa = csa,
necta = necta,
urban.area = urban.area,
congressional.district = congressional.district,
state.legislative.district.upper = state.legislative.district.upper,
state.legislative.district.lower = state.legislative.district.lower,
puma = puma,
zip.code = zip.code,
american.indian.area = american.indian.area,
school.district.elementary = school.district.elementary,
school.district.secondary = school.district.secondary,
school.district.unified = school.district.unified)
ldata <- acs::acs.fetch( t.geo, variable = variables, dataset = dataset, endyear = endyear, span = span, one.zero = TRUE)
}
return(ldata)
}
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