R/seifa.R
In runapp-aus/strayr: Ready-to-use Australian common structures and classifications and tools for working with them
Defines functions
get_seifa_index_sheet
get_seifa
Documented in
get_seifa
get_seifa_index_sheet
#' @title Import SEIFA Data from ABS
#' @description The function will download all SEIFA data, for a specified spatial structure,
#' to a temporary excel file and then merge sheets into a single `data.frame`. This `data.frame`
#' also includes the ABS population count for the given spatial structure. For more information
#' on SEIFA indexes go to
#' \url{https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia}
#'
#' To learn more about the individual data-sets for each year, please visit their respective pages:
#' 2011
#' \url{https://www.abs.gov.au/AUSSTATS/abs@.nsf/allprimarymainfeatures/8C5F5BB699A0921CCA258259000BA619}
#' 2016
#' \url{https://www.abs.gov.au/ausstats/abs@.nsf/mf/2033.0.55.001}
#' 2021
#' \url{https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021}
#' @param structure character value for the desired spatial area. Must be one of:
#' \describe{
#' \item{sa1}{ - download size 51.6 MB}
#' \item{sa2}{ - download size 1.9 MB}
#' \item{lga}{ - download size 660 KB}
#' \item{postcode}{ - download size 2.3 MB}
#' \item{suburb}{ - download size 11.3 MB}
#' }
#' @param data_subclass character vector matching available SEIFA indexes:
#' \describe{
#' \item{irsed}{ - Index of Relative Socio-economic Disadvantage}
#' \item{irsead}{ - Index of Relative Socio-economic Advantage and Disadvantage}
#' \item{ier}{ - Index of Economic Resources}
#' \item{ieo}{ - Index of Education and Occupation}
#' }
#' @param year a character string or numeric of the release year of SEIFA object, eg "2016"; 2011.
#'
#' @importFrom purrr map
#' @importFrom purrr list_rbind
#' @importFrom utils download.file
#' @importFrom dplyr starts_with
#'
#' @return `data.frame` if file successfully downloaded, else returns `NULL`.
#' @note For All ABS SEIFA spreadsheets go to \href{https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012016?OpenDocument}{ABS website}
#' @export
#'
#' @examples
#' \dontrun{
#' get_seifa(structure = "lga", data_subclass = "irsed", year = 2016)
#' }
#'
get_seifa <- function(structure = c("sa1", "sa2", "lga", "postcode", "suburb"),
data_subclass = c("irsed", "irsead", "ier", "ieo"),
year = NULL) {
# TODO: 2006 SEIFA has the Statistical Local Area (SLA) structure, not the
# Statistical Level Areas (SA1, SA2) structures. Would need to update logic to
# handle 2006.
release_years <- c(2011, 2016, 2021)
stopifnot(
"data_subclass must be either:
1. some combination of: 'irsed', 'irsead', 'ier', 'ieo'
2. just the value 'summary'" =
all(data_subclass %in% c("irsed", "irsead", "ier", "ieo")) |
(data_subclass == "summary" & length(data_subclass) == 1)
)
# match excel sheet names to data_subclass
sheet_names <- c(
"summary" = "Table 1",
"irsed" = "Table 2",
"irsead" = "Table 3",
"ier" = "Table 4",
"ieo" = "Table 5"
)
sheet_names <- sheet_names[data_subclass]
# match spatial structures to specific urls
structure <- match.arg(structure, several.ok = FALSE)
urls <- list(
"2011" = c(
"sa1" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20sa1%20indexes.xls&2033.0.55.001&Data%20Cubes&9828E2819C30D96DCA257B43000E923E&0&2011&05.04.2013&Latest",
"sa2" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20SA2%20Indexes.xls&2033.0.55.001&Data%20Cubes&76D0BC44356DC34ACA257B3B001A4913&0&2011&12.11.2014&Latest",
"lga" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20lga%20indexes.xls&2033.0.55.001&Data%20Cubes&28EF8569335AC7CDCA257BAB00136B0F&0&2011&18.07.2013&Latest",
"postcode" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20POA%20Indexes.xls&2033.0.55.001&Data%20Cubes&209B3364525C82CCCA257B3B001A4D56&0&2011&12.11.2014&Latest",
"suburb" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20ssc%20indexes.xls&2033.0.55.001&Data%20Cubes&F40D0630B245D5DCCA257B43000EA0F1&0&2011&05.04.2013&Latest"
),
"2016" = c(
"sa1" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20sa1%20indexes.xls&2033.0.55.001&Data%20Cubes&40A0EFDE970A1511CA25825D000F8E8D&0&2016&27.03.2018&Latest",
"sa2" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20sa2%20indexes.xls&2033.0.55.001&Data%20Cubes&C9F7AD36397CB43DCA25825D000F917C&0&2016&27.03.2018&Latest",
"lga" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20lga%20indexes.xls&2033.0.55.001&Data%20Cubes&5604C75C214CD3D0CA25825D000F91AE&0&2016&27.03.2018&Latest",
"postcode" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20poa%20indexes.xls&2033.0.55.001&Data%20Cubes&DC124D1DAC3D9FDDCA25825D000F9267&0&2016&27.03.2018&Latest",
"suburb" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20ssc%20indexes.xls&2033.0.55.001&Data%20Cubes&863031D939DE8105CA25825D000F91D2&0&2016&27.03.2018&Latest"
),
"2021" = c(
"sa1" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Statistical%20Area%20Level%201%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"sa2" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Statistical%20Area%20Level%202%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"lga" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Local%20Government%20Area%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"postcode" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Postal%20Area%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"suburb" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Suburbs%20and%20Localities%2C%20Indexes%2C%20SEIFA%202021.xlsx"
)
)
if (is.null(year)) {
year <- as.character(max(release_years))
} else {
if (!(is.numeric(year) | is.character(year))) {
stop("year must either be an integer or character string.")
}
year <- as.character(year)
if (!any(year %in% as.character(release_years))) {
stop("year is not a valid release year, please check SEIFA webpage.")
}
}
url <- urls[[year]][structure]
# Get file extension if possible, otherwise assume xls.
url_ext <- tools::file_ext(sub("\\?.+", "", url))
if (url_ext == "") {
url_ext <- "xls"
}
filename <- tempfile(fileext = paste0(".", url_ext))
try({
download.file(url, destfile = filename, mode = "wb")
message(paste0("ABS ", toupper(structure), " file downloaded to: \n"),
paste0(" ", filename),
appendLF = TRUE
)
})
if (file.exists(filename)) {
ind <- map(sheet_names, ~ get_seifa_index_sheet(filename, .x, structure, data_subclass, year), .id = "seifa_index") %>%
list_rbind(names_to = "data_subclass")
return(ind)
} else {
warning("Download of ABS file failed. Please check your internet connection and try again.")
return(NULL)
}
}
#' @title Parse SEIFA index Spreadsheet
#' @description This is a helper function used by \code{\link{get_seifa}}. The function can also
#' be used independently if you have already downloaded one of the SEIFA index score spreadsheets
#' from \url{https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012016?OpenDocument}
#'
#' @param filename character name of temporary file when spreadsheet downloaded
#' @param sheetname character name of the sheet to be imported
#' @param structure character spatial structure of the data to be parsed. The spatial structure is
#' important as the shape of the data in the ABS spreadsheets if different for some structures.
#' @inheritParams get_seifa
#'
#' @import readxl
#' @importFrom dplyr select mutate relocate across
#' @return data.frame
#' @export
#'
#' @examples
#' \dontrun{
#'
#' get_seifa_index_sheet("downloaded_filename.xls", sheetname = "Table 2", structure = "lga")
#' }
#'
get_seifa_index_sheet <- function(filename, sheetname, structure = c("sa1", "sa2", "lga", "postcode", "suburb"), data_subclass, year) {
structure <- match.arg(structure, several.ok = FALSE)
column_names <- c(
"area_code",
"area_name",
"population",
"score",
"blank1",
"rank_aus",
"decile_aus",
"percentile_aus",
"blank2",
"state",
"rank_state",
"decile_state",
"percentile_state",
"min_score_sa1_area",
"max_score_sa1_area",
"percent_usual_resident_pop_without_sa1_score"
)
# Add column for SEIFA releases >= 2016 with structures suburb or postcode.
if (structure %in% c("suburb", "postcode") && year >= 2016) {
column_names <- c(column_names, "caution_poor_sa1_representation")
}
if (structure == "postcode") {
column_names <- column_names[-grep("area_name", column_names)]
if (year >= 2016) {
column_names <- c(column_names, "postcode_crosses_state_boundary")
}
}
if (structure == "sa1") {
column_names <- c(
"sa1_7_code",
"sa1_11_code",
"population",
"score",
"blank1",
"rank_aus",
"decile_aus",
"percentile_aus",
"blank2",
"state",
"rank_state",
"decile_state",
"percentile_state"
)
# remove sa1_11_code column for 2011 release.
if (year == 2011) {
column_names <- column_names[-grep("sa1_11_code", column_names)]
} else if (year == 2021) {
column_names <- column_names[-grep("sa1_7_code", column_names)]
}
}
if (length(data_subclass) == 1) {
if (data_subclass == "summary") {
if ((year == 2011) |
(year == 2021 & structure == "sa1")
) {
column_names <- c(
"area_code",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population"
)
} else if (year == 2016 & structure == "suburb") {
column_names <- c(
"area_code",
"area_name",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population",
"data_warning"
)
} else if (year %in% c(2016, 2021) & structure == "postcode") {
column_names <- c(
"area_code",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population",
"data_warning",
"postcode_crosses_state_boundaries"
)
} else {
column_names <- c(
"area_code",
"area_name",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population"
)
}
}
}
suppressWarnings({
df <- read_excel(filename,
sheetname,
skip = 6,
col_names = column_names,
na = c("", "NA", "-")
) %>%
dplyr::filter(dplyr::if_all(dplyr::ends_with(c("_name","_code")), ~ !is.na(.x))) %>%
dplyr::select(-dplyr::starts_with("blank")) %>%
dplyr::mutate(
structure = structure,
year = year
) %>%
dplyr::mutate(dplyr::across(
.cols = dplyr::any_of(ends_with("_code")), # Specify the column name
.fns = ~ as.character(.) # Conditionally convert to character
)) %>%
dplyr::relocate(structure)
})
return(df)
}
runapp-aus/strayr documentation built on Oct. 15, 2024, 2:19 p.m.
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Defines functions get_seifa_index_sheet get_seifa
Documented in get_seifa get_seifa_index_sheet
#' @title Import SEIFA Data from ABS
#' @description The function will download all SEIFA data, for a specified spatial structure,
#' to a temporary excel file and then merge sheets into a single `data.frame`. This `data.frame`
#' also includes the ABS population count for the given spatial structure. For more information
#' on SEIFA indexes go to
#' \url{https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia}
#'
#' To learn more about the individual data-sets for each year, please visit their respective pages:
#' 2011
#' \url{https://www.abs.gov.au/AUSSTATS/abs@.nsf/allprimarymainfeatures/8C5F5BB699A0921CCA258259000BA619}
#' 2016
#' \url{https://www.abs.gov.au/ausstats/abs@.nsf/mf/2033.0.55.001}
#' 2021
#' \url{https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021}
#' @param structure character value for the desired spatial area. Must be one of:
#' \describe{
#' \item{sa1}{ - download size 51.6 MB}
#' \item{sa2}{ - download size 1.9 MB}
#' \item{lga}{ - download size 660 KB}
#' \item{postcode}{ - download size 2.3 MB}
#' \item{suburb}{ - download size 11.3 MB}
#' }
#' @param data_subclass character vector matching available SEIFA indexes:
#' \describe{
#' \item{irsed}{ - Index of Relative Socio-economic Disadvantage}
#' \item{irsead}{ - Index of Relative Socio-economic Advantage and Disadvantage}
#' \item{ier}{ - Index of Economic Resources}
#' \item{ieo}{ - Index of Education and Occupation}
#' }
#' @param year a character string or numeric of the release year of SEIFA object, eg "2016"; 2011.
#'
#' @importFrom purrr map
#' @importFrom purrr list_rbind
#' @importFrom utils download.file
#' @importFrom dplyr starts_with
#'
#' @return `data.frame` if file successfully downloaded, else returns `NULL`.
#' @note For All ABS SEIFA spreadsheets go to \href{https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012016?OpenDocument}{ABS website}
#' @export
#'
#' @examples
#' \dontrun{
#' get_seifa(structure = "lga", data_subclass = "irsed", year = 2016)
#' }
#'
get_seifa <- function(structure = c("sa1", "sa2", "lga", "postcode", "suburb"),
data_subclass = c("irsed", "irsead", "ier", "ieo"),
year = NULL) {
# TODO: 2006 SEIFA has the Statistical Local Area (SLA) structure, not the
# Statistical Level Areas (SA1, SA2) structures. Would need to update logic to
# handle 2006.
release_years <- c(2011, 2016, 2021)
stopifnot(
"data_subclass must be either:
1. some combination of: 'irsed', 'irsead', 'ier', 'ieo'
2. just the value 'summary'" =
all(data_subclass %in% c("irsed", "irsead", "ier", "ieo")) |
(data_subclass == "summary" & length(data_subclass) == 1)
)
# match excel sheet names to data_subclass
sheet_names <- c(
"summary" = "Table 1",
"irsed" = "Table 2",
"irsead" = "Table 3",
"ier" = "Table 4",
"ieo" = "Table 5"
)
sheet_names <- sheet_names[data_subclass]
# match spatial structures to specific urls
structure <- match.arg(structure, several.ok = FALSE)
urls <- list(
"2011" = c(
"sa1" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20sa1%20indexes.xls&2033.0.55.001&Data%20Cubes&9828E2819C30D96DCA257B43000E923E&0&2011&05.04.2013&Latest",
"sa2" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20SA2%20Indexes.xls&2033.0.55.001&Data%20Cubes&76D0BC44356DC34ACA257B3B001A4913&0&2011&12.11.2014&Latest",
"lga" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20lga%20indexes.xls&2033.0.55.001&Data%20Cubes&28EF8569335AC7CDCA257BAB00136B0F&0&2011&18.07.2013&Latest",
"postcode" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20POA%20Indexes.xls&2033.0.55.001&Data%20Cubes&209B3364525C82CCCA257B3B001A4D56&0&2011&12.11.2014&Latest",
"suburb" = "https://www.abs.gov.au/AUSSTATS/subscriber.nsf/log?openagent&2033.0.55.001%20ssc%20indexes.xls&2033.0.55.001&Data%20Cubes&F40D0630B245D5DCCA257B43000EA0F1&0&2011&05.04.2013&Latest"
),
"2016" = c(
"sa1" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20sa1%20indexes.xls&2033.0.55.001&Data%20Cubes&40A0EFDE970A1511CA25825D000F8E8D&0&2016&27.03.2018&Latest",
"sa2" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20sa2%20indexes.xls&2033.0.55.001&Data%20Cubes&C9F7AD36397CB43DCA25825D000F917C&0&2016&27.03.2018&Latest",
"lga" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20lga%20indexes.xls&2033.0.55.001&Data%20Cubes&5604C75C214CD3D0CA25825D000F91AE&0&2016&27.03.2018&Latest",
"postcode" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20poa%20indexes.xls&2033.0.55.001&Data%20Cubes&DC124D1DAC3D9FDDCA25825D000F9267&0&2016&27.03.2018&Latest",
"suburb" = "https://www.abs.gov.au/ausstats/subscriber.nsf/log?openagent&2033055001%20-%20ssc%20indexes.xls&2033.0.55.001&Data%20Cubes&863031D939DE8105CA25825D000F91D2&0&2016&27.03.2018&Latest"
),
"2021" = c(
"sa1" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Statistical%20Area%20Level%201%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"sa2" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Statistical%20Area%20Level%202%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"lga" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Local%20Government%20Area%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"postcode" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Postal%20Area%2C%20Indexes%2C%20SEIFA%202021.xlsx",
"suburb" = "https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021/Suburbs%20and%20Localities%2C%20Indexes%2C%20SEIFA%202021.xlsx"
)
)
if (is.null(year)) {
year <- as.character(max(release_years))
} else {
if (!(is.numeric(year) | is.character(year))) {
stop("year must either be an integer or character string.")
}
year <- as.character(year)
if (!any(year %in% as.character(release_years))) {
stop("year is not a valid release year, please check SEIFA webpage.")
}
}
url <- urls[[year]][structure]
# Get file extension if possible, otherwise assume xls.
url_ext <- tools::file_ext(sub("\\?.+", "", url))
if (url_ext == "") {
url_ext <- "xls"
}
filename <- tempfile(fileext = paste0(".", url_ext))
try({
download.file(url, destfile = filename, mode = "wb")
message(paste0("ABS ", toupper(structure), " file downloaded to: \n"),
paste0(" ", filename),
appendLF = TRUE
)
})
if (file.exists(filename)) {
ind <- map(sheet_names, ~ get_seifa_index_sheet(filename, .x, structure, data_subclass, year), .id = "seifa_index") %>%
list_rbind(names_to = "data_subclass")
return(ind)
} else {
warning("Download of ABS file failed. Please check your internet connection and try again.")
return(NULL)
}
}
#' @title Parse SEIFA index Spreadsheet
#' @description This is a helper function used by \code{\link{get_seifa}}. The function can also
#' be used independently if you have already downloaded one of the SEIFA index score spreadsheets
#' from \url{https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012016?OpenDocument}
#'
#' @param filename character name of temporary file when spreadsheet downloaded
#' @param sheetname character name of the sheet to be imported
#' @param structure character spatial structure of the data to be parsed. The spatial structure is
#' important as the shape of the data in the ABS spreadsheets if different for some structures.
#' @inheritParams get_seifa
#'
#' @import readxl
#' @importFrom dplyr select mutate relocate across
#' @return data.frame
#' @export
#'
#' @examples
#' \dontrun{
#'
#' get_seifa_index_sheet("downloaded_filename.xls", sheetname = "Table 2", structure = "lga")
#' }
#'
get_seifa_index_sheet <- function(filename, sheetname, structure = c("sa1", "sa2", "lga", "postcode", "suburb"), data_subclass, year) {
structure <- match.arg(structure, several.ok = FALSE)
column_names <- c(
"area_code",
"area_name",
"population",
"score",
"blank1",
"rank_aus",
"decile_aus",
"percentile_aus",
"blank2",
"state",
"rank_state",
"decile_state",
"percentile_state",
"min_score_sa1_area",
"max_score_sa1_area",
"percent_usual_resident_pop_without_sa1_score"
)
# Add column for SEIFA releases >= 2016 with structures suburb or postcode.
if (structure %in% c("suburb", "postcode") && year >= 2016) {
column_names <- c(column_names, "caution_poor_sa1_representation")
}
if (structure == "postcode") {
column_names <- column_names[-grep("area_name", column_names)]
if (year >= 2016) {
column_names <- c(column_names, "postcode_crosses_state_boundary")
}
}
if (structure == "sa1") {
column_names <- c(
"sa1_7_code",
"sa1_11_code",
"population",
"score",
"blank1",
"rank_aus",
"decile_aus",
"percentile_aus",
"blank2",
"state",
"rank_state",
"decile_state",
"percentile_state"
)
# remove sa1_11_code column for 2011 release.
if (year == 2011) {
column_names <- column_names[-grep("sa1_11_code", column_names)]
} else if (year == 2021) {
column_names <- column_names[-grep("sa1_7_code", column_names)]
}
}
if (length(data_subclass) == 1) {
if (data_subclass == "summary") {
if ((year == 2011) |
(year == 2021 & structure == "sa1")
) {
column_names <- c(
"area_code",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population"
)
} else if (year == 2016 & structure == "suburb") {
column_names <- c(
"area_code",
"area_name",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population",
"data_warning"
)
} else if (year %in% c(2016, 2021) & structure == "postcode") {
column_names <- c(
"area_code",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population",
"data_warning",
"postcode_crosses_state_boundaries"
)
} else {
column_names <- c(
"area_code",
"area_name",
"irsed_score",
"irsed_decile",
"irsead_score",
"irsead_decile",
"ier_score",
"ier_decile",
"ieo_score",
"ieo_decile",
"population"
)
}
}
}
suppressWarnings({
df <- read_excel(filename,
sheetname,
skip = 6,
col_names = column_names,
na = c("", "NA", "-")
) %>%
dplyr::filter(dplyr::if_all(dplyr::ends_with(c("_name","_code")), ~ !is.na(.x))) %>%
dplyr::select(-dplyr::starts_with("blank")) %>%
dplyr::mutate(
structure = structure,
year = year
) %>%
dplyr::mutate(dplyr::across(
.cols = dplyr::any_of(ends_with("_code")), # Specify the column name
.fns = ~ as.character(.) # Conditionally convert to character
)) %>%
dplyr::relocate(structure)
})
return(df)
}
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