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#' Read ADI Points of Presence Statistics
#'
#' @description
#' Import the Authorised Deposit-taking Institution Points of Presence
#' Read ADI Points of Presence Statistics from a local file.
#'
#' @param file_path path to the local .xlsx file.
#' @param cur_hist character vector determining whether to download the current
#' publication (`"current"`) or the historic publication (`"historic"`).
#'
#' @return A tibble containing the ADI Points of Presence Statistics data.
#'
#' @noRd
#'
read_adipops <- function(file_path, cur_hist, call = rlang::caller_env()) {
tidyxl_data <- read_tidyxl_data(file_path, sheets = "table.*1", call = call)
formatting_data <- read_tidyxl_formatting_data(file_path)
adipops_data(tidyxl_data, formatting_data, call = call)
}
#' Extracts the ADIPOPS data and cleans it.
#'
#' @param tidyxl_data cell data extracted from a .xlsx file using the tidyxl
#' package
#' @param formatting_data formatting data extracted from a .xlsx file using the
#' tidyxl package
#'
#' @noRd
#'
adipops_data <- function(tidyxl_data,
formatting_data,
call = rlang::caller_env()) {
adipops_data <-
attempt_format_vertical_data(
tidyxl_data = tidyxl_data,
formatting_data = formatting_data,
stat_pub_name = "Authorised Deposit-taking Institutions' Points of Presence Statistics",
frequency = "Quarterly",
call = call
)
adipops_data <- convert_adipops_units(adipops_data)
return(adipops_data)
}
#' Cleans up the units column in the ADIPOPS data so it matches other publications.
#'
#' @param data the ADIPOPS data to be cleaned.
#'
#' @noRd
#'
convert_adipops_units <- function(data) {
adipops_correct_units <-
dplyr::mutate(
.data = data,
unit = dplyr::case_when(
stringr::str_detect(
string = series,
pattern = stringr::regex("number", ignore_case = TRUE)
) ~ unit,
.default = series
)
)
return(adipops_correct_units)
}
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