R/format_dcs.R

In worldbank/pddcs: Prepare data for Data Collection System

#' Convert to DCS format
#'
#' Convert a dataset retrieved with [fetch_indicator()] to DCS format.
#'
#' `r lifecycle::badge("stable")`
#'
#' @inheritParams compare_with_wdi
#' @param type character: Type, either 'data' or 'meta'.
#' @return tibble
#' @examples
#' # Load example data
#' data("bednets")
#'
#' # Convert to 'data' format
#' format_dcs(bednets, type = "data")
#'
#' # Convert to 'metadata' format
#' format_dcs(bednets, type = "meta")
#' @export
format_dcs <- function(df, type = c("data", "meta")) {

  # Match argument
  type <- match.arg(type)

  # Check inputs
  check_inputs_format_dcs(df)

  # Rearrange data
  if (type == "data") {
    # Add scale column
    df$scale <- 0
    # Select and reorder columns
    df <- df[c("year", "iso3c", "indicator", "scale", "value")]
    # Rename columns
    names(df) <- c("Time", "Country", "Series", "Scale", "Data")
  } else if (type == "meta") {
    # Select and reorder columns
    df <- df[c("iso3c", "indicator", "year", "note")]
    # Rename columns
    names(df) <- c("Country", "Series", "Time", "Footnote")
  }

  # Reformat Time column
  df$Time <- paste0("YR", df$Time)

  return(df)
}

#' check_inputs_format_dcs
#' @inheritParams format_dcs
#' @return logical
#' @noRd
check_inputs_format_dcs <- function(df) {

  # Check for correct columns
  cols <- c("iso3c", "year", "indicator", "value", "note", "source")
  if (!isTRUE(all.equal(names(df), cols))) {
    rlang::abort("`df` contains invalid columns.")
  }
}