R/readOECD.R

In pik-piam/moinput: Model Operations Input Data Library

#' Read OECD GDP / ratio PPP2MER
#' 
#' Read-in GDP or ratio PPP2MER data xlsx file from OECD as magclass object
#' 
#' 
#' @param subtype data subtype. Either "gdp" or "ratioPM"
#' @return magpie object of the GDP data
#' @author Lavinia Baumstark
#' @importFrom readxl read_excel
#' @seealso \code{\link{readSource}}
#' @examples
#' 
#' \dontrun{ 
#' a <- readSource("OECD","gdp")
#' a <- readSource("OECD","ratioPM")
#' 
#' }
#' 
readOECD <- function(subtype) {
  files <- c(gdp       = "OECD_v9_25-3-13-3.xlsx",
             ratioPM   = "OECD-WB_PPP-MER2005_conversion_rates.xlsx",
             riskClass = "cre-crc-current-english.xlsx" )
  
  file <- toolSubtypeSelect(subtype,files)
  
  data <- as.data.frame(read_excel(file))
  
  if(subtype=="gdp") {
    data <- data[data$Variable=="GDP|PPP",]
    data <- data[,c(-1,-4,-5)]  # should be done better?
    x <- as.magpie(data)
    getNames(x) <- paste("gdp_",gsub("_v[[:alnum:],[:punct:]]*","",getNames(x)),sep="")
  } else if(subtype=="ratioPM") {
    data <- data[,c(1,2)]
    data[,2] <- as.numeric(data[,2])
    colnames(data) <- c("Region","y2005") #automated?
    x <- as.magpie(data)   
  } else if(subtype=="riskClass") {
    # delete data for Kosovo
    data <- data[-which(data$`Country Name (1)`== "Kosovo"),]
    # delete not needed information
    data$`Country Name (1)`        <- NULL
    data$Notes                     <- NULL
    data$`Previous Classification` <- NULL
    # transform into numeric
    data$`Current Prevailing Classification` <- as.numeric(data$`Current Prevailing Classification`)
    # transfer into a magpie object
    x <- as.magpie(data)
    getSets(x)[1] <- "country"
  }  
    
  return(x)
}