#' prepareForAnalysis
#'
#' creates new columns useful to analyze data
#' @param data
#'
#' @return
#' @export
#'
#' @examples
prepareForAnalysis <-
function(data){
data %>%
mutate(PriceByM2Construccion = PriceInUSD / MtsConstruccion ) %>%
##filter( 300 <= PriceByM2Construccion & PriceByM2Construccion <= 1700 )
group_by(Provincia) %>%
mutate(NormalizedPriceByM2Construccion = as.vector(scale(PriceByM2Construccion) ))
}
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