#' Data Vacia missing
#' xD
#' @param data Data
#' @param por Porcentaje de decision
#' @param plot Muestra grafico
#' @return \code{Data Science}.
#' @author \strong{Luis F. Maron}
#' @examples
#' ##-----Ejemplito------
#' vaciosxD(data, 0.6, F)
#' vaciosxD(data, 0.6, T)
#' @export
vaciosxD <- function(data, por = 0.7, plot = F){
####Luis Maron####
library(ggplot2)
t <- sort(sapply(data, function(x){sum(is.na(x)/length(x))}),decreasing = T)
t <- t[t > por]
if(length(t) == 0) return(cat("\n\t** LA DATA ESTA FULL xD**"))
print(t)
f <- row.names(data.frame(t))
sort1 <- data.frame("variable"=f, t, "num"=1:length(t))
m <- ggplot(sort1 , aes(num,t, col = variable))+ geom_point()+ ggtitle("Variables ordenadas datos faltantes %",subtitle = "LFMI ;)") + geom_text(aes(label=variable),hjust=0, vjust=0) + geom_hline(yintercept = c(por,1), col = "cyan4") + labs(y = " % ");
if (plot == T) return(m) else return(f)
}
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