R/pjp_estadisticos_basicos.R

In perezp44/pjpv.curso.R.2022: Paquete de apoyo a mis cursos

#' @title Crea un resumen de un data.frame.
#' @description Para cada variable del df calcula: número y porcentaje de valores cero (q_zeros and p_zeros respectevly). Same metrics for NA values (q_NA and p_na). Last two columns indicates data type and quantity of unique values.
#' This function uses a df as inputs and returns a dataframe with the names and some chracteristics of the variables (colums) of the input dataframe. By the way, this function comes from the funModeling package made by Pablo Casas <pabloc@datascienceheroes.com>, gracias Pablo!! Solo le he añadido la opcion por defecto print=FALSE y modificado alguna cosa menor. Lo dejo tal cual para no tener dependencias
#' This function print and return the results.
#' @param data  (a data frame)
#' @param print (default to FALSE)
#' @export
#' @examples
#' pjp_estadisticos_basicos(cars)


pjp_estadisticos_basicos <- function(data, print = FALSE) {
  df_status = data.frame(
    q_zeros = sapply(data, function(x) sum(x == 0,na.rm = TRUE)),
    p_zeros = round(100*sapply(data, function(x) sum(x == 0,na.rm = TRUE))/nrow(data),2),
    q_na = sapply(data, function(x) sum(is.na(x))),
    p_na = round(100*sapply(data, function(x) sum(is.na(x)))/nrow(data),2),
    type = sapply(data, function(x) class(x)[1] ),
    unique = sapply(data, function(x) sum(!is.na(unique(x)))),
    min = sapply(data, function(x) ifelse( is.numeric(x), round(min(x,na.rm = TRUE),2), NA)),
    max = sapply(data, function(x) ifelse( is.numeric(x), round(max(x,na.rm = TRUE),2), NA)),
    mean = sapply(data, function(x) ifelse( is.numeric(x), round(mean(x,na.rm = TRUE),2), NA)),
    sd = sapply(data, function(x) ifelse( is.numeric(x), round(sd(x,na.rm = TRUE),2), NA))

  )
  ## Create new variable for column name
  df_status$variable = rownames(df_status)
  rownames(df_status) = NULL

  df_status$NN <- nrow(data)
  df_status$NN_ok <- df_status$NN - df_status$q_na

  ## Reordering columns
  df_status = df_status[, c(11,1,2,3,4,5,6,7,8,9,10,12, 13)]
  if (print == 1) {print(df_status)}
  return(df_status)
}