R/fct_descriptivasFuntions.R
In PAD-LAB/Ro-Statistics: Ro-Statistics
Defines functions
calculoFrecuencias
calculoVariables
make_factors
modafuntion
#' descriptivasFuntions
#'
#' @description A fct function
#'
#' @return The return value, if any, from executing the function.
#'
#' @noRd
#'
#'
modafuntion <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
make_factors <- function(data, max_levels,min_levels) {
# convert all columns in <data> that are not already factors
# and that have fewer than <max_levels> distinct values into factors.
# If the column is numeric, it becomes an ordered factor.
stopifnot(is.data.frame(data))
for(n in names(data)){
if(!is.factor(data[[n]]) && (length(unique(data[[n]])) <= min_levels) ){
data[[n]] <- as.factor(data[[n]]) }
if(!is.factor(data[[n]]) && (length(unique(data[[n]])) >= min_levels && length(unique(data[[n]])) <= max_levels) ){
#golem::golem::print_dev("Ordered")
#golem::golem::print_dev(unique(data[[n]]))
data[[n]] <- ordered(data[[n]], levels = unique(data[[n]])) }
}
data
}
calculoVariables <- function(session,dforiginal,Dependiente,Agrupamiento,Mean,Mediana,Moda,Suma,
SE,MAD,Iqr,Rango,Maximo,DsvEstandar,MADRobust,Varianza,Minimo,
Quartiles,PuntoCorte,PuntoCorteValue,Percentil,PercentilValue){
df <- dforiginal
if ( length(names(Agrupamiento)) > 0 )
{
NoValidos = c()
Validos =c()
Mean_vector = c()
Mediana_vector = c()
Moda_vector =c()
Suma_vector = c()
SE.MEAN_vector= c()
MAD_vector= c()
IQR_vector= c()
Rango_vector = c()
rangoCalc =c()
Max_vector = c()
Desv.Est_vector = c()
MadRobust_vector =c()
Varianza_vector = c()
Min_vector = c()
Quartiles_vector = c()
PuntoCorte_vector = c()
Percentil_vector = c()
PercentilValue_names = c()
summaryVariableTable2 = c()
golem::print_dev(" Con variable de agrupamiento")
nombreAgrupamiento <- c(names(Agrupamiento))
nombreDependiente <- c(names(Dependiente))
numeroVariablesDependientes <-length(nombreDependiente)
numeroVariablesAgrupamiento <- length(nombreAgrupamiento )
for (i in 1:length(Dependiente)){
if(class(Dependiente[[i]])=="numeric"){
df$temp <- as.numeric(Dependiente[[i]])
golem::print_dev("AHORA ES NUMERICO EL NUMERICCO")
}
else{
df$temp <- ( as.numeric(Dependiente[[i]]) -1)
golem::print_dev("AHORA ES NUMERICO EL CATEGORICO")
}
# varActual <- paste0( nombreDependiente[i] ," ~ ",paste(nombreAgrupamiento, collapse = '+'))
varActual <- paste0( "temp" ," ~ ",paste(nombreAgrupamiento, collapse = '+'))
golem::print_dev(varActual)
golem::print_dev(aggregate( eval(parse(text = varActual )) , df, sum))
rowSVariables <- aggregate( eval(parse(text = varActual )) , df, sum)[c(seq(1:(numeroVariablesAgrupamiento)))]
if(Mean==TRUE){
golem::print_dev("Si es True MEAN")
golem::print_dev( aggregate( eval(parse(text = varActual )) , df, mean) )
Mean_vector[i] <- list( round(aggregate( eval(parse(text = varActual )) , df, mean)[[(numeroVariablesAgrupamiento+1)]] ,3) )
}
if(Mediana==TRUE){
golem::print_dev("Si es True Mediana")
Mediana_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, median)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Moda==TRUE){
golem::print_dev("si es moda vector")
Moda_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, modafuntion )[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Suma==TRUE){
golem::print_dev("Si es True Suma")
Suma_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, sum)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(SE==TRUE){
golem::print_dev("Si es True SE")
SE.MEAN_vector[i]<-list(round(aggregate( eval(parse(text = varActual )) , df, rapportools::se.mean)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(MAD==TRUE){
golem::print_dev("Si es True MAD con factor")
MAD_vector[i]<- list( aggregate( eval(parse(text = varActual )) , df, mad ,constant = 1)[[(numeroVariablesAgrupamiento+1)]] )
print(MAD_vector[i])
# MAD_vector[i]<- list(aggregate( eval(parse(text = varActual )) , df, FUN = "mad",constant = 1))
}
if(Iqr==TRUE){
golem::print_dev("Si es True IQR")
IQR_vector[i] <- list(round(aggregate( eval(parse(text = varActual )) , df, IQR)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Rango==TRUE){
golem::print_dev("Si es True Rango con Factor")
golem::print_dev(aggregate( eval(parse(text = varActual )) , df, range)[[(numeroVariablesAgrupamiento+1)]])
rangoCalc [i]<- list(as.list(data.frame(t( aggregate( eval(parse(text = varActual )) , df, range)[[(numeroVariablesAgrupamiento+1)]] ))))
for (j in 1:length(rangoCalc[[1]])) {
Rango_vector[j] =toString( unlist(rangoCalc[[1]][j]) )
}
golem::print_dev(Rango_vector)
}
if(Maximo==TRUE){
golem::print_dev("Si es True Maximo")
Max_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, max)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(DsvEstandar==TRUE){
golem::print_dev("Si es True DsvEstandar")
Desv.Est_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, sd)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(MADRobust==TRUE){
golem::print_dev("Si es True MADRobust")
MadRobust_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, mad ,constant = 1.4826)[[(numeroVariablesAgrupamiento+1)]],3))
# MadRobust_vector[i]
}
if(Varianza==TRUE){
golem::print_dev("Si es True Varianza")
Varianza_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, var)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Minimo==TRUE){
golem::print_dev("Si es True Minimo")
Min_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, min)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Quartiles==TRUE){
golem::print_dev("Si es True Quartiles con factor")
# golem::print_dev(aggregate( eval(parse(text = varActual )) , df, FUN = "quantile",na.rm = TRUE))
Quartiles_vector[i] <- list(round(aggregate( eval(parse(text = varActual )) , df, quantile,na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]][,c(-1,-5)],3))
# golem::print_dev(c(t(dfff[[(numeroVariablesAgrupamiento+1)]])))
# Quartiles_vector[i]
}
if(PuntoCorte==TRUE){
if(as.numeric(PuntoCorteValue) >= 2){
golem::print_dev("Si es True PuntodeCorte con factor")
stepValue <-(1/(as.numeric(PuntoCorteValue)))
#golem::print_dev(stepValue)
#PuntoCorte_vector[i] <- list(quantile(varActual, prob=seq(0,1,(1/(as.numeric(PuntoCorteValue)))) ,na.rm = TRUE))
# golem::print_dev(aggregate( eval(parse(text = varActual )) , df, FUN = "quantile", prob=seq(0,1,stepValue ) ,na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]])
PuntoCorte_vector[i] <- list(round(aggregate( eval(parse(text = varActual )) , df, quantile, prob=seq(0,1,stepValue ) ,na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]] [,c(-1,-(as.numeric(PuntoCorteValue) + 1))],3))
}
#golem::print_dev("Si es True PuntoCorte")
}
if(Percentil==TRUE){
golem::print_dev("Si es True Percentil")
if(as.numeric(PercentilValue) >= 2){
#golem::print_dev( aggregate( eval(parse(text = varActual )) , df, FUN= "quantile",prob=seq(0,1,length = 101),na.rm = TRUE) )
valores <- aggregate( eval(parse(text = varActual )) , df, quantile,prob=seq(0,1,length = 101),na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]]
Percentil_vector[i] <- list(round(valores[,(as.numeric(PercentilValue) + (1))],3))
PercentilValue_names[i] <- colnames(valores)[(as.numeric(PercentilValue) + (1))]
# Percentil_vector[i] <- valores[as.numeric(PercentilValue)]
}
}
Validos[i] <- list(round(aggregate( (eval(parse(text = varActual ))) , df, length )[[(numeroVariablesAgrupamiento+1)]],3))
# golem::print_dev(Validos)
NoValidos [i] <- list(round(aggregate( (eval(parse(text = varActual ))) , df, function(x) {sum(is.na(x))}, na.action = NULL )[[(numeroVariablesAgrupamiento+1)]],3))
summaryVariableTable <- data.frame(NoValidos[i],Validos[i])
colnames(summaryVariableTable) <- c("Missing","Validos")
if(Mean==TRUE){summaryVariableTable$Media=unlist(Mean_vector[i])} else{summaryVariableTable$Media <- NULL}
if(DsvEstandar==TRUE){summaryVariableTable$Dsv.Est=unlist(Desv.Est_vector[1])} else{summaryVariableTable$Dsv.Est <- NULL}
if(Minimo==TRUE){summaryVariableTable$Minimo=unlist(Min_vector[i])} else{summaryVariableTable$Minimo <- NULL}
if(Maximo==TRUE){summaryVariableTable$Maximo=unlist(Max_vector[i])} else{summaryVariableTable$Maximo <- NULL}
if(Mediana==TRUE){summaryVariableTable$Mediana=unlist(Mediana_vector[i])} else{summaryVariableTable$Mediana <- NULL}
if(Moda==TRUE){summaryVariableTable$Moda=unlist(Moda_vector[i])} else{summaryVariableTable$Moda <- NULL}
if(Suma==TRUE){summaryVariableTable$Suma=unlist(Suma_vector[i])} else{summaryVariableTable$Suma <- NULL}
if(SE==TRUE){summaryVariableTable$SE.Media=unlist(SE.MEAN_vector[i])} else{summaryVariableTable$SE.Media <- NULL}
if(MAD==TRUE){summaryVariableTable$MAD=unlist(MAD_vector[i])} else{summaryVariableTable$MAD <- NULL}
if(Iqr==TRUE){summaryVariableTable$IQR=unlist(IQR_vector[i])} else{summaryVariableTable$IQR <- NULL}
if(Rango==TRUE){summaryVariableTable$Rango=unlist(Rango_vector[i])} else{summaryVariableTable$Rango <- NULL}
if(MADRobust==TRUE){summaryVariableTable$MAD.Escalado=unlist(MadRobust_vector[i])} else{summaryVariableTable$MAD.Escalado <- NULL}
if(Varianza==TRUE){summaryVariableTable$Varianza=unlist(Varianza_vector[i])} else{summaryVariableTable$Varianza <- NULL}
if(Quartiles==TRUE){
summaryVariableTable$"25%" = unlist(Quartiles_vector[[i]][,1])
summaryVariableTable$"50%" = unlist(Quartiles_vector[[i]][,2])
summaryVariableTable$"75%" = unlist(Quartiles_vector[[i]][,3])
} else{
summaryVariableTable$"25%" = NULL
summaryVariableTable$"50%" = NULL
summaryVariableTable$"75%" = NULL
}
if(PuntoCorte==TRUE)
{
golem::print_dev( colnames(unlist(PuntoCorte_vector[[1]])) )
lengthNames <-length( colnames(unlist(PuntoCorte_vector[[1]])) )
for(j in 1:lengthNames){
# golem::print_dev(paste0(colnames(unlist(PuntoCorte_vector[[1]]))[j]," "))
# golem::print_dev(PuntoCorte_vector[[1]][,j])
summaryVariableTable[, paste0(colnames(unlist(PuntoCorte_vector[[1]]))[j]," ")] <- unlist( PuntoCorte_vector[[1]][,j])
}
} else{
lengthNames <-length( colnames(unlist(PuntoCorte_vector[[1]])) )
if(lengthNames == 0){
}else{
for(i in 1:lengthNames){
summaryVariableTable[, paste0(colnames(unlist(PuntoCorte_vector[[1]]))[i]," ")] = NULL
}
}
}
if(Percentil==TRUE)
{
# golem::print_dev(i)
# golem::print_dev( paste0(PercentilValue_names[i]," Percentil") )
# golem::print_dev(Percentil_vector[[i]])
# golem::print_dev(paste0(PercentilValue_names[1]," Percentil"))
summaryVariableTable[, paste0(PercentilValue_names[i]," Percentil")] <- Percentil_vector[[i]]
}else
{
summaryVariableTable[, paste0(PercentilValue_names," Percentil")] <- NULL
}
colnamesSummary <- colnames(summaryVariableTable)
length(rownames(summaryVariableTable))
nombreMetodosDescriptivos <- rep(colnamesSummary, each= length(rownames(summaryVariableTable)))
golem::print_dev(summaryVariableTable)
repVacios <- rep("", (length(rownames(summaryVariableTable)) -1 ))
summaryVariableTable2[i] <- data.frame(unlist(summaryVariableTable))
}
nombreMetodos<- c()
for (i in 1: length(colnamesSummary))
{
golem::print_dev(i)
nombreMetodos <- append(nombreMetodos,colnamesSummary[i])
nombreMetodos <- append(nombreMetodos,repVacios)
}
#summaryVariableTable2[i] <- data.frame(nombreMetodosDescriptivos,rowSVariables,unlist(summaryVariableTable))
finalNames <- c(" ",nombreAgrupamiento,nombreDependiente )
golem::print_dev(finalNames)
finalDescriptivas <- data.frame(nombreMetodos,rowSVariables,summaryVariableTable2)
colnames(finalDescriptivas) <- finalNames
summaryVariableTable3 <- dplyr::mutate(finalDescriptivas, dplyr::across(where(is.numeric), round, 3))
}else {
golem::print_dev("Sin variable de Grupo Descriptivas")
Variable=c( names(Dependiente))
NoValidos = c()
Validos =c()
Mean_vector = c()
Mediana_vector = c()
Moda_vector =c()
Suma_vector = c()
SE.MEAN_vector= c()
MAD_vector= c()
IQR_vector= c()
Rango_vector = c()
Max_vector = c()
Desv.Est_vector = c()
MadRobust_vector =c()
Varianza_vector = c()
Min_vector = c()
Quartiles_vector = c()
PuntoCorte_vector = c()
Percentil_vector = c()
PercentilValue_names = c()
for (i in 1:length(Dependiente)){
defaultSelect <- class(Dependiente[[i]])
golem::print_dev("ASSSSSSSSSSSSSDDDDDDDDD")
golem::print_dev(defaultSelect)
golem::print_dev("ASSSSSSSSSSSSSDDDDDDDDD")
if(defaultSelect=="numeric"){
varActual <- (as.numeric(Dependiente[[i]]))
}
else{
varActual <- (as.numeric(Dependiente[[i]]) )
}
golem::print_dev(utils::str(varActual))
if(Mean==TRUE){
golem::print_dev("Si es True MEAN")
Mean_vector[i] <- round( mean(varActual, na.rm = TRUE),digits = 3 )
golem::print_dev(Mean_vector[i])
}
if(Mediana==TRUE){
golem::print_dev("Si es True Mediana")
Mediana_vector[i] <-round( median(varActual,na.rm = TRUE),digits = 3)
}
if(Moda==TRUE){
Moda_vector <- round( modafuntion(varActual),digits = 3)
}
if(Suma==TRUE){
golem::print_dev("Si es True Suma")
Suma_vector[i] <-round( sum(varActual,na.rm = TRUE), digits = 3)
}
if(SE==TRUE){
golem::print_dev("Si es True SE")
SE.MEAN_vector[i]<- round( rapportools::se.mean(varActual), digits = 3)
}
if(MAD==TRUE){
golem::print_dev("Si es True MAD")
MAD_vector[i]<- round( mad(varActual,constant = 1,na.rm = TRUE), digits = 3)
}
if(Iqr==TRUE){
golem::print_dev("Si es True IQR")
IQR_vector[i]<- round( IQR(varActual,na.rm = TRUE), digits = 3)
}
if(Rango==TRUE){
golem::print_dev("Si es True Rango")
#golem::print_dev(range(varActual))
Rango_vector[i]<-paste(range(varActual,na.rm = TRUE), collapse = " ")
}
if(Maximo==TRUE){
golem::print_dev("Si es True Maximo")
Max_vector[i]<- round( max(varActual,na.rm = TRUE), digits = 3)
}
if(DsvEstandar==TRUE){
golem::print_dev("Si es True DsvEstandar")
Desv.Est_vector[i]<-round( sd(varActual,na.rm = TRUE), digits = 3)
}
if(MADRobust==TRUE){
golem::print_dev("Si es True MADRobust")
MadRobust_vector[i] <-round( mad(varActual,constant = 1.4826,na.rm = TRUE), digits = 3)
}
if(Varianza==TRUE){
golem::print_dev("Si es True Varianza")
Varianza_vector[i]<-round( var(varActual,na.rm = TRUE), digits = 3)
}
if(Minimo==TRUE){
golem::print_dev("Si es True Minimo")
Min_vector[i]<- round( min(varActual,na.rm = TRUE), digits = 3)
}
if(Quartiles==TRUE){
golem::print_dev("Si es True Quartiles")
Quartiles_vector[i] <- list(round(quantile(varActual,na.rm = TRUE),3))
print(quantile(varActual,na.rm = TRUE))
}
if(PuntoCorte==TRUE){
if(as.numeric(PuntoCorteValue) >= 2){
golem::print_dev("Si es True PuntodeCorte")
stepValue <-(1/(as.numeric(PuntoCorteValue)))
#golem::print_dev(stepValue)
#PuntoCorte_vector[i] <- list(quantile(varActual, prob=seq(0,1,(1/(as.numeric(PuntoCorteValue)))) ,na.rm = TRUE))
PuntoCorte_vector[i] <- list(round(quantile(varActual, prob=seq(0,1,stepValue ) ,na.rm = TRUE),3) )
}
#golem::print_dev("Si es True PuntoCorte")
}
if(Percentil==TRUE){
golem::print_dev("Si es True Percentil redondeado")
if(as.numeric(PercentilValue) >= 2){
valores <- quantile(varActual, prob=seq(0,1,length = 101) ,na.rm = TRUE)
golem::print_dev(valores)
PercentilValue_names <- names(valores)
Percentil_vector[i] <- round(valores[as.numeric(PercentilValue)],3)
}
}
NoValidos[i] <- sum(is.na(varActual))
Validos[i] <- length(varActual) - NoValidos[i]
}
golem::print_dev(PercentilValue_names)
summaryVariableTable <- data.frame(NoValidos,Validos)
if(Mean==TRUE){summaryVariableTable$Media= Mean_vector} else{summaryVariableTable$Media <- NULL}
if(DsvEstandar==TRUE){summaryVariableTable$Dsv.Est=Desv.Est_vector} else{summaryVariableTable$Dsv.Est <- NULL}
if(Minimo==TRUE){summaryVariableTable$Minimo=Min_vector} else{summaryVariableTable$Minimo <- NULL}
if(Maximo==TRUE){summaryVariableTable$Maximo=Max_vector} else{summaryVariableTable$Maximo <- NULL}
if(Mediana==TRUE){summaryVariableTable$Mediana=Mediana_vector} else{summaryVariableTable$Mediana <- NULL}
if(Moda==TRUE){summaryVariableTable$Moda=Moda_vector} else{summaryVariableTable$Moda <- NULL}
if(Suma==TRUE){summaryVariableTable$Suma=Suma_vector} else{summaryVariableTable$Suma <- NULL}
if(SE==TRUE){summaryVariableTable$SE.Media=SE.MEAN_vector} else{summaryVariableTable$SE.Media <- NULL}
if(MAD==TRUE){summaryVariableTable$MAD=MAD_vector} else{summaryVariableTable$MAD <- NULL}
if(Iqr==TRUE){summaryVariableTable$IQR=IQR_vector} else{summaryVariableTable$IQR <- NULL}
if(Rango==TRUE){summaryVariableTable$Rango=Rango_vector} else{summaryVariableTable$Rango <- NULL}
if(MADRobust==TRUE){summaryVariableTable$MAD.Escalado=MadRobust_vector} else{summaryVariableTable$MAD.Escalado <- NULL}
if(Varianza==TRUE){summaryVariableTable$Varianza=Varianza_vector} else{summaryVariableTable$Varianza <- NULL}
if(Quartiles==TRUE){
summaryVariableTable$"25%" = unlist(Quartiles_vector)[2]
summaryVariableTable$"50%" = unlist(Quartiles_vector)[3]
summaryVariableTable$"75%" = unlist(Quartiles_vector)[4]
}
else{
summaryVariableTable$"25%" = NULL
summaryVariableTable$"50%" = NULL
summaryVariableTable$"75%" = NULL
}
if(PuntoCorte==TRUE)
{
golem::print_dev(names(unlist(PuntoCorte_vector)))
lenghtNamesPC <-length(names(unlist(PuntoCorte_vector)))
for(i in seq(2, as.numeric(lenghtNamesPC) - 1, by=1)){
summaryVariableTable[, paste0(names(unlist(PuntoCorte_vector))[i]," ")] <- unlist(PuntoCorte_vector)[i]
}
}
else{
lenghtNamesPC <-length(names(unlist(PuntoCorte_vector)))
if(lenghtNamesPC == 0){
}else{
for(i in 1:lenghtNamesPC-1){
summaryVariableTable[paste0(names(unlist(PuntoCorte_vector))[i]," ")] = NULL
#names(unlist(PuntoCorte_vector))
}
}
}
if(Percentil==TRUE)
{
summaryVariableTable[, paste0(unlist(stringr::str_split(PercentilValue_names[as.numeric(PercentilValue) + 1],""))[1]," Percentil")] <- Percentil_vector
}
else
{
summaryVariableTable[, paste0(unlist(stringr::str_split(PercentilValue_names[as.numeric(PercentilValue) + 1],""))[1]," Percentil")] <- NULL
}
summaryVariableTable2 <- data.frame(t(summaryVariableTable))
summaryVariableTable2 <- dplyr::mutate(summaryVariableTable2, dplyr::across(where(is.numeric), as.character))
golem::print_dev(str(summaryVariableTable2))
rownames(summaryVariableTable2) <- NULL
golem::print_dev(colnames(summaryVariableTable))
summaryVariableTable3 <- data.frame( colnames(summaryVariableTable), summaryVariableTable2 )
colnames(summaryVariableTable3) <- c(" ",Variable)
#golem::print_dev(str(summaryVariableTable3))
#finalDescriptivas <- dplyr::mutate(summaryVariableTable3, dplyr::across(where(is.numeric), as.character))
}
return(summaryVariableTable3)
}
calculoFrecuencias <- function(session,df,frecuenciaEnable) {
if (frecuenciaEnable == TRUE) {
#nbreaks <- pretty(range.default(as.numeric(df_sel()[[i]])),n = nclass.Sturges(as.numeric(df_sel()[[i]])),min.n = 1)
tablas = c()
nombreVariable <- names(df)[[1]]
golem::print_dev(nombreVariable)
tablaFrecuencia <- summarytools::freq(df[[1]], order = "freq")
# tablaFrecuencia <- summarytools::freq(df, order = "freq")
elemntos <- attributes(tablaFrecuencia)[[2]][[1]]
golem::print_dev(elemntos)
freq <- tablaFrecuencia[,1]
validos <- tablaFrecuencia[,2]
validosCum <- tablaFrecuencia[,3]
total <- tablaFrecuencia[,4]
totalCum <- tablaFrecuencia[,5]
descriptivasFrecuencia <- data.frame(elemntos,freq,validos,totalCum)
row.names(descriptivasFrecuencia) <- NULL
golem::print_dev(descriptivasFrecuencia)
descriptivasFrecuencia <- dplyr::mutate(descriptivasFrecuencia, dplyr::across(where(is.numeric), round, 3))
colnames(descriptivasFrecuencia) <- c(nombreVariable,"Frecuencia","Porcentaje Validos","Porcentaje Acumulado")
#newdata <- mtcars[order(mpg),]
# tablas[[i]] <- df
return(descriptivasFrecuencia)
}
if(frecuenciaEnable == FALSE)
{
elemntos <- " "
freq <- " "
validos <- " "
validosCum <- " "
total <- " "
totalCum <- " "
descriptivasFrecuencia <- data.frame(elemntos,freq,validos,totalCum)
row.names(descriptivasFrecuencia) <- NULL
golem::print_dev(descriptivasFrecuencia)
descriptivasFrecuencia <- dplyr::mutate(descriptivasFrecuencia, dplyr::across(where(is.numeric), round, 3))
colnames(descriptivasFrecuencia) <- c("nombreVariable","Frecuencia","Procentaje Validos","Procentaje Acumulado")
return(descriptivasFrecuencia)
}
}
PAD-LAB/Ro-Statistics documentation built on April 28, 2022, 3:40 p.m.
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Defines functions calculoFrecuencias calculoVariables make_factors modafuntion
#' descriptivasFuntions
#'
#' @description A fct function
#'
#' @return The return value, if any, from executing the function.
#'
#' @noRd
#'
#'
modafuntion <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
make_factors <- function(data, max_levels,min_levels) {
# convert all columns in <data> that are not already factors
# and that have fewer than <max_levels> distinct values into factors.
# If the column is numeric, it becomes an ordered factor.
stopifnot(is.data.frame(data))
for(n in names(data)){
if(!is.factor(data[[n]]) && (length(unique(data[[n]])) <= min_levels) ){
data[[n]] <- as.factor(data[[n]]) }
if(!is.factor(data[[n]]) && (length(unique(data[[n]])) >= min_levels && length(unique(data[[n]])) <= max_levels) ){
#golem::golem::print_dev("Ordered")
#golem::golem::print_dev(unique(data[[n]]))
data[[n]] <- ordered(data[[n]], levels = unique(data[[n]])) }
}
data
}
calculoVariables <- function(session,dforiginal,Dependiente,Agrupamiento,Mean,Mediana,Moda,Suma,
SE,MAD,Iqr,Rango,Maximo,DsvEstandar,MADRobust,Varianza,Minimo,
Quartiles,PuntoCorte,PuntoCorteValue,Percentil,PercentilValue){
df <- dforiginal
if ( length(names(Agrupamiento)) > 0 )
{
NoValidos = c()
Validos =c()
Mean_vector = c()
Mediana_vector = c()
Moda_vector =c()
Suma_vector = c()
SE.MEAN_vector= c()
MAD_vector= c()
IQR_vector= c()
Rango_vector = c()
rangoCalc =c()
Max_vector = c()
Desv.Est_vector = c()
MadRobust_vector =c()
Varianza_vector = c()
Min_vector = c()
Quartiles_vector = c()
PuntoCorte_vector = c()
Percentil_vector = c()
PercentilValue_names = c()
summaryVariableTable2 = c()
golem::print_dev(" Con variable de agrupamiento")
nombreAgrupamiento <- c(names(Agrupamiento))
nombreDependiente <- c(names(Dependiente))
numeroVariablesDependientes <-length(nombreDependiente)
numeroVariablesAgrupamiento <- length(nombreAgrupamiento )
for (i in 1:length(Dependiente)){
if(class(Dependiente[[i]])=="numeric"){
df$temp <- as.numeric(Dependiente[[i]])
golem::print_dev("AHORA ES NUMERICO EL NUMERICCO")
}
else{
df$temp <- ( as.numeric(Dependiente[[i]]) -1)
golem::print_dev("AHORA ES NUMERICO EL CATEGORICO")
}
# varActual <- paste0( nombreDependiente[i] ," ~ ",paste(nombreAgrupamiento, collapse = '+'))
varActual <- paste0( "temp" ," ~ ",paste(nombreAgrupamiento, collapse = '+'))
golem::print_dev(varActual)
golem::print_dev(aggregate( eval(parse(text = varActual )) , df, sum))
rowSVariables <- aggregate( eval(parse(text = varActual )) , df, sum)[c(seq(1:(numeroVariablesAgrupamiento)))]
if(Mean==TRUE){
golem::print_dev("Si es True MEAN")
golem::print_dev( aggregate( eval(parse(text = varActual )) , df, mean) )
Mean_vector[i] <- list( round(aggregate( eval(parse(text = varActual )) , df, mean)[[(numeroVariablesAgrupamiento+1)]] ,3) )
}
if(Mediana==TRUE){
golem::print_dev("Si es True Mediana")
Mediana_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, median)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Moda==TRUE){
golem::print_dev("si es moda vector")
Moda_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, modafuntion )[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Suma==TRUE){
golem::print_dev("Si es True Suma")
Suma_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, sum)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(SE==TRUE){
golem::print_dev("Si es True SE")
SE.MEAN_vector[i]<-list(round(aggregate( eval(parse(text = varActual )) , df, rapportools::se.mean)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(MAD==TRUE){
golem::print_dev("Si es True MAD con factor")
MAD_vector[i]<- list( aggregate( eval(parse(text = varActual )) , df, mad ,constant = 1)[[(numeroVariablesAgrupamiento+1)]] )
print(MAD_vector[i])
# MAD_vector[i]<- list(aggregate( eval(parse(text = varActual )) , df, FUN = "mad",constant = 1))
}
if(Iqr==TRUE){
golem::print_dev("Si es True IQR")
IQR_vector[i] <- list(round(aggregate( eval(parse(text = varActual )) , df, IQR)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Rango==TRUE){
golem::print_dev("Si es True Rango con Factor")
golem::print_dev(aggregate( eval(parse(text = varActual )) , df, range)[[(numeroVariablesAgrupamiento+1)]])
rangoCalc [i]<- list(as.list(data.frame(t( aggregate( eval(parse(text = varActual )) , df, range)[[(numeroVariablesAgrupamiento+1)]] ))))
for (j in 1:length(rangoCalc[[1]])) {
Rango_vector[j] =toString( unlist(rangoCalc[[1]][j]) )
}
golem::print_dev(Rango_vector)
}
if(Maximo==TRUE){
golem::print_dev("Si es True Maximo")
Max_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, max)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(DsvEstandar==TRUE){
golem::print_dev("Si es True DsvEstandar")
Desv.Est_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, sd)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(MADRobust==TRUE){
golem::print_dev("Si es True MADRobust")
MadRobust_vector[i] <- list(round( aggregate( eval(parse(text = varActual )) , df, mad ,constant = 1.4826)[[(numeroVariablesAgrupamiento+1)]],3))
# MadRobust_vector[i]
}
if(Varianza==TRUE){
golem::print_dev("Si es True Varianza")
Varianza_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, var)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Minimo==TRUE){
golem::print_dev("Si es True Minimo")
Min_vector[i]<- list(round(aggregate( eval(parse(text = varActual )) , df, min)[[(numeroVariablesAgrupamiento+1)]],3))
}
if(Quartiles==TRUE){
golem::print_dev("Si es True Quartiles con factor")
# golem::print_dev(aggregate( eval(parse(text = varActual )) , df, FUN = "quantile",na.rm = TRUE))
Quartiles_vector[i] <- list(round(aggregate( eval(parse(text = varActual )) , df, quantile,na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]][,c(-1,-5)],3))
# golem::print_dev(c(t(dfff[[(numeroVariablesAgrupamiento+1)]])))
# Quartiles_vector[i]
}
if(PuntoCorte==TRUE){
if(as.numeric(PuntoCorteValue) >= 2){
golem::print_dev("Si es True PuntodeCorte con factor")
stepValue <-(1/(as.numeric(PuntoCorteValue)))
#golem::print_dev(stepValue)
#PuntoCorte_vector[i] <- list(quantile(varActual, prob=seq(0,1,(1/(as.numeric(PuntoCorteValue)))) ,na.rm = TRUE))
# golem::print_dev(aggregate( eval(parse(text = varActual )) , df, FUN = "quantile", prob=seq(0,1,stepValue ) ,na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]])
PuntoCorte_vector[i] <- list(round(aggregate( eval(parse(text = varActual )) , df, quantile, prob=seq(0,1,stepValue ) ,na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]] [,c(-1,-(as.numeric(PuntoCorteValue) + 1))],3))
}
#golem::print_dev("Si es True PuntoCorte")
}
if(Percentil==TRUE){
golem::print_dev("Si es True Percentil")
if(as.numeric(PercentilValue) >= 2){
#golem::print_dev( aggregate( eval(parse(text = varActual )) , df, FUN= "quantile",prob=seq(0,1,length = 101),na.rm = TRUE) )
valores <- aggregate( eval(parse(text = varActual )) , df, quantile,prob=seq(0,1,length = 101),na.rm = TRUE)[[(numeroVariablesAgrupamiento+1)]]
Percentil_vector[i] <- list(round(valores[,(as.numeric(PercentilValue) + (1))],3))
PercentilValue_names[i] <- colnames(valores)[(as.numeric(PercentilValue) + (1))]
# Percentil_vector[i] <- valores[as.numeric(PercentilValue)]
}
}
Validos[i] <- list(round(aggregate( (eval(parse(text = varActual ))) , df, length )[[(numeroVariablesAgrupamiento+1)]],3))
# golem::print_dev(Validos)
NoValidos [i] <- list(round(aggregate( (eval(parse(text = varActual ))) , df, function(x) {sum(is.na(x))}, na.action = NULL )[[(numeroVariablesAgrupamiento+1)]],3))
summaryVariableTable <- data.frame(NoValidos[i],Validos[i])
colnames(summaryVariableTable) <- c("Missing","Validos")
if(Mean==TRUE){summaryVariableTable$Media=unlist(Mean_vector[i])} else{summaryVariableTable$Media <- NULL}
if(DsvEstandar==TRUE){summaryVariableTable$Dsv.Est=unlist(Desv.Est_vector[1])} else{summaryVariableTable$Dsv.Est <- NULL}
if(Minimo==TRUE){summaryVariableTable$Minimo=unlist(Min_vector[i])} else{summaryVariableTable$Minimo <- NULL}
if(Maximo==TRUE){summaryVariableTable$Maximo=unlist(Max_vector[i])} else{summaryVariableTable$Maximo <- NULL}
if(Mediana==TRUE){summaryVariableTable$Mediana=unlist(Mediana_vector[i])} else{summaryVariableTable$Mediana <- NULL}
if(Moda==TRUE){summaryVariableTable$Moda=unlist(Moda_vector[i])} else{summaryVariableTable$Moda <- NULL}
if(Suma==TRUE){summaryVariableTable$Suma=unlist(Suma_vector[i])} else{summaryVariableTable$Suma <- NULL}
if(SE==TRUE){summaryVariableTable$SE.Media=unlist(SE.MEAN_vector[i])} else{summaryVariableTable$SE.Media <- NULL}
if(MAD==TRUE){summaryVariableTable$MAD=unlist(MAD_vector[i])} else{summaryVariableTable$MAD <- NULL}
if(Iqr==TRUE){summaryVariableTable$IQR=unlist(IQR_vector[i])} else{summaryVariableTable$IQR <- NULL}
if(Rango==TRUE){summaryVariableTable$Rango=unlist(Rango_vector[i])} else{summaryVariableTable$Rango <- NULL}
if(MADRobust==TRUE){summaryVariableTable$MAD.Escalado=unlist(MadRobust_vector[i])} else{summaryVariableTable$MAD.Escalado <- NULL}
if(Varianza==TRUE){summaryVariableTable$Varianza=unlist(Varianza_vector[i])} else{summaryVariableTable$Varianza <- NULL}
if(Quartiles==TRUE){
summaryVariableTable$"25%" = unlist(Quartiles_vector[[i]][,1])
summaryVariableTable$"50%" = unlist(Quartiles_vector[[i]][,2])
summaryVariableTable$"75%" = unlist(Quartiles_vector[[i]][,3])
} else{
summaryVariableTable$"25%" = NULL
summaryVariableTable$"50%" = NULL
summaryVariableTable$"75%" = NULL
}
if(PuntoCorte==TRUE)
{
golem::print_dev( colnames(unlist(PuntoCorte_vector[[1]])) )
lengthNames <-length( colnames(unlist(PuntoCorte_vector[[1]])) )
for(j in 1:lengthNames){
# golem::print_dev(paste0(colnames(unlist(PuntoCorte_vector[[1]]))[j]," "))
# golem::print_dev(PuntoCorte_vector[[1]][,j])
summaryVariableTable[, paste0(colnames(unlist(PuntoCorte_vector[[1]]))[j]," ")] <- unlist( PuntoCorte_vector[[1]][,j])
}
} else{
lengthNames <-length( colnames(unlist(PuntoCorte_vector[[1]])) )
if(lengthNames == 0){
}else{
for(i in 1:lengthNames){
summaryVariableTable[, paste0(colnames(unlist(PuntoCorte_vector[[1]]))[i]," ")] = NULL
}
}
}
if(Percentil==TRUE)
{
# golem::print_dev(i)
# golem::print_dev( paste0(PercentilValue_names[i]," Percentil") )
# golem::print_dev(Percentil_vector[[i]])
# golem::print_dev(paste0(PercentilValue_names[1]," Percentil"))
summaryVariableTable[, paste0(PercentilValue_names[i]," Percentil")] <- Percentil_vector[[i]]
}else
{
summaryVariableTable[, paste0(PercentilValue_names," Percentil")] <- NULL
}
colnamesSummary <- colnames(summaryVariableTable)
length(rownames(summaryVariableTable))
nombreMetodosDescriptivos <- rep(colnamesSummary, each= length(rownames(summaryVariableTable)))
golem::print_dev(summaryVariableTable)
repVacios <- rep("", (length(rownames(summaryVariableTable)) -1 ))
summaryVariableTable2[i] <- data.frame(unlist(summaryVariableTable))
}
nombreMetodos<- c()
for (i in 1: length(colnamesSummary))
{
golem::print_dev(i)
nombreMetodos <- append(nombreMetodos,colnamesSummary[i])
nombreMetodos <- append(nombreMetodos,repVacios)
}
#summaryVariableTable2[i] <- data.frame(nombreMetodosDescriptivos,rowSVariables,unlist(summaryVariableTable))
finalNames <- c(" ",nombreAgrupamiento,nombreDependiente )
golem::print_dev(finalNames)
finalDescriptivas <- data.frame(nombreMetodos,rowSVariables,summaryVariableTable2)
colnames(finalDescriptivas) <- finalNames
summaryVariableTable3 <- dplyr::mutate(finalDescriptivas, dplyr::across(where(is.numeric), round, 3))
}else {
golem::print_dev("Sin variable de Grupo Descriptivas")
Variable=c( names(Dependiente))
NoValidos = c()
Validos =c()
Mean_vector = c()
Mediana_vector = c()
Moda_vector =c()
Suma_vector = c()
SE.MEAN_vector= c()
MAD_vector= c()
IQR_vector= c()
Rango_vector = c()
Max_vector = c()
Desv.Est_vector = c()
MadRobust_vector =c()
Varianza_vector = c()
Min_vector = c()
Quartiles_vector = c()
PuntoCorte_vector = c()
Percentil_vector = c()
PercentilValue_names = c()
for (i in 1:length(Dependiente)){
defaultSelect <- class(Dependiente[[i]])
golem::print_dev("ASSSSSSSSSSSSSDDDDDDDDD")
golem::print_dev(defaultSelect)
golem::print_dev("ASSSSSSSSSSSSSDDDDDDDDD")
if(defaultSelect=="numeric"){
varActual <- (as.numeric(Dependiente[[i]]))
}
else{
varActual <- (as.numeric(Dependiente[[i]]) )
}
golem::print_dev(utils::str(varActual))
if(Mean==TRUE){
golem::print_dev("Si es True MEAN")
Mean_vector[i] <- round( mean(varActual, na.rm = TRUE),digits = 3 )
golem::print_dev(Mean_vector[i])
}
if(Mediana==TRUE){
golem::print_dev("Si es True Mediana")
Mediana_vector[i] <-round( median(varActual,na.rm = TRUE),digits = 3)
}
if(Moda==TRUE){
Moda_vector <- round( modafuntion(varActual),digits = 3)
}
if(Suma==TRUE){
golem::print_dev("Si es True Suma")
Suma_vector[i] <-round( sum(varActual,na.rm = TRUE), digits = 3)
}
if(SE==TRUE){
golem::print_dev("Si es True SE")
SE.MEAN_vector[i]<- round( rapportools::se.mean(varActual), digits = 3)
}
if(MAD==TRUE){
golem::print_dev("Si es True MAD")
MAD_vector[i]<- round( mad(varActual,constant = 1,na.rm = TRUE), digits = 3)
}
if(Iqr==TRUE){
golem::print_dev("Si es True IQR")
IQR_vector[i]<- round( IQR(varActual,na.rm = TRUE), digits = 3)
}
if(Rango==TRUE){
golem::print_dev("Si es True Rango")
#golem::print_dev(range(varActual))
Rango_vector[i]<-paste(range(varActual,na.rm = TRUE), collapse = " ")
}
if(Maximo==TRUE){
golem::print_dev("Si es True Maximo")
Max_vector[i]<- round( max(varActual,na.rm = TRUE), digits = 3)
}
if(DsvEstandar==TRUE){
golem::print_dev("Si es True DsvEstandar")
Desv.Est_vector[i]<-round( sd(varActual,na.rm = TRUE), digits = 3)
}
if(MADRobust==TRUE){
golem::print_dev("Si es True MADRobust")
MadRobust_vector[i] <-round( mad(varActual,constant = 1.4826,na.rm = TRUE), digits = 3)
}
if(Varianza==TRUE){
golem::print_dev("Si es True Varianza")
Varianza_vector[i]<-round( var(varActual,na.rm = TRUE), digits = 3)
}
if(Minimo==TRUE){
golem::print_dev("Si es True Minimo")
Min_vector[i]<- round( min(varActual,na.rm = TRUE), digits = 3)
}
if(Quartiles==TRUE){
golem::print_dev("Si es True Quartiles")
Quartiles_vector[i] <- list(round(quantile(varActual,na.rm = TRUE),3))
print(quantile(varActual,na.rm = TRUE))
}
if(PuntoCorte==TRUE){
if(as.numeric(PuntoCorteValue) >= 2){
golem::print_dev("Si es True PuntodeCorte")
stepValue <-(1/(as.numeric(PuntoCorteValue)))
#golem::print_dev(stepValue)
#PuntoCorte_vector[i] <- list(quantile(varActual, prob=seq(0,1,(1/(as.numeric(PuntoCorteValue)))) ,na.rm = TRUE))
PuntoCorte_vector[i] <- list(round(quantile(varActual, prob=seq(0,1,stepValue ) ,na.rm = TRUE),3) )
}
#golem::print_dev("Si es True PuntoCorte")
}
if(Percentil==TRUE){
golem::print_dev("Si es True Percentil redondeado")
if(as.numeric(PercentilValue) >= 2){
valores <- quantile(varActual, prob=seq(0,1,length = 101) ,na.rm = TRUE)
golem::print_dev(valores)
PercentilValue_names <- names(valores)
Percentil_vector[i] <- round(valores[as.numeric(PercentilValue)],3)
}
}
NoValidos[i] <- sum(is.na(varActual))
Validos[i] <- length(varActual) - NoValidos[i]
}
golem::print_dev(PercentilValue_names)
summaryVariableTable <- data.frame(NoValidos,Validos)
if(Mean==TRUE){summaryVariableTable$Media= Mean_vector} else{summaryVariableTable$Media <- NULL}
if(DsvEstandar==TRUE){summaryVariableTable$Dsv.Est=Desv.Est_vector} else{summaryVariableTable$Dsv.Est <- NULL}
if(Minimo==TRUE){summaryVariableTable$Minimo=Min_vector} else{summaryVariableTable$Minimo <- NULL}
if(Maximo==TRUE){summaryVariableTable$Maximo=Max_vector} else{summaryVariableTable$Maximo <- NULL}
if(Mediana==TRUE){summaryVariableTable$Mediana=Mediana_vector} else{summaryVariableTable$Mediana <- NULL}
if(Moda==TRUE){summaryVariableTable$Moda=Moda_vector} else{summaryVariableTable$Moda <- NULL}
if(Suma==TRUE){summaryVariableTable$Suma=Suma_vector} else{summaryVariableTable$Suma <- NULL}
if(SE==TRUE){summaryVariableTable$SE.Media=SE.MEAN_vector} else{summaryVariableTable$SE.Media <- NULL}
if(MAD==TRUE){summaryVariableTable$MAD=MAD_vector} else{summaryVariableTable$MAD <- NULL}
if(Iqr==TRUE){summaryVariableTable$IQR=IQR_vector} else{summaryVariableTable$IQR <- NULL}
if(Rango==TRUE){summaryVariableTable$Rango=Rango_vector} else{summaryVariableTable$Rango <- NULL}
if(MADRobust==TRUE){summaryVariableTable$MAD.Escalado=MadRobust_vector} else{summaryVariableTable$MAD.Escalado <- NULL}
if(Varianza==TRUE){summaryVariableTable$Varianza=Varianza_vector} else{summaryVariableTable$Varianza <- NULL}
if(Quartiles==TRUE){
summaryVariableTable$"25%" = unlist(Quartiles_vector)[2]
summaryVariableTable$"50%" = unlist(Quartiles_vector)[3]
summaryVariableTable$"75%" = unlist(Quartiles_vector)[4]
}
else{
summaryVariableTable$"25%" = NULL
summaryVariableTable$"50%" = NULL
summaryVariableTable$"75%" = NULL
}
if(PuntoCorte==TRUE)
{
golem::print_dev(names(unlist(PuntoCorte_vector)))
lenghtNamesPC <-length(names(unlist(PuntoCorte_vector)))
for(i in seq(2, as.numeric(lenghtNamesPC) - 1, by=1)){
summaryVariableTable[, paste0(names(unlist(PuntoCorte_vector))[i]," ")] <- unlist(PuntoCorte_vector)[i]
}
}
else{
lenghtNamesPC <-length(names(unlist(PuntoCorte_vector)))
if(lenghtNamesPC == 0){
}else{
for(i in 1:lenghtNamesPC-1){
summaryVariableTable[paste0(names(unlist(PuntoCorte_vector))[i]," ")] = NULL
#names(unlist(PuntoCorte_vector))
}
}
}
if(Percentil==TRUE)
{
summaryVariableTable[, paste0(unlist(stringr::str_split(PercentilValue_names[as.numeric(PercentilValue) + 1],""))[1]," Percentil")] <- Percentil_vector
}
else
{
summaryVariableTable[, paste0(unlist(stringr::str_split(PercentilValue_names[as.numeric(PercentilValue) + 1],""))[1]," Percentil")] <- NULL
}
summaryVariableTable2 <- data.frame(t(summaryVariableTable))
summaryVariableTable2 <- dplyr::mutate(summaryVariableTable2, dplyr::across(where(is.numeric), as.character))
golem::print_dev(str(summaryVariableTable2))
rownames(summaryVariableTable2) <- NULL
golem::print_dev(colnames(summaryVariableTable))
summaryVariableTable3 <- data.frame( colnames(summaryVariableTable), summaryVariableTable2 )
colnames(summaryVariableTable3) <- c(" ",Variable)
#golem::print_dev(str(summaryVariableTable3))
#finalDescriptivas <- dplyr::mutate(summaryVariableTable3, dplyr::across(where(is.numeric), as.character))
}
return(summaryVariableTable3)
}
calculoFrecuencias <- function(session,df,frecuenciaEnable) {
if (frecuenciaEnable == TRUE) {
#nbreaks <- pretty(range.default(as.numeric(df_sel()[[i]])),n = nclass.Sturges(as.numeric(df_sel()[[i]])),min.n = 1)
tablas = c()
nombreVariable <- names(df)[[1]]
golem::print_dev(nombreVariable)
tablaFrecuencia <- summarytools::freq(df[[1]], order = "freq")
# tablaFrecuencia <- summarytools::freq(df, order = "freq")
elemntos <- attributes(tablaFrecuencia)[[2]][[1]]
golem::print_dev(elemntos)
freq <- tablaFrecuencia[,1]
validos <- tablaFrecuencia[,2]
validosCum <- tablaFrecuencia[,3]
total <- tablaFrecuencia[,4]
totalCum <- tablaFrecuencia[,5]
descriptivasFrecuencia <- data.frame(elemntos,freq,validos,totalCum)
row.names(descriptivasFrecuencia) <- NULL
golem::print_dev(descriptivasFrecuencia)
descriptivasFrecuencia <- dplyr::mutate(descriptivasFrecuencia, dplyr::across(where(is.numeric), round, 3))
colnames(descriptivasFrecuencia) <- c(nombreVariable,"Frecuencia","Porcentaje Validos","Porcentaje Acumulado")
#newdata <- mtcars[order(mpg),]
# tablas[[i]] <- df
return(descriptivasFrecuencia)
}
if(frecuenciaEnable == FALSE)
{
elemntos <- " "
freq <- " "
validos <- " "
validosCum <- " "
total <- " "
totalCum <- " "
descriptivasFrecuencia <- data.frame(elemntos,freq,validos,totalCum)
row.names(descriptivasFrecuencia) <- NULL
golem::print_dev(descriptivasFrecuencia)
descriptivasFrecuencia <- dplyr::mutate(descriptivasFrecuencia, dplyr::across(where(is.numeric), round, 3))
colnames(descriptivasFrecuencia) <- c("nombreVariable","Frecuencia","Procentaje Validos","Procentaje Acumulado")
return(descriptivasFrecuencia)
}
}
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