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#' @title Preliminary data check for errors
#' @description
#' Preliminary check of data frame for missing values, numeric format, outliers.
#'
#' Missing items: The number of missing values in each column of the dataset.
#' Numeric format: The number of non-numeric variables in each column of the dataset.
#' Outliers: The number of outliers in each column of the dataset.
#' @usage checkdata(x)
#' @param x is a data frame
#' @import stats
#' @importFrom tseries na.remove
#' @importFrom utils data
#' @importFrom cli console_width
#' @examples
#' data(macroKZ)
#' checkdata(macroKZ)
#' @export
#must be without N/A to run
checkdata<-
function (x)
{
miss<-sapply(x, function(x){
sum(is.na(x))})
missing_total=0
for (i in 1:length(miss)){
missing_total = missing_total+miss[[i]]
}
number<-sapply(x, function(x){
as.logical(sum(is.numeric(x)))})
out <- function(x){
count=0
sdt<-3*sd(x, na.rm=TRUE)
m<-mean(x)
for (c in x)
{
if ((c>m+sdt) & (c<m-sdt))
count<-count+1
return(count)}
}
outlier<-sapply(na.remove(x), out)
outlier_total=0
for (i in 1:length(outlier)){
outlier_total = outlier_total+outlier[[i]]
}
notnum_total=0
for (i in 1:length(number)){
if (!isTRUE(i))
number[[i]]=0
notnum_total = notnum_total+number[[i]]
}
#print
w <- console_width()
w1 <- max(nchar(x))
n <- ncol(x)
cat(paste("There are", missing_total, "missing items in the dataset."),
paste("There are", notnum_total, "items in non-numeric format in the dataset."),
paste("There are", outlier_total, "outliers in the dataset."), sep="\n")
#missing_items
cat(rep("-", w), sep = "", "\n")
cat(fc("Missing items", w), "\n")
cat(rep("-", w), sep = "", "\n")
print(list(miss))
cat(rep("-", w), sep = "", "\n\n")
#numeric_format
cat(rep("-", w), sep = "", "\n")
cat(fc("Numeric format", w), "\n")
cat(rep("-", w), sep = "", "\n")
print(list(number))
cat(rep("-", w), sep = "", "\n\n")
#outliers
cat(rep("-", w), sep = "", "\n")
cat(fc("Outliers", w), "\n")
cat(rep("-", w), sep = "", "\n")
print(list(outlier))
cat(rep("-", w), sep = "", "\n\n")
}
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