Winsorisation in R

I wrote a function to hard-winsorise each column of a data.frame to 3 standard deviations. I couldn't find anything that did this neatly.

It doesn't do any checking of the data, you need to do that yourself. This is licensed under GPL3 or later. Please link back here if cross-posting it elsewhere.

winsor_clip_data <- function (x, std = 3, na.rm = TRUE)

{

clip_vec <- function(dat, min, max){

# hard clip dat to the rangs max, min

dat[dat > max] <- max

dat[dat < min] <- min

return(dat)

}

sds<-as.matrix(apply(x, 2, sd, na.rm=TRUE))

means<-as.matrix(apply(x, 2, mean, na.rm=TRUE))

mins<-means-3*sds

maxs<- means+3*sds

output<- mapply(clip_vec, x, mins, maxs)

return(output)

}

Summary stats in R

I've been looking for an easy way of creating a data.frame of summary statistics in R, and haven't been able to find anything. The summary() function seems to output a list, and it isn't easily malleable into a data.frame. This makes it hard to add other stats to the list, or to query it from other functions. I've written a simple function that uses boxplot() plus a few other bits to make a nice data.frame.

It doesn't do any checking of the data, you need to do that yourself. This is licensed under GPL3 or later. Please link back here if cross-posting it elsewhere.

summary_stats <- function(these_data, output_dir) {

num_NAs=as.data.frame(t(colSums(is.na(these_data))))

rownames(num_NAs)<-"NA count"

means<-as.data.frame(t(colMeans(these_data, na.rm=TRUE)))

rownames(means)<-"means"

num_dat=as.data.frame(t(rep(nrow(these_data),ncol(these_data))))

rownames(num_dat)<-"num data"

names(num_dat)<-names(these_data)

stats<-boxplot(these_data,plot=FALSE)

stats<-as.data.frame(stats$stats[1:5,])

names(stats)<-names(these_data)

rownames(stats)<-c("minimum (excl outliers)","lower quartile","median", "upper quartile", "maximum (excl outliers)")

output<-as.data.frame(rbind(

num_NAs,

num_dat,

means,

stats

))

return(output)

}