Dear Petr
Thanks so much. That is a LOT more efficient.
Tim
-----Original Message-----
From: Petr PIKAL [mailto:petr.pi...@precheza.cz]
Sent: Tuesday, April 19, 2011 3:37 PM
To: tesutton
Cc: r-help@r-project.org
Subject: Odp: [R] Simple Missing cases Function
Hi
Hi
try
colSums(is.na(data.m))
It is not in data frame but you can easily transform it if you want.
Regards
Petr
r-help-boun...@r-project.org napsal dne 19.04.2011 09:29:08:
> Dear all
>
>
>
> I have written a function to perform a very simple but useful task which
I
> do regularly. It is designed to show how many values are missing from
each
> variable in a data.frame. In its current form it works but is slow
because I
> have used several loops to achieve this simple task.
>
>
>
> Can anyone see a more efficient way to get the same results? Or is there
> existing function which does this?
>
>
>
> Thanks for your help
>
> Tim
>
>
>
> Function:
>
> miss <- function (data)
>
> {
>
> miss.list <- list(NA)
>
> for (i in 1:length(data)) {
>
> miss.list[[i]] <- table(is.na(data[i]))
>
> }
>
> for (i in 1:length(miss.list)) {
>
> if (length(miss.list[[i]]) == 2) {
>
> miss.list[[i]] <- miss.list[[i]][2]
>
> }
>
> }
>
> for (i in 1:length(miss.list)) {
>
> if (names(miss.list[[i]]) == "FALSE") {
>
> miss.list[[i]] <- 0
>
> }
>
> }
>
> data.frame(names(data), as.numeric(miss.list))
>
> }
>
>
>
> Example:
>
> data(ToothGrowth)
>
> data.m <- ToothGrowth
>
> data.m$supp[sample(1:nrow(data.m), size=25)] <- NA
>
> miss(data.m)
>
>
> [[alternative HTML version deleted]]
>
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