R bootstrap through all columns in a data frame - r

Question

I'm trying to get bootstrapped descriptive statistics for the columns of a data frame using boot() in R. I can't figure out how to write the "statistic" function required of boot so that it goes through all the columns and returns 4 stats each.
I'm basically trying to modify code from a book chapter introducing bootstrapping, but the example there is using dlply to group up the numeric values in one column based on the group names in another. I don't need that step; I just need to do the same thing to every column. I reproduce the code from the textbook below:
library(boot)
library(plyr)
library(moments)
DescStat <- function(data, i) {
+ temp <- data[i,]
+ desc <- dlply(temp, "GroupName", summarize, mean = mean(ValueColumn), sd = sd(ValueColumn), skew = skewness(ValueColumn), kurt = kurtosis(ValueColumn))
+ l.desc <- unlist(desc)
+ return(l.desc)
+}
DasBoot <- boot(dataframe, DescStat, 1000)
print(DasBoot)
That returns a table of each one of those stats, plus the bias and the SE, each on its own line. So Group1 mean and bias and SE, then Group1 SD and bias and SE on the next line, and on down the list, 4 lines for each group.
I would like to do the exact same thing, but for column in the data frame instead of groups of cases.
I have kind of been floundering. It seems like this should not be that difficult to do, but all the examples and tutorials online are either for one column (which I'm able to do just fine by specifying it in the statistic function), or for trickier manipulations such as in the above.
Any help would be greatly appreciated.

Answer 1

I was able to figure it out using either apply() or purrr::map(). Here's the statistic function that doesn't require any extra packages (tidyverse) installed:
> ApStat <- function(data, i) {
+ temp <- data[i,]
+ desc <- apply(temp, 2, FUN = function(x) {
+ list(mean = mean(x, 0.2), sd = sd(x),
+ skew = skewness(x), kurt = kurtosis(x))
+ })
+ l.desc <- unlist(desc)
+ return(l.desc)
+ }
Thanks to the guys/gals at r/rstats!