apply_to <- function(d, f, ...) {
sapply(d, f)
}
apply_to(mtcars, class)
library(ggplot2)
apply_to(txhousing, class)
num_missing <- function(x) {
sum(is.na(x))
}
apply_to(txhousing, num_missing)
apply_to(txhousing, function(x) sum(is.na(x)))
apply_to(txhousing, f = function(x) { sum(is.na(x)) })
apply_to(txhousing, f = mean)
apply_to(txhousing, f = mean, na.rm=TRUE)
sapply(txhousing, FUN = mean)
sapply(txhousing, FUN = mean, na.rm=TRUE)
sapply(na.rm=TRUE, FU = mean, X = diamonds)
sapply(FU = class, X = diamonds)
apply_to(diamonds, f = mean)
apply_to(mtcars, f = mean)
apply_to <- function(d, f) {
# browser()
res <- c()
for (i in 1:length(d)) {
res[i] <- f(d[[i]])
names(res)[i] <- names(d[i])[1]
}
res
}
apply_to <- function(d, f, ...) {
res <- c()
dots <- length(dots_list())
for (i in 1:length(d)) {
if (dots > 0) res[i] <- f(d[[i]], ...)
else res[i] <- f(d[[i]])
names(res)[i] <- names(d[i])[1]
}
res
}Code from class
code
Week03