histogram in R with for loop

I have a dataset with 74 columns, and I am trying to create a histogram for each one of these in a for loop. When run in the console, my code is fine, but when I try to knit it, R says that my data is not numeric. Anyone know why? I'm also open to other solutions to this problem of plotting multiple histograms (with the column name as an identifier on the plot). Below is a simplified representation of my problem.

library(dplyr) 

data2 <- data.frame(c(1,3,5,5,2,2,1,1,1,1),
                    c(2,4,2,3,4,5,1,2,3,3))

colnames(data2) <- c("A", "B")

for (cols in colnames(data2)) {
  data2 %>% select(cols) %>% hist()
}

Again, works fine line-by-line, but I end up receiving the following error when I try to knit it:

"Error in hist.default(.) : 'x' must be numeric Calls:<Anonymous> ...freduce -> withVisible -><Anonymous> -> hist -> hist.default

Execution halted"

Interestingly, this code knits fine:

library(dplyr)

data2 <- data.frame(c(1,3,5,5,2,2,1,1,1,1),
                    c(2,4,2,3,4,5,1,2,3,3))

colnames(data2) <- c("A", "B")

hist(data2$A)
hist(data2$B)

You can simply use lapply.

lapply(data2, hist)

Edit: Of course you can extend this as you like, e.g. titles, labels.

op <- par(mfrow=c(1, 2))  # to put histograms side by side
lapply(seq(data2), function(x) 
  hist(x=data2[[x]], xlab=names(data2)[x], main=paste("Histogram", names(data2)[x])))
par(op)  # restore

selecting a single column creates a 1-column data frame. hist expects a numeric vector, not a data frame. Use pull instead to extract a column as a vector:

for (cols in colnames(data2)) {
  data2 %>% pull(cols) %>% hist()
}

I'm also not sure what you mean with "My line-by-line code works fine", I get the same error taking the code out of the for loop (but pull still works fine):

data2 %>% select(A) %>% hist
# Error in hist.default(.) : 'x' must be numeric

Thanks, Gregor. In case people are interested, my final code to keep the column names for reference is:

for (cols in colnames(data2)) {
  data2 %>% pull(cols) %>% hist(main = cols)
}

This may also work in base.R, if you like.

data2 <- data.frame(c(1,3,5,5,2,2,1,1,1,1),
                    c(2,4,2,3,4,5,1,2,3,3))

colnames(data2) <- c("A", "B")

for(x in names(data2)) {
  hist(data2[,x], main = paste(x, 'distribution' ))
}