apply() is giving NA values for every column

Question

I\'ve been having this strange problem with apply lately. Consider the following example:

set.seed(42)
df <- data.frame(cars, foo = sample(LE         


        

Answer 1

apply works on a matrix, and a matrix must be of all one type. So df is being transformed into a matrix, and since it contains a character, all the columns are becoming character.

> apply(df, 2, class)
      speed        dist         foo 
"character" "character" "character" 

To get what you want, check out the colwise and numcolwise functions in plyr.

> numcolwise(mean)(df)
  speed  dist
1  15.4 42.98

Answer 2

You are applying a function over the columns of a data.frame. Since a data.frame is a list, you can use lapply or sapply instead of apply:

sapply(df, mean)

speed  dist   foo 
15.40 42.98    NA 
Warning message:
In mean.default(X[[3L]], ...) :
  argument is not numeric or logical: returning NA

And you can remove the warning message by using an anonymous function that tests for class numeric before calculating the mean:

sapply(df, function(x)ifelse(is.numeric(x), mean(x), NA))

speed  dist   foo 
15.40 42.98    NA 

Answer 3

The first sentence of the description for ?apply says:

If X is not an array but an object of a class with a non-null dim value (such as a data frame), apply attempts to coerce it to an array via as.matrix if it is two-dimensional (e.g., a data frame) or via as.array.

Matrices can only be of a single type in R. When the data frame is coerced to a matrix, everything ends up as a character if there is even a single character column.

I guess I owe you an description of an alternative, so here you go. data frames are really just lists, so if you want to apply a function to each column, use lapply or sapply instead.