[FIXED] How to apply different conditions to each column of a dataframe?

Issue

Suppose I have a dataframe with three columns.

a <- c(1,2,3,4)
b <- c(2,4,6,8)
c <- c(3,6,9,12)
df <- cbind(a,b,c)
df

This gives you...

     a b  c
[1,] 1 2  3
[2,] 2 4  6
[3,] 3 6  9
[4,] 4 8 12

Now suppose I want to create a new dataframe that takes the value TRUE if the value is greater than the column mean and FALSE if it's less than the column mean.

If I use the following command it uses the mean for the whole dataframe.

large <- df > mean(df)
large

So I get...

         a     b     c
[1,] FALSE FALSE FALSE
[2,] FALSE FALSE  TRUE
[3,] FALSE  TRUE  TRUE
[4,] FALSE  TRUE  TRUE

I would like to get

         a     b     c
[1,] FALSE FALSE FALSE
[2,] FALSE FALSE FALSE
[3,] TRUE  TRUE  TRUE
[4,] TRUE  TRUE  TRUE

Solution

mean gets a single value for the whole matrix, we need colMeans

df > colMeans(df)[col(df)]

Or transpose the dataset, do the comparison and transpose

t(t(df) > colMeans(df))

Answered By - akrun

Answer Checked By - Clifford M. (PHPFixing Volunteer)