I have a data frame with two column:
x <- c(1, 2, 3, 4, NA, 5, 6)
y <- c(1, 2, 4, 5, 0, 5, 6)
my.df <- data.frame(x, y)
I want to keep only the rows where x != y.
What I did is this:
my.df <- subset(my.df, x != y)
What I expected was:
x y
3 4
4 5
NA 0
What I got was
x y
3 4
4 5
This is because, by a strange convention, NA != 0 is NA.
I really want to keep the NA in the subset because I'm looking for the differences between the columns.
How to achieve this?
This would also work. Only select rows where the subtraction of x and y are different from zero
my.df[!((x-y) %in% 0 ),]
One option would be to create an | condition to get those rows having NA for 'x'
subset(my.df, x != y | is.na(x))
If there are also NA elements in 'y'
subset(my.df, x != y | is.na(x)|is.na(y))
Not clear about the situation where both 'x' and 'y' are NA. If that needs to be taken out as they are same
subset(my.df, (x != y | is.na(x)|is.na(y)) & !(is.na(x) & is.na(y)))