Agfdhyk

When I use filter from the dplyr package to drop a level of a factor variable, filter also drops the NA values. Here's an example:

library(dplyr)

set.seed(919)

(dat <- data.frame(var1 = factor(sample(c(1:3, NA), size = 10, replace = T))))

#    var1

# 1  <NA>

# 2     3

# 3     3

# 4     1

# 5     1

# 6  <NA>

# 7     2

# 8     2

# 9  <NA>

# 10    1



filter(dat, var1 != 1)

#   var1

# 1    3

# 2    3

# 3    2

# 4    2

This does not seem ideal -- I only wanted to drop rows where var1 == 1.

It looks like this is occurring because any comparison with NA returns NA, which filter then drops. So, for example, filter(dat, !(var1 %in% 1)) produces the correct results. But is there a way to tell filter not to drop the NA values?

You could use this:

 filter(dat, var1 != 1 | is.na(var1))

  var1

1 <NA>

2    3

3    3

4 <NA>

5    2

6    2

7 <NA>

And it won't.

Also just for completion, dropping NAs is the intended behavior of filter as you can see from the following:

test_that("filter discards NA", {

  temp <- data.frame(

    i = 1:5,

    x = c(NA, 1L, 1L, 0L, 0L)

  )

  res <- filter(temp, x == 1)

  expect_equal(nrow(res), 2L)

})

This test above was taken from the tests for filter from github.