Six variations on ranking functions, mimicking the ranking functions described in SQL2003. They are currently
implemented using the built in
rank() function. All ranking functions map smallest inputs to smallest outputs. Use
desc() to reverse the direction.
1 2 3 4 5 6 7 8 9 10 11
A vector of values to rank. Missing values are left as is. If you want to treat them as the smallest or
largest values, replace with
cume_dist(): a cumulative distribution function. Proportion of all values less than or equal to the current rank.
min_rank(), but with no gaps between ranks
min_rank(): equivalent to
rank(ties.method = "min")
ntile(): a rough rank, which breaks the input vector into
n buckets. The size of the buckets may differ by up
to one, larger buckets have lower rank.
percent_rank(): a number between
1 computed by rescaling
row_number(): equivalent to
rank(ties.method = "first")
1 2 3 4 5 6 7 8 9 10 11 12 13 14
x <- c(5, 1, 3, 2, 2, NA) row_number(x) min_rank(x) dense_rank(x) percent_rank(x) cume_dist(x) ntile(x, 2) ntile(1:8, 3) # row_number can be used with single table verbs without specifying x # (for data frames and databases that support windowing) mutate(mtcars, row_number() == 1L) mtcars %>% filter(between(row_number(), 1, 10))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.