# ranking

##### Windowed rank functions.

Six variations on ranking functions, mimicing the ranking functions
described in SQL2003. They are currently implemented using the built in
`rank`

function, and are provided mainly as a convenience when
converting between R and SQL. All ranking functions map smallest inputs
to smallest outputs. Use `desc`

to reverse the direction..

##### Usage

`row_number(x)`ntile(x, n)

min_rank(x)

dense_rank(x)

percent_rank(x)

cume_dist(x)

##### Arguments

- x
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 Inf or -Inf before ranking.

- n
number of groups to split up into.

##### Details

`row_number`

: equivalent to`rank(ties.method = "first")`

`min_rank`

: equivalent to`rank(ties.method = "min")`

`dense_rank`

: like`min_rank`

, but with no gaps between ranks`percent_rank`

: a number between 0 and 1 computed by rescaling`min_rank`

to [0, 1]`cume_dist`

: a cumulative distribution function. Proportion of all values less than or equal to the current rank.`ntile`

: a rough rank, which breaks the input vector into`n`

buckets.

##### Examples

`library(dplyr)`

```
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(runif(100), 10)
```

*Documentation reproduced from package dplyr, version 0.5.0, License: MIT + file LICENSE*