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How to Rank by Group in R?, The basic syntax for ranking variables by the group in dplyr is as follows.

The examples that follow with the given data frame demonstrate how to utilize this syntax in practice.

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Let’s create a data frame

df <- data.frame(team = c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'),
                 points = c(12, 28, 19, 22, 32, 45, 22, 28, 13, 19),
                 rebounds = c(5, 7, 7, 12, 11, 4, 10, 7, 8, 8))

Now we can view the data frame

df
team points rebounds
1     A     10       15
2     A     55       17
3     A     25       17
4     A     36       10
5    P2     45       10
6     B     41       14
7     B     82       15
8    P3     25       11
9     C     33        5
10    C     25       18

Example 1: Rank in Ascending Order

The code below demonstrates how to organize points scored by players by the team in ascending order.

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library(dplyr)

Now rank points scored, grouped by team

df %>% arrange(team, points) %>%
    group_by(team) %>%
    mutate(rank = rank(points))
team  points rebounds  rank
   <chr>  <dbl>    <dbl> <dbl>
 1 A         10       15     1
 2 A         25       17     2
 3 A         36       10     3
 4 A         55       17     4
 5 B         41       14     1
 6 B         82       15     2
 7 C         25       18     1
 8 C         33        5     2
 9 P2        45       10     1
10 P3        25       11     1

Example 2: Rank in Descending Order

The rank() function also allows us to sort the points earned by the group in descending order by using a negative sign.

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library(dplyr)

Let’s calculate rank points scored in reverse, grouped by team

df %>% arrange(team, points) %>%
    group_by(team) %>%
    mutate(rank = rank(-points))
team  points rebounds  rank
   <chr>  <dbl>    <dbl> <dbl>
 1 A         10       15     4
 2 A         25       17     3
 3 A         36       10     2
 4 A         55       17     1
 5 B         41       14     2
 6 B         82       15     1
 7 C         25       18     2
 8 C         33        5     1
 9 P2        45       10     1
10 P3        25       11     1

How to Handle Ranking Ties

When ranking numerical values, we may specify how ties should be handled using the ties.method option.

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rank(points, ties.method='average')

To indicate how to manage ties, choose from the available options,

each tied element is assigned to the average rank by default (elements ranked in the 3rd and 4th position would both receive a rank of 3.5)

first: Assigns the lowest rank to the first tied element (elements ranked in the 3rd and 4th positions would receive ranks 3 and 4 respectively)

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Every tied element is given the lowest rank possible, minimum (elements ranked in the 3rd and 4th position would both receive a rank of 3)

max: Gives the highest rank to each tied element (elements ranked in the 3rd and 4th position would both receive a rank of 4)

every linked element is given a random rank at random (either element tied for the 3rd and 4th position could receive either rank)

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