You can use the n() function from the package in R to count the number of observations in a group.

Here are three common ways to use this function in practice:

Method 1: Use n() to Count Observations by Group

df %>%
  group_by(group_variable) %>%
  summarise(count = n())

Method 2: Use n() to Add Column that Shows Observations by Group

df %>%
  group_by(group_variable) %>%
  mutate(count = n())

Method 3: Use n() to Filter Based on Observations by Group

df %>%
  group_by(group_variable) %>%
  filter(n() > 15)

The following examples show how to use each method in practice with the following data frame in R that contains information about various basketball players:

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'B', 'B', 'C'),
                 points=c(22, 25, 25, 20, 29, 13),
                 assists=c(10, 12, 9, 4, 11, 10),
                 rebounds=c(9, 8, 5, 10, 14, 12))

#view data frame
df

  team points assists rebounds
1    A     22      10        9
2    A     25      12        8
3    A     25       9        5
4    B     20       4       10
5    B     29      11       14
6    C     13      10       12

Example 1: Use n() to Count Observations by Group

The following code shows how to use the n() function along with the summarise() function to count the number of observations by team:

library(dplyr)

#count number of observations by team
df %>%
  group_by(team) %>%
  summarise(count = n())

# A tibble: 3 x 2
  team  count
   
1 A         3
2 B         2
3 C         1

From the output we can see:

• Team A occurs 3 times
• Team B occurs 2 times
• Team C occurs 1 time

Example 2: Use n() to Add Column that Shows Observations by Group

The following code shows how to use the n() function along with the mutate() function to add a column to the date frame that contains the number of observations by team:

library(dplyr)

#add new column that shows number of observations by team
df %>%
  group_by(team) %>%
  mutate(count = n())

# A tibble: 6 x 5
# Groups:   team [3]
  team  points assists rebounds count
            
1 A         22      10        9     3
2 A         25      12        8     3
3 A         25       9        5     3
4 B         20       4       10     2
5 B         29      11       14     2
6 C         13      10       12     1

The new column called count contains the team count for each row in the data frame.

Example 3: Use n() to Filter Based on Observations by Group

The following code shows how to use the n() function along with the filter() function to filter the data frame to only show rows where the team occurs greater than one time:

library(dplyr)

#filter rows where team count is greater than 1
df %>%
  group_by(team) %>%
  filter(n() > 1)

# A tibble: 5 x 4
# Groups:   team [2]
  team  points assists rebounds
           
1 A         22      10        9
2 A         25      12        8
3 A         25       9        5
4 B         20       4       10
5 B         29      11       14

Notice that the resulting data frame only contains rows where the team is “A” or “B” because these are the only teams that have a count greater than one.