You can use one of the following methods to count the number of distinct values in an R data frame using the n_distinct() function from :

Method 1: Count Distinct Values in One Column

n_distinct(df$column_name)

Method 2: Count Distinct Values in All Columns

sapply(df, function(x) n_distinct(x))

Method 3: Count Distinct Values by Group

df %>%  group_by(grouping_column) %>%  summarize(count_distinct = n_distinct(values_column))

The following examples show how to use each of these methods in practice with the following data frame:

library(dplyr)

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
                 points=c(6, 6, 8, 10, 9, 9, 12, 12),
                 assists=c(3, 6, 4, 2, 4, 5, 5, 9))

#view data frame
df

  team points assists
1    A      6       3
2    A      6       6
3    A      8       4
4    A     10       2
5    B      9       4
6    B      9       5
7    B     12       5
8    B     12       9

Method 1: Count Distinct Values in One Column

The following code shows how to use n_distinct() to count the number of distinct values in the ‘team’ column:

#count distinct values in 'team' column
n_distinct(df$team)

[1] 2

There are 2 distinct values in the ‘team’ column.

Method 2: Count Distinct Values in All Columns

The following code shows how to use the sapply() and n_distinct() functions to count the number of distinct values in each column of the data frame:

#count distinct values in every column
sapply(df, function(x) n_distinct(x))
   team  points assists 
      2       5       6

From the output we can see:

• There are 2 distinct values in the ‘team’ column
• There are 5 distinct values in the ‘points’ column
• There are 6 distinct values in the ‘assists’ column

Method 3: Count Distinct Values by Group

The following code shows how to use the n_distinct() function to count the number of distinct values by group:

#count distinct 'points' values by 'team'
df %>%
  group_by(team) %>%
  summarize(distinct_points = n_distinct(points))

# A tibble: 2 x 2
  team  distinct_points 
1 A                   3
2 B                   2

From the output we can see:

• There are 3 distinct points values for team A.
• There are 2 distinct points values for team B.

The following tutorials explain how to perform other common operations using dplyr: