You can use the following methods to count the number of unique values in a column of a data frame in R:

Method 1: Using Base R

length(unique(df$my_column))

Method 2: Using dplyr

library(dplyr)

n_distinct(df$my_column)

The following examples show how to use each method in practice with the following data frame:

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'C', 'C', 'D'),
                 points=c(10, 13, 14, 14, 18, 19, 20, 20, 22))

#view data frame
df

  team points
1    A     10
2    A     13
3    A     14
4    A     14
5    B     18
6    B     19
7    C     20
8    C     20
9    D     22

Method 1: Count Unique Values in Column Using Base R

The following code shows how to count the number of unique values in the points column of the data frame using functions from base R:

#count unique values in points column
length(unique(df$points))

[1] 7

There are 7 unique value in the points column.

To count the number of unique values in each column of the data frame, we can use the sapply() function:

#count unique values in each column
sapply(df, function(x) length(unique(x)))

  team points 
     4      7

From the output we can see:

• There are 7 unique values in the points column.
• There are 4 unique values in the team columm.

Method 2: Count Unique Values in Column Using dplyr

The following code shows how to count the number of distinct values in the points column using the n_distinct() function from the dplyr package:

library(dplyr)

#count unique values in points column
n_distinct(df$points)

[1] 7

There are 7 unique value in the points column.

To count the number of unique values in each column of the data frame, we can use the sapply() function:

library(dplyr) 

#count unique values in each column
sapply(df, function(x) n_distinct(x))

  team points 
     4      7

From the output we can see:

• There are 7 unique values in the points column.
• There are 4 unique values in the team columm.

Notice that these results match the ones from the base R method.