Table of Contents
Finding unique values in a column involves using a function such as COUNTIFS or DISTINCTCOUNT to identify distinct values within a column of data. This can be helpful in identifying individual values or categories that are not replicated anywhere else in the column. This process can be used to identify outliers and trends in data, and is a useful tool for data analysis.
You can use the unique() function in R to find unique values in a column of a data frame.
This tutorial provides several examples of how to use this function with the following data frame:
#create data frame
df <- data.frame(team=c('A', 'A', 'B', 'B', 'C', 'C'),
points=c(90, 99, 90, 85, 90, 85),
assists=c(33, 33, 31, 39, 34, 34),
rebounds=c(30, 28, 24, 24, 28, 28))
#view data frame
df
team points assists rebounds
1 A 90 33 30
2 A 99 33 28
3 B 90 31 24
4 B 85 39 24
5 C 90 34 28
6 C 85 34 28
Example 1: Find Unique Values in Column
The following code shows how to find unique values in the ‘team’ column:
#find unique values in 'team' column
unique(df$team)
[1] "A" "B" "C"
We can use similar syntax to find unique values in the ‘points’ column:
#find unique values in 'points' column
unique(df$points)
[1] 90 99 85
Example 2: Find & Sort Unique Values in Column
The following code shows how to find and sort unique values in the ‘points’ column:
#find and sort unique values in 'points' column
sort(unique(df$points))
[1] 85 90 99
We can also sort unique values in a descending order:
#find and sort unique values in 'points' column
sort(unique(df$points), decreasing=TRUE)
[1] 99 90 85
Example 3: Find & Count Unique Values in Column
The following code shows how to find and count the number of each unique value in the ‘points’ column:
#find and count unique values in 'points' column
table(df$points)
85 90 99
2 3 1
From the output we can see:
- The value 85 occurs 2 times.
- The value 90 occurs 3 times.
- The value 99 occurs 1 time.
The following tutorials explain how to perform other common operations in R: