Count Unique Values in R
In this article, we will see how we can count unique values in R programming language.
Example:
Input: 1 2 3 2 4 5 1 6 8 9 8 6 6 6 6
Output: 8
Method 1: Using length(unique()) function
Unique() function when provided with a list will give out only the unique ones from it. Later length() function can calculate the frequency.
Syntax:
length(unique( object )
Example 1:
R
# Sample vector v<-c(1,2,3,2,4,5,1,6,8,9,8,6,6,6,6) v print("Unique values") # count unique elements length(unique(v)) |
Output:
[1] 1 2 3 2 4 5 1 6 8 9 8 6 6 6 6
[1] “Unique values”
[1] 8
With a list with multiple NA value, it will be counted as 1 separate entity.
Example 2:
R
# Sample vector v<-c(NA,2,NA,3,2,4,5,1,6,8,9,8,6,6,6,6) v print("Unique values") # count unique elements length(unique(v)) |
Output:
[1] NA 2 NA 3 2 4 5 1 6 8 9 8 6 6 6 6
[1] “Unique values”
[1] 9
Example 3:
R
# Sample dataframe df<-data.frame(c1=c(NA,2,NA,3,2,4),c2=c(5,1,6,6,6,6)) df print("Unique values") # count unique elements length(unique(df$c1)) |
Output:
c1 c2
1 NA 5
2 2 1
3 NA 6
4 3 6
5 2 6
6 4 6
[1] “Unique values”
[1] 4
This method is not applicable for matrices
Example 4:
R
# Sample matrix mat<-matrix(c(NA,2,NA,3,2,4,5,1,6,6,6,6),ncol=3) mat print("Unique values") # count unique elements length(unique(mat)) |
Output:
[,1] [,2] [,3]
[1,] NA 2 6
[2,] 2 4 6
[3,] NA 5 6
[4,] 3 1 6
[1] “Unique values”
[1] 12
Method 2: Using table() function
We will be using the table() function to get the count of unique values. The table() function in R Language is used to create a categorical representation of data with the variable name and the frequency in the form of a table.
Syntax:
table(object)
Example 1:
R
v <- c(5,NA,NA,2,3,4,5,3,7,8,9,5) v print("Count of unique values") table(v) |
Output:
[1] 5 NA NA 2 3 4 5 3 7 8 9 5
[1] “Count of unique values”
v
2 3 4 5 7 8 9
1 2 1 3 1 1 1
Example 2:
R
# Sample dataframe df<-data.frame(c1=c(NA,2,NA,3,2,4),c2=c(5,1,6,6,6,6)) df print("Unique values") # count unique elements table(df$c2) |
Output:
c1 c2
1 NA 5
2 2 1
3 NA 6
4 3 6
5 2 6
6 4 6
[1] “Unique values”
1 5 6
1 1 4
Example 3:
R
# Sample matrix mat<-matrix(c(NA,2,NA,3,2,4,5,1,6,6,6,6),ncol=3) mat print("Unique values") # count unique elements table(mat) |
Output:
[,1] [,2] [,3]
[1,] NA 2 6
[2,] 2 4 6
[3,] NA 5 6
[4,] 3 1 6
[1] “Unique values”
mat
1 2 3 4 5 6
1 2 1 1 1 4
Method 3: Converting Output into Dataframe using as.data.frame() function
This method will return the individual frequency of each element.
Syntax:
as.data.frame(table(v))
Example:
R
# Sample vector v<-c(1,2,3,2,4,5,1,6,8,9,8,6,6,6,6) v print("Count of Unique values") as.data.frame(table(v)) |
Output:
[1] 1 2 3 2 4 5 1 6 8 9 8 6 6 6 6
[1] “Count of Unique values”
v Freq
1 1 2
2 2 2
3 3 1
4 4 1
5 5 1
6 6 5
7 8 2
8 9 1
Method 4: Using aggregate() function
The aggregate() function will always return a data frame that contains all unique values from the input data frame after applying the specific function. We can only apply a single function inside an aggregate function
Syntax: aggregate(data.frame(count = v), list(value = v), length)
Parameters:
formula: the variable(s) of the input data frame we want to apply functions on.
data: the data that we want to use for group by operation.
function: the function or calculation to be applied.
Example:
R
# Sample vector v<-c(1,2,3,2,4,5,1,6,8,9,8,6,6,6,6) v print("Count of Unique values using aggregate() function") aggregate(data.frame(count = v), list(value = v), length) |
Output:
[1] 1 2 3 2 4 5 1 6 8 9 8 6 6 6 6
[1] “Count of Unique values using aggregate() function”
value count
1 1 2
2 2 2
3 3 1
4 4 1
5 5 1
6 6 5
7 8 2
8 9 1
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