The duplicated() function in R is “used to check which elements of a vector or data frame are duplicates and returns a logical vector suggesting which elements (rows) are duplicates”.
Syntax
duplicated(dataframe)
Parameters
dataframe: It is a data frame.
Return value
The duplicated() method returns the logical vector of the same length as the input data if it is a vector.
Example 1: Apply duplicated() Function to Vector Object
The duplicated() function returns the plain vector of logical values after applying on a vector object.
data <- c(11, 19, 11, 19, 46, 21)
duplicated(data)
Output
[1] FALSE FALSE TRUE TRUE FALSE FALSE
You can use the duplicated() function to find the duplicate elements in Vector.
data <- c(11, 19, 11, 19, 46, 21)
data[duplicated(data)]
Output
[1] 11 19
We are using the indexing of the vector and duplicated() function to extract the duplicate data from the Vector.
Example 1.1 Use duplicated() with ! operator to remove duplicate elements from a vector
To remove duplicated elements, use the “! duplicated()”, where ! is logical negation. The ! is logical negation. !duplicated() means that we don’t want duplicate rows.
data <- c(11, 19, 11, 19, 46, 21)
data[!duplicated(data)]
Output
[1] 11 19 46 21
Here, we are extracting the unique values from the vector.
Example 2: Apply duplicated() Function to Data Frame
The “duplicated()” function returns the rows duplicated in the form of boolean values.
df <- data.frame(
Shares = c("TCS", "Reliance", "TCS", "HUL", "Reliance"),
Price = c(3200, 1900, 3200, 2200, 1900)
)
duplicated(df)
Output
[1] FALSE FALSE TRUE FALSE TRUE
Example 2.1: Use duplicated() with ! operator to remove duplicate elements from a data frame
You can remove duplicate rows from the data frame using the “!duplicated()” expression.
df <- data.frame(Shares = c("TCS", "Reliance", "HDFC Bank", "HUL", "Reliance"),
Price = c(3200, 1900, 1500, 2200, 1900))
df
cat("After Removing Duplicates", "\n")
df[!duplicated(df$Price),]
Output
Shares Price
1 TCS 3200
2 Reliance 1900
3 HDFC Bank 1500
4 HUL 2200
5 Reliance 1900
After Removing Duplicates
Shares Price
1 TCS 3200
2 Reliance 1900
3 HDFC Bank 1500
4 HUL 2200
It completely removes the row from the data frame having duplicate values.

Krunal Lathiya is a Software Engineer with over eight years of experience. He has developed a strong foundation in computer science principles and a passion for problem-solving. In addition, Krunal has excellent knowledge of Data Science and Machine Learning, and he is an expert in R Language.