Removing duplicate rows based on the Single Column
distinct() function can be used to filter out the duplicate rows. We just have to pass our R object and the column name as an argument in the distinct() function.
Note: We have used this parameter “.keep_all= TRUE” in the function because by default its FALSE, and it will print only the distinct values of the specified column, but we want all the columns so we have to make it TRUE, such that it will print all the other columns along with the current column.
Syntax: distinct(df, column_name, .keep_all= TRUE)
Parameters:
df: dataframe object
column_name: column name based on which duplicate rows will be removed
Example: R program to remove duplicate rows based on single column
R
library(dplyr) df <- data.frame (lang =c ('Java','C','Python','GO','RUST','Javascript', 'Cpp','Java','Julia','Typescript','Python','GO'), value = c (21,21,3,5,180,9,12,21,6,0,3,6), usage =c(21,21,0,99,44,48,53,21,6,8,0,6)) distinct(df, lang, .keep_all= TRUE) |
Output:
lang value usage 1 Java 21 21 2 C 21 21 3 Python 3 0 4 GO 5 99 5 RUST 180 44 6 Javascript 9 48 7 Cpp 12 53 8 Julia 6 6 9 Typescript 0 8
Remove duplicate rows based on multiple columns using Dplyr in R
In this article, we will learn how to remove duplicate rows based on multiple columns using dplyr in R programming language.
Dataframe in use:
lang value usage 1 Java 21 21 2 C 21 21 3 Python 3 0 4 GO 5 99 5 RUST 180 44 6 Javascript 9 48 7 Cpp 12 53 8 Java 21 21 9 Julia 6 6 10 Typescript 0 8 11 Python 3 0 12 GO 6 6