Remove duplicated rows

The function distinct() in the dplyr package performs arbitrary duplicate removal, either from specific columns/variables (as in this question) or considering all columns/variables. dplyr is part of the tidyverse.

Data and package

library(dplyr)
dat <- data.frame(a = rep(c(1,2),4), b = rep(LETTERS[1:4],2))

Remove rows duplicated in a specific column (e.g., columna)

Note that .keep_all = TRUE retains all columns, otherwise only column a would be retained.

distinct(dat, a, .keep_all = TRUE)

  a b
1 1 A
2 2 B

Remove rows that are complete duplicates of other rows:

distinct(dat)

  a b
1 1 A
2 2 B
3 1 C
4 2 D

For people who have come here to look for a general answer for duplicate row removal, use !duplicated():

a <- c(rep("A", 3), rep("B", 3), rep("C",2))
b <- c(1,1,2,4,1,1,2,2)
df <-data.frame(a,b)

duplicated(df)
[1] FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE  TRUE

> df[duplicated(df), ]
  a b
2 A 1
6 B 1
8 C 2

> df[!duplicated(df), ]
  a b
1 A 1
3 A 2
4 B 4
5 B 1
7 C 2

Answer from: Removing duplicated rows from R data frame

just isolate your data frame to the columns you need, then use the unique function :D

# in the above example, you only need the first three columns
deduped.data <- unique( yourdata[ , 1:3 ] )
# the fourth column no longer 'distinguishes' them, 
# so they're duplicates and thrown out.