unique() for more than one variable

Solution 1:

How about using unique() itself?

df <- data.frame(yad = c("BARBIE", "BARBIE", "BAKUGAN", "BAKUGAN"),
                 per = c("AYLIK",  "AYLIK",  "2 AYLIK", "2 AYLIK"),
                 hmm = 1:4)

df
#       yad     per hmm
# 1  BARBIE   AYLIK   1
# 2  BARBIE   AYLIK   2
# 3 BAKUGAN 2 AYLIK   3
# 4 BAKUGAN 2 AYLIK   4

unique(df[c("yad", "per")])
#       yad     per
# 1  BARBIE   AYLIK
# 3 BAKUGAN 2 AYLIK

Solution 2:

This is an addition to Josh's answer.

You can also keep the values of other variables while filtering out duplicated rows in data.table

Example:

library(data.table)

#create data table
dt <- data.table(
  V1=LETTERS[c(1,1,1,1,2,3,3,5,7,1)],
  V2=LETTERS[c(2,3,4,2,1,4,4,6,7,2)],
  V3=c(1),
  V4=c(2) )

> dt
# V1 V2 V3 V4
# A  B  1  2
# A  C  1  2
# A  D  1  2
# A  B  1  2
# B  A  1  2
# C  D  1  2
# C  D  1  2
# E  F  1  2
# G  G  1  2
# A  B  1  2

# set the key to all columns
setkey(dt)

# Get Unique lines in the data table
unique( dt[list(V1, V2), nomatch = 0] ) 

# V1 V2 V3 V4
# A  B  1  2
# A  C  1  2
# A  D  1  2
# B  A  1  2
# C  D  1  2
# E  F  1  2
# G  G  1  2

Alert: If there are different combinations of values in the other variables, then your result will be

unique combination of V1 and V2

Solution 3:

There are a few ways to get all unique combinations of a set of factors.

with(df, interaction(yad, per, drop=TRUE))   # gives labels
with(df, yad:per)                            # ditto

aggregate(numeric(nrow(df)), df[c("yad", "per")], length)    # gives a data frame