118

How can I list the distinct values in a vector where the values are replicative? I mean, similarly to the following SQL statement:

SELECT DISTINCT product_code
FROM data
zx8754
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Mehper C. Palavuzlar
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7 Answers7

194

Do you mean unique:

R> x = c(1,1,2,3,4,4,4)
R> x
[1] 1 1 2 3 4 4 4
R> unique(x)
[1] 1 2 3 4
csgillespie
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17

If the data is actually a factor then you can use the levels() function, e.g.

levels( data$product_code )

If it's not a factor, but it should be, you can convert it to factor first by using the factor() function, e.g.

levels( factor( data$product_code ) )

Another option, as mentioned above, is the unique() function:

unique( data$product_code )

The main difference between the two (when applied to a factor) is that levels will return a character vector in the order of levels, including any levels that are coded but do not occur. unique will return a factor in the order the values first appear, with any non-occurring levels omitted (though still included in levels of the returned factor).

Gregor Thomas
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isapir
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8

Try using the duplicated function in combination with the negation operator "!".

Example: 

wdups <- rep(1:5,5)
wodups <- wdups[which(!duplicated(wdups))]

Hope that helps.

Al R.
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7

You can also use the sqldf package in R. 

Z <- sqldf('SELECT DISTINCT tablename.columnname FROM tablename ')
zx8754
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Clay Burns
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0

another way would be to use dplyr package:

x = c(1,1,2,3,4,4,4)
dplyr::distinct(as.data.frame(x))
AlexB
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0

In R Language (version 3.0+) You can apply filter to get unique out of a list-

data.list <- data.list %>% unique

or couple it with other operation as well

data.list.rollnumbers <- data.list %>% pull(RollNumber) %>% unique

unique doesn't require dplyr.

Vishal Kumar Sahu
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0

this may work as well,

1) unlist(lapply(mtcars, function(x) length(unique(x))))
2) lapply(mtcars, function(x) unique(x))

outcomes,

  1. mpg  cyl disp   hp drat   wt qsec   vs   am gear carb 
 25    3   27   22   22   29   30    2    2    3    6 

  2. $mpg
[1] 21.0 22.8 21.4 18.7 18.1 14.3 24.4 19.2 17.8 16.4 17.3 15.2 10.4 14.7 32.4 30.4 33.9 21.5 15.5 13.3 27.3 26.0 15.8 19.7 15.0
$cyl
[1] 6 4 8
$ and so on....
Seyma Kalay
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