List distinct values in a vector in R
RVectorDistinct ValuesR FaqR Problem Overview
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
R Solutions
Solution 1 - R
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
Solution 2 - R
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).
Solution 3 - R
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.
Solution 4 - R
You can also use the sqldf package in R.
Z <- sqldf('SELECT DISTINCT tablename.columnname FROM tablename ')
Solution 5 - R
another way would be to use dplyr package:
x = c(1,1,2,3,4,4,4)
dplyr::distinct(as.data.frame(x))
Solution 6 - R
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.
Solution 7 - R
this may work as well,
1) unlist(lapply(mtcars, function(x) length(unique(x))))
2) lapply(mtcars, function(x) unique(x))
outcomes,
-
mpg cyl disp hp drat wt qsec vs am gear carb 25 3 27 22 22 29 30 2 2 3 6 -
$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....