# duplicated

0th

Percentile

##### Determine Duplicate Rows

duplicated returns a logical vector indicating which rows of a data.table have duplicate rows (by key).

unique returns a data table with duplicated rows (by key) removed, or (when no key) duplicated rows by all columns removed.

Keywords
data
##### Usage
## S3 method for class 'data.table':
duplicated(x, incomparables=FALSE, tolerance=.Machine$double.eps ^ 0.5, ...)## S3 method for class 'data.table': unique(x, incomparables=FALSE, tolerance=.Machine$double.eps ^ 0.5, ...)
##### Arguments
x
A data.table.
...
Not used at this time.
incomparables
Not used. Here for S3 method consistency.
tolerance
Double precision values are considered equal if they are within this tolerance. Same default as all.equal.
##### Details

Because data.tables are usually sorted by key, tests for duplication are especially quick. Unlike unique.data.frame, paste is not used to ensure equality of floating point data. This is done directly (for speed) whilst still respecting tolerance in the same spirit as all.equal.

When x has a key, only key columns are checked for duplication; non-key columns are not checked. When x has no key, all columns are checked.

##### Value

• duplicated returns a logical vector of length nrow(x) indicating which rows are duplicates.

unique returns a data table with duplicated rows removed.

##### See Also

data.table, duplicated, unique, all.equal

##### Aliases
• duplicated.data.table
• unique.data.table
##### Examples
DT <- data.table(A = rep(1:3, each=4), B = rep(1:4, each=3), C = rep(1:2, 6), key = "A,B")
duplicated(DT)
unique(DT)

DT = data.table(a=c(2L,1L,2L), b=c(1L,2L,1L))   # no key
unique(DT)                   # rows 1 and 2 (row 3 is a duplicate of row 1)

DT = data.table(a=c(3.142, 4.2, 4.2, 3.142, 1.223, 1.223), b=rep(1,6))
unique(DT)                   # rows 1,2 and 5

DT = data.table(a=tan(pi*(1/4 + 1:10)), b=rep(1,10))   # example from ?all.equal
length(unique(DT$a)) # 10 strictly unique floating point values all.equal(DT$a,rep(1,10))    # TRUE, all within tolerance of 1.0
DT[,which.min(a)]            # row 10, the strictly smallest floating point value
identical(unique(DT),DT)  # TRUE, stable within tolerance
identical(unique(DT),DT) # FALSE
Documentation reproduced from package data.table, version 1.7.6, License: GPL (>= 2)

### Community examples

Looks like there are no examples yet.