data.table (version 1.8.8)

duplicated: Determine Duplicate Rows

Description

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.

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.

Value

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

  unique returns a data table with duplicated rows removed.

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.

See Also

data.table, duplicated, unique, all.equal

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[1])  # TRUE, stable within tolerance
    identical(unique(DT),DT[10]) # FALSE