Set operations

Source: R/sets.R

Perform set operations using the rows of a data frame.

  • intersect(x, y) finds all rows in both x and y.

  • union(x, y) finds all rows in either x or y, excluding duplicates.

  • union_all(x, y) finds all rows in either x or y, including duplicates.

  • setdiff(x, y) finds all rows in x that aren't in y.

  • symdiff(x, y) computes the symmetric difference, i.e. all rows in x that aren't in y and all rows in y that aren't in x.

  • setequal(x, y) returns TRUE if x and y contain the same rows (ignoring order).

Note that intersect(), union(), setdiff(), and symdiff() remove duplicates in x and y.

intersect(x, y, ...)

union(x, y, ...)

union_all(x, y, ...)

setdiff(x, y, ...)

setequal(x, y, ...)

symdiff(x, y, ...)

Arguments

x, y

Pair of compatible data frames. A pair of data frames is compatible if they have the same column names (possibly in different orders) and compatible types.

...

These dots are for future extensions and must be empty.

Base functions

intersect(), union(), setdiff(), and setequal() override the base functions of the same name in order to make them generic. The existing behaviour for vectors is preserved by providing default methods that call the base functions.

Examples

df1 <- tibble(x = 1:3)
df2 <- tibble(x = 3:5)

intersect(df1, df2)
#> # A tibble: 1 × 1
#>       x
#>   <int>
#> 1     3
union(df1, df2)
#> # A tibble: 5 × 1
#>       x
#>   <int>
#> 1     1
#> 2     2
#> 3     3
#> 4     4
#> 5     5
union_all(df1, df2)
#> # A tibble: 6 × 1
#>       x
#>   <int>
#> 1     1
#> 2     2
#> 3     3
#> 4     3
#> 5     4
#> 6     5
setdiff(df1, df2)
#> # A tibble: 2 × 1
#>       x
#>   <int>
#> 1     1
#> 2     2
setdiff(df2, df1)
#> # A tibble: 2 × 1
#>       x
#>   <int>
#> 1     4
#> 2     5
symdiff(df1, df2)
#> # A tibble: 4 × 1
#>       x
#>   <int>
#> 1     1
#> 2     2
#> 3     4
#> 4     5

setequal(df1, df2)
#> [1] FALSE
setequal(df1, df1[3:1, ])
#> [1] TRUE

# Note that the following functions remove pre-existing duplicates:
df1 <- tibble(x = c(1:3, 3, 3))
df2 <- tibble(x = c(3:5, 5))

intersect(df1, df2)
#> # A tibble: 1 × 1
#>       x
#>   <dbl>
#> 1     3
union(df1, df2)
#> # A tibble: 5 × 1
#>       x
#>   <dbl>
#> 1     1
#> 2     2
#> 3     3
#> 4     4
#> 5     5
setdiff(df1, df2)
#> # A tibble: 2 × 1
#>       x
#>   <dbl>
#> 1     1
#> 2     2
symdiff(df1, df2)
#> # A tibble: 4 × 1
#>       x
#>   <dbl>
#> 1     1
#> 2     2
#> 3     4
#> 4     5