Find the "previous" (lag()) or "next" (lead()) values in a vector.
Useful for comparing values behind of or ahead of the current values.
Usage
lag(x, n = 1L, default = NA, order_by = NULL, ...)
lead(x, n = 1L, default = NA, order_by = NULL, ...)Arguments
- x
Vector of values
- n
Positive integer of length 1, giving the number of positions to lead or lag by
- default
Value used for non-existent rows. Defaults to
NA.- order_by
Override the default ordering to use another vector or column
- ...
Needed for compatibility with lag generic.
Examples
lag(1:5)
#> [1] NA 1 2 3 4
lead(1:5)
#> [1] 2 3 4 5 NA
x <- 1:5
tibble(behind = lag(x), x, ahead = lead(x))
#> # A tibble: 5 × 3
#> behind x ahead
#> <int> <int> <int>
#> 1 NA 1 2
#> 2 1 2 3
#> 3 2 3 4
#> 4 3 4 5
#> 5 4 5 NA
# If you want to look more rows behind or ahead, use `n`
lag(1:5, n = 1)
#> [1] NA 1 2 3 4
lag(1:5, n = 2)
#> [1] NA NA 1 2 3
lead(1:5, n = 1)
#> [1] 2 3 4 5 NA
lead(1:5, n = 2)
#> [1] 3 4 5 NA NA
# If you want to define a value for non-existing rows, use `default`
lag(1:5)
#> [1] NA 1 2 3 4
lag(1:5, default = 0)
#> [1] 0 1 2 3 4
lead(1:5)
#> [1] 2 3 4 5 NA
lead(1:5, default = 6)
#> [1] 2 3 4 5 6
# If data are not already ordered, use `order_by`
scrambled <- slice_sample(tibble(year = 2000:2005, value = (0:5) ^ 2), prop = 1)
wrong <- mutate(scrambled, previous_year_value = lag(value))
arrange(wrong, year)
#> # A tibble: 6 × 3
#> year value previous_year_value
#> <int> <dbl> <dbl>
#> 1 2000 0 4
#> 2 2001 1 16
#> 3 2002 4 NA
#> 4 2003 9 0
#> 5 2004 16 25
#> 6 2005 25 9
right <- mutate(scrambled, previous_year_value = lag(value, order_by = year))
arrange(right, year)
#> # A tibble: 6 × 3
#> year value previous_year_value
#> <int> <dbl> <dbl>
#> 1 2000 0 NA
#> 2 2001 1 0
#> 3 2002 4 1
#> 4 2003 9 4
#> 5 2004 16 9
#> 6 2005 25 16