gap_id.R

set.seed(1)
tibble::tibble(year = seq(1900,1999) * 
                      sample(c(1, NA), 100, replace = TRUE),
               value=runif(100),
               gap_id=inverse.rle(structure(list(lengths=rle(is.na(year))$lengths,
                                            values=cumsum(rle(is.na(year))$values)*
                                              rle(is.na(year))$values), class="rle")))
#> # A tibble: 100 x 3
#>     year value gap_id
#>    <dbl> <dbl>  <int>
#>  1  1900 0.655      0
#>  2  1901 0.353      0
#>  3    NA 0.270      1
#>  4    NA 0.993      1
#>  5  1904 0.633      0
#>  6    NA 0.213      2
#>  7    NA 0.129      2
#>  8    NA 0.478      2
#>  9    NA 0.924      2
#> 10  1909 0.599      0
#> # ... with 90 more rows