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Detect where values fall in a specified range

Source: R/funs.R
between.Rd

This is a shortcut for x >= left & x <= right, implemented for local vectors and translated to the appropriate SQL for remote tables.

Usage

between(x, left, right)

Arguments

x

A vector

left, right

Boundary values. Both left and right are recycled to the size of x.

Value

A logical vector the same size as x.

Details

x, left, and right are all cast to their common type before the comparison is made.

See also

join_by() if you are looking for documentation for the between() overlap join helper.

Examples

between(1:12, 7, 9)
#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE
#> [12] FALSE

x <- rnorm(1e2)
x[between(x, -1, 1)]
#>  [1]  0.93536319  0.17648861  0.24368546  0.11203808 -0.13399701
#>  [6] -0.27923724 -0.31344598  0.07003485 -0.63912332 -0.04996490
#> [11] -0.25148344  0.44479712  0.04653138  0.57770907  0.11819487
#> [16]  0.86208648 -0.24323674 -0.20608719  0.01917759  0.02956075
#> [21]  0.54982754 -0.36122126  0.21335575 -0.66508825 -0.24589641
#> [26] -0.97585062  0.13167063  0.48862881  0.28415034  0.23669628
#> [31]  0.52390979  0.60674805 -0.10993567  0.17218172 -0.09032729
#> [36]  0.74879127  0.55622433 -0.54825726 -0.15569378  0.43388979
#> [41] -0.38195111  0.42418757 -0.03810289  0.48614892 -0.35436116
#> [46]  0.94634789 -0.29664002 -0.38721358 -0.78543266 -0.79554143
#> [51] -0.69053790 -0.55854199 -0.53666333  0.22712713  0.97845492
#> [56] -0.20888265  0.25853729 -0.44179945  0.56859986  0.42485844
#> [61]  0.24940178  0.44945378  0.42656655  0.10758399  0.02229473
#> [66]  0.60361101 -0.26265057 -0.52826408  0.19214942

# On a tibble using `filter()`
filter(starwars, between(height, 100, 150))
#> # A tibble: 5 × 14
#>   name       height  mass hair_color skin_color eye_color birth_year sex  
#>   <chr>       <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr>
#> 1 Leia Orga…    150    49 brown      light      brown             19 fema…
#> 2 Mon Mothma    150    NA auburn     fair       blue              48 fema…
#> 3 Watto         137    NA black      blue, grey yellow            NA male 
#> 4 Sebulba       112    40 none       grey, red  orange            NA male 
#> 5 Gasgano       122    NA none       white, bl… black             NA male 
#> # ℹ 6 more variables: gender <chr>, homeworld <chr>, species <chr>,
#> #   films <list>, vehicles <list>, starships <list>