To reuse filter predicates, wrap them in an expression (the predicate is the condition that must be TRUE to select a row).

library(tidyverse)
library(magrittr)

mtcars <- as_tibble(mtcars)

cyl_eq_6 <- expr(cyl == 6)

Evaluate (i.e. unwrap) the predicate using !! (i.e. bang-bang).

mtcars %>% filter(!!cyl_eq_6)

#> # A tibble: 7 x 11
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#> 2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#> 3  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#> 4  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#> 5  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> 6  17.8     6  168.   123  3.92  3.44  18.9     1     0     4     4
#> 7  19.7     6  145    175  3.62  2.77  15.5     0     1     5     6

Modify predicates by evaluating them and then applying a new function. Here the predicate is negated to take all rows not satisfying the predicate.

mtcars %>% filter(not(!!cyl_eq_6))

#> # A tibble: 25 x 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#>  2  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  3  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  4  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  5  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#>  6  16.4     8  276.   180  3.07  4.07  17.4     0     0     3     3
#>  7  17.3     8  276.   180  3.07  3.73  17.6     0     0     3     3
#>  8  15.2     8  276.   180  3.07  3.78  18       0     0     3     3
#>  9  10.4     8  472    205  2.93  5.25  18.0     0     0     3     4
#> 10  10.4     8  460    215  3     5.42  17.8     0     0     3     4
#> # … with 15 more rows

Reuse modified predicates by unwrapping the predicate, applying the modification (like above), and then re-wrapping the modified predicate into a new expression.

cyl_not_eq_6 <- expr(not(!!cyl_eq_6))

mtcars %>% filter(!!cyl_not_eq_6)

#> # A tibble: 25 x 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#>  2  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  3  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  4  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  5  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#>  6  16.4     8  276.   180  3.07  4.07  17.4     0     0     3     3
#>  7  17.3     8  276.   180  3.07  3.73  17.6     0     0     3     3
#>  8  15.2     8  276.   180  3.07  3.78  18       0     0     3     3
#>  9  10.4     8  472    205  2.93  5.25  18.0     0     0     3     4
#> 10  10.4     8  460    215  3     5.42  17.8     0     0     3     4
#> # … with 15 more rows

Compose/combine multiple predicates to create a new predicate.

disp_gt_200 <- expr(disp > 200)

mtcars %>% filter(!!cyl_eq_6 & !!disp_gt_200)

#> # A tibble: 2 x 11
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1
#> 2  18.1     6   225   105  2.76  3.46  20.2     1     0     3     1

mtcars %>% filter(!!cyl_eq_6 | !!disp_gt_200)

#> # A tibble: 21 x 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#>  3  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#>  4  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  5  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  6  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  7  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#>  8  17.8     6  168.   123  3.92  3.44  18.9     1     0     4     4
#>  9  16.4     8  276.   180  3.07  4.07  17.4     0     0     3     3
#> 10  17.3     8  276.   180  3.07  3.73  17.6     0     0     3     3
#> # … with 11 more rows

Reuse composed predicates by evaluating them and re-wrapping into a new, single predicate.

cyl_eq_6_and_disp_gt_200 <- expr(!!cyl_eq_6 & !!disp_gt_200)

mtcars %>% filter(!!cyl_eq_6_and_disp_gt_200)

#> # A tibble: 2 x 11
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  21.4     6   258   110  3.08  3.22  19.4     1     0     3     1
#> 2  18.1     6   225   105  2.76  3.46  20.2     1     0     3     1

Created on 2020-03-30 by the reprex package (v0.3.0)