Recursively prune a TableTree
Arguments
- tt
TableTree (or related class). A TableTree object representing a populated table.
- prune_func
function. A Function to be called on each subtree which returns TRUE if the entire subtree should be removed.
- stop_depth
numeric(1). The depth after which subtrees should not be checked for pruning. Defaults to
NAwhich indicates pruning should happen at all levels- depth
numeric(1). Used internally, not intended to be set by the end user.
See also
prune_empty_level() for details on this and several other basic
pruning functions included in the rtables package.
Examples
adsl <- ex_adsl
levels(adsl$SEX) <- c(levels(ex_adsl$SEX), "OTHER")
tbl_to_prune <- basic_table() %>%
split_cols_by("ARM") %>%
split_rows_by("SEX") %>%
summarize_row_groups() %>%
split_rows_by("STRATA1") %>%
summarize_row_groups() %>%
analyze("AGE") %>%
build_table(adsl)
tbl_to_prune %>% prune_table()
#> A: Drug X B: Placebo C: Combination
#> ———————————————————————————————————————————————————————————
#> F 79 (59.0%) 77 (57.5%) 66 (50.0%)
#> A 21 (15.7%) 24 (17.9%) 18 (13.6%)
#> Mean 31.14 32.08 34.22
#> B 25 (18.7%) 27 (20.1%) 21 (15.9%)
#> Mean 32.84 35.33 36.57
#> C 33 (24.6%) 26 (19.4%) 27 (20.5%)
#> Mean 33.73 34.73 34.78
#> M 51 (38.1%) 55 (41.0%) 60 (45.5%)
#> A 16 (11.9%) 19 (14.2%) 20 (15.2%)
#> Mean 35.62 39.37 33.55
#> B 21 (15.7%) 17 (12.7%) 21 (15.9%)
#> Mean 35.33 37.12 36.05
#> C 14 (10.4%) 19 (14.2%) 19 (14.4%)
#> Mean 35.86 35.79 36.58
#> U 3 (2.2%) 2 (1.5%) 4 (3.0%)
#> A 1 (0.7%) 1 (0.7%) 1 (0.8%)
#> Mean 33.00 27.00 38.00
#> B 1 (0.7%) 1 (0.7%) 1 (0.8%)
#> Mean 28.00 35.00 37.00
#> C 1 (0.7%) 0 (0.0%) 2 (1.5%)
#> Mean 34.00 NA 33.00
#> UNDIFFERENTIATED 1 (0.7%) 0 (0.0%) 2 (1.5%)
#> A 0 (0.0%) 0 (0.0%) 1 (0.8%)
#> Mean NA NA 44.00
#> C 1 (0.7%) 0 (0.0%) 1 (0.8%)
#> Mean 28.00 NA 46.00