The function provides a way to get column keys
associated with the flextable corresponding to a tabulator()
object. It helps in customizing or programing with tabulator.
The function is using column names from the original dataset, eventually filters and returns the names corresponding to the selection.
tabulator_colnames(x, columns, ..., type = NULL)a tabulator() object
column names to look for
any filter conditions that use variables
names, the same than the argument columns of function tabulator()
(tabulator(columns = c("col1", "col2"))).
the type of column to look for, it can be:
'columns': visible columns, corresponding to names provided in the '...' arguments of your call to 'tabulator()'.
'hidden': unvisible columns, corresponding to names of the original dataset columns.
'rows': visible columns used as 'row' content
'rows_supp': visible columns used as 'rows_supp' content
NULL: any type of column
library(flextable)
cancer_dat <- data.frame(
count = c(
9L, 5L, 1L, 2L, 2L, 1L, 9L, 3L, 1L, 10L, 2L, 1L, 1L, 2L, 0L, 3L,
2L, 1L, 1L, 2L, 0L, 12L, 4L, 1L, 7L, 3L, 1L, 5L, 5L, 3L, 10L,
4L, 1L, 4L, 2L, 0L, 3L, 1L, 0L, 4L, 4L, 2L, 42L, 28L, 19L, 26L,
19L, 11L, 12L, 10L, 7L, 10L, 5L, 6L, 5L, 0L, 3L, 4L, 3L, 3L,
1L, 2L, 3L
),
risktime = c(
157L, 77L, 21L, 139L, 68L, 17L, 126L, 63L, 14L, 102L, 55L,
12L, 88L, 50L, 10L, 82L, 45L, 8L, 76L, 42L, 6L, 134L, 71L,
22L, 110L, 63L, 18L, 96L, 58L, 14L, 86L, 42L, 10L, 66L,
35L, 8L, 59L, 32L, 8L, 51L, 28L, 6L, 212L, 130L, 101L,
136L, 72L, 63L, 90L, 42L, 43L, 64L, 21L, 32L, 47L, 14L,
21L, 39L, 13L, 14L, 29L, 7L, 10L
),
time = rep(as.character(1:7), 3),
histology = rep(as.character(1:3), 21),
stage = rep(as.character(1:3), each = 21)
)
datasup_first <- data.frame(
time = factor(1:7, levels = 1:7),
zzz = runif(7)
)
z <- tabulator(cancer_dat,
rows = "time",
columns = c("histology", "stage"),
datasup_first = datasup_first,
n = as_paragraph(as_chunk(count))
)
j <- tabulator_colnames(
x = z, type = "columns",
columns = c("n"),
stage %in% 1
)
src <- tabulator_colnames(
x = z, type = "hidden",
columns = c("count"),
stage %in% 1
)
if (require("scales")) {
colourer <- col_numeric(
palette = c("wheat", "red"),
domain = c(0, 45)
)
ft_1 <- as_flextable(z)
ft_1 <- bg(
ft_1,
bg = colourer, part = "body",
j = j, source = src
)
ft_1
}
#> a flextable object.
#> col_keys: `time`, `dummy1`, `zzz`, `dummy2`, `1@1@n`, `dummy3`, `1@2@n`, `dummy4`, `1@3@n`, `dummy5`, `2@1@n`, `dummy6`, `2@2@n`, `dummy7`, `2@3@n`, `dummy8`, `3@1@n`, `dummy9`, `3@2@n`, `dummy10`, `3@3@n`
#> header has 2 row(s)
#> body has 7 row(s)
#> original dataset sample:
#> time count@1@1 count@1@2 count@1@3 count@2@1 count@2@2 count@2@3 count@3@1
#> 1 1 9 12 42 3 5 10 0
#> 2 2 3 3 4 5 4 28 1
#> 3 3 10 10 10 2 1 3 1
#> 4 4 2 7 26 2 4 5 1
#> 5 5 1 4 1 2 3 19 1
#> count@3@2 count@3@3 risktime@1@1 risktime@1@2 risktime@1@3 risktime@2@1
#> 1 0 3 157 134 212 63
#> 2 3 7 82 59 39 77
#> 3 1 19 102 86 64 45
#> 4 0 3 139 110 136 55
#> 5 1 6 76 51 29 68
#> risktime@2@2 risktime@2@3 risktime@3@1 risktime@3@2 risktime@3@3 n@1@1 n@1@2
#> 1 58 42 10 8 21
#> 2 71 130 14 14 43
#> 3 32 13 21 22 101
#> 4 42 21 8 8 14
#> 5 63 72 12 10 32
#> n@1@3 n@2@1 n@2@2 n@2@3 n@3@1 n@3@2 n@3@3 zzz dummy1 dummy2 1@1@n
#> 1 0.81042105
#> 2 0.90254769
#> 3 0.05717864
#> 4 0.29712830
#> 5 0.28870855
#> dummy3 1@2@n dummy4 1@3@n dummy5 2@1@n dummy6 2@2@n dummy7 2@3@n dummy8 3@1@n
#> 1
#> 2
#> 3
#> 4
#> 5
#> dummy9 3@2@n dummy10 3@3@n
#> 1
#> 2
#> 3
#> 4
#> 5