View source: R/colby_constructors.R
basic_table | R Documentation |
Every layout must start with a basic table.
basic_table(
title = "",
subtitles = character(),
main_footer = character(),
prov_footer = character(),
show_colcounts = NA,
colcount_format = "(N=xx)",
header_section_div = NA_character_,
top_level_section_div = NA_character_,
inset = 0L
)
title |
( |
subtitles |
( |
main_footer |
( |
prov_footer |
( |
show_colcounts |
( |
colcount_format |
( |
header_section_div |
( |
top_level_section_div |
( |
inset |
( |
colcount_format
is ignored if show_colcounts
is FALSE
(the default). When show_colcounts
is TRUE
,
and colcount_format
is 2-dimensional with a percent component, the value component for the percent is always
populated with 1
(i.e. 100%). 1d formats are used to render the counts exactly as they normally would be,
while 2d formats which don't include a percent, and all 3d formats result in an error. Formats in the form of
functions are not supported for colcount
format. See formatters::list_valid_format_labels()
for the list
of valid format labels to select from.
A PreDataTableLayouts
object suitable for passing to further layouting functions, and to build_table()
.
Because percent components in colcount_format
are always populated with the value 1, we can get arguably
strange results, such as that individual arm columns and a combined "all patients" column all list "100%" as
their percentage, even though the individual arm columns represent strict subsets of the "all patients" column.
Note that subtitles (formatters::subtitles()
) and footers (formatters::main_footer()
and
formatters::prov_footer()
) that span more than one line can be supplied as a character vector to maintain
indentation on multiple lines.
lyt <- basic_table() %>%
analyze("AGE", afun = mean)
tbl <- build_table(lyt, DM)
tbl
lyt2 <- basic_table(
title = "Title of table",
subtitles = c("a number", "of subtitles"),
main_footer = "test footer",
prov_footer = paste(
"test.R program, executed at",
Sys.time()
)
) %>%
split_cols_by("ARM") %>%
analyze("AGE", mean)
tbl2 <- build_table(lyt2, DM)
tbl2
lyt3 <- basic_table(
show_colcounts = TRUE,
colcount_format = "xx. (xx.%)"
) %>%
split_cols_by("ARM")
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