Aggregate table of descriptives according to functions
provided in fn
argument. This function follows
melt/cast approach used in reshape
package. Variable
names specified in measure.vars
argument are treated
as measure.vars
, while the ones in id.vars
are treated as id.vars
(see
melt.data.frame
for details). Other
its formal arguments match with corresponding arguments for
cast
function. Some post-processing
is done after reshaping, in order to get pretty row and
column labels.
rp.desc(measure.vars, id.vars = NULL, fn, data = NULL, na.rm = TRUE,
margins = NULL, subset = TRUE, fill = NA, add.missing = FALSE,
total.name = "Total", varcol.name = "Variable",
use.labels = getOption("rapport.use.labels"), remove.duplicate = TRUE)
either a character vector with
variable names from data
, a numeric vector, or a
data.frame
same rules apply as in
measure.vars
, but defaults to NULL
a list with functions or a character vector with function names
a data.frame
holding variables
specified in id.vars
and measure.vars
a logical value indicating whether NA
values should be removed
should margins be included? (see
documentation for eponymous argument in
melt.data.frame
)
a logical vector to subset the data before aggregating
value to replace missing level combinations
(see documentation for eponymous argument in
melt.data.frame
)
show missing level combinations
a character string with name for "grand" margin (defaults to "Total")
character string for column that
contains summarised variables (defaults to
"Variable"
)
use labels instead of variable names in
table header (handle with care, especially if you have
lengthy labels). Defaults to value specified in
rapport.use.labels
option.
should name/label of the variable
provided in measure.vars
be removed from each
column if only one measure.var
is provided
(defaults to TRUE
)
a data.frame
with aggregated data
# NOT RUN {
rp.desc("cyl", "am", c(mean, sd), mtcars, margins = TRUE)
## c
rp.desc("hp", c("am", "gear"), c("Average" = mean, "Deviation" = sd),
mtcars, remove.duplicate = FALSE)
# }
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