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By default tables produced by functions tables, cro,
cro_fun and cro_fun_df are created with all
possible value labels. If values for this labels are absent in variable there
are NA's in rows and columns.
drop_empty_rows
/drop_empty_columns
are intended to remove
these empty rows/columns. drop_r
and drop_c
are the same
functions with shorter names. drop_rc
drops rows and columns
simultaneously.
drop_empty_rows(x, excluded_rows = NULL, excluded_columns = NULL)drop_empty_columns(x, excluded_rows = NULL, excluded_columns = NULL)
drop_r(x, excluded_rows = NULL, excluded_columns = NULL)
drop_c(x, excluded_rows = NULL, excluded_columns = NULL)
drop_rc(x)
data.frame/etable(result of cro and etc.)
character/logical/numeric rows which won't be dropped
and in which NAs won't be counted. If it is characters then they will be
considered as pattern/vector of patterns. Patterns will be matched with
Perl-style regular expression with values in the first column of x
(see grep, perl = TRUE
argument). Rows which have such
patterns will be excluded. By default for class 'etable' pattern is "#"
because "#" marks totals in the result of cro.
logical/numeric/characters columns which won't be dropped and in which NAs won't be counted. By default for class 'etable' it is first column - column with labels in table.
data.frame with removed rows/columns
# NOT RUN {
data(mtcars)
mtcars = apply_labels(mtcars,
vs = "Engine",
vs = num_lab("
0 V-engine
1 Straight engine
9 Other
"),
am = "Transmission",
am = num_lab("
0 Automatic
1 Manual
9 Other
")
)
with_empty = calculate(mtcars, cro(am, vs))
drop_empty_rows(with_empty)
drop_empty_columns(with_empty)
drop_rc(with_empty)
# }
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