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expss (version 0.11.6)

split_labels: Split character vector to matrix/split columns in data.frame

Description

split_labels/split_columns are auxiliary functions for post-processing tables resulted from cro/cro_fun and etc. In these tables all labels collapsed in the first column with "|" separator. split_columns split first column into multiple columns with separator (split argument). split_table_to_df split first column of table and column names. Result of this operation is data.frame with character columns.

Usage

split_labels(
  x,
  remove_repeated = TRUE,
  split = "\\|",
  fixed = FALSE,
  perl = FALSE
)

split_columns( data, columns = 1, remove_repeated = TRUE, split = "\\|", fixed = FALSE, perl = FALSE )

split_table_to_df( data, digits = get_expss_digits(), remove_repeated = TRUE, split = "\\|", fixed = FALSE, perl = FALSE )

make_subheadings(data, number_of_columns = 1)

Value

split_labels returns character matrix, split_columns returns data.frame with columns replaced by possibly multiple columns with split labels. split_table_to_df returns data.frame with character columns.

Arguments

x

character vector which will be split

remove_repeated

logical. Default is TRUE. Should we remove repeated labels?

split

character vector (or object which can be coerced to such) containing regular expression(s) (unless fixed = TRUE) to use for splitting.

fixed

logical. If TRUE match split exactly, otherwise use regular expressions. Has priority over perl.

perl

logical. Should Perl-compatible regexps be used?

data

data.frame vector which will be split

columns

character/numeric/logical columns in the data.frame data which should be split

digits

numeric. How many digits after decimal point should be left in split_table_to_df?

number_of_columns

integer. Number of columns from row labels which will be used as subheadings in table.

See Also

Examples

Run this code
data.table::setDTthreads(2)
data(mtcars)

# apply labels
mtcars = apply_labels(mtcars,
    cyl = "Number of cylinders",
    vs = "Engine",
    vs = c("V-engine" = 0,
                    "Straight engine" = 1),
    am = "Transmission",
    am = c(automatic = 0,
                    manual=1),
    gear = "Number of forward gears",
    carb = "Number of carburetors"
)

# all row labels in the first column
tabl = mtcars %>% 
       cross_cpct(list(cyl, gear, carb), list(total(), vs, am))

tabl # without subheadings

make_subheadings(tabl) # with subheadings
              
split_labels(tabl[[1]])
split_labels(colnames(tabl))

# replace first column with new columns 
split_columns(tabl) # remove repeated

split_columns(tabl, remove_repeated = FALSE)

split_columns(tabl)

split_table_to_df(tabl)

split_table_to_df(tabl)


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