expss (version 0.10.7)

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)

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.

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.

See Also

strsplit

Examples

# NOT RUN {
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 %>% 
       calculate(cro_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)


# }