separate.ir: Separate a character column in an 'ir' object into multiple...

In ir: Functions to Handle and Preprocess Infrared Spectra

Separate a character column in an ir object into multiple columns with a regular expression or numeric locations

Description

Separate a character column in an ir object into multiple columns with a regular expression or numeric locations

Usage

separate.ir(
  data,
  col,
  into,
  sep = "[^[:alnum:]]+",
  remove = TRUE,
  convert = FALSE,
  extra = "warn",
  fill = "warn",
  ...
)

Arguments

data	An object of class ir.
col	Column name or position. This is passed to tidyselect::vars_pull(). This argument is passed by expression and supports quasiquotation (you can unquote column names or column positions).
into	Names of new variables to create as character vector. Use NA to omit the variable in the output.
sep	Separator between columns. If character, sep is interpreted as a regular expression. The default value is a regular expression that matches any sequence of non-alphanumeric values. If numeric, sep is interpreted as character positions to split at. Positive values start at 1 at the far-left of the string; negative value start at -1 at the far-right of the string. The length of sep should be one less than into.
remove	If TRUE, remove input column from output data frame.
convert	If TRUE, will run type.convert() with as.is = TRUE on new columns. This is useful if the component columns are integer, numeric or logical. NB: this will cause string "NA"s to be converted to NAs.
extra	If sep is a character vector, this controls what happens when there are too many pieces. There are three valid options: "warn" (the default): emit a warning and drop extra values. "drop": drop any extra values without a warning. "merge": only splits at most length(into) times
fill	If sep is a character vector, this controls what happens when there are not enough pieces. There are three valid options: "warn" (the default): emit a warning and fill from the right "right": fill with missing values on the right "left": fill with missing values on the left
...	Additional arguments passed on to methods.

Value

.data with separated columns. If the spectra column is dropped or invalidated (see ir_new_ir()), the ir class is dropped, else the object is of class ir.

Source

tidyr::separate()

See Also

Other tidyverse: arrange.ir(), distinct.ir(), extract.ir(), filter-joins, filter.ir(), group_by, mutate-joins, mutate, nest, pivot_longer.ir(), pivot_wider.ir(), rename, rowwise.ir(), select.ir(), separate_rows.ir(), slice, summarize, unite.ir()

Examples

## separate
ir_sample_data %>%
  tidyr::separate(
    col = "id_sample",  c("a", "b", "c")
  )

ir documentation built on May 2, 2022, 5:06 p.m.