extract {tidyseurat}

Extract a character column into multiple columns using regular expression groups

Description

extract() has been superseded in favour of separate_wider_regex() because it has a more polished API and better handling of problems. Superseded functions will not go away, but will only receive critical bug fixes.

Given a regular expression with capturing groups, extract() turns each group into a new column. If the groups don't match, or the input is NA, the output will be NA.

Usage

## S3 method for class 'Seurat'
extract(
  data,
  col,
  into,
  regex = "([[:alnum:]]+)",
  remove = TRUE,
  convert = FALSE,
  ...
)

Arguments

data

A data frame.

col

<tidy-select> Column to expand.

into

Names of new variables to create as character vector. Use NA to omit the variable in the output.

regex

A string representing a regular expression used to extract the desired values. There should be one group (defined by ⁠()⁠) for each element of 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.

...

Additional arguments passed on to methods.

Value

'tidyseurat'

See Also

separate() to split up by a separator.

Examples

data(pbmc_small)
pbmc_small |>
  extract(groups, 
    into="g", 
    regex="g([0-9])", 
    convert=TRUE)