extract

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Extract one column into multiple columns.

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
extract(data, col, into, regex = "([[:alnum:]]+)", remove = TRUE,
  convert = FALSE, ...)
Arguments
data

A data frame.

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.

regex

a regular expression used to extract the desired values. The 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.

...

Other arguments passed on to regexec() to control how the regular expression is processed.

Aliases
  • extract
Examples
# NOT RUN {
library(dplyr)
df <- data.frame(x = c(NA, "a-b", "a-d", "b-c", "d-e"))
df %>% extract(x, "A")
df %>% extract(x, c("A", "B"), "([[:alnum:]]+)-([[:alnum:]]+)")

# If no match, NA:
df %>% extract(x, c("A", "B"), "([a-d]+)-([a-d]+)")
# }
Documentation reproduced from package tidyr, version 0.8.0, License: MIT + file LICENSE

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