This parses the first number it finds, dropping any non-numeric characters before the first number and all characters after the first number. The grouping mark specified by the locale is ignored inside the number.
Usage
parse_number(
x,
na = c("", "NA"),
locale = default_locale(),
trim_ws = TRUE,
.return_problems = FALSE
)
col_number()Arguments
- x
Character vector of values to parse.
- na
Character vector of strings to interpret as missing values. Set this option to
character()to indicate no missing values.- locale
The locale controls defaults that vary from place to place. The default locale is US-centric (like R), but you can use
locale()to create your own locale that controls things like the default time zone, encoding, decimal mark, big mark, and day/month names.- trim_ws
Should leading and trailing whitespace (ASCII spaces and tabs) be trimmed from each field before parsing it?
- .return_problems
Whether to hide the
problemstibble from the output
See also
Other parsers:
col_skip(),
parse_datetime(),
parse_factor(),
parse_guess(),
parse_logical(),
parse_vector()
Examples
## These all return 1000
parse_number("$1,000") ## leading `$` and grouping character `,` ignored
#> [1] 1000
parse_number("euro1,000") ## leading non-numeric euro ignored
#> [1] 1000
parse_number("t1000t1000") ## only parses first number found
#> [1] 1000
parse_number("1,234.56")
#> [1] 1234.56
## explicit locale specifying European grouping and decimal marks
parse_number("1.234,56", locale = locale(decimal_mark = ",", grouping_mark = "."))
#> [1] 1234.56
## SI/ISO 31-0 standard spaces for number grouping
parse_number("1 234.56", locale = locale(decimal_mark = ".", grouping_mark = " "))
#> [1] 1234.56
## Specifying strings for NAs
parse_number(c("1", "2", "3", "NA"))
#> [1] 1 2 3 NA
parse_number(c("1", "2", "3", "NA", "Nothing"), na = c("NA", "Nothing"))
#> [1] 1 2 3 NA NA