Use parse_ if you have a character vector you want to parse. Use
col_ in conjunction with a read_ function to parse the
values as they're read in.
Usage
parse_guess(x, na = c("", "NA"), locale = default_locale())
col_character()
parse_character(x, na = c("", "NA"), locale = default_locale())
col_integer()
parse_integer(x, na = c("", "NA"), locale = default_locale())
col_double()
parse_double(x, na = c("", "NA"), locale = default_locale())
col_euro_double()
parse_euro_double(x, na = c("", "NA"))
col_number()
parse_number(x, na = c("", "NA"), locale = default_locale())
col_logical()
parse_logical(x, na = c("", "NA"), locale = default_locale())
col_factor(levels, ordered = FALSE)
parse_factor(x, levels, ordered = FALSE, na = c("", "NA"),
locale = default_locale())
col_skip()
col_guess()
Arguments
x
Character vector of values to parse.
na
Character vector of strings to use for 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.
levels
Character vector providing set of allowed levels.
ordered
Is it an ordered factor?
See Also
parse_datetime, type_convert to
automatically re-parse all character columns in a data frame.
Examples
parse_integer(c("1", "2", "3"))
parse_double(c("1", "2", "3.123"))
parse_factor(c("a", "b"), letters)
parse_number("$1,123,456.00")
# Use locale to override default decimal and grouping marks
es_MX <- locale("es", decimal_mark = ",")
parse_number("$1.123.456,00", locale = es_MX)
# Invalid values are replaced with missing values with a warning.
x <- c("1", "2", "3", "-")
parse_double(x)
# Or flag values as missing
parse_double(x, na = "-")