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_logical(x, na = c("", "NA"), locale = default_locale(), trim_ws = TRUE)
parse_integer(x, na = c("", "NA"), locale = default_locale(), trim_ws = TRUE)
parse_double(x, na = c("", "NA"), locale = default_locale(), trim_ws = TRUE)
parse_character(x, na = c("", "NA"), locale = default_locale(), trim_ws = TRUE)
col_logical()
col_integer()
col_double()
col_character()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?
See also
Other parsers:
col_skip(),
cols_condense(),
cols(),
parse_datetime(),
parse_factor(),
parse_guess(),
parse_number(),
parse_vector()
Examples
parse_integer(c("1", "2", "3"))
#> [1] 1 2 3
parse_double(c("1", "2", "3.123"))
#> [1] 1.000 2.000 3.123
parse_number("$1,123,456.00")
#> [1] 1123456
# Use locale to override default decimal and grouping marks
es_MX <- locale("es", decimal_mark = ",")
parse_number("$1.123.456,00", locale = es_MX)
#> [1] 1123456
# Invalid values are replaced with missing values with a warning.
x <- c("1", "2", "3", "-")
parse_double(x)
#> Warning: 1 parsing failure.
#> row col expected actual
#> 4 -- a double -
#> [1] 1 2 3 NA
#> attr(,"problems")
#> # A tibble: 1 × 4
#> row col expected actual
#> <int> <int> <chr> <chr>
#> 1 4 NA a double -
# Or flag values as missing
parse_double(x, na = "-")
#> [1] 1 2 3 NA