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.

parse_logical(x, na = c("", "NA"), locale = default_locale())

parse_integer(x, na = c("", "NA"), locale = default_locale())

parse_double(x, na = c("", "NA"), locale = default_locale())

parse_character(x, na = c("", "NA"), locale = default_locale())

col_logical()

col_integer()

col_double()

col_character()

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.

See also

Other parsers: col_skip, parse_datetime, parse_factor, parse_guess, parse_number

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