cols: Create column specification
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View source: R/col_types.R

cols	R Documentation

Create column specification

Description

cols() includes all columns in the input data, guessing the column types as the default. cols_only() includes only the columns you explicitly specify, skipping the rest.

Usage

cols(..., .default = col_guess(), .delim = NULL)

cols_only(...)

col_logical(...)

col_integer(...)

col_big_integer(...)

col_double(...)

col_character(...)

col_skip(...)

col_number(...)

col_guess(...)

col_factor(levels = NULL, ordered = FALSE, include_na = FALSE, ...)

col_datetime(format = "", ...)

col_date(format = "", ...)

col_time(format = "", ...)

Arguments

`...`	Either column objects created by `⁠col_()⁠`, or their abbreviated character names (as described in the `col_types` argument of `vroom()`). If you're only overriding a few columns, it's best to refer to columns by name. If not named, the column types must match the column names exactly. In `⁠col_()⁠` functions these are stored in the object.
`.default`	Any named columns not explicitly overridden in `...` will be read with this column type.
`.delim`	The delimiter to use when parsing. If the `delim` argument used in the call to `vroom()` it takes precedence over the one specified in `col_types`.
`levels`	Character vector of the allowed levels. When `levels = NULL` (the default), `levels` are discovered from the unique values of `x`, in the order in which they appear in `x`.
`ordered`	Is it an ordered factor?
`include_na`	If `TRUE` and `x` contains at least one `NA`, then `NA` is included in the levels of the constructed factor.
`format`	A format specification, as described below. If set to "", date times are parsed as ISO8601, dates and times used the date and time formats specified in the `locale()`. Unlike `strptime()`, the format specification must match the complete string.

Details

The available specifications are: (long names in quotes and string abbreviations in brackets)

function	long name	short name	description
`col_logical()`	"logical"	"l"	Logical values containing only `T`, `F`, `TRUE` or `FALSE`.
`col_integer()`	"integer"	"i"	Integer numbers.
`col_big_integer()`	"big_integer"	"I"	Big Integers (64bit), requires the `bit64` package.
`col_double()`	"double", "numeric"	"d"	64-bit double floating point numbers.
`col_character()`	"character"	"c"	Character string data.
`col_factor(levels, ordered)`	"factor"	"f"	A fixed set of values.
`col_date(format = "")`	"date"	"D"	Calendar dates formatted with the locale's `date_format`.
`col_time(format = "")`	"time"	"t"	Times formatted with the locale's `time_format`.
`col_datetime(format = "")`	"datetime", "POSIXct"	"T"	ISO8601 date times.
`col_number()`	"number"	"n"	Human readable numbers containing the `grouping_mark`
`col_skip()`	"skip", "NULL"	"_", "-"	Skip and don't import this column.
`col_guess()`	"guess", "NA"	"?"	Parse using the "best" guessed type based on the input.

Examples

cols(a = col_integer())
cols_only(a = col_integer())

# You can also use the standard abbreviations
cols(a = "i")
cols(a = "i", b = "d", c = "_")

# Or long names (like utils::read.csv)
cols(a = "integer", b = "double", c = "skip")

# You can also use multiple sets of column definitions by combining
# them like so:

t1 <- cols(
  column_one = col_integer(),
  column_two = col_number())

t2 <- cols(
 column_three = col_character())

t3 <- t1
t3$cols <- c(t1$cols, t2$cols)
t3

vroom documentation built on July 4, 2024, 9:08 a.m.