Create column specification
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.
cols(..., .default = col_guess()) cols_only(...)
... |
Either column objects created by |
.default |
Any named columns not explicitly overridden in |
The available specifications are: (with string abbreviations in brackets)
col_logical() [l], containing only T, F, TRUE or FALSE.
col_integer() [i], integers.
col_double() [d], doubles.
col_character() [c], everything else.
col_factor(levels, ordered) [f], a fixed set of values.
col_date(format = "") [D]: with the locale's date_format.
col_time(format = "") [t]: with the locale's time_format.
col_datetime(format = "") [T]: ISO8601 date times
col_number() [n], numbers containing the grouping_mark
col_skip() [_, -], don't import this column.
col_guess() [?], parse using the "best" type based on the input.
Other parsers:
col_skip(),
cols_condense(),
parse_datetime(),
parse_factor(),
parse_guess(),
parse_logical(),
parse_number(),
parse_vector()
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 = "_") # 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
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