Build a data frame
tibble() constructs a data frame. It is used like base::data.frame(), but
with a couple notable differences:
The returned data frame has the class tbl_df, in
addition to data.frame. This allows so-called "tibbles" to exhibit some
special behaviour, such as enhanced printing. Tibbles are
fully described in tbl_df.
tibble() is much lazier than base::data.frame() in terms of
transforming the user's input.
Character vectors are not coerced to factor.
List-columns are expressly anticipated and do not require special tricks.
Column names are not modified.
Inner names in columns are left unchanged.
tibble() builds columns sequentially. When defining a column, you can
refer to columns created earlier in the call. Only columns of length one
are recycled.
If a column evaluates to a data frame or tibble, it is nested or spliced. See examples.
tibble_row() constructs a data frame that is guaranteed to occupy one row.
Vector columns are required to have size one, non-vector columns are wrapped
in a list.
tibble(
...,
.rows = NULL,
.name_repair = c("check_unique", "unique", "universal", "minimal")
)
tibble_row(
...,
.name_repair = c("check_unique", "unique", "universal", "minimal")
)... |
< Arguments are evaluated sequentially.
You can refer to previously created elements directly or using the .data
pronoun.
An existing |
.rows |
The number of rows, useful to create a 0-column tibble or just as an additional check. |
.name_repair |
Treatment of problematic column names:
This argument is passed on as |
Use as_tibble() to turn an existing object into a tibble. Use
enframe() to convert a named vector into a tibble. Name repair is
detailed in vctrs::vec_as_names().
See quasiquotation for more details on tidy dots semantics,
i.e. exactly how the ... argument is processed.
# Unnamed arguments are named with their expression:
a <- 1:5
tibble(a, a * 2)
# Scalars (vectors of length one) are recycled:
tibble(a, b = a * 2, c = 1)
# Columns are available in subsequent expressions:
tibble(x = runif(10), y = x * 2)
# tibble() never coerces its inputs,
str(tibble(letters))
str(tibble(x = list(diag(1), diag(2))))
# or munges column names (unless requested),
tibble(`a + b` = 1:5)
# but it forces you to take charge of names, if they need repair:
try(tibble(x = 1, x = 2))
tibble(x = 1, x = 2, .name_repair = "unique")
tibble(x = 1, x = 2, .name_repair = "minimal")
## By default, non-syntactic names are allowed,
df <- tibble(`a 1` = 1, `a 2` = 2)
## because you can still index by name:
df[["a 1"]]
df$`a 1`
with(df, `a 1`)
## Syntactic names are easier to work with, though, and you can request them:
df <- tibble(`a 1` = 1, `a 2` = 2, .name_repair = "universal")
df$a.1
## You can specify your own name repair function:
tibble(x = 1, x = 2, .name_repair = make.unique)
fix_names <- function(x) gsub("\\s+", "_", x)
tibble(`year 1` = 1, `year 2` = 2, .name_repair = fix_names)
## purrr-style anonymous functions and constants
## are also supported
tibble(x = 1, x = 2, .name_repair = ~ make.names(., unique = TRUE))
tibble(x = 1, x = 2, .name_repair = ~ c("a", "b"))
# Tibbles can contain columns that are tibbles or matrices
# if the number of rows is compatible. Unnamed tibbled are
# spliced, i.e. the inner columns are inserted into the
# tibble under construction.
tibble(
a = 1:3,
tibble(
b = 4:6,
c = 7:9
),
d = tibble(
e = tibble(
f = b
)
)
)
tibble(
a = 1:4,
b = diag(4),
c = cov(iris[1:4])
)
# data can not contain POSIXlt columns, or tibbles or matrices
# with incompatible number of rows:
try(tibble(y = strptime("2000/01/01", "%x")))
try(tibble(a = 1:3, b = tibble(c = 4:7)))
# Use := to create columns with names that start with a dot:
tibble(.dotted = 3)
tibble(.dotted := 3)
# You can unquote an expression:
x <- 3
tibble(x = 1, y = x)
tibble(x = 1, y = !!x)
# You can splice-unquote a list of quosures and expressions:
tibble(!!! list(x = rlang::quo(1:10), y = quote(x * 2)))
# Use tibble_row() to construct a one-row tibble:
tibble_row(a = 1, lm = lm(Petal.Width ~ Petal.Length + Species, data = iris))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.