data.frame(..., row.names = NULL, check.rows = FALSE, check.names = TRUE, stringsAsFactors = default.stringsAsFactors())
default.stringsAsFactors()
value
or
tag = value
. Component names are created based on the tag (if
present) or the deparsed argument itself.NULL
or a single integer or character string
specifying a column to be used as row names, or a character or
integer vector giving the row names for the data frame.TRUE
then the rows are checked for
consistency of length and names.TRUE
then the names of the
variables in the data frame are checked to ensure that they are
syntactically valid variable names and are not duplicated.
If necessary they are adjusted (by make.names
)
so that they are.TRUE
, but
this can be changed by setting options(stringsAsFactors
= FALSE)
.I(...)
removed). For a named matrix/list/data frame
argument with more than one named column, the names of the columns are
the name of the argument followed by a dot and the column name inside
the argument: if the argument is unnamed, the argument's column names
are used. For a named or unnamed matrix/list/data frame argument that
contains a single column, the column name in the result is the column
name in the argument. Finally, the names are adjusted to be unique
and syntactically valid unless check.names = FALSE
.
"data.frame"
. If no variables
are included, the row names determine the number of rows. The column names should be non-empty, and attempts to use empty names
will have unsupported results. Duplicate column names are allowed,
but you need to use check.names = FALSE
for data.frame
to generate such a data frame. However, not all operations on data
frames will preserve duplicated column names: for example matrix-like
subsetting will force column names in the result to be unique.
data.frame
converts each of its arguments to a data frame by
calling as.data.frame(optional = TRUE)
. As that is a
generic function, methods can be written to change the behaviour of
arguments according to their classes: R comes with many such methods.
Character variables passed to data.frame
are converted to
factor columns unless protected by I
or argument
stringsAsFactors
is false. If a list or data
frame or matrix is passed to data.frame
it is as if each
component or column had been passed as a separate argument (except for
matrices of class "model.matrix"
and those protected by
I
).
Objects passed to data.frame
should have the same number of
rows, but atomic vectors (see is.vector
), factors and
character vectors protected by I
will be recycled a
whole number of times if necessary (including as elements of list
arguments).
If row names are not supplied in the call to data.frame
, the
row names are taken from the first component that has suitable names,
for example a named vector or a matrix with rownames or a data frame.
(If that component is subsequently recycled, the names are discarded
with a warning.) If row.names
was supplied as NULL
or no
suitable component was found the row names are the integer sequence
starting at one (and such row names are considered to be
automatic, and not preserved by as.matrix
).
If row names are supplied of length one and the data frame has a
single row, the row.names
is taken to specify the row names and
not a column (by name or number).
Names are removed from vector inputs not protected by I
.
default.stringsAsFactors
is a utility that takes
getOption("stringsAsFactors")
and ensures the result is
TRUE
or FALSE
(or throws an error if the value is not
NULL
).
I
,
plot.data.frame
,
print.data.frame
,
row.names
, names
(for the column names),
[.data.frame
for subsetting methods,
Math.data.frame
etc, about
Group methods for data.frame
s;
read.table
,
make.names
.
L3 <- LETTERS[1:3]
fac <- sample(L3, 10, replace = TRUE)
(d <- data.frame(x = 1, y = 1:10, fac = fac))
## The "same" with automatic column names:
data.frame(1, 1:10, sample(L3, 10, replace = TRUE))
is.data.frame(d)
## do not convert to factor, using I() :
(dd <- cbind(d, char = I(letters[1:10])))
rbind(class = sapply(dd, class), mode = sapply(dd, mode))
stopifnot(1:10 == row.names(d)) # {coercion}
(d0 <- d[, FALSE]) # data frame with 0 columns and 10 rows
(d.0 <- d[FALSE, ]) # <0 rows> data frame (3 named cols)
(d00 <- d0[FALSE, ]) # data frame with 0 columns and 0 rows
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