data.frame {base} | R Documentation |
These functions create or manipulate data frames, tightly coupled collections of variables which share many of the properties of matrices and of lists, used as the fundamental data structure by most of R's modeling software.
data.frame(..., row.names = NULL, check.rows = FALSE,
check.names = TRUE)
as.data.frame(x, row.names = NULL, optional = FALSE)
is.data.frame(x)
row.names(x)
row.names(x) <- names
... |
these arguments are of either the form |
row.names |
a character vector giving the row names for the data frame. |
check.rows |
if |
check.names |
logical. If |
optional |
logical. If |
x |
object of class |
Character variables passed to data.frame
are converted to
factor columns unless protected by I
. It also applies to
adding columns to a data frame.
If a list or data frame or matrix is passed to data.frame
it is as if each column had been passed as a separate argument,
with the exception of matrices of class model.matrix
.
For data.frame(.)
a data frame, a matrix-like stucture whose
columns may be of differing types (numeric, factor and character).
as.data.frame
is generic function with many methods. It
attempts to coerce its argument to be a data frame.
is.data.frame
returns TRUE
if its argument is a data
frame and FALSE
otherwise.
row.names
can be used to set and retrieve the row names of a
data frame, similarly to rownames
for arrays (and
it is a generic function that calls rownames
for an
array argument.
In versions of R prior to 1.4.0 (and in S3) logical columns were converted to factors.
print.data.frame
,
read.table
,
Math.data.frame
etc, about
Group methods for data.frame
s;
make.names
.
L3 <- LETTERS[1:3]
str(d <- data.frame(cbind(x=1, y=1:10), fac=sample(L3, 10, repl=TRUE)))
## The same with automatic column names:
str( data.frame(cbind( 1, 1:10), sample(L3, 10, repl=TRUE)))
is.data.frame(d)
## do not convert to factor, using I() :
str(cbind(d, char = I(letters[1:10])), vec.len = 10)
stopifnot(1:10 == row.names(d))# {coercion}
(d0 <- d[, FALSE]) # NULL dataframe with 10 rows
(d.0 <- d[FALSE, ]) # <0 rows> dataframe (3 cols)
(d00 <- d0[FALSE,]) # NULL dataframe with 0 rows