data(..., list = character(), package = NULL, lib.loc = NULL, verbose = getOption("verbose"), envir = .GlobalEnv)
NULL
.By default, all packages in the search path are used, then the data subdirectory (if present) of the current working directory.
NULL
. The default value of NULL
corresponds to all
libraries currently known.TRUE
, additional diagnostics are
printed."packageIQR"
if
none were specified.
data()
was originally intended to allow users to load datasets
from packages for use in their examples, and as such it loaded the
datasets into the workspace .GlobalEnv
. This avoided
having large datasets in memory when not in use. That need has been
almost entirely superseded by lazy-loading of datasets. The ability to specify a dataset by name (without quotes) is a
convenience: in programming the datasets should be specified by
character strings (with quotes). Use of data
within a function without an envir
argument
has the almost always undesirable side-effect of putting an object in
the user's workspace (and indeed, of replacing any object of that name
already there). It would almost always be better to put the object in
the current evaluation environment by data(..., envir =
environment())
. However, two alternatives are usually preferable,
both described in the Writing R Extensions manual.
mytable
as an object from the package,
it is system data and the second approach should be used. In the
unusual case that a package uses a lazy-loaded dataset as a default
argument to a function, that needs to be specified by ::
,
e.g., survival::survexp.us
.
source()
d in, with the R working directory changed
temporarily to the directory containing the respective file.
(data
ensures that the utils package is attached, in
case it had been run via utils::data
.)
load()
ed.
read.table(..., header = TRUE, as.is=FALSE)
,
and hence
result in a data frame.
read.table(..., header = TRUE, sep = ";", as.is=FALSE)
,
and also result in a data frame.
If more than one matching file name is found, the first on this list is used. (Files with extensions .txt, .tab or .csv can be compressed, with or without further extension .gz, .bz2 or .xz.)
The data sets to be loaded can be specified as a set of character
strings or names, or as the character vector list
, or as both.
For each given data set, the first two types (.R or .r, and .RData or .rda files) can create several variables in the load environment, which might all be named differently from the data set. The third and fourth types will always result in the creation of a single variable with the same name (without extension) as the data set.
If no data sets are specified, data
lists the available data
sets. It looks for a new-style data index in the Meta or, if
this is not found, an old-style 00Index file in the data
directory of each specified package, and uses these files to prepare a
listing. If there is a data area but no index, available data
files for loading are computed and included in the listing, and a
warning is given: such packages are incomplete. The information about
available data sets is returned in an object of class
"packageIQR"
. The structure of this class is experimental.
Where the datasets have a different name from the argument that should
be used to retrieve them the index will have an entry like
beaver1 (beavers)
which tells us that dataset beaver1
can be retrieved by the call data(beaver)
.
If lib.loc
and package
are both NULL
(the
default), the data sets are searched for in all the currently loaded
packages then in the data directory (if any) of the current
working directory.
If lib.loc = NULL
but package
is specified as a
character vector, the specified package(s) are searched for first
amongst loaded packages and then in the default library/ies
(see .libPaths
).
If lib.loc
is specified (and not NULL
), packages
are searched for in the specified library/ies, even if they are
already loaded from another library.
To just look in the data directory of the current working
directory, set package = character(0)
(and lib.loc =
NULL
, the default).
help
for obtaining documentation on data sets,
save
for creating the second (.rda) kind
of data, typically the most efficient one.The Writing R Extensions for considerations in preparing the data directory of a package.
require(utils)
data() # list all available data sets
try(data(package = "rpart") ) # list the data sets in the rpart package
data(USArrests, "VADeaths") # load the data sets 'USArrests' and 'VADeaths'
## Not run: ## Alternatively
# ds <- c("USArrests", "VADeaths"); data(list = ds)## End(Not run)
help(USArrests) # give information on data set 'USArrests'
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