Loads specified data sets, or list the available data sets.
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literal character strings or names.
a character vector.
a character vector giving the package(s) to look
in for data sets, or
By default, all packages in the search path are used, then the ‘data’ subdirectory (if present) of the current working directory.
a character vector of directory names of R libraries,
a logical. If
the environment where the data should be loaded.
logical: should existing objects of the same name in envir be replaced?
Currently, four formats of data files are supported:
files ending ‘.R’ or ‘.r’ are
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
files ending ‘.RData’ or ‘.rda’ are
files ending ‘.tab’, ‘.txt’ or ‘.TXT’ are read
read.table(..., header = TRUE, as.is=FALSE),
result in a data frame.
files ending ‘.csv’ or ‘.CSV’ are read using
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
can be retrieved by the call
package are both
default), the data sets are searched for in all the currently loaded
packages then in the ‘data’ directory (if any) of the current
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
lib.loc is specified (and not
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
package = character(0)
lib.loc = NULL, the default).
A character vector of all data sets specified (whether found or not),
or information about all available data sets in an object of class
"packageIQR" if none were specified.
There is no requirement for
data(foo) to create an object
foo (nor to create one object), although it much
reduces confusion if this convention is followed (and it is enforced
if datasets are lazy-loaded).
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).
data within a function without an
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.
For sets of data, set up a package to use lazy-loading of data.
For objects which are system data, for example lookup tables used in calculations within the function, use a file ‘R/sysdata.rda’ in the package sources or create the objects by R code at package installation time.
A sometimes important distinction is that the second approach places
objects in the namespace but the first does not. So if it is important
that the function sees
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
This function creates objects in the
envir environment (by
default the user's workspace) replacing any which already
data("foo") can silently create objects other than
foo: there have been instances in published packages where it
.Random.seed and hence change the seed
for the session.
One can take advantage of the search order and the fact that a
‘.R’ file will change directory. If raw data are stored in
‘mydata.txt’ then one can set up ‘mydata.R’ to read
‘mydata.txt’ and pre-process it, e.g., using
For instance one can convert numeric vectors to factors with the
appropriate labels. Thus, the ‘.R’ file can effectively contain
a metadata specification for the plaintext formats.
In older versions of R, up to 3.6.x, both
package = "base" and
package = "stats" were using
package = "datasets", (with a
warning), as before 2004, (most of) the datasets in datasets were
either in base or stats. For these packages, the result
is now empty as they contain no data sets.
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.
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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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