Since its inception, R has, at least by default, converted (character)
strings to factors when creating data frames directly with
or as the result of using
read.table() variants to read in tabular data.
Quite likely, this will soon change.
In R 0.62 (released 1998), the original internal data frame code was
replaced by the interpreted Statlib code contributed by John Chambers,
to the effect that
data.frame() would always convert strings to
factors (unless protected by
read.table() kept having
as.is argument (defaulting to
In R 2.4.0 (released 2006),
read.table() gained a
stringsAsFactors argument, defaulting to
which in turn would use the
stringsAsFactors option if set, and
TRUE by default. At that time, this seemed an acceptable
way forward, but in hindsight, it was not a very good idea: as code
shared with others could no longer make safe assumptions about the
stringsAsFactors default being used, it should (at least in theory)
always have used
read.table() defensively with
stringsAsFactors arguments. (In addition to this
need for “safe” usage being quite a nuisance, there also was no
straightforward mechanism to programmatically ensure it: one can set
options in user or site profiles, but these are not always read when
There are at least two more good reasons for changing the current mechanism.
Automatic string to factor conversion introduces non-reproducibility. When creating a factor from a character vector, if the levels are not given explicitly the sorted unique values are used for the levels, and of course the result of sorting is locale-dependent. Hence, the results of subsequent statistical analyses can differ with automatic string-to-factor conversion in place.
One might hypothesize that this was not an issue in the good old days
when everything was ASCII-only. However, this is not the case. On my
locale -a finds 872 locales (not all of which are
different, of course). Using these to sort the all-ASCII vector
c("0", "1", "A", "B", "a", "b")
finds the following frequencies of sorting patterns:
01aAbB 01AaBb 01ABab aAbB01 793 57 14 8
The second group contains e.g. Danish, Norwegian and Turkish; the third C/POSIX, Japanese and Korean; and the last Czech and Slovak.
This clearly shows that reproducible data analysis should really avoid all automatic string to factor conversions. (After careful deliberation, the R Core Team has come to the conclusion that making these conversions locale-independent by employing a specific locale for the sorting is not feasible in general.)
Finally, looking at modern alternatives to data frames shows that data.table uses stringsAsFactors = FALSE by default, and tibble never converts.
Hence, in the R Core meetings in Toulouse in 2019, it was decided to
move towards using
stringsAsFactors = FALSE by default, ideally
starting with the 4.0.0 release.
Eventually, the stringsAsFactors option will thus disappear. For the
time being, it was actually made possible to consistently set the option
(and hence the stringsAsFactors default) via an internal environment
_R_OPTIONS_STRINGS_AS_FACTORS_: the base and recommended
packages were already modified last year to work correctly irrespective
of the default setting, and some of the regular CRAN checks will soon
switch to using
Unfortunately, things are not as simple as changing the default value
stringsAsFactors arguments to
read.table() (which of course, even though in theory it should not
matter, will have considerable impact). When adding the
stringsAsFactors argument to
read.table() in R 2.4.0,
changed to use
read.table(..., header = TRUE, as.is = FALSE)
when reading in data files in
.csv formats. Thus, when
reading in such data files, strings are always converted to factors.
As this conversion was always performed, irrespective of the
stringsAsFactors settings, it will remain, but get modified to always
use the C sort order in the conversions, to the effect that loading such
data sets will become locale-independent.
In the interest of enhancing reproducibility, the R Core Team is also
considering adding a mechanism for optionally noting automatic string to
factor conversions (i.e., calling
factor() on a character vector without
giving the levels, or calling
as.factor() on a character vector).