Since its inception, R has, at least by default, converted (character) strings to factors when creating data frames directly with data.frame() 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 I()), whereas read.table() kept having an argument (defaulting to FALSE).

In R 2.4.0 (released 2006), data.frame() and read.table() gained a stringsAsFactors argument, defaulting to default.stringsAsFactors(), which in turn would use the stringsAsFactors option if set, and otherwise give 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 data.frame() and read.table() defensively with explicitly specified 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 checking.)

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 Debian system, 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 variable _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 _R_OPTIONS_STRINGS_AS_FACTORS_=false.

Unfortunately, things are not as simple as changing the default value for the stringsAsFactors arguments to data.frame() and 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, data() was changed to use

  read.table(..., header = TRUE, = FALSE)

when reading in data files in .tab or .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).