R tip: use
stringsAsFactors = FALSE.
R often uses a concept of
factors to re-encode strings. This can be too early and too aggressive. Sometimes a string is just a string.
It is often claimed Sigmund Freud said “Sometimes a cigar is just a cigar.”
To avoid problems delay re-encoding of strings by using
stringsAsFactors = FALSE when creating
d <- data.frame(label = rep("tbd", 5)) d$label[] <- "north" #> Warning in `[[<-.factor`(`*tmp*`, 2, value = structure(c(1L, NA, 1L, 1L, : #> invalid factor level, NA generated print(d) #> label #> 1 tbd #> 2 <NA> #> 3 tbd #> 4 tbd #> 5 tbd
Notice our new value was not copied in!
The fix is easy: use
stringsAsFactors = FALSE.
d <- data.frame(label = rep("tbd", 5), stringsAsFactors = FALSE) d$label[] <- "north" print(d) #> label #> 1 tbd #> 2 north #> 3 tbd #> 4 tbd #> 5 tbd
As is often the case: base
R works okay in default mode and works very well if you judiciously change a few defaults. There is much less need to whole-hog replace
R functionality than some claim.
Note: the above pattern of pre-building a
data.frame and filling values by addressing row/column index sets is a very effective (and under appreciated) way to build up data (often easier and quicker than binding rows or columns).
Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.
Great article. Completely agree.
This comment is just as an aside that the new factor level is automatically added for you in data.table.
As you know, stringsAsFactors=FALSE is the default in data.table for 10 years. So to demonstrate this feature of a factor column, we first need to set it to TRUE :
The point is just that it added in the new factor level automatically for you, whereas in base R that’s an error. I agree most of the time plain character type is probably best, but I’m just adding minor information that if you do have a factor (sometimes a factor is better when modelling, and ordered factors are also sometimes useful) then := in data.table copes with new factor levels.
It’s one convenience/ease-of-use feature of data.table that is nothing to do with size or speed.
Thanks, Matt. My impression has been that
data.tableis definitely designed with actual production use very much in mind.
I appreciate your work on data science. It’s such a wonderful read on data science. Keep sharing stuffs like this. I am also educating people on similar technologies so if you are interested to know more you can watch this:- https://www.youtube.com/watch?v=1ek7IdGhbXI
And for anyone who has ever had to deal with the frustration of factors, a very cathartic way to implement this tip is
d <- data.frame(label = rep("tbd", 5),
stringsAsFactors = HELLNO)