CONTRIBUTED ARTI CLE 1
stringr: modern, consistent string
processing
Hadley Wickham
Abstract String processing is not glamorous, but
it is frequently used in data cleaning and prepa-
ration. The existing string functions in R are
powerful, but not friendly. To remedy this, the
stringr package provides string functions that
are simpler and more consistent, and also fixes
some functionality that R is missing compared
to other programming languages.
Introduction
Strings are not glamorous, high-profile components
of R, but they do play a big role in many data clean-
ing and preparations tasks. R provides a solid set of
string operations, but because they have grown or-
ganically over time, they can be inconsistent and a
little hard to learn. Additionally, they lag behind the
string operations in other programming languages,
so that some things that are easy to do in languages
like Ruby or Python are rather hard to do in R.
The stringr package aims to remedy these problems
by providing a clean, modern interface to common
string operations.
More concretely, stringr:
• Processes factors and characters in the same
way.
• Gives functions consistent names and argu-
ments.
• Simplifies string operations by eliminating op-
tions that you don’t need 95% of the time (the
other 5% of the time you can use the base func-
tions).
• Produces outputs than can easily be used as in-
puts. This includes ensuring that missing in-
puts result in missing outputs, and zero length
inputs result in zero length outputs.
• Completes R’s string handling functions with
useful functions from other programming lan-
guages.
To meet these goals, stringr provides two basic
families of functions:
• basic string operations, and
• pattern matching functions which use regular
expressions to detect, locate, match, replace,
extract, and split strings.
These are described in more detail in the follow-
ing sections.
Basic string operations
There are three string functions that are closely re-
lated to their base R equivalents, but with a few en-
hancements:
•str_c is equivalent to paste, but it uses the
empty string (“”) as the default separator and
silently removes zero length arguments.
•str_length is equivalent to nchar, but it pre-
serves NA’s (rather than giving them length
2) and converts factors to characters (not inte-
gers).
•str_sub is equivalent to substr but it returns a
zero length vector if any of its inputs are zero
length, and otherwise expands each argument
to match the longest. It also accepts negative
positions, which are calculated from the left of
the last character. The end position defaults to
-1, which corresponds to the last character.
•str_str<- is equivalent to substr<-, but like
str_sub it understands negative indices, and
replacement strings not do need to be the same
length as the string they are replacing.
Three functions add new functionality:
•str_dup to duplicate the characters within a
string.
•str_trim to remove leading and trailing
whitespace.
•str_pad to pad a string with extra whitespace
on the left, right, or both sides.
Pattern matching
stringr provides pattern matching functions to de-
tect,locate,extract,match,replace, and split strings:
•str_detect detects the presence or absence of
a pattern and returns a logical vector. Based on
grepl.
•str_locate locates the first position of a
pattern and returns a numeric matrix with
columns start and end. str_locate_all locates
all matches, returning a list of numeric matri-
ces. Based on regexpr and gregexpr.
The R Journal Vol. X/Y, Month, Year ISSN 2073-4859
