Learning Objectives

  • Understand basic functions in the stringr library for working with character data.
  • Understand how to deal with whitespace.
  • Understand how to split strings.
  • Understand how to match strings.

Suggested readings

A “string” is the generic word for character type variables. Base R has many built-in functions for working with strings, but they are often difficult to remember and unintuitive to use. Fortunately, the wonderful folks over at the tidyverse developed a lovely package called "stringr", which makes working with strings a lot nicer.

Before going any further, make sure you install the stringr package and load it before trying to use any of the functions in this lesson:


1 Making a string

You can create strings with either single quotes ('') or double quotes (""). There is no difference in behavior.

cat("This is a string")
## This is a string
cat('This is a string')
## This is a string

If you have a string that contains a ' symbol, use double quotes: Use them where it makes sense, e.g.:

cat("It's a boy!")
## It's a boy!

Likewise, if you have a string that contains a " symbol, use single quotes: Use them where it makes sense, e.g.:

cat('I said, "Hi!"')
## I said, "Hi!"

But what if you have a string that has both single and double quotes, like this: It's nice to say, "Hi!"

In this case, you have to “escape” the quotes by using the \ symbol:

cat("It's nice to say, \"Hi!\"") # Double quotes escaped
## It's nice to say, "Hi!"
cat('It\'s nice to say, "Hi!"') # Single quote escaped
## It's nice to say, "Hi!"

Escaping can be used for a lot of different string literals, such as starting a new line, adding a tab space, and even entering the \ symbol itself:

cat('New line:', 'This\nthat')
## New line: This
## that
cat('Tab space:', 'This\tthat')
## Tab space: This  that
cat('Backslash:', 'This\\that')
## Backslash: This\that

Beware that the printed representation of a string in the R console is not the same as string itself, because the printed representation shows the escapes. To see the raw contents of the string, use cat() or writeLines().

2 String constants

R has a small number of built-in string constants: LETTERS, letters, month.abb, and month.name. These are common values stored in variables with convenient names:

##  [1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S"
## [20] "T" "U" "V" "W" "X" "Y" "Z"
##  [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s"
## [20] "t" "u" "v" "w" "x" "y" "z"
##  [1] "Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec"
##  [1] "January"   "February"  "March"     "April"     "May"       "June"     
##  [7] "July"      "August"    "September" "October"   "November"  "December"

If you assign-over one of these constants, you can always retrieve the constant by putting the base:: prefix in front:

letters <- 7
## [1] 7
letters <- base::letters
##  [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s"
## [20] "t" "u" "v" "w" "x" "y" "z"

In addition to the Base R constants, the stringr library also comes with three constants: words, sentences, and fruit. These are much longer, so let’s use the head() function to just preview the first 6 elements in each:

## [1] "a"        "able"     "about"    "absolute" "accept"   "account"
## [1] "The birch canoe slid on the smooth planks." 
## [2] "Glue the sheet to the dark blue background."
## [3] "It's easy to tell the depth of a well."     
## [4] "These days a chicken leg is a rare dish."   
## [5] "Rice is often served in round bowls."       
## [6] "The juice of lemons makes fine punch."
## [1] "apple"       "apricot"     "avocado"     "banana"      "bell pepper"
## [6] "bilberry"

3 Basic "stringr" Operations

Most stringr functions start with str_, which makes it particularly easy to remember. The following table contains the main stringr functions we’ll cover:

Function Description
str_to_lower() converts string to lower case
str_to_upper() converts string to upper case
str_to_title() converts string to title case
str_length() number of characters
str_sub() extracts substrings
str_locate() returns indices of substrings
str_dup() duplicates characters
str_trim() removes leading and trailing whitespace
str_pad() pads a string
str_c() string concatenation
str_split() split a string into a vector
str_sort() sort a string alphabetically
str_order() get the order of a sorted string
str_detect() match a string in another string
str_replace() replace a string in another string

The common str_ prefix is particularly useful in RStudio, because typing str_ will trigger autocomplete, allowing you to see all stringr functions:

3.1 Case conversion

You can convert whole strings to lower-case, upper-case, and title-case using some conveniently-named functions:

x <- "Want to hear a joke about paper? Never mind, it's tearable."
## [1] "want to hear a joke about paper? never mind, it's tearable."
## [1] "Want To Hear A Joke About Paper? Never Mind, It's Tearable."

Sidenote: Notice that str_to_title() makes every first letter in each word upper case. This is slightly different from what you might expect, since most “titles” don’t make articles like “a” and “the” upper case. An alternative function that makes a more appropriate title case is the toTitleCase() function from the tools library:

## [1] "Want to Hear a Joke About Paper? Never Mind, It's Tearable."

3.2 Get the number of characters in a string

If you want to find how long a string is (i.e. how many characters it contains), the length() function won’t work:

length("hello world")
## [1] 1

That’s be length() returns how many elements are in a vector (in the above case, there’s just one element). Instead, you should use str_length():

str_length("hello world")
## [1] 11

Note that the space character has a length:

str_length(" ")
## [1] 1

Also note that the “empty” string ("") has no length:

## [1] 0

3.3 Access characters by their index

You can access individual character using str_sub(). It takes three arguments: a string (or character vector), a start position, and an end position. Either position can either be a positive integer, which counts from the left, or a negative integer which counts from the right. The positions are inclusive, and if longer than the string, will be silently truncated.

x <- "Apple"
str_sub(x, 1, 3)
## [1] "App"
# Negative numbers count backwards from the end
str_sub(x, -3, -1)
## [1] "ple"

Note that str_sub() won’t fail if the string is too short: it will just return as much as possible:

str_sub("Apple", 1, 10)
## [1] "Apple"

You can also use the assignment form of str_sub() to modify specific elements in strings:

x <- 'abcdef'
str_sub(x, 1, 3) <- 'ABC'
## [1] "ABCdef"

3.4 Get the indices of substrings

If you want to know the start and end indices of a particular substring, use str_locate(). This is a helpful function to use in combination with str_sub() so you don’t have to count the characters to find a substring.

For example, let’s say I want to extract the substring "Good" from the following string:

x <- 'thisIsGoodPractice'

I could first use str_locate() to get the start and end indices:

indices <- str_locate(x, 'Good')
##      start end
## [1,]     7  10

Now that I have the start and end locations, I can use them within str_sub():

str_sub(x, indices[1], indices[2])
## [1] "Good"

3.5 Repeat a string

To duplicate strings, use str_dup():

str_dup("hola", 3)
## [1] "holaholahola"

Note the difference with rep() (which returns a vector):

rep("hola", 3)
## [1] "hola" "hola" "hola"

3.6 Removing “whitespace”

str_trim() removes leading and trailing whitespace:

x <- "         aStringWithSpace        "
## [1] "         aStringWithSpace        "
## [1] "aStringWithSpace"

By default, str_trim() removes whitespace on both sides, but you can specify a single side:

str_trim(x, side = "left") # Only trim left side
## [1] "aStringWithSpace        "
str_trim(x, side = "right") # Only trim right side
## [1] "         aStringWithSpace"

3.7 Add whitespace (or other characters)

str_pad() pads a string to a fixed length by adding extra whitespace on the left, right, or both sides. Note that the width argument is the length of the final string (not the length of the added padding):

x <- "hello"
## [1] "hello"
str_pad(x, width = 10) # Inserts pad on left by default
## [1] "     hello"
str_pad(x, width = 10, side = "both") # Pad both sides
## [1] "  hello   "

You can pad with other characters by using the pad argument:

str_pad(x, 10, side="both", pad='-')
## [1] "--hello---"

Also, str_pad() will never make a string shorter:

str_pad(x, 4)
## [1] "hello"

3.8 Combine strings into one string

To combine two or more strings, use str_c():

str_c('x', 'y', 'z')
## [1] "xyz"

Use the sep argument to control how they’re separated:

str_c('x', 'y', 'z', sep = "-")
## [1] "x-y-z"

You can also concatenate a vector of strings by adding the collapse argument to the str_c() function:

##  [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s"
## [20] "t" "u" "v" "w" "x" "y" "z"
str_c(letters, collapse = '')
## [1] "abcdefghijklmnopqrstuvwxyz"
str_c(letters, collapse = '-')
## [1] "a-b-c-d-e-f-g-h-i-j-k-l-m-n-o-p-q-r-s-t-u-v-w-x-y-z"

Objects of length 0 are silently dropped. This is particularly useful in conjunction with if statements:

printGreeting <- function(name, timeOfDay, isBirthday) {
    greeting <- str_c(
        "Good ", timeOfDay, " ", name,
            if (isBirthday) {
                ", and HAPPY BIRTHDAY!"
            } else {
printGreeting('John', 'morning', isBirthday = FALSE)
## Good morning John.
printGreeting('John', 'morning', isBirthday = TRUE)
## Good morning John, and HAPPY BIRTHDAY!

3.9 Split a string into multiple strings

Use str_split() to split a string up into pieces along a particular delimiter.

string <- 'This string has spaces-and-dashes'
str_split(string, " ") # Split on the spaces
## [[1]]
## [1] "This"              "string"            "has"              
## [4] "spaces-and-dashes"
str_split(string, "-") # Split on the dashes
## [[1]]
## [1] "This string has spaces" "and"                    "dashes"

By default, str_split() returns a list (another R data structure) of vectors. Each item in the list is a vector of strings. In the above cases, we gave str_split() a single string, so there is only one item in the returned list. In these cases, the easiest way to access the resulting vector of split strings is to use the double bracket [[]] operator to access the first list item:

str_split(string, " ") # Returns a list of vectors
## [[1]]
## [1] "This"              "string"            "has"              
## [4] "spaces-and-dashes"
str_split(string, " ")[[1]] # Returns the first vector in the list
## [1] "This"              "string"            "has"              
## [4] "spaces-and-dashes"

If you give str_split() a vector of strings, it will return a list of length equal to the number of elements in the vector:

x <- c('babble', 'scrabblebabble')
str_split(x, 'bb') # Returns a list with two elements (each a vector)
## [[1]]
## [1] "ba" "le"
## [[2]]
## [1] "scra" "leba" "le"

A particularly useful string split is to split on the empty string (""), which breaks a string up into its individual characters:

str_split(string, "")[[1]]
##  [1] "T" "h" "i" "s" " " "s" "t" "r" "i" "n" "g" " " "h" "a" "s" " " "s" "p" "a"
## [20] "c" "e" "s" "-" "a" "n" "d" "-" "d" "a" "s" "h" "e" "s"

3.10 Word extraction with word()

The word() function that another way to split up a longer string. It is designed to extract words from a sentence. You use word() by by passing it a string together with a start position of the first word to extract and an end position of the last word to extract. By default, the separator sep used between words is a single space. Here’s some examples:

sentence <- c("Be the change you want to be")
# Extract first word
word(sentence, 1)
## [1] "Be"
# Extract second word
word(sentence, 2)
## [1] "the"
# Extract last word
word(sentence, -1)
## [1] "be"
# Extract all but the first word
word(sentence, 2, -1)
## [1] "the change you want to be"

3.11 Alphabetically sorting string vectors

You can sort a vector of strings alphabetically using str_sort() and str_order():

x <- c('Y', 'M', 'C', 'A')
## [1] "A" "C" "M" "Y"
str_sort(x, decreasing = TRUE)
## [1] "Y" "M" "C" "A"
## [1] 4 3 2 1
## [1] "A" "C" "M" "Y"

3.12 Detect if a pattern is in a string

To determine if a character vector matches a pattern, use str_detect(). It returns a logical vector the same length as the input:

tenFruit <- fruit[1:10]
##  [1] "apple"        "apricot"      "avocado"      "banana"       "bell pepper" 
##  [6] "bilberry"     "blackberry"   "blackcurrant" "blood orange" "blueberry"
str_detect(tenFruit, "berry")

Remember that when you use a logical vector in a numeric context, FALSE becomes 0 and TRUE becomes 1. That makes sum() and mean() useful if you want to answer questions about matches across a vector:

# How many fruit in tenFruit contain the string "berry"?
# How many words in the stringr "words" vector contain the letter "a"?
sum(str_detect(tenFruit, "berry"))
## [1] 3
# What proportion contain the string "berry"?
mean(str_detect(tenFruit, "berry"))
## [1] 0.3

If you want to count the number of times a particular string pattern appears, use str_count:

x <- c("apple", "banana", "pear")
str_count(x, "a")
## [1] 1 3 1

3.13 Anchors

By default, str_detect() will match any part of a string. But it’s often useful to anchor the matching condition so that it matches from the start or end of the string. You can use:

  • ^ to match the start of the string.
  • $ to match the end of the string.
# Which fruit start with "a"?
str_detect(tenFruit, "^a")
# Which fruit end with "y"?
str_detect(tenFruit, "e$")

To remember which is which, try this mnemonic:

If you start with power (^), you’ll end up with money ($).

To force a match to a complete string, anchor it with both ^ and $:

x <- c("apple pie", "apple", "apple cake")
str_detect(x, "apple")
str_detect(x, "^apple$")

In the second example above, 1 & 3 are FALSE because there’s a space after apple.

3.14 Replacing matched pattern with another string

str_replace() and str_replace_all() allow you to replace matches with new strings. The simplest use is to replace a pattern with a fixed string:

x <- c("apple", "pear", "banana")
str_replace(x, "a", "-")
## [1] "-pple"  "pe-r"   "b-nana"
str_replace_all(x, "a", "-")
## [1] "-pple"  "pe-r"   "b-n-n-"

4 stringr functions work on vectors

In many of the above examples, we used a single string, but most stringr functions are designed to work on vectors of strings. For example, consider a vector of two “fruit”:

x <- c("apples", "oranges")
## [1] "apples"  "oranges"

Get the first 3 letters in each string in x:

str_sub(x, 1, 3)
## [1] "app" "ora"

Duplicate each string in x twice:

str_dup(x, 2)
## [1] "applesapples"   "orangesoranges"

Convert all strings in x to upper case:

## [1] "APPLES"  "ORANGES"

Replace all "a" characters with a "-" character:

str_replace_all(x, "a", "-")
## [1] "-pples"  "or-nges"

5 Tips

5.1 Breaking a string into characters

Often times you’ll want to break a string into it’s individual character components. To do that, use str_split() with the empty string "" as the delimiter:

chars <- str_split("apples", "")[[1]]
## [1] "a" "p" "p" "l" "e" "s"

5.2 Breaking a sentence into words

Similarly, if you have a single string that contains words separated by spaces, splitting on " " will break it into words:

x <- "If you want to view paradise, simply look around and view it"
str_split(x, " ")[[1]]
##  [1] "If"        "you"       "want"      "to"        "view"      "paradise,"
##  [7] "simply"    "look"      "around"    "and"       "view"      "it"

5.3 Comparing strings

If you want to compare whether two strings are the same, you must also consider their cases. For example:

a <- "Apples"
b <- "apples"
a == b
## [1] FALSE

The above returns FALSE because the cases are different on the "a" characters. If you want to ignore case, then a common strategy is to first convert the strings to a common case before comparing. For example:

str_to_lower(a) == str_to_lower(b)
## [1] TRUE

Page sources:

Some content on this page has been modified from other courses, including:

EMSE 6574, Sec. 11: Programming for Analytics (Fall 2019)
George Washington University | School of Engineering & Applied Science
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