Character strings manipulation.

Basics of character data

  • A character string is placed between single or double quotes (otherwise it is something else):
mean == "mean"
## Error in mean == "mean": comparison (1) is possible only for atomic and list types
class(mean)
## [1] "function"
class("mean")
## [1] "character"
"The 'R' project for statistical computing" != 'The "R" project for statistical computing'
## [1] TRUE
  • Empty string vs Empty character vector
a <- "" # empty string
b <- character(0) # empty character vector

  • Counting the number of characters in a string
month.name[1:4]
## [1] "January"  "February" "March"    "April"
length(month.name)
## [1] 12
nchar(month.name)
##  [1] 7 8 5 5 3 4 4 6 9 7 8 8

Character translation and case folding:

  • Character translation or substitution
chartr("u", "o", "union") # One characer is substituted
## [1] "onion"
chartr(old = "ao", new = "A0", "This is a boring string") # Several characters can be is substituted
## [1] "This is A b0ring string"
crazy = c("Here's to the crazy ones", "The misfits", "The rebels") # It is vectorized
chartr("aei", "#!?", crazy)
## [1] "H!r!'s to th! cr#zy on!s" "Th! m?sf?ts"             
## [3] "Th! r!b!ls"
chartr("a-c", "D-F", letters[1:8]) # One can use ranges of characters
## [1] "D" "E" "F" "d" "e" "f" "g" "h"

This is nice but regular expressions are far more powerfull…

  • Case folding
casefold("aLL ChaRacterS in LoweR caSe")
## [1] "all characters in lower case"
casefold("All ChaRacterS in Upper Case", upper = TRUE)
## [1] "ALL CHARACTERS IN UPPER CASE"

Note that tolower()and toupper() do as their name imply.

Combining character strings

For combining text and variable values and have some control on the way the values are formatted.

  • Vectorized concatenation of strings
paste("la", "maison", sep = " ") # basic concatenation, separator is a space
## [1] "la maison"
# Vectorized concatenation. Note that numeric vectors are converted to character.
paste("Section", 1:3, sep = "-")
## [1] "Section-1" "Section-2" "Section-3"
paste("Section", 1:3, LETTERS[1:4], sep = "-") # Rules of recycling apply
## [1] "Section-1-A" "Section-2-B" "Section-3-C" "Section-1-D"
paste("Section", 1:3, LETTERS[1:4], sep = "-", collapse = " & ") # Collapse everything to a single string
## [1] "Section-1-A & Section-2-B & Section-3-C & Section-1-D"
paste("Section", rep(1:3, each = 5), 1:5, sep = "-") # What is this doing!?
##  [1] "Section-1-1" "Section-1-2" "Section-1-3" "Section-1-4" "Section-1-5"
##  [6] "Section-2-1" "Section-2-2" "Section-2-3" "Section-2-4" "Section-2-5"
## [11] "Section-3-1" "Section-3-2" "Section-3-3" "Section-3-4" "Section-3-5"

  • To have more control on how, mostly numerical values are formated there are a number of function available. sprintf() is extremely convenient but a bit complex too.
sprintf(fmt = "The number pi = %f", pi)
## [1] "The number pi = 3.141593"

The argument fmt is a character vector mixing plain text with format strings. The % symbol terminated by a letter acts as a positional and convertion flag for insertion of the formated value of the other argument(s).

sprintf("The number pi = %E", pi) # scientific notation
## [1] "The number pi = 3.141593E+00"
sprintf("The number pi = %.2f %s", pi, c(". Yes ?", "or not?")) # specify precision. concatenate with text
## [1] "The number pi = 3.14 . Yes ?" "The number pi = 3.14 or not?"
sprintf("This is %-8s justification of text", "LEFT") # Also fixing field width to 8 characters.
## [1] "This is LEFT     justification of text"
sprintf("This is %8s justification of text", "RIGHT")
## [1] "This is    RIGHT justification of text"

Displaying character strings

  • Displaying strings in the screen, notably to generate information messages (progress of computation, weird things happening, …) in function body.
diceResult <- 4
cat("The dice result is: ", diceResult, "!\nTry again.", sep = "")
## The dice result is: 4!
## Try again.
cat("Long strings can", "be displayed over", "several lines using",
    "the fill= argument.", fill = 40)
## Long strings can be displayed over 
## several lines using the fill= argument.

By default cat() prints to the stout (screen) cat() returns no value (invisible NULL)

  • Displaying information in connection with exception handling.

Use message(), warning(), stop() as appropriate. These functions are part of the R condition system (?conditions), a mechanism for signaling and handling anomalous or exceptional events occuring during the execution of your code.

howRU <- function(x) {
  message("Will first check the type of the argument.")
  if (!is.logical(x)) {stop("Argument must be either 'TRUE' or 'FALSE'.\n")} # asserting argument type
  if (x) cat("I am fine, thank you!\n") else warning("I don't feel so good.\n") # issue a warning if feel sick
  cat("Good bye")
}
howRU("bof") # Trows an error: execution alted
## Will first check the type of the argument.
## Error in howRU("bof"): Argument must be either 'TRUE' or 'FALSE'.
howRU(TRUE) # prints something to stdout
## Will first check the type of the argument.
## I am fine, thank you!
## Good bye
howRU(FALSE) # warns you that something is unusual
## Will first check the type of the argument.
## Warning in howRU(FALSE): I don't feel so good.
## Good bye

Text Extraction with substring()

# extract based on a range of positions
substring(text = "abcdef", first = 2, last = 4)
## [1] "bcd"

# vectorized extraction
substring("abcdef", first = 1:4, last = 4:5) # the 'x' and 'last' vectors are recycled
## [1] "abcd" "bcde" "cd"   "de"

# replacing portions of strings with the assignment operator
x = c("may", "the", "force", "be", "with", "you")
substring(x, 2, 2) <- "#"
x
## [1] "m#y"   "t#e"   "f#rce" "b#"    "w#th"  "y#u"

# everything is a vector...
s <- c("more", "emotions", "are", "better", "than", "less")
substring(s, 1:3, 2:4) <- c(" ", "zzz")
s
## [1] " ore"     "ezztions" "ar "      "zztter"   "t an"     "lezz"

Can you insert a string longer than the range provided in the first and last arguments?

A touch of regular expressions

  • Regular expressions is a powerfull and flexible tool for finding and replacing text using patterns/motifs.
# What strings are email adresses?
s <- c("object@attribute", "Rstudio", maintainer("base"))
# The litteral approach
grep(pattern = "@", x = s, value = TRUE)
## [1] "object@attribute"                  
## [2] "R Core Team <R-core@r-project.org>"
# Accurate with a more specifc pattern
myPat <- "([a-z0-9_\\.-]+)@([\\da-z\\.-]+)\\.([a-z\\.]{2,6})"
grep(pattern = myPat, x = s, value = TRUE)
## [1] "R Core Team <R-core@r-project.org>"

A touch of regular expressions

  • Base R has a variety of functions that use regular expressions for different but related purposes:

  • Note that for most of these functions you can specify, via its arguments, whether to interpret the provided pattern literally or to use one the two available regexp engines : Perl or POSIX 1003.2 (unix). There are differences in the fonctionalities depending on the engine used. So be aware of what you use.

A touch of regular expressions

  • Finding vector elements that have the pattern:
s <- c("tobacco pipe (hazardous!)", "pile of junk", "directory of files")
grepl("pi", s)
## [1]  TRUE  TRUE FALSE
  • Double escaping of metacharacters (special characters) and search for their literal meaning.
grep("(", s, value = TRUE) # parentheses create capturing groups
## Error in grep("(", s, value = TRUE): invalid regular expression '(', reason 'Missing ')''
grep("\\(", s, value = TRUE) # escape special meanning with DOUBLE backslash
## [1] "tobacco pipe (hazardous!)"

  • Extracting only the matched substrings from match data obtained by regexpr(), gregexpr() or regexec().
m <- regexpr(pattern = "pi[pl]e", text = s) # brakets define a character set
m
## [1]  9  1 -1
## attr(,"match.length")
## [1]  4  4 -1
## attr(,"useBytes")
## [1] TRUE
regmatches(x = s, m = m, invert = FALSE)
## [1] "pipe" "pile"

Note that similar to sub functions below, regmatches() can do substitution tasks via the assignemnt operator.

  • Replacing the matched pattern with a new value
sub(pattern = "pi[pl]e", replacement = "cigarette", x = s)
## [1] "tobacco cigarette (hazardous!)" "cigarette of junk"             
## [3] "directory of files"
gsub("\\d", "_", "1789, the revolution") # global substitution of digits
## [1] "____, the revolution"

  • Split strings based on a separator defined by a regexp
# Often used to get the words of a sentence
s <- c("Killian! I'll be back!",
"You cannot teach a man anything; you can only help him find it within himself – Galileo")
words <- strsplit(x = s, split = " ")
words # the returned object is a list of vectors
## [[1]]
## [1] "Killian!" "I'll"     "be"       "back!"   
## 
## [[2]]
##  [1] "You"       "cannot"    "teach"     "a"         "man"      
##  [6] "anything;" "you"       "can"       "only"      "help"     
## [11] "him"       "find"      "it"        "within"    "himself"  
## [16] "–"         "Galileo"

# It can be flattened
unlist(words)[1:10]
##  [1] "Killian!"  "I'll"      "be"        "back!"     "You"      
##  [6] "cannot"    "teach"     "a"         "man"       "anything;"

# It can be used in a `apply` construct
sapply(words, length) # number of words in the sentense
## [1]  4 17

strsplit() with sep = “” is used to break a string into a vector of single characters. Try it!

Exercice

You have 12 samples and want to create dummy labels like “S_1”. How would you do that with paste()? Assign your resulting character vector to the name “lab1”

Can you do it with sprintf() so that the numeric field is of width 2 with padding with zeros like “S_03”? Tip: look for “0” in the sprintf() help page. Assign your resulting character vector to the name “lab2”

Sort lab1 and lab2. What format is the most convenient?

Exercice

How would you find the position(s) at which the letter s occurs in saucisson sec? As usual with R, there are several ways to do that…

Bottom line: learn regular expressions… Also, when you want to accomplish a task, think twice about the approach, some are easier to implement, more elegant and more efficient than others.

Exercice

How would you capitalize the first letter of each word of a sentence? Create a function for that.

Exercice:

You are running a full factorial experiment on subjects treated with a drug. Here are the factors involved and their levels:

dose <- seq(60, 80, 10)
exposureTime <- c(100, 200)
sex <- c("Male","Female")

You want to create treatment labels corresponding to combinations of the levels of the factors. How would you do that? Tip: use expand.grid()

Exercice

Read the file englishWords.txt in R. It contains a compedium of the words in the English language.

What is the longest word? What is the median word length in English? How many words end with “tion”?

Generate 10E6 random five letter words. Tip use the function replicate(). Do you have any of them that turns out to be genuine English? What are they? How would you run that a decent number of times to get a chance to have a match?