# ab? matches an "a", optionally followed by "b".
str_view(c("a", "ab", "abb"), "ab?")

[1] │ <a>
[2] │ <ab>
[3] │ <ab>b

# ab+ matches an "a", followed by at >=1 "b".
str_view(c("a", "ab", "abb"), "ab+")

[2] │ <ab>
[3] │ <abb>

str_view(words, "[aeiou]x[aeoiu]")

[284] │ <exa>ct
[285] │ <exa>mple
[288] │ <exe>rcise
[289] │ <exi>st

str_view(words, "[^aeiou]y[^aeiou]")

[836] │ <sys>tem
[901] │ <typ>e

• Since returns logical vectors, can be used with filter(), e.g. most popular names containing an “x”:

babynames

# A tibble: 1,924,665 × 5
    year sex   name          n   prop
   <dbl> <chr> <chr>     <int>  <dbl>
 1  1880 F     Mary       7065 0.0724
 2  1880 F     Anna       2604 0.0267
...

babynames %>%
  count(name) %>%
  mutate(
    vowels = str_count(name, "[aeiou]"),
    consonants = str_count(name, "[^aeiou]")
  )

# A tibble: 97,310 × 4
   name          n vowels consonants
   <chr>     <int>  <int>      <int>
 1 Aaban        10      2          3
 2 Aabha         5      2          3
 3 Aabid         2      2          3
 4 Aabir         1      2          3
 5 Aabriella     5      4          5
 6 Aada          1      2          2
 7 Aadam        26      2          3
 8 Aadan        11      2          3
 9 Aadarsh      17      2          5
10 Aaden        18      2          3
# ℹ 97,300 more rows

str_remove(x, "[aeiou]")

[1] "pple"  "par"   "bnana"

x <- c("apple", "aardvark", "happy", "haaahaha")
( str_view(x, "a*") )

[1] │ <a><>p<>p<>l<>e<>
[2] │ <aa><>r<>d<>v<a><>r<>k<>
[3] │ <>h<a><>p<>p<>y<>
[4] │ <>h<aaa><>h<a><>h<a><>

( str_remove(x, "a*") )

[1] "pple"     "rdvark"   "happy"    "haaahaha"

str_remove_all(x, "a*")

[1] "pple"  "rdvrk" "hppy"  "hhh"  

x <- c("apple", "aardvark", "happy", "haaahaha")
(str_view(x, "a?"))

[1] │ <a><>p<>p<>l<>e<>
[2] │ <a><a><>r<>d<>v<a><>r<>k<>
[3] │ <>h<a><>p<>p<>y<>
[4] │ <>h<a><a><a><>h<a><>h<a><>

(str_view(x, "a+"))

[1] │ <a>pple
[2] │ <aa>rdv<a>rk
[3] │ h<a>ppy
[4] │ h<aaa>h<a>h<a>

An example with letters:

x <- c("happy", "ab", "zap", "war")
( str_view(x, "[a-u]") )

[1] │ <h><a><p><p>y
[2] │ <a><b>
[3] │ z<a><p>
[4] │ w<a><r>

str_replace_all(x, "[a-u]", "x")

[1] "xxxxy" "xx"    "zxx"   "wxx"  

• Very useful to use ranges in conjunction with ?, *, +
• E.g. let’s find all words with at least three consecutive vowels

str_view(words, "[aeiou][aeiou][aeiou]+")

 [79] │ b<eau>ty
[565] │ obv<iou>s
[644] │ prev<iou>s
[670] │ q<uie>t
[741] │ ser<iou>s
[915] │ var<iou>s

• Useful for parsing strings which are partitioned by letters/numbers

df <- tribble(
  ~str,
  "<Sheryl>-F_34",
  "<Kisha>-F_45", 
  "<Pat>-X_33",
  "<Sharon>-F_38", 
  "<Penny>-F_58",
  "<Justin>-M_41", 
  "<Patricia>-F_84", 
)

• To extract data, construct sequence of regex that match each piece.
• If you want contents of that piece to appear in output, give it a name.

• Since the characters “.”, “?”, “+”, “*” have extra functions in regex, need to use escapes to help parse literal instances of these characters
• In regex, we require a \ in front of characters to denote an escape
• But to create a string with an actual \ in it, we need to use an escape, so need double \\:

str_view(c("abc", "a.c", "bef"), "a\\.c")

[2] │ <a.c>

str_view(c("a*rdvark", "*pple", "m*n"), "\\*")

[1] │ a<*>rdvark
[2] │ <*>pple
[3] │ m<*>n

• By default: regex will match any part of a string.
• If you only want to match at beginning or end, you need to anchor:
  • ^ indicates “starts with”
  • $ indicates “ends with”

str_view(fruit, "^a")

[1] │ <a>pple
[2] │ <a>pricot
[3] │ <a>vocado

str_view(fruit, "a$")

 [4] │ banan<a>
[15] │ cherimoy<a>
[30] │ feijo<a>
[36] │ guav<a>
[56] │ papay<a>
[74] │ satsum<a>

• We already saw how we can construct sets with []: e.g. [abc] matches if any character is an “a”, “b”, or “c”

• We also saw how to use - to denote ranges, e.g. [a-z] lowercase letters, [0-9] numbers

• A few others:

  • \d matches any digit; \D matches anything that isn’t a digit.
  • \s matches any whitespace (e.g., space, tab, newline); \S matches anything that isn’t whitespace.
  • \w matches any “word” character, i.e. letters and numbers; \W matches any “non-word” character.

• Remember: to represent \ in a string, need double backslash.

• We already discussed ? (0 or 1 match), + (1+ matches), * (0+ matches)

  • colou?r: matches American and British English
  • \d+: matches 1+ digits
  • \s?: matches 0+ whitespaces

• Can specify exact number of matches using {}:

  • {n} matches exactly n times.
  • {n,} matches at least n times.
  • {n,m} matches between n and m times.

• Not immediately clear in which order R processes different operators.
  • ab+: is this “a” and then 1+ “b”, or is it “ab” repeated 1+ times? (1st case)
  • ^a|b$: match the string “a” or the string “b”, OR: string starting with “a” or string starting with “b” (2nd case)
• Generally: quantifiers (?+*) have high precedence, alternation | low.

• With paranthesis, you can back-reference matches that appeared in parens, using \1 for match in first parens, \2 for match in second, etc.
• e.g. all fruits which have repeated pair of letters.
  • Pair of letters = “(..)”; back-ref: “\1”

str_view(fruit, "(..)\\1")

 [4] │ b<anan>a
[20] │ <coco>nut
[22] │ <cucu>mber
[41] │ <juju>be
[56] │ <papa>ya
[73] │ s<alal> berry

• Can also use back references in str_replace(), e.g. switching second and third words in sentences:

sentences |> 
  str_replace(
    "(\\w+) (\\w+) (\\w+)", 
    "\\1 \\3 \\2") |> 
  str_view()

 [1] │ The canoe birch slid on the smooth planks.
 [2] │ Glue sheet the to the dark blue background.
 [3] │ It's to easy tell the depth of a well.
 [4] │ These a days chicken leg is a rare dish.
 [5] │ Rice often is served in round bowls.
 [6] │ The of juice lemons makes fine punch.
 [7] │ The was box thrown beside the parked truck.
...

• Words that start with “y”:

str_view(words, "^y")

[975] │ <y>ear
[976] │ <y>es
[977] │ <y>esterday
[978] │ <y>et
[979] │ <y>ou
...

• Words that don’t start with “y”:

str_view(words, "^[^y]")

 [1] │ <a>
 [2] │ <a>ble
 [3] │ <a>bout
 [4] │ <a>bsolute
 [5] │ <a>ccept
...

• We already saw how ^ inside [] negates the set, i.e. words with no vowels:

str_view(words, "^[^aeiou]+$")

[123] │ <by>
[249] │ <dry>
[328] │ <fly>
[538] │ <mrs>
[895] │ <try>
...

• Another way: return vector of booleans indicating presence of vowels, then negate:

str_view(words[!str_detect(words, "[aeiou]")])

[1] │ by
[2] │ dry
[3] │ fly
[4] │ mrs
[5] │ try
...

• What if we want all sentences which mention a color?
  • Combine alternation with word boundaries \b:

str_view(sentences, "\\b(red|green|blue)\\b")

  [2] │ Glue the sheet to the dark <blue> background.
 [26] │ Two <blue> fish swam in the tank.
 [92] │ A wisp of cloud hung in the <blue> air.
[148] │ The spot on the blotter was made by <green> ink.
[160] │ The sofa cushion is <red> and of light weight.
...

• But if we wanted to update this code to have more colors, would be pretty tedious to construct pattern by hand.
• We can build up larger regex’s using functions we have seen before.