Regular Expressions/Cleaning Text Data

James Normington

Announcements

Regular Expressions

Regular expressions allow us to describe character patterns.

After class, try: Interactive Regex Tutorial

Text Examples

(example <- "The quick brown fox jumps over the lazy dog.")

[1] "The quick brown fox jumps over the lazy dog."

We’ll practice:

• Replacing text patterns
• Detecting text patterns
• Locating text patterns
• Changing case
• Separate/split text

Search and replace patterns

To search for a pattern and replace it, we can use the functions str_replace and str_replace_all.

example

[1] "The quick brown fox jumps over the lazy dog."

str_replace(example, pattern = "quick", replacement = "really quick")

[1] "The really quick brown fox jumps over the lazy dog."

str_replace_all(example, pattern = "(fox|dog)",  replacement = "****") 

[1] "The quick brown **** jumps over the lazy ****."

str_replace_all(example, "(fox|dog).", "****") # "." for any character

[1] "The quick brown ****jumps over the lazy ****"

str_replace_all(example, "(fox|dog)\\.$", "****") # at end of sentence only, "\\." only for a period

[1] "The quick brown fox jumps over the lazy ****"

str_replace(example, "[Tt]he", "a") # only first match

[1] "a quick brown fox jumps over the lazy dog."

str_replace_all(example, "[Tt]he", "a") # all matches

[1] "a quick brown fox jumps over a lazy dog."

Detect patterns

example2 <- "Two roads diverged in a yellow wood, / And sorry I could not travel both / And be one traveler, long I stood / And looked down one as far as I could"
example3 <- "This is a test"
(examples <- c(example, example2, example3))

[1] "The quick brown fox jumps over the lazy dog."                                                                                                        
[2] "Two roads diverged in a yellow wood, / And sorry I could not travel both / And be one traveler, long I stood / And looked down one as far as I could"
[3] "This is a test"                                                                                                                                      

pat <- "[^aeiouAEIOU ]{3}" # Regular expression for three straight consonants. Note that I've excluded spaces as well

str_detect(examples, pat) 

[1]  TRUE  TRUE FALSE

str_subset(examples, pat)

[1] "The quick brown fox jumps over the lazy dog."                                                                                                        
[2] "Two roads diverged in a yellow wood, / And sorry I could not travel both / And be one traveler, long I stood / And looked down one as far as I could"

Locate patterns

example

[1] "The quick brown fox jumps over the lazy dog."

str_locate(example, pat) # starting position and ending position of first match

     start end
[1,]    23  25

Let’s check the answer:

str_sub(example, 23, 25)

[1] "mps"

Extract patterns

example2

[1] "Two roads diverged in a yellow wood, / And sorry I could not travel both / And be one traveler, long I stood / And looked down one as far as I could"

pat2 <- "[^aeiouAEIOU ][aeiouAEIOU]{2}[^aeiouAEIOU ]{1}" # consonant followed by two vowels followed by a consonant

str_extract(example2, pat2) # extract first match

[1] "road"

str_extract_all(example2, pat2, simplify = TRUE) # extract all matches

     [,1]   [,2]   [,3]   [,4]   [,5]   [,6]  
[1,] "road" "wood" "coul" "tood" "look" "coul"

Count the number of characters

example2

[1] "Two roads diverged in a yellow wood, / And sorry I could not travel both / And be one traveler, long I stood / And looked down one as far as I could"

str_length(example2)

[1] 148

Change case

example2

[1] "Two roads diverged in a yellow wood, / And sorry I could not travel both / And be one traveler, long I stood / And looked down one as far as I could"

str_to_lower(example2)

[1] "two roads diverged in a yellow wood, / and sorry i could not travel both / and be one traveler, long i stood / and looked down one as far as i could"

Split strings

df <- tibble(ex = example2)
df <- df %>% separate(ex, c("line1", "line2", "line3", "line4"), sep = " / ")
df

# A tibble: 1 × 4
  line1                                line2                         line3 line4
  <chr>                                <chr>                         <chr> <chr>
1 Two roads diverged in a yellow wood, And sorry I could not travel… And … And …

Practice

Go to our course website and download the Rmd template file.

After Class

Regular Expressions

• Try Interactive Regex Tutorial
• Continue working on Regex (HW 9, due Wednesday)

Other Assignments

• Iterative Viz
• Continue thinking about Final Project