Week 3 Assignment

DATA-607, Spring 2019

3. Copy the introductory example. The vector name stores the extracted names.

library(stringr)
raw.data <- "555-1239Moe Szyslak(636) 555-0113Burns, C. Montgomery555-6542Rev. Timothy Lovejoy555 8904Ned Flanders636-555-3226Simpson, Homer5553642Dr. Julius Hibbert"

1. Use the tools of this chapter to rearrange the vector so that all elements conform to the standard first_name last_name.

name <- unlist(str_extract_all(raw.data, "[[:alpha:]., ]{2,}"))

custxtfun <- function(string) {
  if (str_detect(string,",") == TRUE) {
    string_split = strsplit(as.character(string), split = ", | ")
    reversed_split = rev(string_split[[1]])
    reversed_string = paste(reversed_split, collapse = " ")
  }else {reversed_string = string }
  if (str_detect(word(reversed_string,1),"Rev.|Dr.") == TRUE) {
    finalstring = paste(word(reversed_string,2),word(reversed_string,-1)) 
    } 
  else {finalstring = paste(word(reversed_string,1),word(reversed_string,-1))
  }
  return(finalstring)
}

namelist <- sapply(name, custxtfun, USE.NAMES = FALSE)
print(namelist)

## [1] "Moe Szyslak"      "Montgomery Burns" "Timothy Lovejoy" 
## [4] "Ned Flanders"     "Homer Simpson"    "Julius Hibbert"

2. Construct a logical vector indicating whether a character has a title(i.e., Rev. and Dr.).

has_title <- str_detect(name,"Rev.|Dr.")

data.frame(name,has_title)

3. Construct a logical vector indicating whether acharacter has a second name.

has_sname <- str_detect(name,"([A-Z])\\. ")

data.frame(name,has_sname)

4. Describe the types of strings that conform to the following regular expressions and construct an example that is matched by the regular expression.

1. [0-9]+\$

#The expression will extract any sequence of 1 to n digits followed by a dollar sign. This could be used to extract dollar amounts.

str_extract(
  c(               #Sample strings
    "10$",
    "1234567$",
    "1 asdf 123$",
    "$",
    "$123"),
  "[0-9]+\\$"      #Regex
  )

## [1] "10$"      "1234567$" "123$"     NA         NA

2. \b[a-z]{1,4}\b

#The expression will return the first sequence of 1 to 4 lower-case letters. 

str_extract(
  c(             #Sample strings
    "a",
    "abcd",
    "as d",
    "abcdef",
    "ab3d"
    ),
  "\\b[a-z]{1,4}\\b"   #Regex
  )

## [1] "a"    "abcd" "as"   NA     NA

3. .*?\.txt$

#The expression will extract strings which are terminated by .txt
str_extract(
  c(             #Sample strings
    "file1.exe",
    "file",
    "letter3.txt"
    ),
  ".*?\\.txt$"   #Regex
  )

## [1] NA            NA            "letter3.txt"

4. \d{2}/\d{2}/\d{4}

# The expression could be used to extract dates of forma DD/MM/YYYY or MM/DD/YYYY.

str_extract(
  c(                #Sample strings
    "1/1/1",
    "01/30/2000",
    "30/01/2000"
    ),
  "\\d{2}/\\d{2}/\\d{4}"   #Regex
  )

## [1] NA           "01/30/2000" "30/01/2000"

5. <(.+?)>.+?</\1>

# The expression will extract XML tags.

str_extract_all("Content outside the tag <xmltag1>content</xmltag1> and other<xmltag2>content</xmltag2> elements 123","<(.+?)>.+?</\\1>")

## [[1]]
## [1] "<xmltag1>content</xmltag1>" "<xmltag2>content</xmltag2>"

9.The following code hides a secret message. Crack it with R and regular expressions. Hint: Some of the characters are more revealing than others! The code snippet is also available in the materials at www.r-datacollection.com.

secret <- "clcopCow1zmstc0d87wnkig7OvdicpNuggvhryn92Gjuwczi8hqrfpRxs5Aj5dwpn0TanwoUwisdij7Lj8kpf03AT5Idr3coc0bt7yczjatOaootj55t3Nj3ne6c4Sfek.r1w1YwwojigOd6vrfUrbz2.2bkAnbhzgv4R9i05zEcrop.wAgnb.SqoU65fPa1otfb7wEm24k6t3sR9zqe5fy89n6Nd5t9kc4fE905gmc4Rgxo5nhDk!gr"