Week 4 Assignement - Regular Expressions

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

a.

library(stringr)
## Warning: package 'stringr' was built under R version 3.2.2
string1 <- c("190050$",
           "54$",
           "1$.25 cents",
           "abcd$")

str_extract(string1, "[0-9]+\\$")
## [1] "190050$" "54$"     "1$"      NA

b.

string1 <- c("abcd",
           "do i know you",
           "where are you?",
           "DO I Know You",
           "3 keys",
           "3 ducks")
           
str_extract(string1, "\\b[a-z]{1,4}\\b")
## [1] "abcd" "do"   "are"  NA     "keys" NA

c.

string1 <- c("abcd.txt",
           "1234.txt",
           "where are you.txt",
           "3 keys.txt",
           "abcd_txt",
           "1234.txt ")
           
str_extract(string1, ".*?\\.txt$")
## [1] "abcd.txt"          "1234.txt"          "where are you.txt"
## [4] "3 keys.txt"        NA                  NA

d.

string1 <- c("09/20/2015",
           "The classes start from 08/29/2015",
           "0009/20/2015",
           "09_20_2015",
           "9/20/2015",
           "09/2/20150")
           
str_extract(string1, "\\d{2}/\\d{2}/\\d{4}")
## [1] "09/20/2015" "08/29/2015" "09/20/2015" NA           NA          
## [6] NA

d.

string1 <- c("<abc>abc</abc>",
           "<The Story> </The Story>",
           "<$version></#version>",
           "</tag>")
           
str_extract(string1, "<(.+?)>.+?</\\1>")
## [1] "<abc>abc</abc>"           "<The Story> </The Story>"
## [3] NA                         NA

5. Rewrite the expression [0-9]+\$ in a way that all the elements are altered but the expression performs the same task.

library(stringr)
string1 <- c("190050$",
           "54$",
           "1$.25 cents",
           "abcd$")

str_extract(string1, "[[:digit:]]{1,}\\x24")
## [1] "190050$" "54$"     "1$"      NA

6. Consider the mail address chunkylover53[at]aol[dot]com.

  1. Transform the string to a standard mail format using regular expressions.
  2. Imagine we are trying to extract the digits in the mail address. To do so we write the expression [:digit:]. Explain why this fails and correct the expression.
  3. Instead of using the predefined character classes, we would like to use the predefined symbols to extract the digits in the mail address. To do so we write the expression \D Explain why this fails and correct the expression.

a.

formatted_email <- str_replace("chunkylover53[at]aol[dot]com", "\\[at\\]", '@')
formatted_email <- str_replace(formatted_email, "\\[dot\\]", '.')


formatted_email
## [1] "chunkylover53@aol.com"

b.

formatted_email <- str_replace("chunkylover53[at]aol[dot]com", "\\[at\\]", '@')
formatted_email <- str_replace(formatted_email, "\\[dot\\]", '.')

str_extract(formatted_email, "[:digit:]") # would not extract both the digits
## [1] "5"
str_extract(formatted_email, "[[:digit:]]+") # would extract both the digits by using + 
## [1] "53"

c

str_extract("chunkylover53[at]aol[dot]com", "\\D+") # Gives the letters not digits
## [1] "chunkylover"
str_extract("chunkylover53[at]aol[dot]com", "\\d+") # Gives the digits, due to can sensitivity.
## [1] "53"