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"
names <- unlist(str_extract_all(raw.data, "[[:alpha:]., ]{2,}"))
names
## [1] "Moe Szyslak"          "Burns, C. Montgomery" "Rev. Timothy Lovejoy"
## [4] "Ned Flanders"         "Simpson, Homer"       "Dr. Julius Hibbert"

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

In order to get standart first name ,last name we need to remove middle names and titles

remove middle names : 

names_no_middle_name <- sub(" [A-z]{1}\\. ","",names)
names_no_middle_name
## [1] "Moe Szyslak"          "Burns,Montgomery"     "Rev. Timothy Lovejoy"
## [4] "Ned Flanders"         "Simpson, Homer"       "Dr. Julius Hibbert"

remove titles from the names :

names_final <- sub("[A-z]{2,3}\\. ","",names_no_middle_name)
names_final
## [1] "Moe Szyslak"      "Burns,Montgomery" "Timothy Lovejoy" 
## [4] "Ned Flanders"     "Simpson, Homer"   "Julius Hibbert"

DataFrame 

df.names <- data.frame(names_final)
df.names
##        names_final
## 1      Moe Szyslak
## 2 Burns,Montgomery
## 3  Timothy Lovejoy
## 4     Ned Flanders
## 5   Simpson, Homer
## 6   Julius Hibbert

3.2 Construct a logical vector indicating whether a character has a title

#Recall the original sample 'name2' from part a
titles <- str_detect(names_no_middle_name, "[[:alpha:]]{2,}\\.")
titles
## [1] FALSE FALSE  TRUE FALSE FALSE  TRUE
df.titles<- data.frame(names,titles)
df.titles
##                  names titles
## 1          Moe Szyslak  FALSE
## 2 Burns, C. Montgomery  FALSE
## 3 Rev. Timothy Lovejoy   TRUE
## 4         Ned Flanders  FALSE
## 5       Simpson, Homer  FALSE
## 6   Dr. Julius Hibbert   TRUE

3.3 Contruct a logical vector that indicates if a character has a second name

secondname <- str_detect(names, "[A-Z]\\.{1}")
df.secondname <- data.frame(names,secondname)
df.secondname
##                  names secondname
## 1          Moe Szyslak      FALSE
## 2 Burns, C. Montgomery       TRUE
## 3 Rev. Timothy Lovejoy      FALSE
## 4         Ned Flanders      FALSE
## 5       Simpson, Homer      FALSE
## 6   Dr. Julius Hibbert      FALSE

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

4.1 [0-9]+$

Any numbers 0-9 zero or more followed by the dollar $ string

sample <- c("5748900000$","omer35$", "38$","38")  
expression = "[0-9]+\\$"
str_detect(sample, expression)
## [1]  TRUE  TRUE  TRUE FALSE

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

Any word that has anywhere between 1 to 4 letters

sample_2 <- c("car","cats","door", "hi", "datascience")
expression_2 <-"\\b[a-z]{1,4}\\b"
str_detect(sample_2, expression_2)
## [1]  TRUE  TRUE  TRUE  TRUE FALSE

4.3 .*?\.txt$

Any string that ends with a .txt

sample_3 <- c("cars.txt", "txt", "timeseries.txt","code3434.txt")
expression_3 <-".*?\\.txt$"
str_detect(sample_3, expression_3)
## [1]  TRUE FALSE  TRUE  TRUE

4.4 \d{2}/\d{2}/\d{4}

Any Numbers that are written in format dd/dd/dddd

sample_4 <- c("100/1000/10000", "02/12/2019", "2/12/2019")
expression_4 <-"\\d{2}/\\d{2}/\\d{4}"
str_detect(sample_4, expression_4)
## [1] FALSE  TRUE FALSE

4.5 <(.+?)>.+?</\1>

Text that starts and ends <> with and also at the end string starts with “/”" 

sample_5 <- c("<omer>hello</omer>", "<omer>hello<omer>")
expression_5 <-"<(.+?)>.+?</\\1>"
str_detect(sample_5, expression_5)
## [1]  TRUE FALSE

9) Extra Credit-The following code hides a secret message. Crack it with R and regular expressions.

code <-"clcopCow1zmstc0d87wnkig7OvdicpNuggvhryn92Gjuwczi8hqrfpRxs5Aj5dwpn0TanwoUwisdij7Lj8kpf03AT5Idr3coc0bt7yczjatOaootj55t3Nj3ne6c4Sfek.r1w1YwwojigOd6vrfUrbz2.2bkAnbhzgv4R9i05zEcrop.wAgnb.SqoU65fPa1otfb7wEm24k6t3sR9zqe5fy89n6Nd5t9kc4fE905gmc4Rgxo5nhDk!gr"
code
## [1] "clcopCow1zmstc0d87wnkig7OvdicpNuggvhryn92Gjuwczi8hqrfpRxs5Aj5dwpn0TanwoUwisdij7Lj8kpf03AT5Idr3coc0bt7yczjatOaootj55t3Nj3ne6c4Sfek.r1w1YwwojigOd6vrfUrbz2.2bkAnbhzgv4R9i05zEcrop.wAgnb.SqoU65fPa1otfb7wEm24k6t3sR9zqe5fy89n6Nd5t9kc4fE905gmc4Rgxo5nhDk!gr"
#Find all uppercase letters
str_extract_all(code, "[[:upper:]]")
## [[1]]
##  [1] "C" "O" "N" "G" "R" "A" "T" "U" "L" "A" "T" "I" "O" "N" "S" "Y" "O"
## [18] "U" "A" "R" "E" "A" "S" "U" "P" "E" "R" "N" "E" "R" "D"