Assignment 3: R Character Manipulation

Mario Pena

9/15/2019

In this assignment we will work with regular expressions used to manipulate characters in R:

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

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

library(stringr)
raw.data <- "555-1239Moe Szyslak(636) 555-0113Burns, C. Montgomery555 -6542Rev. Timothy Lovejoy555 8904Ned Flanders636-555-3226Simpson, Homer5553642Dr. Julius Hibbert"
name <- unlist(str_extract_all(raw.data, "[[:alpha:]., ]{2,}"))
name
## [1] "Moe Szyslak"          "Burns, C. Montgomery" "Rev. Timothy Lovejoy"
## [4] "Ned Flanders"         "Simpson, Homer"       "Dr. Julius Hibbert"

We will now change the order of two of these names so they conform to the standard first_name last_name:

first_change<-sub("(\\w+),\\s([[:upper:]].)\\s(\\w+)","\\2 \\3 \\1", name) # I have made the changes in two steps, hence the "first_change", which I will use in the code below.
first_last_name<-sub("(\\w+),\\s(\\w+)","\\2 \\1", first_change)
first_last_name
## [1] "Moe Szyslak"          "C. Montgomery Burns"  "Rev. Timothy Lovejoy"
## [4] "Ned Flanders"         "Homer Simpson"        "Dr. Julius Hibbert"

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

In this next step we’ll extract the titles from the names above:

title<-unlist(str_extract_all(first_last_name, "[[:alpha:]]{2,}[.]"))
title
## [1] "Rev." "Dr."

-Construct a logical vector indicating whether a character has a second name.

And now we will extract any second name from the character:

first_change_2<-unlist(str_extract_all(name, "([[:upper:]].)\\s(\\w+)")) # I have made the changes in two steps, hence the "first_change_2", which I will use in the code below.
second_name<-unlist(str_extract_all(first_change_2, "[[:alpha:]]{2,}"))
second_name
## [1] "Montgomery"
  1. Describe the types of strings that conform to the following regular expressions and construct an example that is matched by the regular expression.

-[0-9]+\$: Pattern that has any number followed by $ sign attached.

Example:

example <- ("This will get extracted '533$' below")
str_extract(example, "[0-9]+\\$")
## [1] "533$"

-\b[a-z]{1,4}\b: Pattern that excludes any word with a capital letter, and includes words of character length from 1 to 4 only.

Example:

example_2 <- ("This example will nOt show the number 10 but it will show ten")
unlist(str_extract_all(example_2, "\\b[a-z]{1,4}\\b"))
## [1] "will" "show" "the"  "but"  "it"   "will" "show" "ten"

-.*?\.txt$: This pattern includes any characters, numbers, spaces but it needs to end in .txt other wise it will not be matched.

Example:

example_3 <- ("This whole sentence with numbers '45' and special characters *# will not get extracted")
unlist(str_extract_all(example_3, ".*?\\.txt$"))
## character(0)
example_4 <- ("This whole sentence with numbers '45' and special characters *# will get extracted .txt")
unlist(str_extract_all(example_4, ".*?\\.txt$"))
## [1] "This whole sentence with numbers '45' and special characters *# will get extracted .txt"

-\d{2}/\d{2}/\d{4}: This pattern matches dates in the form dd/mm/yyyy.

Example:

example_5 <- "Let's extract the date 09/15/2019 and show it below:"
unlist(str_extract_all(example_5, "\\d{2}/\\d{2}/\\d{4}"))
## [1] "09/15/2019"

-<(.+?)>.+?</\\1>: This pattern matches any characters inside < > and then anything in between until we reach the same pattern again but this time ending with </ >.

Example:

example_6 <- "We will build <this sentence> and repeat </this sentence> again."
unlist(str_extract_all(example_6, "<(.+?)>.+?</\\1>")) #Notice only matched pattern is extracted below.
## [1] "<this sentence> and repeat </this sentence>"