Question 1

Using the 173 majors listed in fivethirtyeight.com’s College Majors dataset [https://fivethirtyeight.com/features/the-economic-guide-to-picking-a-college-major/], provide code that identifies the majors that contain either “DATA” or “STATISTICS”.

knitr::opts_chunk$set(echo = TRUE)

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library('RCurl')
## 
## Attaching package: 'RCurl'
## 
## The following object is masked from 'package:tidyr':
## 
##     complete
library(stringr)

data <- getURL(
  'https://raw.githubusercontent.com/fivethirtyeight/data/master/college-majors/recent-grads.csv')
majors <- pull(read.csv(text = data), Major)
stat_majors <- str_subset(majors, "\\bSTATISTICS\\b")
data_majors <- str_subset(majors, "\\bDATA\\b")
combined_results <- c(stat_majors, data_majors)
combined_results
## [1] "MANAGEMENT INFORMATION SYSTEMS AND STATISTICS"
## [2] "STATISTICS AND DECISION SCIENCE"              
## [3] "COMPUTER PROGRAMMING AND DATA PROCESSING"

Question 2

Transform the output data into a vector in alphabetical order.

library(knitr)
pasted_text <- '[1] "bell pepper"  "bilberry"     "blackberry"   "blood orange"

[5] "blueberry"    "cantaloupe"   "chili pepper" "cloudberry"  

[9] "elderberry"   "lime"         "lychee"       "mulberry"    

[13] "olive"        "salal berry"'


extracted <- str_match_all(pasted_text, '(\\")([a-zA-Z]+\\s*[a-zA-Z]*)(\\")')

matches = extracted[[1]]
vector_match = c(matches[1:14, 3])
vector_match

[1] “bell pepper” “bilberry” “blackberry” “blood orange” “blueberry”
[6] “cantaloupe” “chili pepper” “cloudberry” “elderberry” “lime”
[11] “lychee” “mulberry” “olive” “salal berry”

Question 3

(.)\1\1

This pattern will not match anything since the pattern is not enclosed in parentheses. Even if parentheses were present, each \1 needs another backslash in front of it.

“(.)(.)\2\1”

This pattern will match any pattern in which the 1st character matches the last, and the 2nd character matches the 3rd.

(..)\1

This pattern will not match anything since it is missing parentheses and the \1 requires an additional backslash.

“(.).\1.\1”

This pattern will match any pattern of five characters in which the 3rd and last character is the same as the first.

“(.)(.)(.).*\3\2\1”

This pattern will match any pattern of at least six characters lenght in which the 1st character == the last, 2nd character == 2nd to last character, and the 3rd character == the 3rd to last character.

Question 4

Construct regular expressions to match words that:

Start and end with the same character.

“b(.).*\1”

Contain a repeated pair of letters (e.g. “church” contains “ch” repeated twice.)

“.([a-zA-Z]{1}[a-zA-Z]{1}]).\1.*”

Contain one letter repeated in at least three places (e.g. “eleven” contains three “e”s.)

“.(.){1,3}.\1{1,2}.\1{1,2}.”