Data 607 Assignment 03

library(tidyverse)
library(openintro)
library(lubridate)

##Loading data from website

raw_file = 
  'https://raw.githubusercontent.com/fivethirtyeight/data/master/college-majors/majors-list.csv'

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”

## Warning: Using one column matrices in `filter()` was deprecated in dplyr 1.1.0.
## ℹ Please use one dimensional logical vectors instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

## # A tibble: 3 × 2
##   Major                                         matched_name[,1]                
##   <chr>                                         <chr>                           
## 1 MANAGEMENT INFORMATION SYSTEMS AND STATISTICS MANAGEMENT INFORMATION SYSTEMS …
## 2 COMPUTER PROGRAMMING AND DATA PROCESSING      COMPUTER PROGRAMMING AND DATA P…
## 3 STATISTICS AND DECISION SCIENCE               STATISTICS AND DECISION SCIENCE

##Write code that transforms the data below: #create the vector of the DATA

fruits <- c("bell pepper","bilberry", "blackberry","blood orange","blueberry","
            cantaloupe", "chili pepper", "cloudberry",  "elderberry", "lime",
            "lychee" , "mulberry" , "olive", "salal berry")
fruits

##  [1] "bell pepper"              "bilberry"                
##  [3] "blackberry"               "blood orange"            
##  [5] "blueberry"                "\n            cantaloupe"
##  [7] "chili pepper"             "cloudberry"              
##  [9] "elderberry"               "lime"                    
## [11] "lychee"                   "mulberry"                
## [13] "olive"                    "salal berry"

fruits <- c("bell pepper","bilberry", "blackberry","blood orange","blueberry",
            "cantaloupe", "chili pepper", "cloudberry",  "elderberry", "lime", 
            "lychee" , "mulberry" , "olive", "salal berry")

cat(paste0("c(",paste0(sep = '"',fruits, collapse = ', ', sep='"'),paste(")")))

## c("bell pepper", "bilberry", "blackberry", "blood orange", "blueberry", "cantaloupe", "chili pepper", "cloudberry", "elderberry", "lime", "lychee", "mulberry", "olive", "salal berry")

#3 Describe, in words, what these expressions will match:

(.)\1\1 “(.)(.)\2\1” (..)\1 “(.).\1.\1” “(.)(.)(.).*\3\2\1”

##Answer:

(.)\1\1 - Any two characters that repeats in the reverse order. “(.)(.)\2\1” - Any two characters that repeats in the same order. “(.).\1.\1” - Any single character that repeats two more times, with each repetition after another single variable character. “(.)(.)(.).*\3\2\1” - Any three characters that repeat in the reverse order after any number of variable characters.

#4 Construct regular expressions to match words that: Start and end with the same character. Contain a repeated pair of letters (e.g. “church” contains “ch” repeated twice.) Contain one letter repeated in at least three places (e.g. “eleven” contains three “e”s.)

##A_regex_expr1_Start and end with the same character

df.names <-c("anna", "church", "bob", "harry","paul", "eleven", "bubble")
regex_expr1 ="^(.)((.*\\1$)|\\1?$)"
str_subset(df.names,regex_expr1)

## [1] "anna" "bob"

##B_regex_expr2_Contain a repeated pair of letters

regex_expr2 = "([A-Za-z][A-Za-z]).*\\1"
str_subset(df.names,regex_expr2)

## [1] "church"

##C_regex_expr3_Contain one letter repeated in at least three places

regex_expr3 = "([A-Za-z]).*\\1.*\\1"
str_subset(df.names,regex_expr3 )

## [1] "eleven" "bubble"