Week 3 Assignment

Question 1

Code that identifies majors that contain either “DATA” or “STATISTICS” from [Five Thirty Eight] (https://fivethirtyeight.com/features/the-economic-guide-to-picking-a-college-major/).

library(rvest)
library(xml2)
library(tidyverse)

# Get URL of College Majors list
site <- "https://projects.fivethirtyeight.com/mid-levels/college-majors/index.html?v=3"
majors_list <- read_html(site)

# Scrape all data from the website
majors_df <- majors_list %>%
  html_nodes(xpath = '//*[@id="example"]') %>%
  html_table(fill = TRUE)

# Scrapped data is in the form of a list. 
# Convert list to data frame and save the majors column only to its own data frame
majors_df <- as.data.frame(majors_df)
mj <- majors_df$MAJOR

# look for majors with statistics in name
major.stats <- str_view(mj, regex("statistics", ignore_case = TRUE), match = TRUE)

# look for majors with data in the name
major.data <- str_view(mj, regex("data", ignore_case = TRUE), match = TRUE)

# Display all majors with Statistics in the name
major.stats

# Display all majors with Data in the name
major.data

Question 2

Data transformation

library(RCurl)
library(dplyr)

# get fruit list from Github
x <- getURL("https://raw.githubusercontent.com/ltcancel/Homework3_Data607_F20/master/fruit.txt")
fruit <- read.delim(text = x, header = FALSE, sep = '"')

fruit

##      V1          V2 V3          V4 V5           V6 V7           V8 V9
## 1  [1]  bell pepper NA    bilberry NA   blackberry NA blood orange NA
## 2  [5]    blueberry NA  cantaloupe NA chili pepper NA   cloudberry NA
## 3  [9]   elderberry NA        lime NA       lychee NA     mulberry NA
## 4 [13]        olive NA salal berry NA              NA              NA

# filter to only include columns with values
fruit.clean <- fruit %>%
  select(2,4,6,8)

fruit.clean

##            V2          V4           V6           V8
## 1 bell pepper    bilberry   blackberry blood orange
## 2   blueberry  cantaloupe chili pepper   cloudberry
## 3  elderberry        lime       lychee     mulberry
## 4       olive salal berry

# loop through data frame to create final string

for (x in 1:nrow(fruit.clean)){
  for (y in 1:ncol(fruit.clean)){
    if (x == 1 && y == 1){
      final.string <- c("c(",fruit.clean[x,y])
    }
    else if (x == nrow(fruit.clean) && y == ncol(fruit.clean)){
      final.string <- paste0(final.string,")")
    }
    else{
      final.string <- paste0(final.string,",",fruit.clean[x,y])
    }
  }
}

# Display new string
final.string

## [1] "c(,bilberry,blackberry,blood orange,blueberry,cantaloupe,chili pepper,cloudberry,elderberry,lime,lychee,mulberry,olive,salal berry,)"
## [2] "1,bilberry,blackberry,blood orange,blueberry,cantaloupe,chili pepper,cloudberry,elderberry,lime,lychee,mulberry,olive,salal berry,)"

Question 3

Describe, in words, what these expressions will match:

• (.)\1\1
  • This will find the same letter repeating 3 times in a row. Example: bbb
• “(.)(.)\2\1”
  • This will find 2 letters grouped, then find the same letters grouped in reverse. Example: chhc
• (..)\1
  • This will find 2 letters that repeat once. Example: Chch
• “(.).\1.\1”
  • This will find 1 letter that repeats 3 times but is not grouped together. Example: exexe
• "(.)(.)(.).*\3\2\1"
  • This will find 3 letters grouped, followed by any character, and then find the same 3 letter but grouped in reverse. Example: xyz1zyx

Question 4

Construct regular expressions to match words that:

Start and end with the same character.

str_view(c("dad","apple","eye"),"^(.).*\\1$")

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

str_view(c("church","house","pressure"),"(..).*\\1", match = TRUE)

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

str_view(c("eleven","six","between"),"(.).*\\1.*\\1")