Question: 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”
Answer: First, I’ll get the data from github, and create a data frame from the CSV of major names:
x <- getURL("https://raw.github.com/fivethirtyeight/data/master/college-majors/majors-list.csv",.opts=curlOptions(followlocation = TRUE))
majors <- read.csv(text = x, header=FALSE)Then I’ll create a vector of major names and identify those that match “DATA” or “STATISTICS”:
major_names <- majors$V2
majors %>%
filter(str_detect(major_names, "STATISTICS|DATA"))Write code that transforms the data below:
[1] “bell pepper” “bilberry” “blackberry” “blood orange”
[5] “blueberry” “cantaloupe” “chili pepper” “cloudberry”
[9] “elderberry” “lime” “lychee” “mulberry”
[13] “olive” “salal berry”
Into a format like this:
c(“bell pepper”, “bilberry”, “blackberry”, “blood orange”, “blueberry”, “cantaloupe”, “chili pepper”, “cloudberry”, “elderberry”, “lime”, “lychee”, “mulberry”, “olive”, “salal berry”)
fruit_vector <- '[1] "bell pepper" "bilberry" "blackberry" "blood orange"
[5] "blueberry" "cantaloupe" "chili pepper" "cloudberry"
[9] "elderberry" "lime" "lychee" "mulberry"
[13] "olive" "salal berry"'
fruit_vector <- str_extract_all(fruit_vector, pattern = "([a-z]+.[a-z]+)")
fruit_vector <- unlist(fruit_vector) #found on stack overflow, to turn from list back into a vector
# I wasn't sure if the goal was to have a string output, so took a crack at it here:
final_string <- paste('c("',paste(fruit_vector,collapse = '","'),'")',collapse = '')
final_string## [1] "c(\" bell pepper\",\"bilberry\",\"blackberry\",\"blood orange\",\"blueberry\",\"cantaloupe\",\"chili pepper\",\"cloudberry\",\"elderberry\",\"lime\",\"lychee\",\"mulberry\",\"olive\",\"salal berry \")"Leveraged these Regex resources: - https://rstudio.com/wp-content/uploads/2016/09/RegExCheatsheet.pdf - https://www.regular-expressions.info/backref.html
Question: Describe, in words, what these expressions will match: (.)\1\1 “(.)(.)\2\1” (..)\1 “(.).\1.\1” "(.)(.)(.).*\3\2\1"
Answer:
(.)\1\1 : This isn’t in quotes, so it’s not ready for subsetting in R. If this were in quotes and with a double \, it would match the first 3 matching characters in a string. Put into quotes as is, it’s looking for two backslash and 1s.
“(.)(.)\2\1” : This will match the first 2 characters that aren’t a newline (.) and then the second captured character (\2) and then the first (\1), e.g. in afternoon, ‘noon’
(..)\1 : This isn’t in quotes, so it’s not ready for subsetting in R. If this were in quotes and with a double \, it would match the first instance when two captured characters (..) immediately repeat each other. e.g. in banana - ‘anan’. Put into quotes as is, it looks for a backslash and 1.
“(.).\1.\1” : This will match two characters, the first captured character again, another character, and the first character again, .e.g abaca.
"(.)(.)(.).*\3\2\1" : This will match 3 characters, followed by 0 or more characters, followed by the first 3 characters in reverse, e.g. in paragraph, ‘paragrap’
Question: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.)
Answer: * Start and end with the same character: "^(.).*\1$"
str_subset(words, pattern = "^(.).*\\1$") ## [1] "america" "area" "dad" "dead" "depend"
## [6] "educate" "else" "encourage" "engine" "europe"
## [11] "evidence" "example" "excuse" "exercise" "expense"
## [16] "experience" "eye" "health" "high" "knock"
## [21] "level" "local" "nation" "non" "rather"
## [26] "refer" "remember" "serious" "stairs" "test"
## [31] "tonight" "transport" "treat" "trust" "window"
## [36] "yesterday"str_subset(words, pattern = "([a-z][a-z]).*\\1") ## [1] "appropriate" "church" "condition" "decide" "environment"
## [6] "london" "paragraph" "particular" "photograph" "prepare"
## [11] "pressure" "remember" "represent" "require" "sense"
## [16] "therefore" "understand" "whether"str_subset(words, pattern = "([a-z]).*\\1.*\\1")## [1] "appropriate" "available" "believe" "between" "business"
## [6] "degree" "difference" "discuss" "eleven" "environment"
## [11] "evidence" "exercise" "expense" "experience" "individual"
## [16] "paragraph" "receive" "remember" "represent" "telephone"
## [21] "therefore" "tomorrow"