Please deliver links to an R Markdown file (in GitHub and rpubs.com) with solutions to the problems below.
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”
Load required packages
library("stringr")Read the CSV file and grep for “DATA” or “STATISTICS”
#Read the file
col_majors_ds<-read.csv("https://raw.githubusercontent.com/fivethirtyeight/data/master/college-majors/majors-list.csv")
col_majors_ds[grep("DATA", col_majors_ds$Major,ignore.case ="True"),]## FOD1P Major Major_Category
## 52 2101 COMPUTER PROGRAMMING AND DATA PROCESSING Computers & Mathematicscol_majors_ds[grep("STATISTICS", col_majors_ds$Major,ignore.case ="True"),]## FOD1P Major Major_Category
## 44 6212 MANAGEMENT INFORMATION SYSTEMS AND STATISTICS Business
## 59 3702 STATISTICS AND DECISION SCIENCE Computers & Mathematics2 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”)
The two exercises below are taken from R for Data Science, 14.3.5.1 in the on-line version:
input_str <- '[1] "bell pepper" "bilberry" "blackberry" "blood orange"
[5] "blueberry" "cantaloupe" "chili pepper" "cloudberry"
[9] "elderberry" "lime" "lychee" "mulberry"
[13] "olive" "salal berry"'
extracted_str <- str_extract_all(input_str, pattern = "\"([:alpha:]+.[:alpha:]+)\"")
final_str <- str_replace_all(extracted_str[[1]], "\"", "")
final_str## [1] "bell pepper" "bilberry" "blackberry" "blood orange" "blueberry"
## [6] "cantaloupe" "chili pepper" "cloudberry" "elderberry" "lime"
## [11] "lychee" "mulberry" "olive" "salal berry"Describe, in words, what these expressions will match:
(.)\1\1
Ans -
Pattern for matching any single character, followed by two repetitions (3 repeating characters)
eg : aaa, 111
testData <- c("111")
str_extract_all(testData , regex("(.)\\1\\1"))## [[1]]
## [1] "111"“(.)(.)\2\1”
Ans I assume \ and \\ (escaped \) are the same ,even though they are not literally same. In R , \ has to be escaped (\\). But with regard to a regular expression context \\1 means character \ followed by group 1 and \1 mean the group 1.
Two consecutive characters are repeated but in reverse order eg: 1221 or abba
testData <- c("abba")
str_extract_all(testData , regex("(.)(.)\\2\\1"))## [[1]]
## [1] "abba"(..)\1
Ans Two consecutive characters are repeated eg : abab, 1212
testData <- c("abab")
str_extract_all(testData , regex("(..)\\1"))## [[1]]
## [1] "abab"“(.).\1.\1”
Ans In a string ,if there is a 5 consecutive character with 3 are repeating which are in 1,3,5 character positions.
eg :12141 ,abaca
testData <- c("12141")
str_extract_all(testData , regex("(.).\\1.\\1"))## [[1]]
## [1] "12141""(.)(.)(.).*\3\2\1"
*Ans
a set of characters with first 3 and last 3 characters are same ,but in reverse order with any number of characters in between them
eg : abc12345cba
{firstcharacter}{secondcharacter}{thirdcharacter}{any number of characters}{group3}{group2}{group1}
testData <- c("abc12345cba")
str_extract_all(testData , regex("(.)(.)(.).*\\3\\2\\1"))## [[1]]
## [1] "abc12345cba"Start and end with the same character.
Ans
"(.).*\1"
Contain a repeated pair of letters (e.g. “church” contains “ch” repeated twice.)
Ans
".([a-z][a-z]).\1.*" - without escape
".*([a-z][a-z]).*\1.*" –with escape
Contain one letter repeated in at least three places (e.g. “eleven” contains three “e”s.)
Ans
“.([a-z]).\1.\1.” - without escape
“.*([a-z]).*\1.*\1.*” –with escape