
library(testthat)

source("user_code.R")
test_that("combine_names returns correct full names", {
  test_first <- c("Anna", "Ben")
  test_last <- c("Lee", "Turner")
  result <- combine_names(test_first, test_last)
  expect_equal(result, c("Anna Lee", "Ben Turner"),
               info = "combine_names should concatenate first and last names with a space.")
})

test_that("extract_initials returns correct initials string", {
  test_names <- c("Anna", "Ben", "Charlie")
  result <- extract_initials(test_names)
  expect_equal(result, "ABC",
               info = "extract_initials should return the first letter of each name as a single string.")
})

test_that("combine_names handles vectors of length greater than zero", {
  test_first <- c("John")
  test_last <- c("Doe")
  result <- combine_names(test_first, test_last)
  expect_equal(result, c("John Doe"),
               info = "combine_names should work for single-element vectors.")
})

test_that("extract_initials handles single name", {
  test_names <- c("Zoe")
  result <- extract_initials(test_names)
  expect_equal(result, "Z",
               info = "extract_initials should return the first letter for a single-element vector.")
})

test_main.R

Master the essentials of handling text, dates, and files in R. This course guides you through string manipulation, regular expressions, date-time operations, and file I/O, with engaging explanations and practical challenges for beginners.

Learn to work with text data in R, from basic string operations to cleaning messy data using regular expressions.

Master handling dates and times in R, from parsing and formatting to performing calculations and managing time zones.

Explore the foundations of data cleaning and quality assurance in R. Each chapter introduces a core concept, followed by a hands-on challenge to reinforce your learning.

Challenge: Combine and Extract Text

Oplossing

Challenge: Combine and Extract Text

Oplossing