
library(testthat)

source("user_code.R")
test_that("Function returns numeric vector with correct values", {
  ratings <- factor(c("Good", "Poor", "Excellent", "Fair", "Good", "Excellent"))
  result <- convert_and_reorder_ratings(ratings)
  expect_true(is.numeric(result), info = "Returned value should be numeric.")
  expect_equal(result, c(3,1,4,2,3,4),
    info = "Numeric values should correspond to ordered levels: Poor=1, Fair=2, Good=3, Excellent=4.")
})

test_that("Levels are set so that Poor=1, Fair=2, Good=3, Excellent=4", {
  ratings <- factor(c("Poor", "Fair", "Good", "Excellent"))
  result <- convert_and_reorder_ratings(ratings)
  expect_equal(result, 1:4,
    info = "Returned values should be 1, 2, 3, 4 for Poor, Fair, Good, Excellent.")
})

test_that("Handles input where levels are not initially in order", {
  ratings <- factor(c("Excellent", "Good", "Poor", "Fair"), levels = c("Excellent", "Good", "Poor", "Fair"))
  result <- convert_and_reorder_ratings(ratings)
  expect_equal(result, c(4,3,1,2),
    info = "Function should correctly reorder and assign numeric values regardless of initial levels.")
})

test_that("Handles repeated values and all possible rating levels", {
  ratings <- factor(c("Poor", "Poor", "Fair", "Good", "Good", "Excellent", "Fair", "Excellent"))
  result <- convert_and_reorder_ratings(ratings)
  expect_equal(result, c(1,1,2,3,3,4,2,4),
    info = "Function should correctly handle repeated values and all possible levels.")
})

test_main.R

Focus on practical skills for cleaning and transforming tabular data in R using data frames. Learn to create, modify, filter, and sort data for analysis, with hands-on challenges to reinforce each concept.

Challenge: Avoid Factor Pitfalls

Oplossing

Challenge: Avoid Factor Pitfalls

Oplossing