
library(testthat)

source("user_code.R")
test_that("converts character vector to factor and summarizes in order1", {
  vec1 <- c("Low", "Medium", "High", "Medium", "Low", "High", "Medium")
  order1 <- c("Low", "Medium", "High")
  result <- convert_and_summarize(vec1, order1)
  expect_true(is.numeric(result) || is.integer(result))
  expect_named(result, order1)
  expect_equal(as.vector(result), c(2, 3, 2))
})

test_that("converts character vector to factor and summarizes in order2", {
  vec2 <- c("Apple", "Banana", "Apple", "Cherry", "Banana", "Cherry", "Apple")
  order2 <- c("Cherry", "Banana", "Apple")
  result <- convert_and_summarize(vec2, order2)
  expect_true(is.numeric(result) || is.integer(result))
  expect_named(result, order2)
  expect_equal(as.vector(result), c(2, 2, 3))
})

test_that("handles levels in new_order not present in input vector", {
  vec3 <- c("Cat", "Dog", "Dog", "Cat")
  order3 <- c("Cat", "Dog", "Fish")
  result <- convert_and_summarize(vec3, order3)
  expect_named(result, order3)
  expect_equal(as.vector(result), c(2, 2, 0))
})

test_that("returns zero count for all levels if none present in input vector", {
  vec4 <- c()
  order4 <- c("A", "B", "C")
  result <- convert_and_summarize(vec4, order4)
  expect_named(result, order4)
  expect_equal(as.vector(result), c(0, 0, 0))
})

test_main.R

Master the essential R data structures used in exploratory data analysis (EDA), focusing on practical applications and hands-on challenges. This course is designed for learners already familiar with R syntax, core data structures, and data cleaning/wrangling techniques.

Explore the essential R data structures that power effective exploratory data analysis, with a focus on practical usage and hands-on challenges.

Challenge: Factors

Ratkaisu