
library(testthat)

source("user_code.R")
test_that("data frame has correct columns", {
  expect_true(exists("updated_students"), info = "'updated_students' does not exist.")
  expect_true(is.data.frame(updated_students), info = "'updated_students' is not a data frame.")
  expected_cols <- c("name", "grade", "attendance")
  expect_equal(colnames(updated_students), expected_cols, info = "Column names are not correct.")
})

test_that("age column has been removed", {
  expect_false("age" %in% colnames(updated_students), info = "'age' column should not be present.")
})

test_that("attendance column has correct values", {
  expect_true("attendance" %in% colnames(updated_students), info = "'attendance' column missing.")
  expect_equal(updated_students$attendance, c(90, 95, 88, 98), info = "'attendance' values are incorrect.")
})

test_that("Diana row is added correctly", {
  expect_true("Diana" %in% updated_students$name, info = "Diana is not present in the data frame.")
  diana_row <- updated_students[updated_students$name == "Diana", ]
  expect_equal(diana_row$grade, 87, info = "Diana's grade is incorrect.")
  expect_equal(diana_row$attendance, 98, info = "Diana's attendance is incorrect.")
})

test_that("original students' data remains correct", {
  expect_equal(as.character(updated_students$name[1:3]), c("Alice", "Bob", "Charlie"), info = "Original names are incorrect.")
  expect_equal(updated_students$grade[1:3], c(85, 92, 78), info = "Original grades are incorrect.")
  expect_equal(updated_students$attendance[1:3], c(90, 95, 88), info = "Original attendance values are incorrect for first three students.")
})

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: Modify Data Frames

Oplossing

Challenge: Modify Data Frames

Oplossing