
library(testthat)

source("user_code.R")
library(testthat)

source("user_code.R")

test_that("score_scaled column is correct", {
  df <- data.frame(id = 1:3, score = c(60, 80, 100), group = c("A", "B", "C"))
  res <- transform_and_recode(df)
  expect_true("score_scaled" %in% colnames(res), info = "score_scaled column should exist")
  expect_equal(res$score_scaled, df$score / 100, info = "score_scaled values should be score divided by 100")
})

test_that("group_label recoding is correct", {
  df <- data.frame(id = 1:4, score = c(60, 70, 80, 90), group = c("A", "B", "C", NA))
  res <- transform_and_recode(df)
  expect_true("group_label" %in% colnames(res), info = "group_label column should exist")
  expect_equal(res$group_label[1], "Control", info = "group 'A' should be recoded as 'Control'")
  expect_equal(res$group_label[2], "Treatment", info = "group 'B' should be recoded as 'Treatment'")
  expect_equal(res$group_label[3], "Unknown", info = "group other than 'A' or 'B' should be 'Unknown'")
  expect_equal(res$group_label[4], "Unknown", info = "NA group should be 'Unknown'")
})

test_that("structure and row count matches input", {
  df <- data.frame(id = 1:5, score = c(60, 70, 80, 90, 100), group = c("A", "B", "C", "A", "B"))
  res <- transform_and_recode(df)
  expect_equal(nrow(res), nrow(df), info = "Row count should match input")
  expect_equal(res$id, df$id, info = "IDs should match input")
})

test_main.R

This practical course introduces learners to essential data cleaning and wrangling techniques in R. Through hands-on exercises, students will learn how to handle missing data, transform and recode variables, filter and select relevant data, and prepare datasets for analysis. The course emphasizes using popular R packages such as dplyr and tidyr to streamline and automate data preparation workflows, equipping learners with the foundational skills needed for effective data analysis.

Master the core techniques for cleaning and wrangling data in R using dplyr and tidyr. Each concept is introduced in a theory chapter, followed by a practical challenge.

Challenge: Transforming and Recoding Variables

Ratkaisu