
library(testthat)

source("user_code.R")
test_that("create_boxplot produces a boxplot for a numeric vector", {
    numeric_data <- c(5, 7, 8, 5, 10, 12, 9, 4, 6, 8, 7)
    # Should not error and should produce a boxplot
    expect_silent(create_boxplot(numeric_data))
})

test_that("create_grouped_boxplot produces grouped boxplots for numeric vector split by groups", {
    numeric_data <- c(5, 7, 8, 5, 10, 12, 9, 4, 6, 8, 7)
    group_labels <- c("A", "A", "B", "B", "A", "B", "A", "B", "A", "B", "A")
    # Should not error and should produce grouped boxplots
    expect_silent(create_grouped_boxplot(numeric_data, group_labels))
})

test_that("both functions handle input vectors of equal length without error", {
    values <- c(1, 2, 3, 4, 5)
    groups <- c("X", "Y", "X", "Y", "X")
    expect_silent(create_boxplot(values))
    expect_silent(create_grouped_boxplot(values, groups))
})

test_main.R

Master the foundational techniques of data visualization in R. This course guides you through the most important plotting tools and concepts, helping you create clear, insightful, and publication-ready graphics using base R and popular visualization approaches.

Explore the essential plotting tools and visualization strategies in R, focusing on practical skills for creating and customizing a wide range of charts and graphs.

Challenge: Boxplots

Ratkaisu