
library(testthat)

source("user_code.R")
test_that("function produces correct number of bars", {
    categories <- c("A", "B", "C")
    counts <- c(2, 4, 6)
    colors <- c("red", "green", "blue")
    # Capture output invisibly
    res <- try(build_custom_bar_chart(categories, counts, colors, horizontal = FALSE), silent = TRUE)
    expect_false(inherits(res, "try-error"), info = "Function should run without error for vertical bars.")
})

test_that("function works for horizontal bars", {
    categories <- c("A", "B", "C")
    counts <- c(2, 4, 6)
    colors <- c("red", "green", "blue")
    res <- try(build_custom_bar_chart(categories, counts, colors, horizontal = TRUE), silent = TRUE)
    expect_false(inherits(res, "try-error"), info = "Function should run without error for horizontal bars.")
})

test_that("function works for different color vectors", {
    categories <- c("Dog", "Cat")
    counts <- c(7, 9)
    colors <- c("black", "gray")
    res <- try(build_custom_bar_chart(categories, counts, colors, horizontal = FALSE), silent = TRUE)
    expect_false(inherits(res, "try-error"), info = "Function should accept color vector and run without error.")
})

test_that("function works for length 1 color vector", {
    categories <- c("Dog", "Cat")
    counts <- c(7, 9)
    colors <- c("black")
    res <- try(build_custom_bar_chart(categories, counts, colors, horizontal = FALSE), silent = TRUE)
    expect_false(inherits(res, "try-error"), info = "Function should accept single color for all bars.")
})

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: Bar Charts

Ratkaisu