
library(testthat)

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

source("user_code.R")
test_that("plot_histogram function exists and is callable", {
  expect_true(exists("plot_histogram"),
              info = "plot_histogram function should exist.")
  expect_true(is.function(plot_histogram),
              info = "plot_histogram should be a function.")
})

test_that("plot_histogram runs without error for valid arguments (5 bins, blue)", {
  sample_data <- c(2, 3, 5, 7, 8, 8, 10, 12, 12, 13, 15, 17, 18, 18, 20, 21, 22, 23, 25, 27)
  expect_error(plot_histogram(sample_data, 5, "blue"), NA,
               info = "plot_histogram should run without error for valid arguments (5 bins, blue).")
})

test_that("plot_histogram runs without error for valid arguments (10 bins, red)", {
  sample_data <- c(2, 3, 5, 7, 8, 8, 10, 12, 12, 13, 15, 17, 18, 18, 20, 21, 22, 23, 25, 27)
  expect_error(plot_histogram(sample_data, 10, "red"), NA,
               info = "plot_histogram should run without error for valid arguments (10 bins, red).")
})

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: Histograms

Ratkaisu