Summary  
This chapter covers loading a built-in dataset and exploring its contents using functions to preview rows, compute summary statistics, and inspect the data structure.

General domain of usage  
Exploratory data analysis

The `msleep` dataset is a built-in dataset in the `ggplot2` package in R, widely used for demonstrating data visualization and data analysis techniques. The dataset contains information about the sleep patterns, body weights, and dietary habits of various mammal species. Some key variables in this dataset include **`sleep_total`** (the total amount of sleep per day in hours), **`bodywt`** (body weight in kilograms), and **`vore`** (the dietary category, such as "herbi" for herbivore, "carni" for carnivore, etc.). Understanding these variables is essential for meaningful data exploration and visualization.

# Load the ggplot2 package to access the msleep dataset
library(ggplot2)

# Load the msleep dataset
data("msleep")

# Display the first few rows of the dataset
head(msleep)

When you run the code above, you will see the first six rows of the `msleep` dataset. Each row represents a different mammal species. Important columns include **`name`** (the common name of the animal), **`genus`**, **`vore`** (dietary category), **`order`** (taxonomic order), **`conservation`** (conservation status), **`sleep_total`** (total hours of sleep per day), **`sleep_rem`** (hours of REM sleep), **`sleep_cycle`** (length of a sleep cycle in hours), **`bodywt`** (body weight in kilograms), and **`brainwt`** (brain weight in kilograms). These columns provide a broad overview of the biological and ecological traits captured in the dataset.

# Summarize the msleep dataset
summary(msleep)

# Display the structure of the msleep dataset
str(msleep)

The `summary()` function in R provides a statistical summary of each column in the dataset. For numeric columns, it shows the minimum, first quartile, median, mean, third quartile, and maximum values. For categorical columns (factors), it displays the count of each category. The `str()` function, short for "structure," prints a concise summary of the dataset's structure, including the type of each variable (such as numeric, integer, or factor), and the first few entries for each column. Both functions take the dataset as their main argument, such as `summary(msleep)` or `str(msleep)`, and are essential for quickly understanding the dataset's contents and data types.

Interpreting the output from `summary(msleep)` helps you spot the range and distribution of values for each variable, such as how much sleep mammals get or the spread of body weights. The structure output from `str(msleep)` shows which variables are numeric and which are categorical, helping you decide how to handle them in further analysis. For instance, knowing that `vore` is a **factor** (categorical variable) and `bodywt` is **numeric** informs your approach to visualization and statistical modeling.

library(testthat)
library(ggplot2)

# Завантажуємо код студента
source("user_code.R")

# Наш стандартний помічник для чистого виводу
check_logic <- function(test_name, condition, error_msg) {
  test_that(test_name, {
    if (isTRUE(condition)) {
      expect_true(TRUE)
    } else {
      fail(error_msg)
    }
  })
}

# --- ТЕСТИ ---

# 1. Перевірка наявності датасету
# msleep автоматично доступний при завантаженні ggplot2
ok1 <- exists("msleep") && inherits(msleep, "data.frame")

check_logic(
  "1. msleep dataset is loaded",
  ok1,
  "The 'msleep' dataset should be available. Did you load library(ggplot2)?"
)

# 2. Перевірка вибірки перших 10 рядків
ok2 <- FALSE
if (exists("first_ten") && exists("msleep")) {
  ok2 <- nrow(first_ten) == 10 && 
         isTRUE(all.equal(first_ten, head(msleep, 10)))
}

check_logic(
  "2. first_ten contains the first 10 rows of msleep",
  ok2,
  "Variable 'first_ten' must contain exactly the first 10 rows of the msleep data frame."
)

# 3. Перевірка об'єкта summary
ok3 <- FALSE
if (exists("msleep_summary") && exists("msleep")) {
  # summary() повертає об'єкт класу 'table' (який є масивом/матрицею)
  ok3 <- (is.list(msleep_summary) || is.matrix(msleep_summary) || inherits(msleep_summary, "table")) &&
         length(msleep_summary) == (ncol(msleep) * 6) # summary зазвичай має 6 показників на колонку
}

# Спрощена перевірка довжини, щоб уникнути помилок через версії R
ok3_simple <- exists("msleep_summary") && !is.null(msleep_summary)

check_logic(
  "3. msleep_summary contains summary statistics",
  ok3_simple,
  "Ensure you assigned the result of summary(msleep) to the variable 'msleep_summary'."
)

# 4. Перевірка виклику str()
# Функція str() завжди повертає NULL (invisible). 
# Ми перевіряємо, чи студент створив змінну і чи вона порожня.
ok4 <- exists("msleep_structure") && is.null(msleep_structure)

check_logic(
  "4. msleep_structure was created using str()",
  ok4,
  "Variable 'msleep_structure' should exist and be NULL (the default return value of str())."
)

test_main.R

A hands-on project-based course guiding learners through the process of exploring, analyzing, and visualizing the msleep dataset using R and ggplot2. Learners will develop practical skills in data visualization, from basic plots to advanced customization and storytelling with data.

This section contains all hands-on tasks for the Data Visualization Project with R and ggplot2, focusing on the msleep dataset.

Loading and Exploring the msleep Dataset

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