Chapter 4 R Objects (III): Other Types

Learning Objectives

After completing this chapter, you will be able to:

  • Create and manipulate matrices and arrays for multi-dimensional data
  • Understand data frames and tibbles as the primary structures for tabular data
  • Use lists to store heterogeneous collections of objects
  • Recognize the differences between NULL, NaN, and Inf

In Chapters 2 and 3, we introduced atomic vectors. In a typical application, we usually need a more complex object type to represent the data. In this chapter, we will introduce a few commonly used object types including matrix in Section 4.1, array in Section 4.2, data frame in Section 4.3, tibble in Section 4.4, and list in Section 4.5.

At a glance – Chapter ROADMAP

Section 4.1. Matrix: Create and manipulate 2D arrays of the same type.
Section 4.2. Array: Work with higher-dimensional data structures.
Section 4.3. Data Frame: Store tabular data with mixed types.
Section 4.4. Tibble: Use a modern, user-friendly version of data frames.
Section 4.5. List: Create heterogeneous collections of objects.
Section 4.6. Special values: Understand NULL, NaN, and Inf.

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