R Programming

What are Data Structures in R? Data Structures define how multiple data values are organized, related, and stored in memory so they can be efficiently processed, searched, filtered, sorted, and analyzed. Core Data Structures Comparison Table Structure Dimension Data Type Primary Use Vector 1D Same Lists of numbers/text Matrix 2D Same Mathematical computation Array Multi … Read more

1. Creating a Matrix Using the matix( ) Function Explanation: By default, R fills the matrix column-wise. This means: The print() function simply displays the matrix on the console so that the user can visually inspect the structure. 2. Creating a Matrix with Row-wise Filling Explanation: As a result: This option is particularly useful when … Read more

1. What Is Programming? Programming is the process of writing instructions for a computer so that it can perform specific tasks. A computer is a powerful machine, but it cannot think or make decisions on its own. It only works according to the instructions given by humans. These instructions must be written in a special … Read more

Understanding how Inf, NaN, and Lists work in R is essential for data cleaning, debugging, and structuring complex information. These concepts often appear when handling real‑world datasets where missing values, undefined results, and mixed‑type data structures are common. The following notes provide clear, point‑wise explanations along with practical R examples. 1. Understanding Inf in R … Read more

1. Introduction Missing observations are common in empirical datasets originating from surveys, experiments, sensor records, and transactional systems. In R, missing values are represented using the symbol NA, indicating that the information for that particular position is unavailable or undefined. When reading external files such as CSVs or spreadsheets, R automatically converts empty fields or … Read more

Introduction Vectors in R are ordered data structures in which each element occupies a fixed position. The process of extracting or altering values relies on the language’s 1‑based indexing system. In this system, the first element of a vector is referenced by index 1, the second by index 2, and so forth. This indexing approach … Read more

R offers several helpful built‑in functions that allow you to examine vector objects. These functions tell you how many elements a vector has, what type of data it stores, and how R handles that data internally. Understanding these functions is important when working with datasets, debugging code, or verifying the structure of your objects. Understanding … Read more

R provides several built-in data structures designed to store, organise, and analyse data effectively. These structures use basic data types such as numeric, integer, character, and logical. For anyone learning R for analytics, statistics, or data science, a strong understanding of these structures is essential. The five primary data structures in R are: Among these, … Read more

Goal of This Chapter Before doing real data science, you must understand: This chapter explains EVERYTHING clearly. How R Executes Code R is an interpreted language, meaning: Try this: Output: Comments in R Comments are notes for humans, ignored by R. Used for: Assignment Operators. Assignment means: store a value inside a variable. R has … Read more