R Tutorial | Learn R Programming Language (original) (raw)

Last Updated : 04 Jun, 2025

**R is an **interpreted programming language widely used for statistical computing, data analysis and visualization. R language is open-source with large community support. R provides structured approach to data manipulation, along with decent libraries and packages like Dplyr, Ggplot2, shiny, Janitor and more.

Hello World Program in R Language

Here is an example of the first Hello World program in R Programming Language. To print in R language you just need to use a Print function.

R `

Code

print("Hello World!")

`

Output

Hello World!

Why Learn R?

Learning R is a smart choice for anyone working with data due to its powerful statistical and graphical capabilities. It’s widely used in academia and industry, backed by a large, active community and a vast library of packages. R excels at data manipulation, analysis, and creating high-quality visual reports.

Installation and Setup

In this section, we will explore the steps to install and set up R and RStudio on your system. We'll also cover the necessary configurations to get started with writing and executing R code.

Fundamentals of R

In this section, we will cover the basic concepts and syntax of R programming. This will include understanding variables, data types, and basic operations that form the foundation of programming in R.

Data Structures

In this section, we will the core cover data structures in R, such as vectors, lists, matrices, data frames, and arrays. We will explain how to use and manipulate these structures to store and process data effectively.

Control Flow

In this section, we will learn about control flow mechanisms in R, including conditional statements (if, else) and looping structures (for, while). These concepts allow you to control the flow of execution in your programs.

Functions and Object Oriented Programming

In this section, we will discuss the creation and use of **functions in R for modular and reusable code. Additionally, we will touch on **Object-Oriented Programming (OOP) in R, exploring the basics of class creation and inheritance.

File and Error Handling

In this section, we will focus on reading from and writing to files in R, such as text, CSV, and other formats. We will also cover error handling techniques to ensure that your code runs smoothly and handles exceptions effectively

Data Visualization

In this section, we will explore how to visualize data in R using various plotting techniques. We will introduce popular visualization libraries like ggplot2 and cover how to create different types of charts, including histograms, bar charts, and scatter plots.

Statistics and Machine Learning

In this section, we will dive into the statistical methods and machine learning algorithms that R offers. We will explore common statistical tests, regression models, and machine learning workflows to analyze and model data.

In this section, we will highlight some of the most commonly used R packages that extend its functionality. We'll introduce libraries such as dplyr, ggplot2, caret, and others to help you streamline your data analysis and visualization tasks.

Projects In R

In this section, we will discuss the practical application of R by building projects. These hands-on examples will help you apply the concepts you've learned and deepen your understanding of R in real-world scenarios.

Applications of R Programming Language

R is widely used across many industries due to its strong capabilities in data analysis and visualization. Some key applications include: