Overview of R
Learn what R is, its features and where it is used for statistics and data analysis.
📚 Programming Tutorial
R Programming
R is an open-source programming language and software environment for statistical computing, data analysis and graphics. This tutorial covers R from the basics to vectors, lists, data frames, graphics and debugging.
R Programming Tutorial Index
57 Topics📘 Introduction
Installing R
Learn how to download and install R and RStudio on Windows, Linux and macOS.
Running R
Learn the ways of running R: the console, script files and RStudio.
Comments in R
Learn how to write comments with # to document R code.
Variables in R
Learn how to create variables, assign values and follow the naming rules.
Datatypes in R
Learn the basic data types: numeric, integer, character, logical and complex.
Type conversion in R
Learn how to convert values from one data type to another.
Input & Output Functions in R
Learn how to read input and display output using functions such as readline(), scan(), print() and cat().
Operators in R
Learn the arithmetic, relational, logical and assignment operators of R.
Objects in R
Learn what objects are in R and how their attributes and classes work.
Sub setting R Objects
Learn how to extract parts of vectors, lists, matrices and data frames.
Packages in R
Learn how to install, load and use packages in R.
Rounding in R
Learn the rounding functions round(), signif(), ceiling(), floor() and trunc().
Complex numbers in R
Learn how to create and work with complex numbers in R.
🔀 Control Structures
Control Structures in R
Learn decision making and looping in R: if, if-else, for, while, repeat, break and next.
⚙️ Functions
Functions in R
Learn how to define and call functions, and how arguments, default values and return values work.
📏 Vector
Vectors in R
Learn how to create vectors and the basic operations on them.
Vector Indexing
Learn how to access vector elements using positive, negative, logical and named indexes.
Adding and Deleting Vector Element
Learn how to add elements to a vector and delete elements from it.
Obtaining the Length of a Vector
Learn how to find the number of elements of a vector.
Matrices and Arrays as Vectors
Learn how matrices and arrays are stored and handled as vectors.
Vector Arithmetic and Logical Operations
Learn element-wise arithmetic, recycling and logical operations on vectors.
Dates and Times in R
Learn how to work with dates and times in R.
🗒️ Lists
Creating Lists in R
Learn how to create lists that hold elements of different types.
General List Operations
Learn the common operations on lists such as indexing, naming and modifying elements.
Adding and Deleting List Elements
Learn how to add elements to a list and delete elements from it.
Getting the Size of a List
Learn how to find the size of a list.
Extended Example
Work through an extended example that applies the list operations.
Accessing List Components and Values
Learn how to access list components and their values.
Applying Functions to Lists
Learn how to apply a function to every element of a list with lapply() and sapply().
🗃️ Data Frame
Creating a Data Frame
Learn how to create data frames and how to read data into them.
Accessing Data Frames
Learn how to access the rows, columns and cells of a data frame.
Extended Example
Work through an extended example that applies the data frame operations.
Other Matrix-Like Operations
Learn matrix-like operations on data frames such as extracting subsets, rbind(), cbind() and apply().
🏷️ Factors
Factors and Levels
Learn how factors store categorical data as levels.
Common Functions Used with Factors
Learn the common functions used with factors such as tapply(), split() and by().
📊 Tables
Working with Tables
Learn how to create tables of counts and work with them.
Matrix/Array-Like Operations on Tables
Learn how to apply matrix-like and array-like operations to tables.
Extracting a Subtable
Learn how to extract a part (subtable) of a table.
Finding the Largest Cells in a Table
Learn how to find the cells with the largest counts in a table.
➗ Math Functions
Math Functions
Learn the built-in math functions of R such as sqrt(), exp(), log() and abs().
Calculating a Probability
Learn how to calculate a probability in R with a worked example.
Cumulative Sums and Products
Learn how to compute cumulative sums and products with cumsum() and cumprod().
Minima and Maxima
Learn min(), max(), pmin(), pmax(), which.min() and which.max().
Calculus
Learn how to do derivatives and integrals in R.
Functions for Statistical Distributions
Learn the d, p, q and r functions for statistical distributions such as the normal and binomial.
📈 Graphics
Creating Graphs
Learn how to create graphs in R with plot(), lines(), hist() and barplot().
Customizing Graphs
Learn how to customize the titles, labels, colors, symbols and axes of a graph.
Saving Graphs to Files
Learn how to save graphs to PNG, JPEG and PDF files.
Creating Three-Dimensional Plots
Learn how to create three-dimensional plots in R.
🐞 Debugging
Fundamental Principles of Debugging
Learn the basic principles of finding and fixing errors in a program.
Why Use a Debugging Tool?
Understand why a debugging tool is better than adding print statements.
Using R Debugging Facilities
Learn the debugging facilities of R such as debug(), browser() and traceback().
Moving Up in the World
Learn how to move up and down the call stack while debugging.
Ensuring Consistency in Debugging Simulation Code
Learn how to get repeatable results when debugging simulation code.
Syntax and Runtime Errors
Learn how to find and fix syntax errors and runtime errors.
Running GDB on R Itself
Learn how to run the GDB debugger on R itself.
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