# Introduction to R Programming (RPR101)

**Course Length: 3 days**

**Delivery Methods**: Available as private class only

Course Overview

In this R training course, students learn to program in the R language. Whether you are learning R because you plan to use it for data science, data analytics, machine learning, statistical computing, this R course provides you with the prerequisite R programming knowledge to get you started.

Course Benefits

- Learn to create and use functions and packages.
- Learn to work with math in R.
- Learn to work with character data in R.
- Learn to work with dates and times in R.
- Learn to create vectors and lists.
- Learn to create conditional code and work with loops.
- Learn to handle dates and times.
- Learn to work with arrays and matrices.
- Learn to work with data frames.
- Learn to plot data with
`matplot`

.

Course Outline

- R Programming Basics
- Using R Studio
- Running R Statements
- Running an R File
- Exercise: Hello, World!
- Literals
- Exercise: Exploring Types
- Variables
- Exercise: A Simple R Script
- Constants and Deleting Variables
`print()`

Function- Using
`paste()`

and`paste0()`

with`print()`

- C-style Printing with
`sprint()`

- Collecting User Input
- Exercise: Hello, You!

- Functions and Packages
- Defining Functions
- Variables as Vectors
- Using
`typeof()`

and`class()`

- Function Parameters
- Exercise: A Function with Parameters
- Returning Values
- Exercise: Parameters with Default Values
- Packages

- Math
- Arithmetic Operators
- Exercise: Floor and Modulus
- Assignment Operators
- Precedence of Operations
- Built-in Math Functions
- Using Random Numbers
- Exercise: How Many Pizzas Do We Need?
- Exercise: Dice Rolling

- Character
- Quotation Marks and Special Characters
- String Split
- Exercise: Splitting Strings
- Substring and Slicing
- Exercise: Substring
- Paste (Concatenate) Strings
- Exercise: Repetition
- Combining Concatenation and Repetition
- Exercise: Combining Concatenation and Repetition

- Vectors and Lists
- Definitions
- Atomic Vectors
- Lists (Non-atomic vectors)
- Sequences and Random
- Ranges
- Indexing using
`[`

and`[[`

- Exercise: Simple Rock, Paper, Scissors Game
`$`

operator- Exercise: Slicing Sequences

- Flow Control
- Conditional Statements
- Compound Conditions
- The
`is`

and`is not`

Operators `all()`

and`any()`

and the Ternary Operator- Loops in R
- Exercise: All True and Any True
- break and next

- Exception Handling
- Exception Basics
`try()`

`tryCatch()`

- Dates and Times
`date()`

`Sys.Date()`

`Sys.time()`

- Dates as Strings
- Time and Formatted Strings
- Exercise: What Color Pants Should I Wear?
- Date and Time arithmetic
- Exercise: Report on Departure Times

- Matrices and Arrays
- What is a Matrix?
- Creating a Matrix
`rbind()`

and`cbind()`

`matrix()`

- Performing Arithmetic on Matrices
- Retrieving Rows and Columns
- Exercise: Working with an Array
- What is an Array?
- Creating an Array
- Naming Rows and Columns
- Exercise: Working with an Array

- Data Frames
- What is a Data Frame?
- Creating a Data Frame using
`data.frame()`

- Creating a Data Frame from a CSV
- Exploring a Data Frame using
`str()`

and`summary()`

- Exercise: Practice Exploring a Data Frame
- Changing Values
- Retrieving Rows and Columns
- Combining Row and Column Selection
- Adding a Column to the Data Frame
- Add a Row to the Data Frame with
`rbind()`

- Plotting with
`matplot`

- Exercise: Plotting a Data Frame
- Other Kinds of Plots

Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the class examples.

##### Live Private Class

- Private Class for your Team
- Live training
- Online or On-location
- Customizable
- Expert Instructors