Swirl Package in R

Francis Mensah showed us how to use the Swirl package to interactively learn R

R
Swirl package
workshop
self-learn
Author

Simisani Ndaba

Published

July 22, 2023

Meetup Description

Francis Mensah explored the features and benefits of the Swirl package and its significance for R users with a live demonstration.

Swirl Package

Install and run a course automatically from swirl

  1. Make sure you have a recent version version of swirl and Load the package and type “swirl()” when you are ready.
install.package("swirl")
library("swirl")
"| Hi! Type swirl() when you are ready to begin."
swirl()
  1. The prompt will ask what to call you during your session. You can type your name or your username.
"| Welcome to swirl! Please sign in. If you've been here before, use the same name as you did then. If you | are new, call yourself something unique."

What shall I call you? | "Simi"
  1. The prompt will show you a list of modules to choose from. From selecting from either 0 to 5, the course selection will generate the course you want to practice.
"| To begin, you must install a course. I can install a course for you from the internet, or I can send you 
| to a web page (https://github.com/swirldev/swirl_courses) which will provide course options and directions
| for installing courses yourself. (If you are not connected to the internet, type 0 to exit.)"

1: R Programming: The basics of programming in R
2: Regression Models: The basics of regression modeling in R
3: Statistical Inference: The basics of statistical inference in R
4: Exploratory Data Analysis: The basics of exploring data in R
5: Don't install anything for me. I'll do it myself.

"Selection: 1
  |===================================================================================================| 100%

| Course installed successfully!


| Please choose a course, or type 0 to exit swirl."

1: R Programming
2: Take me to the swirl course repository!

"Selection: "

"| Please choose a lesson, or type 0 to return to course menu.

 1: Basic Building Blocks      2: Workspace and Files        3: Sequences of Numbers    
 4: Vectors                    5: Missing Values             6: Subsetting Vectors      
 7: Matrices and Data Frames   8: Logic                      9: Functions               
10: lapply and sapply         11: vapply and tapply         12: Looking at Data         
13: Simulation                14: Dates and Times           15: Base Graphics"           

Selection: 1

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