This lesson is in the early stages of development (Alpha version)

r-novice-inflammation

This repository is a way for me to test out the new features in {sandpaper} on a real repository. It’s derived from Programming With R and hopefully, I can get it to a point where it will be identical without using Jekyll.

To render this lesson, first clone it and then use {sandpaper} to render it

remotes::install_github("zkamvar/sandpaper", dep = TRUE)
usethis::create_from_github("zkamvar/miniature-octo-waffle", "~/Desktop")
## you will be moved to that directory

sandpaper::build_lesson()

I converted this site by using the {dovetail} package:

remotes::install_github("zkamvar/sandpaper", dep = TRUE)
remotes::install_github("carpentries/dovetail") # contains script to convert lessons
remotes::install_github("carpentries/pegboard") # for converting 

# Download the repo from github
usethis::create_from_github("swcarpentry/r-novice-inflammation", "~/Desktop")

# convert the materials
source(system.file("convert", "convert.R", package = "dovetail"))

# Create sandpaper repo
sandpaper::create_lesson("~/Desktop/new-rni")

system("cp -R ~/Desktop/rni/_episodes_rmd/* ~/Desktop/new-rni/episodes")

## change ../fig to fig
## change latex link to latex equation

After that was done, I had to make a couple of changes like making sure the hard-coded figures were no longer sourcing above their current directory, by changing all instances of ../fig to fig and changing the reference to the latex equation in episode 8 to actual latex code.

I could then build the lesson inside of the new-rni directory

sandpaper::build_lesson()
Setup Download files and setup software required for this lesson
00:00  1. Analyzing Patient Data How do I read data into R?
How do I assign variables?
What is a data frame?
How do I access subsets of a data frame?
How do I calculate simple statistics like mean and median?
Where can I get help?
How can I plot my data?
00:45  2. Creating Functions How do I make a function?
How can I test my functions?
How should I document my code?
01:15  3. Analyzing Multiple Data Sets How can I do the same thing to multiple data sets?
How do I write a for loop?
01:45  4. Making Choices How do I make choices using if and else statements?
How do I compare values?
How do I save my plots to a PDF file?
02:15  5. Command-Line Programs How do I write a command-line script?
How do I read in arguments from the command-line?
02:45  6. Best Practices for Writing R Code How can I write R code that other people can understand and use?
02:55  7. Dynamic Reports with knitr How can I put my text, code, and results all in one document?
How do I use knitr?
How do I write in Markdown?
03:15  8. Making Packages in R How do I collect my code together so I can reuse it and share it?
How do I make my own packages?
03:45  9. Introduction to RStudio How do I use the RStudio graphical user interface?
04:00 10. Addressing Data What are the different methods for accessing parts of a data frame?
04:20 11. Reading and Writing CSV Files How do I read data from a CSV file into R?
How do I write data to a CSV file?
04:50 12. Understanding Factors How is categorical data represented in R?
How do I work with factors?
05:10 13. Data Types and Structures What are the different data types in R?
What are the different data structures in R?
How do I access data within the various data structures?
05:55 14. The Call Stack What is the call stack, and how does R know what order to do things in?
How does scope work in R?
06:10 15. Loops in R How can I do the same thing multiple times more efficiently in R?
What is vectorization?
Should I use a loop or an apply statement?
06:40 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.