Recap of session 5

• Creating projects in R
• Importing your own dataset into R

Reminder: Project proposals are due tomorrow night!

• 1-2 paragraph description of project (datset, problem of interest, potential visualizations)
• Submit text file on Canvas (link to or sample of dataset preferred, not necessary)

Agenda for today

• Reproducible research
  • R scripts
  • R markdown
    
• More transforming and plotting practice!

Reproducible research: what & why

Reproducible research: publishing data analyses together with their data and code so that others may “reproduce” the findings.

Why reproducible research?

• Increase transparency and robustness of analyses
• Preserve integrity of analyses over time
• Reduce incentive for dishonest practices

R scripts

• An R script is a file containing lines of R code that are meant to be run altogether
• R scripts are typically working files, not intended for presentation
• R scripts have .R file extensions
• Comments can be inserted to explain the code

R markdown

RStudio: R markdown is a document format which allows you to “weave together narrative text and code to produce elegantly formatted output.”

Made possible by the knitr package (Yihui Xie)

(Source: Vimeo)

R markdown: output (1)

(Source: Github: kjytay/FIFA-world-cup-2018)

R markdown: output (2)

(Source: Github: kjytay/FIFA-world-cup-2018)

R markdown: output (3)

(Source: Github: kjytay/FIFA-world-cup-2018)

R markdown: input

R markdown: more details

• Text (written in Markdown), interspersed with code chunks, “knit” into a document using the knitr package
• Typically used for presentation
• R markdown files have .Rmd extensions
  
• R markdown cheatsheet and reference guide available here

Surprise: (Almost) all the class material (including slides) was created with R markdown!

Quick intro to Markdown

Markdown is a simple way to convert a text document into a web file (i.e. HTML) with basic styling.

Has support for:

• Headers
• Emphasis (italics, bold, strikethrough)
• Lists
• Links
• Images
• Etc…

Markdown reference here.

To see how your Markdown (.md) document looks like in real-time, use an online Markdown editor (e.g. dillinger.io)

Today’s dataset: 2016 US Presidential Elections

(Source: Christianity Today)

Optional material

Rmd workflow (basic)

1. Edit .Rmd file in RStudio.
   
2. Knit the document (either by hitting the “Knit” button or using a keyboard shortcut).
   • When you press “Knit”, the file is automatically saved.
     
   • Next, RStudio opens a new console, “knits” the document there, then closes that console. No code is run in your original console!
     
   • RStudio creates a .html file in the same folder as the .Rmd file.
3. Preview output in the preview pane, or by opening the .html file.
   • If you want to make changes, go back to Step 1.

Rmd workflow (advanced)

1. Edit .Rmd file in RStudio. As you are typing code in the .Rmd file, enter this code into the RStudio console to see if it works.
   • If the code doesn’t work, keeping editing the .Rmd file until it does.
     
2. Periodically knit the document.
   • When you press “Knit”, the file is automatically saved.
     
   • Next, RStudio opens a new console, “knits” the document there, then closes that console. No code is run in your original console!
     
   • If you’ve done everything correctly, it should knit properly.
   • If it doesn’t, it’s probably because you made code changes in the RStudio console which are not reflected in the .Rmd file. Use rm(list = ls()) to empty your environment, run the code in your .Rmd file sequentially in the RStudio console to see what went wrong.

Common Rmd chunk options

• include = FALSE: prevents code and results from appearing in the finished file. R Markdown still runs the code in the chunk, and the results can be used by other chunks.
  • Useful for decluttering your Rmd output, showing only essential code.
• echo = FALSE: prevents code, but not the results from appearing in the finished file.
  • Useful if you just want to show figures but not code that generated it.
• eval = FALSE: Code appears in the output but is not run.
  • Useful for presenting code for demonstration purposes.
• message = FALSE: prevents messages that are generated by code from appearing in the finished file.
  • Useful for suppressing messages when loading packages.
• warning = FALSE: prevents warnings that are generated by code from appearing in the finished.
  • Useful for suppressing warnings when loading packages, plotting data or fitting models.