Recap of session 7

• Importing data with readr
• Where does your data live?
• Factors

File paths and working directories

• A character string that tells you the location of a file
• Absolute path: starts from the “root” directory
  • e.g. /Users/kjytay/Downloads/datafile.csv
• Relative path: starts from the current directory (denoted by .)
  • e.g. If I am in the folder /Users/kjytay: ./Downloads/datafile.csv
  • e.g. If I am in the folder /Users/kjytay/Downloads: ./datafile.csv or simply datafile.csv

File paths and working directories

• Working directory: where R looks for files that you ask it to load
• Also where R will put any files that you ask it to save
• You can see your current working directory at the top of the console or by typing getwd()
• You can change the working directory with setwd() function or Session > Set Working Directory > …

Factors

• A concept unique to R
• Useful for working with categorical variables: variables that have a fixed and known set of possible values
• Why use factor variables instead of character variables?
  • Character variables don’t protect you from typos
  • Character variables don’t sort in a useful way

Functions for factors

• fct_recode(): change factor levels
• fct_collapse() and fct_lump(): reduce the number of factor levels
• fct_infreq(): to sort factor levels by how often they appear
• fct_reorder(): to sort factor levels by some other variable
• fct_rev(): reverse the order of the factor levels

All these functions are part of the forcats package, which is automatically loaded when you load the tidyverse package.

Agenda for today

• Reproducible research
  • R scripts
  • R markdown

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: Airbnb listings

(Source: Hotel Technology News)

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.

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.