Chapter 3 RStudio Projects

What is this?

Projects make it easy to keep your work organized.
All files, scripts, documentation related to a specific project are bound together with a .Rproj file

Encourages reproducibility and easy sharing

3.1 Create a new project

Use the Create project command (available in the Projects menu and the global toolbar)

One project = one folder

Place similar files inside of their own folders

Keep track of versions

Datasets should be stored as comma separated files (.csv) in Data folder.
comma separated files (.csv) can be created from almost all applications (Excel, LibreOffice, GoogleDocs)
file -> save as .csv

Good:
- rawDatasetAgo2017.csv
- co2_concentrations_QB.csv
- 01_figIntro.R
Bad:
- final.csv (Uninformative!)
- safnnejs.csv (Random!)
- 1-4.csv (Avoid using numbers!)
- Dont.separate.names.with.dots.csv (Can lead to reading file errors!)

Use short informative titles (i.e. “Time_1” not “First time measurement”)
- Good: “Measurements”, “SpeciesNames”, “Site”
- Bad: “a”, “3”, “supercomplicatedverylongname”
Column values must match their intended use

No text in numeric columns
Do not include spaces!
NA (not available) can be used for missing values, and blank entries will automatically be replaced with NA
Name your variables informatively
Look for typos!
Avoid numeric values for data that do not have a numeric meaning (i.e. subject, replicate, treatment)
- For example, if subjects are “1,2,3” change to “A,B,C” or “S1,S2,S3”
Use CONSISTENT formats for dates, numbers, metrics, etc.
Do not include notes, additional headings, or merged cells!
One variable per column!

It is possible to do all your data preparation work within R. This has several benefits:

Saves time for large datasets
Keeps original data intact
Keeps track of the manipulation and transformation you did
Can switch between long and wide format data very easily (more on this later and in workshop 4)
For a useful resource, see https://www.zoology.ubc.ca/~schluter/R/data/