Topic: Data management

Goals

We will discuss some principles of data management, data flow and reproducible research
Participants will continue to practice with R, and will examine their data and make some products

If you used a simplified/domesticated data set for assignment 1, please find a ‘real’/wild-caught data set for this assignment.
If you are using code you’ve developed for a previous project, please streamline it as much as possible! Update/improve your code to take our R style recommendations into account, repeat yourself less, etc.. (We prefer that you write new code for these assignments …)

Examine the structure of the data you imported
Examine the data for problems, and to make sure you understand the R classes
Make one or two plots that might help you see whether your data have any errors or anomalies
- Report your results; fix any problems that you conveniently can
Use the saveRDS function in R to save a clean (or clean-ish) version of your data
- Use the .gitignore functionality in git – do not in general put “made” objects into your repo
Write a separate script that reads in your .rds file and does something with it: either a calculation or a plot
In your README.md file:
- Describe your two scripts – what they do, where they are, what directory they should be run from.
- Discuss what sort of investigations you are thinking you might do with your data, and how you might break your project into replicable components