Lesson 15: Good coding practices, debugging strategies, and getting help

Readings

• Look over the The tidyverse style guide for inspiration - you don’t have to read the whole guide carefully

Today, Erika Mudrak from the Cornell Statistical Consultation Unit will give a guest lecture. Her slides will be available on the Canvas site.

Optional resources:

From R for Excel users:

Getting help, or really helping you help yourself, means moving beyond “it’s not working” and towards solution-oriented approaches. Part of this is the mindset where you expect that someone has encountered this problem before and that most likely the problem is your typo or misuse, and not that R is broken or hates you.

There is excellent advice for trouble-shooting R-code and how to get help in Lecture 2 from ESM 206: Statistics and Data Analysis in Environmental Science and Management by Allison Horst.

Also check out the slide deck or recorded talk for Jenny Bryan’s talk “Object of type ‘closure’ is not subsettable” at the 2020 RStudio conference. You can also check out her Reprex webinar.

Announcements

• Homework 7 is due tonight
• Reminder that we will have short students presentations during our final class on March 31 (details here) - start thinking about what you want to show the class

A consistent coding style maximizes readability

Developing a consistent style in your coding, makes it a lot easier to read. Here is some inspiration:

• The tidyverse style guide
• A more concise overview of the style Hadley Wickham uses in his books “R for Data Science” and “Advanced R”
• There are also great tips for styling, organizing and optimizing your code in the blogpost R Best Practices: R you writing the R way! by Milind Paradkar
• Many of the same principles are also summarized by JEFworks here