Applying some “code first aid” can help address problems in your
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Helpers can more easily debug your code if you provide them with a
small example of the problem (a “reprex”) that they can tinker with
themselves.
In the process of building a reprex, you may find the solution
yourself.
In the rest of this lesson, we will be working through a “road map”
to getting unstuck that includes code first aid and the process of
making a reprex.
The surveys dataset includes records of rodents
captured in a variety of experimental plots over a 12-year period,
including some data about each rodent’s sex and morphology.
The first step to getting unstuck is identifying a problem,
isolating the problem area, and interpreting the problem
Often, using “code first aid” – acting on error messages, looking at
data, inputs, etc., pulling up documentation, asking a search engine or
LLM, can help us to quickly fix the error on our own.
If code first aid doesn’t work, we can ask for help and prepare a
reproducible example (reprex) with a defined problem and isolated
code
We’ll cover future steps to prepare a reproducible example (reprex)
in future episodes.
A minimal reproducible dataset (a) contains the minimum number of
lines, variables, and categories, in the correct format, to replicate
your problem; and (b) must be fully reproducible, meaning that someone
else can run the same code from anywhere without additional steps.
To make it accessible, you can create a dataset from scratch using
as.data.frame, you can use an R-built dataset like
cars, or you can use a subset of your own dataset and then
use dput() to generate reproducible code.
