Dealing with errors
As you work through the practicals, you will encounter some code that does not work as you want it to. Don’t despair! Errors (when R is unable to run your code) and bugs (when the code doesn’t do what you hoped) are a natural part of coding. Even the best of the best deal with these problems regularly - learning to track down the issue is a skill that you can learn and practice.
Advice for dealing with errors
Errors can be sneaky - check results often
If a chunk of code runs smoothly without giving you any error or warnings this does not necessarily mean it accomplished the desired task.
It is a good habit to check the results of your code every time you finish a task.
In the text before the code chunk, make sure to briefly state what the point of the chunk is. This will remind later readers - which might be your future self! - what the desired output is.
If you created a new object, take a look at it, either by clicking its name in your Environment tab or by typing its name into the console. Make sure it looks about how you expect.
If you created or updated a data frame, make sure your edits did what you hoped. Use the Environment or the
head()function to investigate your changes.
Two heads are better than one
It can be hard to spot bugs in code that you wrote.
Work with those around you - if something goes wrong, ask a friend to take a peek at your code and see if any glaring errors (like syntax error) pop out.
Explain your code out loud
The best way to troubleshoot a sneaky but is to explain out loud each step of your code, and what you hoped to accomplish.
If you are alone, try Rubber Duck Debugging!
Google is your friend
The whole of the internet is at your disposal! Use it early, use it often.
Some tricks:
Copy-paste the exact error message into Google. Chances are, somebody else had a similar problem and got a similar message.
Include package names in your search terms. For example, “bar plot in ggplot” is a better search than “bar plot in R”.