Help from the experts

Sometimes, you know the function that you need, and you (think you) are using the function correctly, but the code generates an error or doesn't work as expected. Of course, the first thing to do is google the error message or a general description of the problem. I find that >98% of the time, that generates a solution to the problem (though it might take multiple rounds of search terms or crawling down rabbit holes of recursive help pages before landing on the solution).

But for that <2% of the time, the information is just not available. Now you may need to post a question on a forum (e.g., Posit Community or Stack Overflow) or even submit a bug report to a package's GitHub repository. Keep in mind, these options should be last resorts after you've scoured the internet (and asked me!). Code developers are busy people, and personally I want them developing amazing new tools rather than answering questions that have already been answered in documentation or help forums.

Posting to forums

Before you post something on a forum, you should learn how to ask a good question. This involves writing an informative title, including relevant tags, and describing the problem, the expected behavior, and the actual behavior. But a critical piece of asking for help is including a reproducible example---that is, a minimal amount of code that someone else can use to reproduce the problem. This is such an important component of getting help that...of course...there's a package for that: {reprex}.

Data for reproducible examples

Step one of creating a reproducible example is to create the code that you want to post that demonstrates the problem with the least amount of code that you can make public. This means that you cannot post your data or the entire workflow getting to this part of your data analysis. Probably the best option here is to use an example data set loaded to base R (e.g., mtcars) or a data set included in a commonly used package (e.g., {palmerpenguins}). To see the data sets included in base R, type data(). Alternatively, you can type a small data frame into your example.

Go ahead and load the {palmerpenguins} package on your computer in RStudio, as we'll use it here and in future sessions.

library("palmerpenguins")

Creating a reproducible example

Now that you have an available data set, you need to write the smallest chunk of code that generates the problem. Once you have that, you're ready to evaluate your code. Now, you need to install and load the {reprex} package in RStudio.

install.packages("reprex")
library("reprex")

The {reprex} packages basically spins up a new R session, runs your code in it, and returns the output from that code. So the first thing that you need to do in your reproducible example is load any packages that are required for the code to run (because, remember, the people testing your code don't necessarily have the packages loaded already). If you forget to include the packages, you'll see this very quickly when you run reprex(). Next, you need to make sure that the data are available.

Once you have your code ready, copy it to the clipboard, and run reprex() from the R console. This will run the copied code in a new R session. Then it will post the output to the Viewer pane in RStudio and copy it to the clipboard so you can paste it into your forum form or text document.

Testing a reprex

OK, let's try it! Let's assume that for our reprex, we just want to show the first three rows of the penguins data set using the head() function. After you've installed and loaded {reprex}, copy the following code to your clipboard and then type reprex() in the RStudio R console.

head(penguins, 3)

After you run the code, click Continue to see what went wrong.

Running a reprex

OK, I set you up to fail there. You likely received an error. Here's what happened, if you received one of the following errors.

If you received Error in reprex() : could not find function "reprex" in the R console, this means either you did not install or load the {reprex} package. Please install and load the package.

If reprex() worked properly, you should have had this output in the Viewer tab:

head(penguins, 3)
#> Error in head(penguins, 3): object 'penguins' not found

^{Created on 2023-01-14 with reprex v2.0.2}

This is the expected behavior.

Running a reprex

Remember, we need to include all packages that are required to run the reprex. Now copy the following text and run reprex().

library("palmerpenguins")
head(penguins, 3)

You should have generated the following:

library("palmerpenguins")
head(penguins, 3)
#> # A tibble: 3 × 8
#>   species island    bill_length_mm bill_depth_mm flipper_l…¹ body_…² sex    year
#>   <fct>   <fct>              <dbl>         <dbl>       <int>   <int> <fct> <int>
#> 1 Adelie  Torgersen           39.1          18.7         181    3750 male   2007
#> 2 Adelie  Torgersen           39.5          17.4         186    3800 fema…  2007
#> 3 Adelie  Torgersen           40.3          18           195    3250 fema…  2007
#> # … with abbreviated variable names ¹​flipper_length_mm, ²​body_mass_g

^{Created on 2023-01-14 with reprex v2.0.2}

Congratulations, you just created your first reproducible example! Not only is this important for posting questions to forums, but I would like you to run reprex() before sending questions to me, too.

Panels

Spend some time exploring the RStudio menus and panels. While you can customize the positions of the panels, using the standard configuration will make it easier for other people (read: me) to understand what you are doing if you ask for help.

Here is a list the tabs that you'll be using most often. Make sure you are familiar with them.

• Source/Editor
• Console
• Environment
• History
• Plots
• Packages
• Help

Keyboard shortcuts

Using keyboard shortcuts will greatly simplify your RStudio workflow and allow you to work more quickly. There are dozens of keyboard shortcuts in RStudio. You can find them by going to the menu bar Tools > Keyboard Shortcuts Help. Explore the keyboard shortcuts and answer the following questions:

Wrap-up

Congratulations, you finished the tutorial!

To get credit for this assignment, replace my name with the first name that you submitted in the course introduction form in the code below and click Run Code to generate the text for you to submit to Canvas.

# replace my name below with your first name (surrounded by quotes)
first_name <- "Jeff"
generate_text(first_name)

Assignment complete

Copy that code into Canvas, and you're all set for this tutorial.