Thread by @sctyner

THREAD/RANT: Just watched a great #rstats webinar. Presenter is an author of many📦s. At the end, the host suggested that the (100s of) attendees go file issues on the 📦s Github repos & comment on the presenter's blog posts to ask Qs they didn't get answered in the webinar. 1/?

This is absolutely NOT how you get answers to #rstats questions. Not only will you waste the package author's time, you will waste your own time. So, here are some tips on how to get help in #rstats. TL;DR: filing Github issues, tweeting/emailing pkg author are LAST RESORTS. 2/?

(These tips are ordered based on my experience to get you an answer as fast as possible.)

#1: Read the relevant documentation. #rstats Many packages have websites & vignettes. Consult those, too.

#2. Google the error message, removing any terms specific to your problem (e.g. object names). This will often take you to @StackOverflow or a @Github issue where your problem has already been solved. #rstats 4/?

@StackOverflow @github #3: Smart search on google, stackoverflow, @rstudio community, github issues: pick a few words/tags and use only the bare minimum to get results. On stackoverflow, maybe search “[ggplot2] margin” if you’re having trouble with plot margins. 5/?

@StackOverflow @github @rstudio For google, use things like "ggplot2 AND margin AND error." You can directly search open and closed issues on github using keywords. Again, you’re likely to find that your problem has already been solved. #rstats 6/?

@StackOverflow @github @rstudio Make the problem as small as possible, aka make a “minimally reproducible example.” Isolate what is happening. (e.g. if it’s a ggplot question, make a toy data frame with the minimum number of columns to reproduce the error message from #2) 7/?

@StackOverflow @github @rstudio Watch @JennyBryan's webinar on the {reprex} 📦resources.rstudio.com/webinars/help-…
In my experience, the process of making a min reprex isolates the issue so I can figure out what’s going on and solve the problem without going elsewhere at least 75% of the time. 8/?

@StackOverflow @github @rstudio @JennyBryan #5. Use the #rstats hashtag on twitter. Post your reprex on a github gist and link to it in the tweet. I’ve found that the #rstats hashtag is the best option for conceptual questions like “Hey #rstats in #rmarkdown is there a way to do XYZ?” 9/?

@StackOverflow @github @rstudio @JennyBryan This is useful if your question is difficult to google or describe in exact language. If I haven’t found an answer in 1-4, this will get me one 90% of the time. #rstats 10/?

@StackOverflow @github @rstudio @JennyBryan #6. Ask a colleague or a friend. By this point, your question will be very well-defined and if they know the answer and have a couple minutes, they’ll be able to get it to you quickly. 11/? #rstats

@StackOverflow @github @rstudio @JennyBryan #7. Sleep on it. Especially if you’ve been battling with an error for many hours or late at night, just stop and try again the next day. Find another project to work on that works a different part of your brain. #rstats 12/?

@StackOverflow @github @rstudio @JennyBryan #8. Open a brand new R session, with nothing in it: no objects, libraries, nothing. Start from the beginning. Ideally, you have a script or two that you can step through line by line to get you exactly to the trouble code at hand. #rstats 13/?

@StackOverflow @github @rstudio @JennyBryan (This arguably could be higher on the list, but I don’t think “blow everything up first” works here.) Starting from scratch the next day will solve your problem more often than you’d think. 14/? #rstats

@StackOverflow @github @rstudio @JennyBryan #9. Ask a question on StackOverflow or in RStudio community. Use the {reprex} package to help others help you.

Wait 24 hours before going to the next step.

Maybe repeat some previous steps in the meantime to see if you can answer your own question. 15/?

@StackOverflow @github @rstudio @JennyBryan #10. If you still haven’t figured it out, file a github issue, and include the {reprex} with it.

Wait.

Maybe repeat some previous steps in the meantime to see if you can answer your own question. #rstats 16/?

@StackOverflow @github @rstudio @JennyBryan Since I've started thinking about #rstats problems this way, I have not gotten past step #8. There have been times where I did file an issue on @Github and I shouldn't have, and I was called out for it. This does not feel good!!! 17/?

@StackOverflow @github @rstudio @JennyBryan In 1 case, I hadn't read the docs carefully (step 1!). If I had, I could've saved myself & others time. Learn from my mistakes! This 🧵 should probs be a blog post; look for that soon. I know I'm not the 1st to say this, so drop some links if you have 'em! END RANT #rstats 18/18