25 Getting Help

How do I solve this problem? How do I get my skills up to snuff?

We have an #data-sci-discuss channel on Slack to ask questions and also news about useful resources and packages. We prefer that you ask question on this channel rather than privately. This way you draw on the group’s knowledge and everyone can learn from the conversation. In general, if you spend 20 minutes banging your head against your screen trying to figure something out, it’s time to ask someone.

Some good questions for the Slack room:

  • Which package should I use for something?
  • Anyone have a good reference or tutorial for package, method?
  • What does this error mean?

Our technology team are a tremendous resource for a number of computing topics (especially web technologies and development operations), but remember that they are our collaborators, not IT support. (We do have straight IT support, mostly for office network issues, through Profound Cloud)

Also, outside EHA:

  • There’s an almost-monthly NYC R Meetup and even rarer Data Visualization Meetup that EHA members sometimes attend.
  • There’s also an R-Ladies NYC chapter that has regular meetups and a Slack Chat room. WiMLDS offers support to attend machine learning and data science conferences.
  • Stack Overflow is a popular Q&A site for computer programming that a lot of discussions about R.
  • R-Weekly publishes a useful weekly newsletter on new R developments, packages, and publications.
  • The #rstats hashtag on Mastodon and X (formerly Twitter) is a good place for news and short questions, and general ranting.
  • The Big Book of R provides a comprehensive catalog of books on R (~350 different books across many topics).

If there’s a course, workshop, or conference you want to attend to improve these skills, speak with your supervisor, we can often support this. Dataquest provides high quality courses that help build data science and statistical skill sets. If you feel they would match your learning style and needs, discuss EHA purchasing a subscription for you with your supervisor.

25.1 Minimal reproducible examples - helping others help you

Minimal reproducible examples are small, self-contained code and data packets that will allow others to recreate the issue you are experiencing on their machine. The reprex package is really helpful for creating preformatted code for github, stackoverflow, or slack. This stackoverflow answer provides a succinct walk through of how to create a minimal reproducible example.