getting-help.Rmd

# Getting Help {#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](https://support.profoundcloud.com/home))

Also, outside EHA:

-   There's an almost-monthly [NYC R Meetup](https://www.meetup.com/nyhackr/)
    and even rarer [Data Visualization Meetup](https://www.meetup.com/DataVisualization/) that EHA members sometimes attend.
-   There's also an [R-Ladies NYC chapter](http://www.rladiesnyc.org/) that has
    regular meetups and a Slack Chat room. [WiMLDS](http://wimlds.org/chapters/about-nyc/) 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](https://stackoverflow.com/questions/tagged/r?sort=newest&pagesize=50).
-   [R-Weekly](https://rweekly.org/) publishes a useful weekly newsletter on new
    R developments, packages, and publications.
-   The [\#rstats hashtag](https://twitter.com/hashtag/rstats) on Mastodon and X (formerly Twitter) is a
    good place for news and short questions, and general ranting.
-   The [Big Book of R](https://www.bigbookofr.com/) 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](https://www.dataquest.io/) 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.

## 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](https://reprex.tidyverse.org/articles/articles/learn-reprex.html) is
really helpful for creating preformatted code for github, stackoverflow, or slack. 
This [stackoverflow answer](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) provides a succinct walk through of how to create a 
minimal reproducible example.