When you are stuck

Look for information

1. Read carefully any error message
2. Read the documentation (local or online)
3. Make sure you have up-to-date versions
4. Google (using carefully selected keywords or the error message)
5. Look for open issues & bug reports

Error messages

Read them!

Familiarise yourself with the error types in the languages you use

Warnings ≠ errors

Look for bits you understand (don’t get put off by what you don’t understand)

Identify the locations of the errors to go investigate that part of the code

Documentation

Finding documentation

Up-to-date versions

Google

Google’s algorithms are great at guessing what we are looking for.

Open issues & bug reports

If the tool you are using is open source, look for issues matching your problem in the source repository (e.g. on GitHub or GitLab).

What if the answer isn’t out there?

When everything has failed & you have to ask for help, you need to know:

Where to ask

Q&A sites

Mostly, Stack Overflow & the Stack Exchange network.

Co-founded in 2008 & 2009 by Jeff Atwood & Joel Spolsky.

Forums

Mostly, Discourse.

Co-founded in 2013 by Jeff Atwood, Robin Ward & Sam Saffron.

A few other older forums.

Where to ask

Which one to choose is a matter of personal preference.

Possible considerations:

• Some niche topics have very active communities on Discourse
• Stack Overflow & some older forums can be intimidating with higher expectations for the questions quality & a more direct handling of mistakes
• For conversations, advice, or multiple step questions, go to Discourse
• Stack Overflow has over 13 million users
• Stack Overflow & co have a very efficient approach

Stack Overflow & co

Pick the best site to ask your question.

A few of the Stack Exchange network sites:

Stack Overflow: programming
Super User: computer hardware & software
Unix & Linux: *nix OS TEX: TeX/LaTeX
Cross Validated: stats; data mining, collecting, analysis & visualization; ML
Data Science: focus on implementation & processes
Open Data
GIS

How to ask

How to ask: SO & co

Formatting your question

Nowadays, most sites (including Stack Overflow & Discourse) allow markdown rendering.

Some older forums implement other markup languages (e.g. BBCode).

The information is always easy to find. Spend the time to format your question properly. People will be much less inclined to help you if you don’t show any effort & if your question is a nightmare to read.

Example of a typical downvoted question

Code:

howdy!!
i am new to R sorry for a very silly question.i looked all oever the itnernwet, but i dint find
anyanswer. i tried to use ggplot i get the error: Error in loadNamespace(i, c(lib.loc, .libPaths()),
versionCheck = vI[[i]]) : there is no package called 'stringi'
thank youu very much!!!!!
marie

Rendered output:

Same question, fixed

When I try to load the package `ggplot2` with:

```{r}
library(ggplot2)
```
I get the error:

> Error in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]) :
there is no package called 'stringi'

What am I doing wrong?

Still not good enough

This question is actually a duplicate of a question asked which is itself a duplicate of another question.

Creating a minimal reproducible example

There are great posts on how to create a good minimal reproducible example. In particular:

How to create a Minimal, Reproducible Example

For R (but concepts apply to any language):

How to make a great R reproducible example
What’s a reproducible example (reprex) and how do I do one?

Creating a minimal reproducible example

• Load all necessary packages
• Load or create necessary data
• Simplify the data & the code as much as possible while still reproducing the problem
• Use simple variable names

Data for your example: your own data

Do not upload data somewhere on the web to be downloaded.

Make sure that the data is anonymised.

Don’t keep more variables & more data points than are necessary to reproduce the problem.

Simplify the variable names.

In R, you can use functions such as dput() to turn your reduced, anonymised data into text that is easy to copy/paste & can then be used to recreate the data.

Data for your example: create a toy dataset

You can also create a toy dataset.

Functions that create random data, series, or repetitions are very useful here.

Data for your example: pre-packaged datasets

Some languages/packages come with pre-packaged datasets. If your code involves such languages/packages, you can make use of these datasets to create your reproducible example.

For example, R comes with many datasets directly available, including iris, mtcars, trees, airquality. In the R console, try:

?iris
?mtcars

Additional considerations

Even if you always find answers to your questions without having to post yourself, consider signing up to these sites:

• It allows you to upvote (SO/SE) or like (Discourse) the questions & answers that help you—and why not thank in this fashion those that are making your life easier?

• It makes you a part of these communities.

• Once you are signed up, maybe you will start being more involved & contribute with questions & answers of your own.

A last word

While it takes some work to ask a good question, do not let this discourage you from posting on Stack Overflow: if you ask a good question, you will get many great answers.

You will learn in the process of developing your question (you may actually find the answer in that process) & you will learn from the answers.

It is forth the effort.

Here is the Stack Overflow documentation on how to ask a good question.