Does your workflow look anything like this?
- Receive data
- Import data to SPSS
- Do data cleaning and analysis in SPSS
- Export data to Excel
- Make figures in Excel
- Copy figures from Excel to Word
- Write your report
This, or some slight variation on it, is the workflow than many of us in evaluation use. It’s mostly fine … until it’s not.
Has this ever happened to you? You go through steps one through seven, only to realize that you made a mistake at step three. So, you have to go back to SPSS, redo your analysis, export your data to Excel, make your figures again, and copy them again to Word.
It feels kind of like rolling up a ball of yarn, only to realize you made a mistake along the way that requires you to unroll the ball and then roll it back up again.
In your re-rolling of that ball of yarn, have you ever wondered if there’s a better way? There is. It’s called RMarkdown.
RMarkdown is the tool that you never knew you needed, but once you learn it, you’ll wonder how you ever lived without it. It’s one of the best reasons to learn R.
The basic idea behind RMarkdown is that your data import, cleaning, analysis, visualization all happens in one document, alongside your narrative text. When you’re ready, you export (also known as “knitting”) your RMarkdown document to other formats (Word documents, for example) that you can then share with others.
Here’s a quick example of what this looks like in practice.
As I’ve been designingworkshops, online courses, and custom trainings, I always include the use of RMarkdown. I want people to develop workflows that are more efficient, more accurate (I didn’t even go into the possibility for copy-paste errors in the workflow above!), and less frustrating. R is a fantastic tool for doing that.
I don’t want you to ever have to roll that ball of yarn twice.