Data visualization
Data visualization can be an effective way to get the 3 or 4 messages of your manuscript across very quickly. Owing to this though, data visualizations can be very tough to do well, and you can spend a lot of time messing with the small details.In general, try and keep things simple - what is the easiest and most convincing way to make your point?
Tables are really tough - when you have a table in mind, think in columns (most journals have 2-3 columns per page), and look at what the journal does in their previous publications
For figures, some guidance from Dr. Matthew Kay at the University of Michigan:
- Locality
- Order
- Layering
- Grids and synchronized axes
- Obey the pen
- Treat visual attributes like adjectives
- Color
From this article by data visualization journalist Rosamund Pierce
- Color palettes for various needs, including black/white printing and color blindness: link
- Another color palette called visibly
- Color Brewer: discrete color palettes
- The R Graph Gallery: thanks MS!
- Colorblindness testing: https://colororacle.org/
Some plotting tips: