4 ms·
Eh, the article title should actually be just "how to pick more beautiful colours" period, since it talks very little about actually choosing colours for data v
by andrepd 6y ago
Eh, the article title should actually be just "how to pick more beautiful colours" period, since it talks very little about actually choosing colours for data visualisation, that is, how to choose a visual presentation that helps make sense of the data you're showing. Example: https://colorbrewer2.org/ https://colorbrewer2.org/
- gerbler 6y agoI completely agree - this is almost entirely around visual presentation (which is subjective) and not around practical limitations for color choice. I'm a big fan of colorbrewer to help make these choices for me!
- jeffbee 6y agoFor visualizations you will probably reach for a convenient palette already provided by your software, like https://ggplot2.tidyverse.org/reference/scale_brewer.html https://ggplot2.tidyverse.org/reference/scale_brewer.html or https://observablehq.com/@d3/color-schemes https://observablehq.com/@d3/color-schemes.
- JadeNB 6y agoFor some reason the HN title, which was originally the actual title, has been changed to "Common color mistakes and how to avoid them", which seems weird. The actual title ("How to pick more beautiful colors for your data visualizations") doesn't seem clickbait-y, so why take the subtitle instead?