This is the second of 10 posts where I’m listing tips for better charts. Please take a look at the first post where the project is discussed. These are my chart formatting tips: Use the right chart type for the data and the problem; Apply sound design
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This is the first in a series of 10 posts where I’ll suggest a (hopefully) coherent set of tips to improve our charts and, more important, to improve the way we make sense of the data. These are the planned posts: General charting; Formating; Column/Bar charts; Line
Read more →The relevance principle means that every variation should carry a meaning, derived from data variation, not from design variation. If it doesn’t, it can be confusing or misleading. Suppose chart A displays population density by country. “Vary colors by point” is an option in Excel, but why
Read more →How to create better charts? Search the web and you’ll find many specific advices, not always backed up by scientific evidence (can there be any?). Tufte’s advices are great for us, rational, positivist members of the human race, but what about those emotional poor fellows for whom
Read more →Scatterplots are not used by the NY Times because readers simply can’t make sense of them. Don’t oversimplify, but don’t assume that your audience can read a complex chart. Know your audience, and if possible test your charts with a small sample. Know what they expect, deliver
Read more →Suppose you are sharing a list of orders with some co-workers. One of them wants to see the higher sales orders [list]. Another one wants to know how much was exported to France [table]. The next one needs the average items per order [descriptive statistics]. You want
Read more →A chart is just one of the available tools to communicate and help you and your audience to understand the data; sometimes using a chart is just plain wrong: if variation seems random or non-existent, what’s the point of displaying the data graphically (yes, I know, sometimes
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