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A few days ago on the internet, I stumbled upon a person who criticized what I took for granted: The W3C Accessibility Guidelines (WCAG) for color contrast. If you’ve been choosing colors and you or your organization cares about accessibility, you’ve seen the infinite number of color contrast checkers — 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, etc. They all answer the question: “Which color should your text
This is part 1 of a series on “Which color scale to use when visualizing data” (Part 2 / Part 3 / Part 4). If you already have a good understanding of color scales, skip to the end of this article, “It’s not as clear-cut as it seems”. When visualizing data, you’re almost always working with color – e.g., with different hues (red, yellow, blue) for categories or color gradients (light blue, medium
They’re different. The red that Nadieh uses ⬤ is different from your typical red ⬤. The green ⬤ is… can you even call it a green ⬤? So before we impose rules that limit us, let me freak you out a bit: There are thousands of colors you can use. There is yellow-ish red ⬤ and blue-ish red ⬤ and everything in between. There is gray ⬤, but there is also cold gray ⬤ and there is warm gray ⬤. And then th
Data Visualisation can be defined as representing numbers with shapes – and no matter what these shapes look like (areas, lines, dots), they need to have a color. Sometimes colors just make the shapes visible, sometimes they encode data or categories themselves. We’ll focus mostly on the latter in this article. But we’ll also take a general look at colors and what to consider when choosing them: W
Product Product Datawrapper lets you show your data as beautiful charts, maps or tables with a few clicks. Find out more about all the available visualization types.
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