Uncharted

What to consider when choosing colors for race, ethnicity, and world regions

Data on race and ethnicity is often important. (Especially U.S.) newsrooms, NGOs, and others should and will use data to show that racism exists — until the day it doesn’t. But just as with data visualizations on gender, visualizations of race can come with subconscious biases and even reinforce racist stereotypes. This article explains what to keep in mind when choosing colors for a visualization with racial categories – so that all readers feel respected.

https://pixelfed.zoo-logique.org/storage/m/_v2/578583396227231930/19c3981d1-f52fd9/8GWvlkhEPJ4J/Ij6RHFkF9Uy2p7s54XedzdLIOTQZxKPChVrWn3Ui.png https://pixelfed.zoo-logique.org/storage/m/_v2/578583396227231930/19c3981d1-f52fd9/EipINZMalKZL/wjY0tLg04Vkhj6ERG3d6nQhcoq4HBJG4cG6Cjqyl.png https://pixelfed.zoo-logique.org/storage/m/_v2/578583396227231930/19c3981d1-f52fd9/tnp75NRExA5B/auQG3jUPkfz7dZpBdl9k8b88thidNYEwngzb2gnB.png

▻https://blog.datawrapper.de/colors-for-race-ethnicity-world-regions
via @fil

#stéréotypes #couleurs #visualisation #cartographie #couleur_de_peau

How to choose an interpolation for your color scale - Datawrapper Blog
▻https://blog.datawrapper.de/interpolation-for-color-scales-and-maps

https://blog.datawrapper.de/wp-content/uploads/2022/07/Artboard-46-copy-2.png

Which interpolation you choose for your color scale has a massive impact on how the data is perceived, how well your statement is communicated, and how intuitively the reader understands the data.
“Interpolation? What’s that?” you might ask. It’s a method to assign each of your data values to a certain color. In Datawrapper, you can choose an interpolation for both stepped (classed) and continuous (unclassed) color scales. (If you’re not sure which type of scale to use, visit our article When to use classed and when to use unclassed color scales.)
In this article, we focus on the effect of interpolations on choropleth maps like the one above — but you can also use classed and unclassed color scales for symbol maps, heat maps, and wherever else you’re trying to map data to a color gradient.

#discrétisation #palette_de_couleurs #échelle_de_couleurs
revue d’ensemble avec visualisation des résultats de chaque choix

note : tout logiciel de #cartographie digne de ce nom contient un module permettant d’opérer ce paramétrage.

Exemple ci-dessous : Magrit

https://i.imgur.com/eJqmxCO.png

How to pick more beautiful colors for your data visualizations | Chartable

▻https://blog.datawrapper.de/beautifulcolors/index.html

https://blog.datawrapper.de/img/200805_goodcolors34.png

Choosing good colors for your charts is hard. This article tries to make it easier.

I want you to feel more confident in your color choices. And if you have no sense for colors at all, here’s my attempt to help you find good ones anyway. We’ll talk about common color mistakes I see out there in the wild, and how to avoid them.

This is not the right article for you if you’re trying to find good gradients or shades. But if you need to find beautiful, distinctive colors for different categories (e.g. continents, industries, bird species) for your line charts, pie charts, stacked bar charts, etc., read on.

#couleur #sémiologie #cartoexperiment

What to consider when creating choropleth maps | Uncharted

▻https://blog.datawrapper.de/choroplethmaps/index.html

https://blog.datawrapper.de/img/180320_choropleth-f.png

What to consider when creating choropleth maps

Maps are not objective, but a version of reality. When creating them, lots of choices are made: What to map, how to map and whether or not to use a map in the first place. Here we’ll try to find guidelines to all of these questions, for a specific subset of maps: Choropleth maps (the ones in which each region is filled with a color that represents a value).

#cartographie #sémiologie #couleur #méthodologie

One map, 500 cities | Uncharted

▻https://blog.datawrapper.de/weekly-chart-cities/index.html

https://blog.datawrapper.de/img/weeklycharts/016.png

One map, 500 cities

After publishing the cartogram world map last week, I had to notice that we’ve never featured one specific map type in the Weekly Charts: the symbol map. Of course that had to change. So this week, I’ll present you yet another world map:

#urban_matter #urbanisation #villes #agglomérations #population #démographie

I’m surrounded by old people | Uncharted
▻https://blog.datawrapper.de/weekly-chart-old-people/index.html

https://blog.datawrapper.de/img/weeklycharts/001.png

Let’s talk about age. Age demographics give me great joy (just look at population pyramids. They’re amazing!), so I wikiprocrastinate my way sometimes through articles and lists of life expectancy and other delicates. And there I was, this morning, looking at a list of countries ranked by their median age – and I couldn’t believe my eyes. I decided to make a chart out of it, so that my eyes can get used to that shocking fact:

#population #démographie #âge_médian #vieillesse #vieux