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Author Archives: richardbrath
The Origin of Thematic Maps — and the problem with base maps
Why is there such a big gap between thematic maps and label maps? Both types of maps show data about places. Thematic maps typically use lots of color to show data about places; whereas label maps use a lot of … Continue reading
Top NY Picks: Me vs. Reviews
I have a few upcoming speaking appearances, including the International Cartography Conference (DC July 6); Information Visualization 2017 (London July 13) and Strata Data Conference (NYC Sept 26-28). Since NYC is a city I often visit, I thought I’d make … Continue reading
Posted in Alphanumeric Chart, Data Visualization
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50 categoric colors, inspired by telephone wires
Using colors to represent different categories of data is challenging to scale past ten unique colors. Many authors and researchers recommend against it. Colobrewer2 doesn’t go past 12 unique colors. D3.js offers three variants of color scales with 20 unique colors. … Continue reading
Readability
Readability and what it means for data visualization Type can be legible, but still unreadable. Consider this image: Beautiful Helvetica, mirrored and rotated 180 degrees. Two highly common words from the English language. Letters are perfectly legible and even turn … Continue reading
The 19 Dimensional Word Cloud of Pokémon
If you want to catch all 719 Pokémon, the serious gamer needs to know their different skills and abilities. At a high-level, Pokémon classify into 18 different types, such as fire, water or grass. For example, Pikachu is an electric type, Charmander … Continue reading
Posted in Data Visualization, Pokemon, Text Visualization
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Papers, Rejections and Critiques
There have been a few recent blog posts after VisWeek about paper rejections such as Niklas’ Elmqvist’s Dealing with Rejection and Robert Kosara’s related Dealing with Paper Rejections. Rejections are certainly a painful part of the academic review process I’ve … Continue reading
Microtext Line Charts
Sometimes a line chart needs to display a lot of lines. Instead of splitting into a grid of charts, consider replacing the lines with text. Continue reading
Posted in Alphanumeric Chart, Data Visualization, Line Chart, Microtext
Tagged dataviz
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