Common mistakes & misleading dataviz

An dataviz journalist at The Economist is sharing useful common mistakes that ends up to misleading datavisualizations. Good tips in there!

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Another good guide for avoiding to lie with data by Flowing Data.

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A catalogue of Dataviz

This catalogue offers an overview of the main types of representations used to best visualize data. For each DataViz, tools and functions and similar charts are described (you will also find useful mini tutorials).Screenshot 2019-02-05 09.46.49

The fundamental Visual Variables

In its Semiology of Graphics, Jacques Bertin defined 7 visual variables that form the scope of any graphic system:

bertin_variables

 

  1. Place (position)
  2. Shape
  3. Size
  4. Value (light, size)
  5. Texture (within the shape)
  6. Hue
  7. Orientation (shape) /Direction (line)

 

DataViz Project

DataViz Project aims to present existing data visualizations in an exhaustive way and explains the structure of the data required to build them as well as give a series of examples related to each one.

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Why?

The Data Viz Project started out as an internal tool box, where we simply stuck data visualizations up on our wall as visual inspiration. Of course, there are a lot of books, websites, libraries, and tools that include a lot of visualization types, but not as comprehensive and logical as we liked. So instead of continuing to stick these visualizations on our wall, we thought we might as well just put it online, so you and others can use it as a tool and inspiration.

Who?

We are ferdio – an infographic and data visualization agency in Copenhagen. We transform data and information into captivating visuals. We add value to data and information by telling visual stories that inform and inspire.