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[2/x] Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks (Data column)

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Continue. first I will tell you about the two remaining chapters of the first part about the basic principles of visualization.

The second chapter contains five tips for improving visualizations. 1) Show the data In order for the audience to better capture the meaning of visualization, we need to show the data, not necessarily show all the data, but the data that highlights your message should be on the visualization. 2) Reduce the clutter Visualization should contain only the necessary elements, the rest should be removed so as not to distract attention. Conventionally, it is rare that unnecessary design elements or 3D versions of charts are useful, even if they are in Excel. 3) Integrate the graphic and text The author gives several tips at once.

  • It is better to remove a separate legend and integrate it directly into the schedule - but in practice, the legend is often removed and the chart does not give any clues how to read it. Write a headline for visualization that resembles a newspaper one and speaks directly about the main idea of visualization. Add explanatory elements to key visualization locations (For example, comments on top of peaks and dips in a conventional linear graph) 4) Avoid the spaghetti chart Even if there is a lot of information, you do not need to dump it on one visualization. You can make several separate visualizations that highlight the question from different sides. But if we do that, then we need to make visualizations similar so that they're easy to navigate. 5) Start with gray The author suggests starting with the gray version of the chart, and adding colors later to highlight the main points At the same time, the author talks about the types of data: qualitative and quantitative, where there are discrete and continuous, which can be interval or maintain relationships. Understanding the type of data is very important for proper visualization.

The last chapter is called “Form and Function” and contains a subtitle that contains the key to successful visualization.

Let you audience's needs drive your data visualization choices The form can be static and interactive, while the function is explanatory and exploratory. The book is more about static and explanatory visualizations, but other types can be effective for their purposes. For example, before. (into 1997 year) There was a mantra working with visualizations of the species. Overview first, zoom and filter, then details-on-demand But now the approach has changed and in the era of mobile first we have changed to scrolling on the run, which means you need to have time to communicate the main idea immediately. And only if something spectacular happens, then people are ready to do something other than scroll:) This should be taken into account to build effective visualizations.

Continue review of the book in the following posts.

P.S. I’ve written about visualizations before:

Well, scientifically popular books on statistics (More scientific books on statistics are not about visualization, but about mathematics.)

#Data #Visualization #Patterns #Leadership