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Data Visualization with Python and JavaScript by Kyran Dale

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Chapter 14. Imagining a Nobel Visualization

In Chapter 13, we explored the Nobel Prize dataset, looking for interesting stories to tell based on aspects of the data that should engage and educate. We found some interesting nuggets, among them:

  • Maria Goeppert, the only female physicist other than Marie Curie to win a Physics Nobel

  • The post-WWII surge of American Nobels, passing the declining tallies of the three biggest European winners, the UK, Germany, and France

  • The difference in continental prize distributions

  • The dominance of the Scandinavian countries when prize tallies are adjusted for population size

These and a number of other narratives require particular types of visualization. Comparison of Nobel Prize numbers by nation is probably best achieved by means of a conventional bar chart, whereas geographic prize distributions demand a map. In this chapter we will try to design a modern, interactive visualization that incorporates some of the key stories we discovered while exploring the dataset.

Who Is It For?

The first consideration when imagining a visualization is its target audience. A visualization intended for display in a gallery or museum will likely be very different from one intended for an in-house dashboard, even though they could use the same dataset. The Nobel Prize visualization anticipated for this book has as its chief constraint that it teach a key subset of D3 and the JavaScript needed to create a modern interactive web visualization. It is ...

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