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Applied Data Science with Python and Jupyter

You're reading from   Applied Data Science with Python and Jupyter Use powerful industry-standard tools to unlock new, actionable insights from your data

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Product type Paperback
Published in Oct 2018
Publisher
ISBN-13 9781789958171
Length 192 pages
Edition 1st Edition
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Author (1):
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Alex Galea Alex Galea
Author Profile Icon Alex Galea
Alex Galea
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Toc

Interactive Visualizations


Visualizations are quite useful as a means of extracting information from a dataset. For example, with a bar graph it's very easy to distinguish the value distribution, compared to looking at the values in a table. Of course, as we have seen earlier in this book, they can be used to study patterns in the dataset that would otherwise be quite difficult to identify. Furthermore, they can be used to help explain a dataset to an unfamiliar party. If included in a blog post, for example, they can boost reader interest levels and be used to break up blocks of text.

When thinking about interactive visualizations, the benefits are similar to static visualizations, but enhanced because they allow for active exploration on the viewer's part. Not only do they allow the viewer to answer questions they may have about the data, they also think of new questions while exploring. This can benefit a separate party such as a blog reader or co-worker, but also a creator, as it allows...

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