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2019 | OriginalPaper | Chapter

6. Data Visualization

Author : Ervin Varga

Published in: Practical Data Science with Python 3

Publisher: Apress

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Abstract

Visualization is a powerful method to gain more insight about data and underlying processes. It is extensively used during the exploration phase to attain a better sense of how data is structured. Visual presentation of results is also an effective way to convey the key findings; people usually grasp nice and informative diagrams much easier than they grasp facts embedded in convoluted tabular form. Of course, this doesn’t mean that visualization should replace other approaches; the best effect is achieved by judiciously combining multiple ways to describe data and outcomes. The topic of visualization itself is very broad, so this chapter focuses on two aspects that are not commonly discussed elsewhere: how visualization may help in optimizing applications, and how to create dynamic dashboards for high-velocity data. You can find examples of other uses throughout this book.

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Footnotes
1
A box’s size is commensurate to the cumulative time of the given method. This allows you to easily spot critical parts in your program. Don’t forget that profiling adds some overhead.
 
Metadata
Title
Data Visualization
Author
Ervin Varga
Copyright Year
2019
Publisher
Apress
DOI
https://doi.org/10.1007/978-1-4842-4859-1_6

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