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Mastering Matplotlib

Mastering Matplotlib

By : Duncan M. McGreggor, Duncan M McGreggor
3.5 (8)
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Mastering Matplotlib

Mastering Matplotlib

3.5 (8)
By: Duncan M. McGreggor, Duncan M McGreggor

Overview of this book

If you are a scientist, programmer, software engineer, or student who has working knowledge of matplotlib and now want to extend your usage of matplotlib to plot complex graphs and charts and handle large datasets, then this book is for you.
Table of Contents (11 chapters)
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10
Index

Big data


The term "big data" is semantically ambiguous due to the varying contexts to which it is applied and the motivations of the users applying it. The first question that may have occurred to you on seeing this chapter's title is "how is this applicable to matplotlib or even plotting in general?" Before we answer this question though, let's establish a working definition of big data.

The Wikipedia article on big data opens with the following informal definition:

"Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate."

This description is honest, as it admits that the definition is imprecise. It also implies that the definition may change given the differing contexts. The words large and complex are relative, and the term traditional data processing is not going to mean the same thing in different segments of the industry. In fact, different departments in a single organization may have widely varying data processing "traditions...

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