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You're reading from  The Data Visualization Workshop

Product typeBook
Published inJul 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781800568846
Edition1st Edition
Languages
Python
Tools
Jupyter
Concepts
Data Visualization
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Authors (2):
Mario Döbler
Mario Döbler
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Mario Döbler

Mario Döbler is a Ph.D. student with a focus on deep learning at the University of Stuttgart. He previously interned at the Bosch Center for artificial intelligence in the Silicon Valley in the field of deep learning. He used state-of-the-art algorithms to develop cutting-edge products. In his master thesis, he dedicated himself to applying deep learning to medical data to drive medical applications.
Read more about Mario Döbler

Tim Großmann
Tim Großmann
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Tim Großmann

Tim Großmann is a computer scientist with interest in diverse topics, ranging from AI and IoT to Security. He previously worked in the field of big data engineering at the Bosch Center for Artificial Intelligence in Silicon Valley. In addition to that, he worked on an Eclipse project for IoT device abstractions in Singapore. He's highly involved in several open-source projects and actively speaks at tech meetups and conferences about his projects and experiences.
Read more about Tim Großmann

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Introduction

In the previous chapter, we took an in-depth look at Matplotlib, one of the most popular plotting libraries for Python. Various plot types were covered, and we looked into customizing plots to create aesthetic plots.

Unlike Matplotlib, Seaborn is not a standalone Python library. It is built on top of Matplotlib and provides a higher-level abstraction to make visually appealing statistical visualizations. A neat feature of Seaborn is the ability to integrate with DataFrames from the pandas library.

With Seaborn, we attempt to make visualization a central part of data exploration and understanding. Internally, Seaborn operates on DataFrames and arrays that contain the complete dataset. This enables it to perform semantic mappings and statistical aggregations that are essential for displaying informative visualizations. Seaborn can also be used to simply change the style and appearance of Matplotlib visualizations.

The most prominent features of Seaborn are as follows...

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The Data Visualization Workshop
Published in: Jul 2020Publisher: PacktISBN-13: 9781800568846
© 2020 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
Mario Döbler

Mario Döbler is a Ph.D. student with a focus on deep learning at the University of Stuttgart. He previously interned at the Bosch Center for artificial intelligence in the Silicon Valley in the field of deep learning. He used state-of-the-art algorithms to develop cutting-edge products. In his master thesis, he dedicated himself to applying deep learning to medical data to drive medical applications.
Read more about Mario Döbler

author image
Tim Großmann

Tim Großmann is a computer scientist with interest in diverse topics, ranging from AI and IoT to Security. He previously worked in the field of big data engineering at the Bosch Center for Artificial Intelligence in Silicon Valley. In addition to that, he worked on an Eclipse project for IoT device abstractions in Singapore. He's highly involved in several open-source projects and actively speaks at tech meetups and conferences about his projects and experiences.
Read more about Tim Großmann

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