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The Data Visualization Workshop

You're reading from The Data Visualization Workshop A self-paced, practical approach to transforming your complex data into compelling, captivating graphics

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781800568846

Length 536 pages

Edition 1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Visualization

Authors (2):

Mario Döbler

Tim Großmann

View More author details

Table of Contents (9) Chapters

Preface

1. The Importance of Data Visualization and Data Exploration

2. All You Need to Know about Plots FREE CHAPTER

3. A Deep Dive into Matplotlib

4. Simplifying Visualizations Using Seaborn

5. Plotting Geospatial Data

6. Making Things Interactive with Bokeh

7. Combining What We Have Learned

Appendix

2. All You Need to Know about Plots

Overview

This chapter will teach you the fundamentals of the various types of plots such as line charts, bar charts, bubble plots, radar charts, and so on. For each plot type that we discuss, we will also describe best practices and use cases. The activities presented in this chapter will enable you to apply the knowledge gained. By the end of this chapter, you will be equipped with the important skill of identifying the best plot type for a given dataset and scenario.

You have been reading a chapter from

The Data Visualization Workshop

Published in: Jul 2020

Publisher: Packt

ISBN-13: 9781800568846

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Authors (2)

Mario Döbler

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.

See other products by Mario Döbler

Tim Großmann

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.

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