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You're reading from  The Data Visualization Workshop

Product typeBook
Published inJul 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781800568846
Edition1st Edition
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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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Summary

This chapter covered the most important visualizations, categorized into comparison, relation, composition, distribution, and geological plots. For each plot, a description, practical examples, and design practices were given. Comparison plots, such as line charts, bar charts, and radar charts, are well suited to comparing multiple variables or variables over time. Relation plots are perfectly suited to show relationships between variables. Scatter plots, bubble plots, which are an extension of scatter plots, correlograms, and heatmaps were considered.

Composition plots are ideal if you need to think about something as part of a whole. We first covered pie charts and continued with stacked bar charts, stacked area charts, and Venn diagrams. For distribution plots that give a deep insight into how your data is distributed, histograms, density plots, box plots, and violin plots were considered. Regarding geospatial data, we discussed dot maps, connection maps, and choropleth...

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The Data Visualization Workshop
Published in: Jul 2020Publisher: PacktISBN-13: 9781800568846
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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