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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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Basic Plots

In this section, we are going to go through the different types of simple plots. This includes bar charts, pie charts, stacked bar, and area charts, histograms, box plots, scatter plots and bubble plots. Please refer to the previous chapter to get more details about these plots. More sophisticated plots, such as violin plots, will be covered in the next chapter, using Seaborn instead of Matplotlib.

Bar Chart

The plt.bar(x, height, [width]) creates a vertical bar plot. For horizontal bars, use the plt.barh() function.

Important parameters:

  • x: Specifies the x coordinates of the bars
  • height: Specifies the height of the bars
  • width (optional): Specifies the width of all bars; the default is 0.8

Example:

plt.bar(['A', 'B', 'C', 'D'], [20, 25, 40, 10])

The preceding code creates a bar plot, as shown in the following diagram:

Figure 3.16: A simple bar chart

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

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