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Data Display

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An Introduction to Statistics with Python

Part of the book series: Statistics and Computing ((SCO))

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Abstract

This chapter presents the basic concepts of plotting in Python. It also provides help in turning Python plots into good-looking figures for presentations. Examples of different 2D and 3D plot types provide the first look into the capabilities of the plotting package matplotlib. The most important display types for statistical data are explained (histograms, KDE-plots, distribution functions, and boxplots) as well as their relation to each other. A special module helps with the generation of interactive plots, and the exact positioning of plots on the computer screen.

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Notes

  1. 1.

    Depending on your build of Python, this command may also be %matplotlib tk.

  2. 2.

    <ISP2e> /04_DataDisplay/gettingStarted/ISP_gettingStarted.py.

  3. 3.

    <ISP2e> /04_DataDisplay/interactivePlots/ISP_interactive_plots.py.

  4. 4.

    <ISP2e> /code_quantlets/04_DataDisplay/ISP_showPlots.py.

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Authors and Affiliations

  1. School of Medical Engineering and Applied Social Sciences, University of Applied Sciences Upper Austria, Linz, Austria

    Thomas Haslwanter

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  1. Thomas Haslwanter
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Correspondence to Thomas Haslwanter .

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Cite this chapter

Haslwanter, T. (2022). Data Display. In: An Introduction to Statistics with Python. Statistics and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-97371-1_4

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