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Python Data Visualization Cookbook by Igor Milovanović

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Making errorbars

Error bars are useful to display the dispersion of data on a plot. They are relatively simple as a form of visualization; however, they are also a bit problematic because what is shown as an error varies across different sciences and publications. This does not lessen the usefulness of error bars, it just imposes the need to always be careful and explicitly state the nature of the error visualized as an error bar.

Getting ready

To be able to plot an error bar in the raw observed data, we need to compute the mean and the error we want to display.

The error we compute represents the 95 percent confidence interval that the mean we get from our observation is stable, which means our observations are good estimates of the whole population. ...

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