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Two sets of data:

Two y axis. In the above example, we import matplotlib.pyplot and numpylibrary. Many functions specific to visual calculations have an optional axis parameter, which influences how the visual. This allows you to plot two different data sets with different scales on the same graph, making it easier to see.

To add more axes to a chart, you must specify the yaxisid option in the datas.datasets property, and configure. Create the x values using the np.linspace method (refer this ). This matplotlib tutorial shows how to create a plot with two y axes (two different scales):

You can easily get x with logscale using semilogx. It is important to understand the relationship between. For this, we have to use the grid()method with the axes object of the plot to which we want to create grid lines.

Before we can format dual. You can specify styles as a positional argument after the data. Axis determines how the calculation is evaluated.

Customizing visualizations with dual y axes. Combo charts are a good example. You can either add the secondary axes after.

Some visualizations can benefit from having two y axes.

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