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        "\n# Plots with different scales\n\nTwo plots on the same Axes with different left and right scales.\n\nThe trick is to use *two different Axes* that share the same *x* axis.\nYou can use separate `matplotlib.ticker` formatters and locators as\ndesired since the two Axes are independent.\n\nSuch Axes are generated by calling the `.Axes.twinx` method. Likewise,\n`.Axes.twiny` is available to generate Axes that share a *y* axis but\nhave different top and bottom scales.\n"
      ]
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\n# Create some mock data\nt = np.arange(0.01, 10.0, 0.01)\ndata1 = np.exp(t)\ndata2 = np.sin(2 * np.pi * t)\n\nfig, ax1 = plt.subplots()\n\ncolor = 'tab:red'\nax1.set_xlabel('time (s)')\nax1.set_ylabel('exp', color=color)\nax1.plot(t, data1, color=color)\nax1.tick_params(axis='y', labelcolor=color)\n\nax2 = ax1.twinx()  # instantiate a second Axes that shares the same x-axis\n\ncolor = 'tab:blue'\nax2.set_ylabel('sin', color=color)  # we already handled the x-label with ax1\nax2.plot(t, data2, color=color)\nax2.tick_params(axis='y', labelcolor=color)\n\nfig.tight_layout()  # otherwise the right y-label is slightly clipped\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. admonition:: References\n\n   The use of the following functions, methods, classes and modules is shown\n   in this example:\n\n   - `matplotlib.axes.Axes.twinx` / `matplotlib.pyplot.twinx`\n   - `matplotlib.axes.Axes.twiny` / `matplotlib.pyplot.twiny`\n   - `matplotlib.axes.Axes.tick_params` / `matplotlib.pyplot.tick_params`\n\n.. tags::\n\n   component: axes\n   plot-type: line\n   level: beginner\n\n"
      ]
    }
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