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        "%matplotlib inline"
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      "source": [
        "# Errorbar\n\nDemo of errorbar function with different ways of specifying error bars.\n\nErrors can be specified as a constant value (as shown in ``errorbar_demo.py``),\nor as demonstrated in this example, they can be specified by an ``N x 1`` or ``2 x N``,\nwhere ``N`` is the number of data points.\n\n**N x 1**:\n    Error varies for each point, but the error values are symmetric (i.e. the\n    lower and upper values are equal).\n\n**2 x N**:\n    Error varies for each point, and the lower and upper limits (in that order)\n    are different (asymmetric case)\n\nIn addition, this example demonstrates how to use log scale with errorbar.\n"
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    {
      "cell_type": "code",
      "execution_count": null,
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      "source": [
        "import numpy as np\nimport matplotlib.pyplot as plt\n\n# example data\nx = np.arange(0.1, 4, 0.5)\ny = np.exp(-x)\n\n# example error bar values that vary with x-position\nerror = 0.1 + 0.2 * x\n\n# error bar values w/ different -/+ errors\nlower_error = 0.4 * error\nupper_error = error\nasymmetric_error = [lower_error, upper_error]\n\nfig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True)\nax0.errorbar(x, y, yerr=error, fmt=\"-o\")\nax0.set_title(\"variable, symmetric error\")\n\nax1.errorbar(x, y, xerr=asymmetric_error, fmt=\"o\")\nax1.set_title(\"variable, asymmetric error\")\nax1.set_yscale(\"log\")\nplt.show()"
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