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      "cell_type": "markdown",
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      "source": [
        "\n# Grouped bar chart with labels\n\nThis example shows a how to create a grouped bar chart and how to annotate\nbars with labels.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "# data from https://allisonhorst.github.io/palmerpenguins/\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nspecies = (\"Adelie\", \"Chinstrap\", \"Gentoo\")\npenguin_means = {\n    'Bill Depth': (18.35, 18.43, 14.98),\n    'Bill Length': (38.79, 48.83, 47.50),\n    'Flipper Length': (189.95, 195.82, 217.19),\n}\n\nx = np.arange(len(species))  # the label locations\nwidth = 0.25  # the width of the bars\nmultiplier = 0\n\nfig, ax = plt.subplots(layout='constrained')\n\nfor attribute, measurement in penguin_means.items():\n    offset = width * multiplier\n    rects = ax.bar(x + offset, measurement, width, label=attribute)\n    ax.bar_label(rects, padding=3)\n    multiplier += 1\n\n# Add some text for labels, title and custom x-axis tick labels, etc.\nax.set_ylabel('Length (mm)')\nax.set_title('Penguin attributes by species')\nax.set_xticks(x + width, species)\nax.legend(loc='upper left', ncols=3)\nax.set_ylim(0, 250)\n\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.bar` / `matplotlib.pyplot.bar`\n   - `matplotlib.axes.Axes.bar_label` / `matplotlib.pyplot.bar_label`\n\n.. tags::\n\n   component: label\n   plot-type: bar\n   level: beginner\n\n"
      ]
    }
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