{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Box plots with custom fill colors\n\nTo color each box of a box plot individually:\n\n1) use the keyword argument ``patch_artist=True`` to create filled boxes.\n2) loop through the created boxes and adapt their color.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nnp.random.seed(19680801)\nfruit_weights = [\n    np.random.normal(130, 10, size=100),\n    np.random.normal(125, 20, size=100),\n    np.random.normal(120, 30, size=100),\n]\nlabels = ['peaches', 'oranges', 'tomatoes']\ncolors = ['peachpuff', 'orange', 'tomato']\n\nfig, ax = plt.subplots()\nax.set_ylabel('fruit weight (g)')\n\nbplot = ax.boxplot(fruit_weights,\n                   patch_artist=True,  # fill with color\n                   tick_labels=labels)  # will be used to label x-ticks\n\n# fill with colors\nfor patch, color in zip(bplot['boxes'], colors):\n    patch.set_facecolor(color)\n\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. tags:: styling: color, domain: statistics, plot-type: boxplot\n\n.. 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.boxplot` / `matplotlib.pyplot.boxplot`\n\n"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.13.2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}