{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Hexagonal binned plot\n\n`~.Axes.hexbin` is a 2D histogram plot, in which the bins are hexagons and\nthe color represents the number of data points within each bin.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\nn = 100_000\nx = np.random.standard_normal(n)\ny = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)\nxlim = x.min(), x.max()\nylim = y.min(), y.max()\n\nfig, (ax0, ax1) = plt.subplots(ncols=2, sharey=True, figsize=(9, 4))\n\nhb = ax0.hexbin(x, y, gridsize=50, cmap='inferno')\nax0.set(xlim=xlim, ylim=ylim)\nax0.set_title(\"Hexagon binning\")\ncb = fig.colorbar(hb, ax=ax0, label='counts')\n\nhb = ax1.hexbin(x, y, gridsize=50, bins='log', cmap='inferno')\nax1.set(xlim=xlim, ylim=ylim)\nax1.set_title(\"With a log color scale\")\ncb = fig.colorbar(hb, ax=ax1, label='counts')\n\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. tags:: plot-type: histogram, plot-type: hexbin, domain: statistics\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.hexbin` / `matplotlib.pyplot.hexbin`\n\n"
      ]
    }
  ],
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