{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Create 3D histogram of 2D data\n\nDemo of a histogram for 2D data as a bar graph in 3D.\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\n\nfig = plt.figure()\nax = fig.add_subplot(projection='3d')\nx, y = np.random.rand(2, 100) * 4\nhist, xedges, yedges = np.histogram2d(x, y, bins=4, range=[[0, 4], [0, 4]])\n\n# Construct arrays for the anchor positions of the 16 bars.\nxpos, ypos = np.meshgrid(xedges[:-1] + 0.25, yedges[:-1] + 0.25, indexing=\"ij\")\nxpos = xpos.ravel()\nypos = ypos.ravel()\nzpos = 0\n\n# Construct arrays with the dimensions for the 16 bars.\ndx = dy = 0.5 * np.ones_like(zpos)\ndz = hist.ravel()\n\nax.bar3d(xpos, ypos, zpos, dx, dy, dz, zsort='average')\n\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. tags::\n   plot-type: 3D, plot-type: histogram,\n   level: beginner\n\n"
      ]
    }
  ],
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      "display_name": "Python 3",
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      "file_extension": ".py",
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