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<h1>Create 3D histogram of 2D data<a class="headerlink" href="#create-3d-histogram-of-2d-data" title="Permalink to this headline">¶</a></h1>

Demo of a histogram for 2 dimensional data as a bar graph in 3D.

<div class="highlight-python notranslate"><div class="highlight"><pre>from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

# Fixing random state for reproducibility

<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.seed.html#numpy.random.seed" title="View documentation for numpy.random.seed">np.random.seed</a>(19680801)

fig = <a href="../../api/_as_gen/matplotlib.pyplot.figure.html#matplotlib.pyplot.figure" title="View documentation for matplotlib.pyplot.figure">plt.figure</a>()

ax = fig.add_subplot(111, projection='3d')

x, y = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.rand.html#numpy.random.rand" title="View documentation for numpy.random.rand">np.random.rand</a>(2, 100) * 4

hist, xedges, yedges = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html#numpy.histogram2d" title="View documentation for numpy.histogram2d">np.histogram2d</a>(x, y, bins=4, range=[[0, 4], [0, 4]])

# Construct arrays for the anchor positions of the 16 bars.

# Note: np.meshgrid gives arrays in (ny, nx) so we use 'F' to flatten xpos,

# ypos in column-major order. For numpy >= 1.7, we could instead call meshgrid

# with indexing='ij'.

xpos, ypos = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.meshgrid.html#numpy.meshgrid" title="View documentation for numpy.meshgrid">np.meshgrid</a>(xedges[:-1] + 0.25, yedges[:-1] + 0.25)

xpos = xpos.flatten('F')

ypos = ypos.flatten('F')

zpos = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.zeros_like.html#numpy.zeros_like" title="View documentation for numpy.zeros_like">np.zeros_like</a>(xpos)

# Construct arrays with the dimensions for the 16 bars.

dx = 0.5 * <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones_like.html#numpy.ones_like" title="View documentation for numpy.ones_like">np.ones_like</a>(zpos)

dy = dx.copy()

dz = hist.flatten()

ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='b', zsort='average')

<a href="../../api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="View documentation for matplotlib.pyplot.show">plt.show</a>()

</pre></div>

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<a class="reference download internal" href="../../_downloads/hist3d.py" download=""><code class="xref download docutils literal notranslate">Download Python source code: hist3d.py</code></a></div>

<a class="reference download internal" href="../../_downloads/hist3d.ipynb" download=""><code class="xref download docutils literal notranslate">Download Jupyter notebook: hist3d.ipynb</code></a></div>

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