Matplotlib.axes.Axes.hist2d() in Python

• Last Updated : 13 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.hist2d() Function

The Axes.hist2d() function in axes module of matplotlib library is used to make a 2D histogram plot.

Syntax: Axes.hist2d(self, x, y, bins=10, range=None, density=False, weights=None, cmin=None, cmax=None, *, data=None, **kwargs)

Parameters: This method accept the following parameters that are described below:

• x, y : These parameter are the sequence of data.
• bins : This parameter is an optional parameter and it contains the integer or sequence or string.
• range : This parameter is an optional parameter and it the lower and upper range of the bins.
• density : This parameter is an optional parameter and it contains the boolean values.
• weights : This parameter is an optional parameter and it is an array of weights, of the same shape as x.
• cmin : This parameter has all bins that has count less than cmin will not be displayed.
• cmax : This parameter has all bins that has count more than cmax will not be displayed.

Returns: This returns the following:

• h :This returns the bi-dimensional histogram of samples x and y.
• xedges :This returns the bin edges along the x axis.
• yedges :This returns the bin edges along the y axis.
• image :This returns the QuadMesh.

Below examples illustrate the matplotlib.axes.Axes.hist2d() function in matplotlib.axes:

Example-1:

 `   ` `# Implementation of matplotlib function``from` `matplotlib ``import` `colors``from` `matplotlib.ticker ``import` `PercentFormatter``import` `numpy as np``import` `matplotlib.pyplot as plt`` ` `N_points ``=` `100000``x ``=` `np.random.randn(N_points)``y ``=` `.``4` `*` `x ``+` `np.random.randn(``100000``) ``+` `5`` ` `fig, ax ``=` `plt.subplots()``ax.hist2d(x, y, bins ``=` `100``, ``          ``norm ``=` `colors.LogNorm(),``          ``cmap ``=``"Greens"``)`` ` `ax.set_title('matplotlib.axes.Axes.\``hist2d() Example')`` ` `plt.show()`

Output:

Example-2:

 `# Implementation of matplotlib function``from` `matplotlib ``import` `colors``import` `numpy as np``from` `numpy.random ``import` `multivariate_normal``import` `matplotlib.pyplot as plt`` ` `result ``=` `np.vstack([``    ``multivariate_normal([``10``, ``10``],``            ``[[``3``, ``2``], [``2``, ``3``]], size ``=` `100000``),``    ``multivariate_normal([``30``, ``20``],``            ``[[``2``, ``3``], [``1``, ``3``]], size ``=` `1000``)``])`` ` `fig, [axes, axes1] ``=` `plt.subplots(nrows ``=` `2``, ``                                  ``ncols ``=` `1``,``                                  ``sharex ``=` `True``)`` ` `axes.hist2d(result[:, ``0``], result[:, ``1``],``            ``bins ``=` `100``, cmap ``=``"GnBu"``,``            ``norm ``=` `colors.LogNorm())`` ` `axes1.hist2d(result[:, ``0``], result[:, ``1``],``             ``bins ``=` `100``, norm ``=` `colors.LogNorm())`` ` `axes.set_title('matplotlib.axes.Axes.\``hist2d() Example')`` ` `plt.show()`

Output:

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