.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "_examples\matplotlib\plot_main02_hexbin.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download__examples_matplotlib_plot_main02_hexbin.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr__examples_matplotlib_plot_main02_hexbin.py:


02. Point density with ``matplotlib.hexbin``
=============================================

This script demonstrates how to create a 2D hexagonal binning
plot with ``matplotlib.hexbin``. 🐝 This type of plot is an
excellent alternative to a scatter plot for visualizing the
density of a large number of points. The example generates
random data and displays it using both linear and logarithmic
color scales to represent point concentration.

.. GENERATED FROM PYTHON SOURCE LINES 13-59



.. image-sg:: /_examples/matplotlib/images/sphx_glr_plot_main02_hexbin_001.png
   :alt: Hexagon binning, With a log color scale
   :srcset: /_examples/matplotlib/images/sphx_glr_plot_main02_hexbin_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    C:\Users\kelda\Desktop\repositories\github\python-spare-code\main\examples\matplotlib\plot_main02_hexbin.py:59: UserWarning:

    FigureCanvasAgg is non-interactive, and thus cannot be shown







|

.. code-block:: default
   :lineno-start: 14


    import pandas as pd
    import numpy as np
    import matplotlib.pyplot as plt

    # constant
    n = 100000

    # Fixing random state for reproducibility
    np.random.seed(19680801)

    # Generate data
    x = np.random.standard_normal(n)
    y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
    z = None

    # Compute limits
    xmin = x.min()
    xmax = x.max()
    ymin = y.min()
    ymax = y.max()

    # Display hexagon binning (linear)
    fig, axs = plt.subplots(ncols=2, sharey=True, figsize=(7, 4))
    fig.subplots_adjust(hspace=0.5, left=0.07, right=0.93)
    ax = axs[0]
    hb = ax.hexbin(x, y, C=z, cmap='coolwarm', reduce_C_function=np.median)
    ax.axis([xmin, xmax, ymin, ymax])
    ax.set_title("Hexagon binning")
    ax.invert_xaxis()
    cb = fig.colorbar(hb, ax=ax)
    cb.set_label('N=median')

    # Display hexagon binning (log)
    ax = axs[1]
    hb = ax.hexbin(x, y, C=z, gridsize=50,
        bins='log', cmap='coolwarm',
        reduce_C_function=np.median)
    ax.axis([xmin, xmax, ymin, ymax])
    ax.set_title("With a log color scale")
    ax.invert_xaxis()
    cb = fig.colorbar(hb, ax=ax)
    cb.set_label('log10(N)')

    # Show
    plt.tight_layout()
    plt.show()

.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  1.188 seconds)


.. _sphx_glr_download__examples_matplotlib_plot_main02_hexbin.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_main02_hexbin.py <plot_main02_hexbin.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_main02_hexbin.ipynb <plot_main02_hexbin.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_