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

.. only:: html

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

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

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

.. _sphx_glr_gallery_discretisation.py:


Retour sur la discrétisation des variables quantitatives
----------------------------------------------------------------
Les méthodes de discrétisation les plus courantes sont disponibles sous Geopandas (quantile, intervalle égal, Jenks). La discrétisation dite de Jenks qui recherche à construire des classes les plus homogènes possibles est en générale la plus pertinente. Néanmoins, ce n'est pas toujours le cas, comme en témoigne les cartes suivantes de densité de population départementale.

.. GENERATED FROM PYTHON SOURCE LINES 6-12

.. code-block:: default

    # sphinx_gallery_thumbnail_number = 3
    import pandas as pd
    import geopandas as gpd
    import numpy as np

    import matplotlib.pyplot as plt







.. GENERATED FROM PYTHON SOURCE LINES 13-17

Lecture des données
================================

On ouvre le fond du bâti de la ville de Caen.


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

   **Total running time of the script:** ( 0 minutes  0.278 seconds)


.. _sphx_glr_download_gallery_discretisation.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: discretisation.py <discretisation.py>`



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

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


.. only:: html

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

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