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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_oil_well.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_plot_oil_well.py:


Fat content in cooking oils
===========================

This example shows how to apply x-layout on statistical plots.

.. GENERATED FROM PYTHON SOURCE LINES 8-17

.. code-block:: Python


    import marsilea as ma
    import marsilea.plotter as mp

    import mpl_fontkit as fk

    fk.install_fontawesome(verbose=False)
    fk.install("Lato", verbose=False)








.. GENERATED FROM PYTHON SOURCE LINES 18-20

Load data
---------

.. GENERATED FROM PYTHON SOURCE LINES 20-34

.. code-block:: Python

    oils = ma.load_data('cooking_oils')

    red = "#cd442a"
    yellow = "#f0bd00"
    green = "#7e9437"
    gray = "#eee"

    mapper = {0: "\uf58a", 1: "\uf11a", 2: "\uf567"}
    cmapper = {0: '#609966', 1: '#DC8449', 2: '#F16767'}
    flavour = [mapper[i] for i in oils['flavour'].values]
    flavour_colors = [cmapper[i] for i in oils['flavour'].values]
    fat_content = oils[['saturated', 'polyunsaturated (omega 3 & 6)',
                        'monounsaturated', 'other fat']]








.. GENERATED FROM PYTHON SOURCE LINES 35-37

Visualize the oil contents
--------------------------

.. GENERATED FROM PYTHON SOURCE LINES 37-85

.. code-block:: Python


    cb = ma.ClusterBoard(fat_content.to_numpy(), height=10)
    cb.add_layer(
        mp.StackBar(fat_content.T * 100, colors=[red, yellow, green, gray],
                    width=.8, orient="h", label="Fat Content (%)",
                    legend_kws={'ncol': 2, 'fontsize': 10}))

    fmt = lambda x: f"{x:.1f}" if x > 0 else ""
    cb.add_left(
        mp.Numbers(oils['trans fat'] * 100, fmt=fmt,
                   label="Trans Fat (%)", color="#3A98B9"),
        pad=.2, name="trans fat")

    cb.add_right(
        mp.Labels(flavour, fontfamily="Font Awesome 6 Free",
                  text_props={'color': flavour_colors}))

    cb.add_right(
        mp.Labels(oils.index.str.capitalize()), pad=.1)

    fmt = lambda x: f"{int(x)}" if x > 0 else ""
    cb.add_right(
        ma.plotter.CenterBar((oils[['omega 3', 'omega 6']] * 100).astype(int),
                             names=["Omega 3 (%)", "Omega 6 (%)"],
                             colors=["#7DB9B6", "#F5E9CF"],
                             fmt=fmt, show_value=True),
        size=2, pad=.2)

    order = ["Control", ">230 °C (Deep-frying)", "200-229 °C (Stir-frying)",
             "150-199 °C (Light saute)", "<150 °C (Dressings)"]
    cb.hsplit(labels=oils['cooking conditions'], order=order)
    colors = ["#e5e7eb", "#c2410c", "#fb923c", "#fca5a5", "#fecaca"]

    chunk_text = ["Control", ">230 °C\nDeep-frying", "200-229 °C\nStir-frying",
                  "150-199 °C\nLight saute", "<150 °C\nDressings"]
    cb.add_left(
        ma.plotter.Chunk(chunk_text, colors, rotation=0, padding=10),
        pad=.1)

    cb.add_dendrogram("left", add_meta=False, colors=colors,
                      linewidth=1.5, size=.5, pad=.02)
    cb.add_title(top="Fat in Cooking Oils", fontsize=16)
    cb.add_legends("bottom", pad=.3)
    cb.render()

    axes = cb.get_ax("trans fat")
    for ax in axes:
        ax.set_xlim(4.2, 0)



.. image-sg:: /auto_examples/images/sphx_glr_plot_oil_well_001.png
   :alt: plot oil well
   :srcset: /auto_examples/images/sphx_glr_plot_oil_well_001.png, /auto_examples/images/sphx_glr_plot_oil_well_001_2_00x.png 2.00x
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 4.855 seconds)


.. _sphx_glr_download_auto_examples_plot_oil_well.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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