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

.. only:: html

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

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

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

.. _sphx_glr_source_auto_examples_plotting_plot_pie_chart.py:


Calculate and View Aerosol Percentages
--------------------------------------

Calculate the percentages of different aerosols in a Aerosol
Chemical Speciation (AOS) monitor dataset and view the percentages
in a pie chart.

Written: Zach Sherman

.. GENERATED FROM PYTHON SOURCE LINES 12-53



.. image-sg:: /source/auto_examples/plotting/images/sphx_glr_plot_pie_chart_001.png
   :alt: sgpaosacsmE13.b2 on 20230420
   :srcset: /source/auto_examples/plotting/images/sphx_glr_plot_pie_chart_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    KeysView(Data variables:
        base_time                     datetime64[ns] 8B 2023-04-20
        time_offset                   (time) datetime64[ns] 408B 2023-04-20T00:01...
        time_bounds                   (time, bound) object 816B dask.array<chunksize=(51, 2), meta=np.ndarray>
        total_organics                (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        qc_total_organics             (time) int32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        sulfate                       (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        qc_sulfate                    (time) int32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        ammonium                      (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        qc_ammonium                   (time) int32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        nitrate                       (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        qc_nitrate                    (time) int32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        chloride                      (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        qc_chloride                   (time) int32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        airbeam_normalization_factor  (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        inlet_pressure                (time) float32 204B dask.array<chunksize=(51,), meta=np.ndarray>
        lat                           float32 4B ...
        lon                           float32 4B ...
        alt                           float32 4B ...)
    /home/runner/work/ACT/ACT/act/utils/data_utils.py:1398: UserWarning: No time parameter used, calculating a mean for each field for the whole dataset.
      warnings.warn(






|

.. code-block:: Python


    from arm_test_data import DATASETS
    import matplotlib.pyplot as plt

    import act
    from act.io.arm import read_arm_netcdf

    # Read an ARM AOS dataset
    filename = DATASETS.fetch('sgpaosacsmE13.b2.20230420.000109.nc')
    ds = read_arm_netcdf(filename)

    # Let us print out the fields in the dataset and see what it contains.
    print(ds.data_vars.keys())

    # Knowing what fields the dataset contains, let's create a list of fields
    # to use in the plot.

    fields = ['sulfate', 'ammonium', 'nitrate', 'chloride']

    # We also want to provide some keyword arguments to avoid invalid data such
    # as negative values.
    threshold = 0.0
    fill_value = 0.0

    # Create a DistributionDisplay object to compare fields
    display = act.plotting.DistributionDisplay(ds)

    # We can set one of the slices to explode and give it a nice shadow.
    explode = (0, 0.1, 0, 0)
    shadow = True

    # Create a pie chart using the fields list. The percentages of the
    # fields will be calculated using act.utils.calculate_percentages.
    display.plot_pie_chart(
        fields,
        threshold=threshold,
        fill_value=fill_value,
        explode=explode,
        shadow=True,
    )
    plt.show()


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

   **Total running time of the script:** (0 minutes 0.080 seconds)


.. _sphx_glr_download_source_auto_examples_plotting_plot_pie_chart.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_pie_chart.zip <plot_pie_chart.zip>`


.. only:: html

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

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