.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/001_basic_usage.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_001_basic_usage.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_001_basic_usage.py:


Basic usage
===========

A simple example demonstrating how to use mass-composition.

Design notes:
Once data is loaded chemical analyte names and H2O will conform to the internal standard.

.. GENERATED FROM PYTHON SOURCE LINES 11-17

.. code-block:: default


    import pandas as pd

    from elphick.mass_composition import MassComposition
    from elphick.mass_composition.datasets.sample_data import sample_data








.. GENERATED FROM PYTHON SOURCE LINES 18-22

Create a MassComposition object
-------------------------------

We get some demo data in the form of a pandas DataFrame

.. GENERATED FROM PYTHON SOURCE LINES 23-27

.. code-block:: default


    df_data: pd.DataFrame = sample_data()
    df_data






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    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>wet_mass</th>
          <th>mass_dry</th>
          <th>FE</th>
          <th>SIO2</th>
          <th>al2o3</th>
          <th>LOI</th>
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      </tbody>
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    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 28-29

Construct a MassComposition object

.. GENERATED FROM PYTHON SOURCE LINES 30-34

.. code-block:: default


    obj_mc: MassComposition = MassComposition(df_data)
    print(obj_mc)





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

 .. code-block:: none


    unnamed
    <xarray.Dataset> Size: 216B
    Dimensions:   (index: 3)
    Coordinates:
      * index     (index) int64 24B 0 1 2
    Data variables:
        mass_wet  (index) float64 24B 100.0 90.0 110.0
        mass_dry  (index) float64 24B 90.0 80.0 90.0
        H2O       (index) float64 24B 10.0 11.11 18.18
        Fe        (index) float64 24B 57.0 59.0 61.0
        SiO2      (index) float64 24B 5.2 3.1 2.2
        Al2O3     (index) float64 24B 3.0 1.7 0.9
        LOI       (index) float64 24B 5.0 4.0 3.0
        group     (index) object 24B 'grp_1' 'grp_1' 'grp_2'
    Attributes:
        mc_name:            unnamed
        mc_vars_mass:       ['mass_wet', 'mass_dry']
        mc_vars_chem:       ['Fe', 'SiO2', 'Al2O3', 'LOI']
        mc_vars_attrs:      ['group']
        mc_interval_edges:  {}




.. GENERATED FROM PYTHON SOURCE LINES 35-39

Demonstrate the aggregate method
--------------------------------

i.e. weight average of the dataset, a.k.a. head grade

.. GENERATED FROM PYTHON SOURCE LINES 40-43

.. code-block:: default


    obj_mc.aggregate()






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.. GENERATED FROM PYTHON SOURCE LINES 44-46

.. code-block:: default

    obj_mc.aggregate(as_dataframe=False)






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    </style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 56B
    Dimensions:   (index: 1)
    Dimensions without coordinates: index
    Data variables:
        mass_wet  (index) float64 8B 300.0
        mass_dry  (index) float64 8B 260.0
        H2O       (index) float64 8B 13.33
        Fe        (index) float64 8B 59.0
        SiO2      (index) float64 8B 3.515
        Al2O3     (index) float64 8B 1.873
        LOI       (index) float64 8B 4.0
    Attributes:
        mc_name:            Aggregate of unnamed
        mc_vars_mass:       [&#x27;mass_wet&#x27;, &#x27;mass_dry&#x27;]
        mc_vars_chem:       [&#x27;Fe&#x27;, &#x27;SiO2&#x27;, &#x27;Al2O3&#x27;, &#x27;LOI&#x27;]
        mc_vars_attrs:      []
        mc_interval_edges:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f504bef4-46a2-44c6-9e11-e8521523e411' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f504bef4-46a2-44c6-9e11-e8521523e411' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>index</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5e509c95-8882-49de-bad5-874cc5b06eff' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5e509c95-8882-49de-bad5-874cc5b06eff' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-33ca3207-a9d9-447c-a162-1cc0e5a6c0c5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-33ca3207-a9d9-447c-a162-1cc0e5a6c0c5' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mass_wet</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>300.0</div><input id='attrs-140c7e72-a618-43b5-b726-86a946789f2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-140c7e72-a618-43b5-b726-86a946789f2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91ad711f-989d-401a-886e-58c1d7b10649' class='xr-var-data-in' type='checkbox'><label for='data-91ad711f-989d-401a-886e-58c1d7b10649' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mass_units</dd><dt><span>standard_name :</span></dt><dd>Wet Mass</dd><dt><span>mc_type :</span></dt><dd>mass</dd><dt><span>mc_col_orig :</span></dt><dd>wet_mass</dd></dl></div><div class='xr-var-data'><pre>array([300.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mass_dry</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>260.0</div><input id='attrs-306982c2-aa9b-4236-98ba-5bf4da4b6e98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-306982c2-aa9b-4236-98ba-5bf4da4b6e98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8f95ba9-b9ed-4a53-927e-7b22a23dffe8' class='xr-var-data-in' type='checkbox'><label for='data-a8f95ba9-b9ed-4a53-927e-7b22a23dffe8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mass_units</dd><dt><span>standard_name :</span></dt><dd>Dry Mass</dd><dt><span>mc_type :</span></dt><dd>mass</dd><dt><span>mc_col_orig :</span></dt><dd>mass_dry</dd></dl></div><div class='xr-var-data'><pre>array([260.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>13.33</div><input id='attrs-e3aa3670-216a-426e-8e6e-86e82bece212' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3aa3670-216a-426e-8e6e-86e82bece212' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-995a39eb-5775-4a86-87ce-4fc9d507da2c' class='xr-var-data-in' type='checkbox'><label for='data-995a39eb-5775-4a86-87ce-4fc9d507da2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>H2O</dd><dt><span>mc_type :</span></dt><dd>moisture</dd><dt><span>mc_col_orig :</span></dt><dd>H2O</dd></dl></div><div class='xr-var-data'><pre>array([13.33333333])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Fe</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>59.0</div><input id='attrs-5db7af44-dd81-45c8-b6f8-89e4d8ad104b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5db7af44-dd81-45c8-b6f8-89e4d8ad104b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c1ac277-93ea-42e0-b0b5-98e7e0069d5d' class='xr-var-data-in' type='checkbox'><label for='data-4c1ac277-93ea-42e0-b0b5-98e7e0069d5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>Fe</dd><dt><span>mc_type :</span></dt><dd>chemistry</dd><dt><span>mc_col_orig :</span></dt><dd>FE</dd></dl></div><div class='xr-var-data'><pre>array([59.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SiO2</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.515</div><input id='attrs-f71cba26-6d17-4f28-829a-c284590a6dc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f71cba26-6d17-4f28-829a-c284590a6dc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c06f4013-f9b9-4c05-93bb-b5cc4a2fca56' class='xr-var-data-in' type='checkbox'><label for='data-c06f4013-f9b9-4c05-93bb-b5cc4a2fca56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>SiO2</dd><dt><span>mc_type :</span></dt><dd>chemistry</dd><dt><span>mc_col_orig :</span></dt><dd>SIO2</dd></dl></div><div class='xr-var-data'><pre>array([3.51538462])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Al2O3</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.873</div><input id='attrs-8d907cc2-12d6-48d8-9984-976dfea1e336' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d907cc2-12d6-48d8-9984-976dfea1e336' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f375472-ace4-407c-b1f6-7e5654bf4cee' class='xr-var-data-in' type='checkbox'><label for='data-1f375472-ace4-407c-b1f6-7e5654bf4cee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>Al2O3</dd><dt><span>mc_type :</span></dt><dd>chemistry</dd><dt><span>mc_col_orig :</span></dt><dd>al2o3</dd></dl></div><div class='xr-var-data'><pre>array([1.87307692])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LOI</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.0</div><input id='attrs-8cc42f38-64ae-4b99-a074-159ab58ed16a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cc42f38-64ae-4b99-a074-159ab58ed16a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fba01a73-7b5d-4440-9c9a-820b8cdc2b31' class='xr-var-data-in' type='checkbox'><label for='data-fba01a73-7b5d-4440-9c9a-820b8cdc2b31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>LOI</dd><dt><span>mc_type :</span></dt><dd>chemistry</dd><dt><span>mc_col_orig :</span></dt><dd>LOI</dd></dl></div><div class='xr-var-data'><pre>array([4.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6ceced96-9057-4b65-bd58-43a8b70b52f8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ceced96-9057-4b65-bd58-43a8b70b52f8' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-3954b348-ee19-4025-98d7-92adfb3d4014' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3954b348-ee19-4025-98d7-92adfb3d4014' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>mc_name :</span></dt><dd>Aggregate of unnamed</dd><dt><span>mc_vars_mass :</span></dt><dd>[&#x27;mass_wet&#x27;, &#x27;mass_dry&#x27;]</dd><dt><span>mc_vars_chem :</span></dt><dd>[&#x27;Fe&#x27;, &#x27;SiO2&#x27;, &#x27;Al2O3&#x27;, &#x27;LOI&#x27;]</dd><dt><span>mc_vars_attrs :</span></dt><dd>[]</dd><dt><span>mc_interval_edges :</span></dt><dd>{}</dd></dl></div></li></ul></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 47-48

Aggregate by a group variable

.. GENERATED FROM PYTHON SOURCE LINES 49-52

.. code-block:: default


    obj_mc.aggregate(group_var='group')






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>mass_wet</th>
          <th>mass_dry</th>
          <th>H2O</th>
          <th>Fe</th>
          <th>SiO2</th>
          <th>Al2O3</th>
          <th>LOI</th>
        </tr>
        <tr>
          <th>group</th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>grp_1</th>
          <td>190.0</td>
          <td>170.0</td>
          <td>10.526316</td>
          <td>57.941176</td>
          <td>4.211765</td>
          <td>2.388235</td>
          <td>4.529412</td>
        </tr>
        <tr>
          <th>grp_2</th>
          <td>110.0</td>
          <td>90.0</td>
          <td>18.181818</td>
          <td>61.000000</td>
          <td>2.200000</td>
          <td>0.900000</td>
          <td>3.000000</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 53-57

Filter the object
-----------------

Filter with a criteria, just like pandas

.. GENERATED FROM PYTHON SOURCE LINES 58-61

.. code-block:: default


    obj_mc.query(queries={'index': 'Fe>58'}).aggregate()






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>mass_wet</th>
          <th>mass_dry</th>
          <th>H2O</th>
          <th>Fe</th>
          <th>SiO2</th>
          <th>Al2O3</th>
          <th>LOI</th>
        </tr>
        <tr>
          <th>name</th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>unnamed</th>
          <td>200.0</td>
          <td>170.0</td>
          <td>15.0</td>
          <td>60.058824</td>
          <td>2.623529</td>
          <td>1.276471</td>
          <td>3.470588</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />


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

   **Total running time of the script:** ( 0 minutes  0.151 seconds)


.. _sphx_glr_download_auto_examples_001_basic_usage.py:

.. only:: html

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


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

      :download:`Download Python source code: 001_basic_usage.py <001_basic_usage.py>`

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

      :download:`Download Jupyter notebook: 001_basic_usage.ipynb <001_basic_usage.ipynb>`


.. only:: html

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

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