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

.. only:: html

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

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

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

.. _sphx_glr_checks_gallery_tabular_distribution_plot_train_test_label_drift.py:


Train Test Label Drift
**********************

.. GENERATED FROM PYTHON SOURCE LINES 8-17

.. code-block:: default


    import pprint

    import numpy as np
    import pandas as pd

    from deepchecks.tabular import Dataset
    from deepchecks.tabular.checks import TrainTestLabelDrift








.. GENERATED FROM PYTHON SOURCE LINES 18-20

Generate data - Classification label
====================================

.. GENERATED FROM PYTHON SOURCE LINES 20-33

.. code-block:: default


    np.random.seed(42)

    train_data = np.concatenate([np.random.randn(1000,2), np.random.choice(a=[1,0], p=[0.5, 0.5], size=(1000, 1))], axis=1)
    #Create test_data with drift in label:
    test_data = np.concatenate([np.random.randn(1000,2), np.random.choice(a=[1,0], p=[0.35, 0.65], size=(1000, 1))], axis=1) 

    df_train = pd.DataFrame(train_data, columns=['col1', 'col2', 'target'])
    df_test = pd.DataFrame(test_data, columns=['col1', 'col2', 'target'])

    train_dataset = Dataset(df_train, label='target')
    test_dataset = Dataset(df_test, label='target')








.. GENERATED FROM PYTHON SOURCE LINES 34-37

.. code-block:: default


    df_train.head()






.. 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>col1</th>
          <th>col2</th>
          <th>target</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>0.496714</td>
          <td>-0.138264</td>
          <td>1.0</td>
        </tr>
        <tr>
          <th>1</th>
          <td>0.647689</td>
          <td>1.523030</td>
          <td>1.0</td>
        </tr>
        <tr>
          <th>2</th>
          <td>-0.234153</td>
          <td>-0.234137</td>
          <td>1.0</td>
        </tr>
        <tr>
          <th>3</th>
          <td>1.579213</td>
          <td>0.767435</td>
          <td>1.0</td>
        </tr>
        <tr>
          <th>4</th>
          <td>-0.469474</td>
          <td>0.542560</td>
          <td>0.0</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 38-40

Run Check
=========

.. GENERATED FROM PYTHON SOURCE LINES 40-45

.. code-block:: default


    check = TrainTestLabelDrift()
    result = check.run(train_dataset=train_dataset, test_dataset=test_dataset)
    result






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

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        src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.6/require.min.js"
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    <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
    <script type="text/javascript">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: "STIX-Web"}});}</script>
    <script type="text/javascript">
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                },
                function() {console.log('Failed to load plotly')}
            );
        } else {
            console.log('requirejs is not present');
        }
    </script>
    <h4><b>Train Test Label Drift</b></h4><p>    Calculate label drift between train dataset and test dataset, using statistical measures.</p><h5><b>Additional Outputs</b></h5><div><span>
                The Drift score is a measure for the difference between two distributions, in this check - the test
                and train distributions.<br> The check shows the drift score and distributions for the label.
            </span></div><div>                            <div id="1c3ac1df-1a27-4b24-bb6b-201428584c11" class="plotly-graph-div" style="height:400px; width:700px;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("1c3ac1df-1a27-4b24-bb6b-201428584c11")) {                    Plotly.newPlot(                        "1c3ac1df-1a27-4b24-bb6b-201428584c11",                        [{"base":0,"marker":{"color":"#01B8AA"},"offsetgroup":"0","orientation":"h","showlegend":false,"x":[0.08069723178368182],"y":["Drift Score"],"type":"bar","xaxis":"x","yaxis":"y"},{"marker":{"color":"#00008b"},"name":"Train Dataset","x":[0.0,1.0],"y":[0.503,0.497],"type":"bar","xaxis":"x2","yaxis":"y2"},{"marker":{"color":"#69b3a2"},"name":"Test Dataset","x":[0.0,1.0],"y":[0.643,0.357],"type":"bar","xaxis":"x2","yaxis":"y2"}],                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.. GENERATED FROM PYTHON SOURCE LINES 46-48

Generate data - Regression label
================================

.. GENERATED FROM PYTHON SOURCE LINES 48-60

.. code-block:: default


    train_data = np.concatenate([np.random.randn(1000,2), np.random.randn(1000, 1)], axis=1)
    test_data = np.concatenate([np.random.randn(1000,2), np.random.randn(1000, 1)], axis=1)

    df_train = pd.DataFrame(train_data, columns=['col1', 'col2', 'target'])
    df_test = pd.DataFrame(test_data, columns=['col1', 'col2', 'target'])
    #Create drift in test:
    df_test['target'] = df_test['target'].astype('float') + abs(np.random.randn(1000)) + np.arange(0, 1, 0.001) * 4

    train_dataset = Dataset(df_train, label='target')
    test_dataset = Dataset(df_test, label='target')








.. GENERATED FROM PYTHON SOURCE LINES 61-63

Run check
=========

.. GENERATED FROM PYTHON SOURCE LINES 63-68

.. code-block:: default


    check = TrainTestLabelDrift()
    result = check.run(train_dataset=train_dataset, test_dataset=test_dataset)
    result






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    <h4><b>Train Test Label Drift</b></h4><p>    Calculate label drift between train dataset and test dataset, using statistical measures.</p><h5><b>Additional Outputs</b></h5><div><span>
                The Drift score is a measure for the difference between two distributions, in this check - the test
                and train distributions.<br> The check shows the drift score and distributions for the label.
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.. GENERATED FROM PYTHON SOURCE LINES 69-70

Add condition

.. GENERATED FROM PYTHON SOURCE LINES 70-73

.. code-block:: default


    check_cond = TrainTestLabelDrift().add_condition_drift_score_not_greater_than()
    check_cond.run(train_dataset=train_dataset, test_dataset=test_dataset)





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    <h4><b>Train Test Label Drift</b></h4><p>    Calculate label drift between train dataset and test dataset, using statistical measures.</p><h5><b>Conditions Summary</b></h5><style type="text/css">
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          <th id="T_0df6a_level0_col0" class="col_heading level0 col0" >Status</th>
          <th id="T_0df6a_level0_col1" class="col_heading level0 col1" >Condition</th>
          <th id="T_0df6a_level0_col2" class="col_heading level0 col2" >More Info</th>
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          <td id="T_0df6a_row0_col0" class="data row0 col0" ><div style="color: red;text-align: center">✖</div></td>
          <td id="T_0df6a_row0_col1" class="data row0 col1" >PSI <= 0.2 and Earth Mover's Distance <= 0.1 for label drift</td>
          <td id="T_0df6a_row0_col2" class="data row0 col2" >Label's Earth Mover's Distance above threshold: 0.34</td>
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    <h5><b>Additional Outputs</b></h5><div><span>
                The Drift score is a measure for the difference between two distributions, in this check - the test
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.. _sphx_glr_download_checks_gallery_tabular_distribution_plot_train_test_label_drift.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_train_test_label_drift.py <plot_train_test_label_drift.py>`



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

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


.. only:: html

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