.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/miscellaneous/plot_pipeline_display.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_miscellaneous_plot_pipeline_display.py>`
        to download the full example code or to run this example in your browser via JupyterLite or Binder

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

.. _sphx_glr_auto_examples_miscellaneous_plot_pipeline_display.py:


=================================================================
Displaying Pipelines
=================================================================

The default configuration for displaying a pipeline in a Jupyter Notebook is
`'diagram'` where `set_config(display='diagram')`. To deactivate HTML representation,
use `set_config(display='text')`.

To see more detailed steps in the visualization of the pipeline, click on the
steps in the pipeline.

.. GENERATED FROM PYTHON SOURCE LINES 15-21

Displaying a Pipeline with a Preprocessing Step and Classifier
###############################################################################
 This section constructs a :class:`~sklearn.pipeline.Pipeline` with a preprocessing
 step, :class:`~sklearn.preprocessing.StandardScaler`, and classifier,
 :class:`~sklearn.linear_model.LogisticRegression`, and displays its visual
 representation.

.. GENERATED FROM PYTHON SOURCE LINES 21-33

.. code-block:: Python


    from sklearn import set_config
    from sklearn.linear_model import LogisticRegression
    from sklearn.pipeline import Pipeline
    from sklearn.preprocessing import StandardScaler

    steps = [
        ("preprocessing", StandardScaler()),
        ("classifier", LogisticRegression()),
    ]
    pipe = Pipeline(steps)








.. GENERATED FROM PYTHON SOURCE LINES 34-35

To visualize the diagram, the default is `display='diagram'`.

.. GENERATED FROM PYTHON SOURCE LINES 35-38

.. code-block:: Python

    set_config(display="diagram")
    pipe  # click on the diagram below to see the details of each step






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>#sk-container-id-39 {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: black;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;

      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
      --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-icon: #696969;

      @media (prefers-color-scheme: dark) {
        /* Redefinition of color scheme for dark theme */
        --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
        --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-icon: #878787;
      }
    }

    #sk-container-id-39 {
      color: var(--sklearn-color-text);
    }

    #sk-container-id-39 pre {
      padding: 0;
    }

    #sk-container-id-39 input.sk-hidden--visually {
      border: 0;
      clip: rect(1px 1px 1px 1px);
      clip: rect(1px, 1px, 1px, 1px);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    #sk-container-id-39 div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    #sk-container-id-39 div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    #sk-container-id-39 div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    #sk-container-id-39 div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    #sk-container-id-39 div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    #sk-container-id-39 div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    #sk-container-id-39 div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    #sk-container-id-39 div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    #sk-container-id-39 div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    #sk-container-id-39 div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    #sk-container-id-39 div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    #sk-container-id-39 label.sk-toggleable__label {
      cursor: pointer;
      display: block;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
    }

    #sk-container-id-39 label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    #sk-container-id-39 label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    #sk-container-id-39 div.sk-toggleable__content {
      max-height: 0;
      max-width: 0;
      overflow: hidden;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-39 div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-39 div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-39 div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-39 input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      max-height: 200px;
      max-width: 100%;
      overflow: auto;
    }

    #sk-container-id-39 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    #sk-container-id-39 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-39 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    #sk-container-id-39 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-39 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    #sk-container-id-39 div.sk-label label.sk-toggleable__label,
    #sk-container-id-39 div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    #sk-container-id-39 div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    #sk-container-id-39 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    #sk-container-id-39 div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      display: inline-block;
      line-height: 1.2em;
    }

    #sk-container-id-39 div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    #sk-container-id-39 div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-39 div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    #sk-container-id-39 div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-39 div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 1ex;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
      color: var(--sklearn-color-unfitted-level-1);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    #sk-container-id-39 a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    #sk-container-id-39 a.estimator_doc_link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    #sk-container-id-39 a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    #sk-container-id-39 a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }
    </style><div id="sk-container-id-39" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, StandardScaler()),
                    (&#x27;classifier&#x27;, LogisticRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-168" type="checkbox" ><label for="sk-estimator-id-168" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link ">i<span>Not fitted</span></span></label><div class="sk-toggleable__content "><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, StandardScaler()),
                    (&#x27;classifier&#x27;, LogisticRegression())])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-169" type="checkbox" ><label for="sk-estimator-id-169" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;StandardScaler<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html">?<span>Documentation for StandardScaler</span></a></label><div class="sk-toggleable__content "><pre>StandardScaler()</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-170" type="checkbox" ><label for="sk-estimator-id-170" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;LogisticRegression<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html">?<span>Documentation for LogisticRegression</span></a></label><div class="sk-toggleable__content "><pre>LogisticRegression()</pre></div> </div></div></div></div></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 39-40

To view the text pipeline, change to `display='text'`.

.. GENERATED FROM PYTHON SOURCE LINES 40-43

.. code-block:: Python

    set_config(display="text")
    pipe





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

 .. code-block:: none


    Pipeline(steps=[('preprocessing', StandardScaler()),
                    ('classifier', LogisticRegression())])



.. GENERATED FROM PYTHON SOURCE LINES 44-45

Put back the default display

.. GENERATED FROM PYTHON SOURCE LINES 45-47

.. code-block:: Python

    set_config(display="diagram")








.. GENERATED FROM PYTHON SOURCE LINES 48-55

Displaying a Pipeline Chaining Multiple Preprocessing Steps & Classifier
###############################################################################
 This section constructs a :class:`~sklearn.pipeline.Pipeline` with multiple
 preprocessing steps, :class:`~sklearn.preprocessing.PolynomialFeatures` and
 :class:`~sklearn.preprocessing.StandardScaler`, and a classifier step,
 :class:`~sklearn.linear_model.LogisticRegression`, and displays its visual
 representation.

.. GENERATED FROM PYTHON SOURCE LINES 55-68

.. code-block:: Python


    from sklearn.linear_model import LogisticRegression
    from sklearn.pipeline import Pipeline
    from sklearn.preprocessing import PolynomialFeatures, StandardScaler

    steps = [
        ("standard_scaler", StandardScaler()),
        ("polynomial", PolynomialFeatures(degree=3)),
        ("classifier", LogisticRegression(C=2.0)),
    ]
    pipe = Pipeline(steps)
    pipe  # click on the diagram below to see the details of each step






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>#sk-container-id-40 {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: black;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;

      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
      --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-icon: #696969;

      @media (prefers-color-scheme: dark) {
        /* Redefinition of color scheme for dark theme */
        --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
        --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-icon: #878787;
      }
    }

    #sk-container-id-40 {
      color: var(--sklearn-color-text);
    }

    #sk-container-id-40 pre {
      padding: 0;
    }

    #sk-container-id-40 input.sk-hidden--visually {
      border: 0;
      clip: rect(1px 1px 1px 1px);
      clip: rect(1px, 1px, 1px, 1px);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    #sk-container-id-40 div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    #sk-container-id-40 div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    #sk-container-id-40 div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    #sk-container-id-40 div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    #sk-container-id-40 div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    #sk-container-id-40 div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    #sk-container-id-40 div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    #sk-container-id-40 div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    #sk-container-id-40 div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    #sk-container-id-40 div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    #sk-container-id-40 div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    #sk-container-id-40 label.sk-toggleable__label {
      cursor: pointer;
      display: block;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
    }

    #sk-container-id-40 label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    #sk-container-id-40 label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    #sk-container-id-40 div.sk-toggleable__content {
      max-height: 0;
      max-width: 0;
      overflow: hidden;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-40 div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-40 div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-40 div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-40 input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      max-height: 200px;
      max-width: 100%;
      overflow: auto;
    }

    #sk-container-id-40 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    #sk-container-id-40 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-40 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    #sk-container-id-40 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-40 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    #sk-container-id-40 div.sk-label label.sk-toggleable__label,
    #sk-container-id-40 div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    #sk-container-id-40 div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    #sk-container-id-40 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    #sk-container-id-40 div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      display: inline-block;
      line-height: 1.2em;
    }

    #sk-container-id-40 div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    #sk-container-id-40 div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-40 div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    #sk-container-id-40 div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-40 div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 1ex;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
      color: var(--sklearn-color-unfitted-level-1);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    #sk-container-id-40 a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    #sk-container-id-40 a.estimator_doc_link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    #sk-container-id-40 a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    #sk-container-id-40 a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }
    </style><div id="sk-container-id-40" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;standard_scaler&#x27;, StandardScaler()),
                    (&#x27;polynomial&#x27;, PolynomialFeatures(degree=3)),
                    (&#x27;classifier&#x27;, LogisticRegression(C=2.0))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-171" type="checkbox" ><label for="sk-estimator-id-171" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link ">i<span>Not fitted</span></span></label><div class="sk-toggleable__content "><pre>Pipeline(steps=[(&#x27;standard_scaler&#x27;, StandardScaler()),
                    (&#x27;polynomial&#x27;, PolynomialFeatures(degree=3)),
                    (&#x27;classifier&#x27;, LogisticRegression(C=2.0))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-172" type="checkbox" ><label for="sk-estimator-id-172" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;StandardScaler<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html">?<span>Documentation for StandardScaler</span></a></label><div class="sk-toggleable__content "><pre>StandardScaler()</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-173" type="checkbox" ><label for="sk-estimator-id-173" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;PolynomialFeatures<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.PolynomialFeatures.html">?<span>Documentation for PolynomialFeatures</span></a></label><div class="sk-toggleable__content "><pre>PolynomialFeatures(degree=3)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-174" type="checkbox" ><label for="sk-estimator-id-174" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;LogisticRegression<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html">?<span>Documentation for LogisticRegression</span></a></label><div class="sk-toggleable__content "><pre>LogisticRegression(C=2.0)</pre></div> </div></div></div></div></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 69-75

Displaying a Pipeline and Dimensionality Reduction and Classifier
###############################################################################
 This section constructs a :class:`~sklearn.pipeline.Pipeline` with a
 dimensionality reduction step, :class:`~sklearn.decomposition.PCA`,
 a classifier, :class:`~sklearn.svm.SVC`, and displays its visual
 representation.

.. GENERATED FROM PYTHON SOURCE LINES 75-84

.. code-block:: Python


    from sklearn.decomposition import PCA
    from sklearn.pipeline import Pipeline
    from sklearn.svm import SVC

    steps = [("reduce_dim", PCA(n_components=4)), ("classifier", SVC(kernel="linear"))]
    pipe = Pipeline(steps)
    pipe  # click on the diagram below to see the details of each step






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>#sk-container-id-41 {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: black;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;

      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
      --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-icon: #696969;

      @media (prefers-color-scheme: dark) {
        /* Redefinition of color scheme for dark theme */
        --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
        --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-icon: #878787;
      }
    }

    #sk-container-id-41 {
      color: var(--sklearn-color-text);
    }

    #sk-container-id-41 pre {
      padding: 0;
    }

    #sk-container-id-41 input.sk-hidden--visually {
      border: 0;
      clip: rect(1px 1px 1px 1px);
      clip: rect(1px, 1px, 1px, 1px);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    #sk-container-id-41 div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    #sk-container-id-41 div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    #sk-container-id-41 div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    #sk-container-id-41 div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    #sk-container-id-41 div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    #sk-container-id-41 div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    #sk-container-id-41 div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    #sk-container-id-41 div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    #sk-container-id-41 div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    #sk-container-id-41 div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    #sk-container-id-41 div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    #sk-container-id-41 label.sk-toggleable__label {
      cursor: pointer;
      display: block;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
    }

    #sk-container-id-41 label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    #sk-container-id-41 label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    #sk-container-id-41 div.sk-toggleable__content {
      max-height: 0;
      max-width: 0;
      overflow: hidden;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-41 div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-41 div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-41 div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-41 input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      max-height: 200px;
      max-width: 100%;
      overflow: auto;
    }

    #sk-container-id-41 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    #sk-container-id-41 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-41 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    #sk-container-id-41 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-41 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    #sk-container-id-41 div.sk-label label.sk-toggleable__label,
    #sk-container-id-41 div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    #sk-container-id-41 div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    #sk-container-id-41 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    #sk-container-id-41 div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      display: inline-block;
      line-height: 1.2em;
    }

    #sk-container-id-41 div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    #sk-container-id-41 div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-41 div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    #sk-container-id-41 div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-41 div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 1ex;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
      color: var(--sklearn-color-unfitted-level-1);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    #sk-container-id-41 a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    #sk-container-id-41 a.estimator_doc_link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    #sk-container-id-41 a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    #sk-container-id-41 a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }
    </style><div id="sk-container-id-41" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;reduce_dim&#x27;, PCA(n_components=4)),
                    (&#x27;classifier&#x27;, SVC(kernel=&#x27;linear&#x27;))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-175" type="checkbox" ><label for="sk-estimator-id-175" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link ">i<span>Not fitted</span></span></label><div class="sk-toggleable__content "><pre>Pipeline(steps=[(&#x27;reduce_dim&#x27;, PCA(n_components=4)),
                    (&#x27;classifier&#x27;, SVC(kernel=&#x27;linear&#x27;))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-176" type="checkbox" ><label for="sk-estimator-id-176" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;PCA<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.decomposition.PCA.html">?<span>Documentation for PCA</span></a></label><div class="sk-toggleable__content "><pre>PCA(n_components=4)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-177" type="checkbox" ><label for="sk-estimator-id-177" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;SVC<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.svm.SVC.html">?<span>Documentation for SVC</span></a></label><div class="sk-toggleable__content "><pre>SVC(kernel=&#x27;linear&#x27;)</pre></div> </div></div></div></div></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 85-91

Displaying a Complex Pipeline Chaining a Column Transformer
###############################################################################
 This section constructs a complex :class:`~sklearn.pipeline.Pipeline` with a
 :class:`~sklearn.compose.ColumnTransformer` and a classifier,
 :class:`~sklearn.linear_model.LogisticRegression`, and displays its visual
 representation.

.. GENERATED FROM PYTHON SOURCE LINES 91-127

.. code-block:: Python


    import numpy as np

    from sklearn.compose import ColumnTransformer
    from sklearn.impute import SimpleImputer
    from sklearn.linear_model import LogisticRegression
    from sklearn.pipeline import Pipeline, make_pipeline
    from sklearn.preprocessing import OneHotEncoder, StandardScaler

    numeric_preprocessor = Pipeline(
        steps=[
            ("imputation_mean", SimpleImputer(missing_values=np.nan, strategy="mean")),
            ("scaler", StandardScaler()),
        ]
    )

    categorical_preprocessor = Pipeline(
        steps=[
            (
                "imputation_constant",
                SimpleImputer(fill_value="missing", strategy="constant"),
            ),
            ("onehot", OneHotEncoder(handle_unknown="ignore")),
        ]
    )

    preprocessor = ColumnTransformer(
        [
            ("categorical", categorical_preprocessor, ["state", "gender"]),
            ("numerical", numeric_preprocessor, ["age", "weight"]),
        ]
    )

    pipe = make_pipeline(preprocessor, LogisticRegression(max_iter=500))
    pipe  # click on the diagram below to see the details of each step






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>#sk-container-id-42 {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: black;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;

      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
      --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-icon: #696969;

      @media (prefers-color-scheme: dark) {
        /* Redefinition of color scheme for dark theme */
        --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
        --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-icon: #878787;
      }
    }

    #sk-container-id-42 {
      color: var(--sklearn-color-text);
    }

    #sk-container-id-42 pre {
      padding: 0;
    }

    #sk-container-id-42 input.sk-hidden--visually {
      border: 0;
      clip: rect(1px 1px 1px 1px);
      clip: rect(1px, 1px, 1px, 1px);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    #sk-container-id-42 div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    #sk-container-id-42 div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    #sk-container-id-42 div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    #sk-container-id-42 div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    #sk-container-id-42 div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    #sk-container-id-42 div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    #sk-container-id-42 div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    #sk-container-id-42 div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    #sk-container-id-42 div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    #sk-container-id-42 div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    #sk-container-id-42 div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    #sk-container-id-42 label.sk-toggleable__label {
      cursor: pointer;
      display: block;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
    }

    #sk-container-id-42 label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    #sk-container-id-42 label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    #sk-container-id-42 div.sk-toggleable__content {
      max-height: 0;
      max-width: 0;
      overflow: hidden;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-42 div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-42 div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-42 div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-42 input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      max-height: 200px;
      max-width: 100%;
      overflow: auto;
    }

    #sk-container-id-42 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    #sk-container-id-42 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-42 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    #sk-container-id-42 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-42 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    #sk-container-id-42 div.sk-label label.sk-toggleable__label,
    #sk-container-id-42 div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    #sk-container-id-42 div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    #sk-container-id-42 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    #sk-container-id-42 div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      display: inline-block;
      line-height: 1.2em;
    }

    #sk-container-id-42 div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    #sk-container-id-42 div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-42 div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    #sk-container-id-42 div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-42 div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 1ex;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
      color: var(--sklearn-color-unfitted-level-1);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    #sk-container-id-42 a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    #sk-container-id-42 a.estimator_doc_link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    #sk-container-id-42 a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    #sk-container-id-42 a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }
    </style><div id="sk-container-id-42" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,
                     ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                                      Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                                       SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                                     strategy=&#x27;constant&#x27;)),
                                                                      (&#x27;onehot&#x27;,
                                                                       OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                                      [&#x27;state&#x27;, &#x27;gender&#x27;]),
                                                     (&#x27;numerical&#x27;,
                                                      Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                                       SimpleImputer()),
                                                                      (&#x27;scaler&#x27;,
                                                                       StandardScaler())]),
                                                      [&#x27;age&#x27;, &#x27;weight&#x27;])])),
                    (&#x27;logisticregression&#x27;, LogisticRegression(max_iter=500))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-178" type="checkbox" ><label for="sk-estimator-id-178" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link ">i<span>Not fitted</span></span></label><div class="sk-toggleable__content "><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,
                     ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                                      Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                                       SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                                     strategy=&#x27;constant&#x27;)),
                                                                      (&#x27;onehot&#x27;,
                                                                       OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                                      [&#x27;state&#x27;, &#x27;gender&#x27;]),
                                                     (&#x27;numerical&#x27;,
                                                      Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                                       SimpleImputer()),
                                                                      (&#x27;scaler&#x27;,
                                                                       StandardScaler())]),
                                                      [&#x27;age&#x27;, &#x27;weight&#x27;])])),
                    (&#x27;logisticregression&#x27;, LogisticRegression(max_iter=500))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-179" type="checkbox" ><label for="sk-estimator-id-179" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;columntransformer: ColumnTransformer<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.compose.ColumnTransformer.html">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class="sk-toggleable__content "><pre>ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                     Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                      SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                    strategy=&#x27;constant&#x27;)),
                                                     (&#x27;onehot&#x27;,
                                                      OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                     [&#x27;state&#x27;, &#x27;gender&#x27;]),
                                    (&#x27;numerical&#x27;,
                                     Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                      SimpleImputer()),
                                                     (&#x27;scaler&#x27;, StandardScaler())]),
                                     [&#x27;age&#x27;, &#x27;weight&#x27;])])</pre></div> </div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-180" type="checkbox" ><label for="sk-estimator-id-180" class="sk-toggleable__label  sk-toggleable__label-arrow ">categorical</label><div class="sk-toggleable__content "><pre>[&#x27;state&#x27;, &#x27;gender&#x27;]</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-181" type="checkbox" ><label for="sk-estimator-id-181" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;SimpleImputer<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.impute.SimpleImputer.html">?<span>Documentation for SimpleImputer</span></a></label><div class="sk-toggleable__content "><pre>SimpleImputer(fill_value=&#x27;missing&#x27;, strategy=&#x27;constant&#x27;)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-182" type="checkbox" ><label for="sk-estimator-id-182" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;OneHotEncoder<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.OneHotEncoder.html">?<span>Documentation for OneHotEncoder</span></a></label><div class="sk-toggleable__content "><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-183" type="checkbox" ><label for="sk-estimator-id-183" class="sk-toggleable__label  sk-toggleable__label-arrow ">numerical</label><div class="sk-toggleable__content "><pre>[&#x27;age&#x27;, &#x27;weight&#x27;]</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-184" type="checkbox" ><label for="sk-estimator-id-184" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;SimpleImputer<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.impute.SimpleImputer.html">?<span>Documentation for SimpleImputer</span></a></label><div class="sk-toggleable__content "><pre>SimpleImputer()</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-185" type="checkbox" ><label for="sk-estimator-id-185" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;StandardScaler<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html">?<span>Documentation for StandardScaler</span></a></label><div class="sk-toggleable__content "><pre>StandardScaler()</pre></div> </div></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-186" type="checkbox" ><label for="sk-estimator-id-186" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;LogisticRegression<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html">?<span>Documentation for LogisticRegression</span></a></label><div class="sk-toggleable__content "><pre>LogisticRegression(max_iter=500)</pre></div> </div></div></div></div></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 128-134

Displaying a Grid Search over a Pipeline with a Classifier
###############################################################################
 This section constructs a :class:`~sklearn.model_selection.GridSearchCV`
 over a :class:`~sklearn.pipeline.Pipeline` with
 :class:`~sklearn.ensemble.RandomForestClassifier` and displays its visual
 representation.

.. GENERATED FROM PYTHON SOURCE LINES 134-181

.. code-block:: Python


    import numpy as np

    from sklearn.compose import ColumnTransformer
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.impute import SimpleImputer
    from sklearn.model_selection import GridSearchCV
    from sklearn.pipeline import Pipeline, make_pipeline
    from sklearn.preprocessing import OneHotEncoder, StandardScaler

    numeric_preprocessor = Pipeline(
        steps=[
            ("imputation_mean", SimpleImputer(missing_values=np.nan, strategy="mean")),
            ("scaler", StandardScaler()),
        ]
    )

    categorical_preprocessor = Pipeline(
        steps=[
            (
                "imputation_constant",
                SimpleImputer(fill_value="missing", strategy="constant"),
            ),
            ("onehot", OneHotEncoder(handle_unknown="ignore")),
        ]
    )

    preprocessor = ColumnTransformer(
        [
            ("categorical", categorical_preprocessor, ["state", "gender"]),
            ("numerical", numeric_preprocessor, ["age", "weight"]),
        ]
    )

    pipe = Pipeline(
        steps=[("preprocessor", preprocessor), ("classifier", RandomForestClassifier())]
    )

    param_grid = {
        "classifier__n_estimators": [200, 500],
        "classifier__max_features": ["auto", "sqrt", "log2"],
        "classifier__max_depth": [4, 5, 6, 7, 8],
        "classifier__criterion": ["gini", "entropy"],
    }

    grid_search = GridSearchCV(pipe, param_grid=param_grid, n_jobs=1)
    grid_search  # click on the diagram below to see the details of each step





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <style>#sk-container-id-43 {
      /* Definition of color scheme common for light and dark mode */
      --sklearn-color-text: black;
      --sklearn-color-line: gray;
      /* Definition of color scheme for unfitted estimators */
      --sklearn-color-unfitted-level-0: #fff5e6;
      --sklearn-color-unfitted-level-1: #f6e4d2;
      --sklearn-color-unfitted-level-2: #ffe0b3;
      --sklearn-color-unfitted-level-3: chocolate;
      /* Definition of color scheme for fitted estimators */
      --sklearn-color-fitted-level-0: #f0f8ff;
      --sklearn-color-fitted-level-1: #d4ebff;
      --sklearn-color-fitted-level-2: #b3dbfd;
      --sklearn-color-fitted-level-3: cornflowerblue;

      /* Specific color for light theme */
      --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
      --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
      --sklearn-color-icon: #696969;

      @media (prefers-color-scheme: dark) {
        /* Redefinition of color scheme for dark theme */
        --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
        --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
        --sklearn-color-icon: #878787;
      }
    }

    #sk-container-id-43 {
      color: var(--sklearn-color-text);
    }

    #sk-container-id-43 pre {
      padding: 0;
    }

    #sk-container-id-43 input.sk-hidden--visually {
      border: 0;
      clip: rect(1px 1px 1px 1px);
      clip: rect(1px, 1px, 1px, 1px);
      height: 1px;
      margin: -1px;
      overflow: hidden;
      padding: 0;
      position: absolute;
      width: 1px;
    }

    #sk-container-id-43 div.sk-dashed-wrapped {
      border: 1px dashed var(--sklearn-color-line);
      margin: 0 0.4em 0.5em 0.4em;
      box-sizing: border-box;
      padding-bottom: 0.4em;
      background-color: var(--sklearn-color-background);
    }

    #sk-container-id-43 div.sk-container {
      /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
         but bootstrap.min.css set `[hidden] { display: none !important; }`
         so we also need the `!important` here to be able to override the
         default hidden behavior on the sphinx rendered scikit-learn.org.
         See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
      display: inline-block !important;
      position: relative;
    }

    #sk-container-id-43 div.sk-text-repr-fallback {
      display: none;
    }

    div.sk-parallel-item,
    div.sk-serial,
    div.sk-item {
      /* draw centered vertical line to link estimators */
      background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
      background-size: 2px 100%;
      background-repeat: no-repeat;
      background-position: center center;
    }

    /* Parallel-specific style estimator block */

    #sk-container-id-43 div.sk-parallel-item::after {
      content: "";
      width: 100%;
      border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
      flex-grow: 1;
    }

    #sk-container-id-43 div.sk-parallel {
      display: flex;
      align-items: stretch;
      justify-content: center;
      background-color: var(--sklearn-color-background);
      position: relative;
    }

    #sk-container-id-43 div.sk-parallel-item {
      display: flex;
      flex-direction: column;
    }

    #sk-container-id-43 div.sk-parallel-item:first-child::after {
      align-self: flex-end;
      width: 50%;
    }

    #sk-container-id-43 div.sk-parallel-item:last-child::after {
      align-self: flex-start;
      width: 50%;
    }

    #sk-container-id-43 div.sk-parallel-item:only-child::after {
      width: 0;
    }

    /* Serial-specific style estimator block */

    #sk-container-id-43 div.sk-serial {
      display: flex;
      flex-direction: column;
      align-items: center;
      background-color: var(--sklearn-color-background);
      padding-right: 1em;
      padding-left: 1em;
    }


    /* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
    clickable and can be expanded/collapsed.
    - Pipeline and ColumnTransformer use this feature and define the default style
    - Estimators will overwrite some part of the style using the `sk-estimator` class
    */

    /* Pipeline and ColumnTransformer style (default) */

    #sk-container-id-43 div.sk-toggleable {
      /* Default theme specific background. It is overwritten whether we have a
      specific estimator or a Pipeline/ColumnTransformer */
      background-color: var(--sklearn-color-background);
    }

    /* Toggleable label */
    #sk-container-id-43 label.sk-toggleable__label {
      cursor: pointer;
      display: block;
      width: 100%;
      margin-bottom: 0;
      padding: 0.5em;
      box-sizing: border-box;
      text-align: center;
    }

    #sk-container-id-43 label.sk-toggleable__label-arrow:before {
      /* Arrow on the left of the label */
      content: "▸";
      float: left;
      margin-right: 0.25em;
      color: var(--sklearn-color-icon);
    }

    #sk-container-id-43 label.sk-toggleable__label-arrow:hover:before {
      color: var(--sklearn-color-text);
    }

    /* Toggleable content - dropdown */

    #sk-container-id-43 div.sk-toggleable__content {
      max-height: 0;
      max-width: 0;
      overflow: hidden;
      text-align: left;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-43 div.sk-toggleable__content.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-43 div.sk-toggleable__content pre {
      margin: 0.2em;
      border-radius: 0.25em;
      color: var(--sklearn-color-text);
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-43 div.sk-toggleable__content.fitted pre {
      /* unfitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    #sk-container-id-43 input.sk-toggleable__control:checked~div.sk-toggleable__content {
      /* Expand drop-down */
      max-height: 200px;
      max-width: 100%;
      overflow: auto;
    }

    #sk-container-id-43 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
      content: "▾";
    }

    /* Pipeline/ColumnTransformer-specific style */

    #sk-container-id-43 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-43 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator-specific style */

    /* Colorize estimator box */
    #sk-container-id-43 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-43 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    #sk-container-id-43 div.sk-label label.sk-toggleable__label,
    #sk-container-id-43 div.sk-label label {
      /* The background is the default theme color */
      color: var(--sklearn-color-text-on-default-background);
    }

    /* On hover, darken the color of the background */
    #sk-container-id-43 div.sk-label:hover label.sk-toggleable__label {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    /* Label box, darken color on hover, fitted */
    #sk-container-id-43 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
      color: var(--sklearn-color-text);
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Estimator label */

    #sk-container-id-43 div.sk-label label {
      font-family: monospace;
      font-weight: bold;
      display: inline-block;
      line-height: 1.2em;
    }

    #sk-container-id-43 div.sk-label-container {
      text-align: center;
    }

    /* Estimator-specific */
    #sk-container-id-43 div.sk-estimator {
      font-family: monospace;
      border: 1px dotted var(--sklearn-color-border-box);
      border-radius: 0.25em;
      box-sizing: border-box;
      margin-bottom: 0.5em;
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-0);
    }

    #sk-container-id-43 div.sk-estimator.fitted {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-0);
    }

    /* on hover */
    #sk-container-id-43 div.sk-estimator:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-2);
    }

    #sk-container-id-43 div.sk-estimator.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-2);
    }

    /* Specification for estimator info (e.g. "i" and "?") */

    /* Common style for "i" and "?" */

    .sk-estimator-doc-link,
    a:link.sk-estimator-doc-link,
    a:visited.sk-estimator-doc-link {
      float: right;
      font-size: smaller;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1em;
      height: 1em;
      width: 1em;
      text-decoration: none !important;
      margin-left: 1ex;
      /* unfitted */
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
      color: var(--sklearn-color-unfitted-level-1);
    }

    .sk-estimator-doc-link.fitted,
    a:link.sk-estimator-doc-link.fitted,
    a:visited.sk-estimator-doc-link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    div.sk-estimator:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover,
    div.sk-label-container:hover .sk-estimator-doc-link:hover,
    .sk-estimator-doc-link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover,
    div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
    .sk-estimator-doc-link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    /* Span, style for the box shown on hovering the info icon */
    .sk-estimator-doc-link span {
      display: none;
      z-index: 9999;
      position: relative;
      font-weight: normal;
      right: .2ex;
      padding: .5ex;
      margin: .5ex;
      width: min-content;
      min-width: 20ex;
      max-width: 50ex;
      color: var(--sklearn-color-text);
      box-shadow: 2pt 2pt 4pt #999;
      /* unfitted */
      background: var(--sklearn-color-unfitted-level-0);
      border: .5pt solid var(--sklearn-color-unfitted-level-3);
    }

    .sk-estimator-doc-link.fitted span {
      /* fitted */
      background: var(--sklearn-color-fitted-level-0);
      border: var(--sklearn-color-fitted-level-3);
    }

    .sk-estimator-doc-link:hover span {
      display: block;
    }

    /* "?"-specific style due to the `<a>` HTML tag */

    #sk-container-id-43 a.estimator_doc_link {
      float: right;
      font-size: 1rem;
      line-height: 1em;
      font-family: monospace;
      background-color: var(--sklearn-color-background);
      border-radius: 1rem;
      height: 1rem;
      width: 1rem;
      text-decoration: none;
      /* unfitted */
      color: var(--sklearn-color-unfitted-level-1);
      border: var(--sklearn-color-unfitted-level-1) 1pt solid;
    }

    #sk-container-id-43 a.estimator_doc_link.fitted {
      /* fitted */
      border: var(--sklearn-color-fitted-level-1) 1pt solid;
      color: var(--sklearn-color-fitted-level-1);
    }

    /* On hover */
    #sk-container-id-43 a.estimator_doc_link:hover {
      /* unfitted */
      background-color: var(--sklearn-color-unfitted-level-3);
      color: var(--sklearn-color-background);
      text-decoration: none;
    }

    #sk-container-id-43 a.estimator_doc_link.fitted:hover {
      /* fitted */
      background-color: var(--sklearn-color-fitted-level-3);
    }
    </style><div id="sk-container-id-43" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>GridSearchCV(estimator=Pipeline(steps=[(&#x27;preprocessor&#x27;,
                                            ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                                                             Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                                                              SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                                                            strategy=&#x27;constant&#x27;)),
                                                                                             (&#x27;onehot&#x27;,
                                                                                              OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                                                             [&#x27;state&#x27;,
                                                                              &#x27;gender&#x27;]),
                                                                            (&#x27;numerical&#x27;,
                                                                             Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                                                              SimpleImputer()),
                                                                                             (&#x27;scaler&#x27;,
                                                                                              StandardScaler())]),
                                                                             [&#x27;age&#x27;,
                                                                              &#x27;weight&#x27;])])),
                                           (&#x27;classifier&#x27;,
                                            RandomForestClassifier())]),
                 n_jobs=1,
                 param_grid={&#x27;classifier__criterion&#x27;: [&#x27;gini&#x27;, &#x27;entropy&#x27;],
                             &#x27;classifier__max_depth&#x27;: [4, 5, 6, 7, 8],
                             &#x27;classifier__max_features&#x27;: [&#x27;auto&#x27;, &#x27;sqrt&#x27;, &#x27;log2&#x27;],
                             &#x27;classifier__n_estimators&#x27;: [200, 500]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-187" type="checkbox" ><label for="sk-estimator-id-187" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;&nbsp;GridSearchCV<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.model_selection.GridSearchCV.html">?<span>Documentation for GridSearchCV</span></a><span class="sk-estimator-doc-link ">i<span>Not fitted</span></span></label><div class="sk-toggleable__content "><pre>GridSearchCV(estimator=Pipeline(steps=[(&#x27;preprocessor&#x27;,
                                            ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                                                             Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                                                              SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                                                            strategy=&#x27;constant&#x27;)),
                                                                                             (&#x27;onehot&#x27;,
                                                                                              OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                                                             [&#x27;state&#x27;,
                                                                              &#x27;gender&#x27;]),
                                                                            (&#x27;numerical&#x27;,
                                                                             Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                                                              SimpleImputer()),
                                                                                             (&#x27;scaler&#x27;,
                                                                                              StandardScaler())]),
                                                                             [&#x27;age&#x27;,
                                                                              &#x27;weight&#x27;])])),
                                           (&#x27;classifier&#x27;,
                                            RandomForestClassifier())]),
                 n_jobs=1,
                 param_grid={&#x27;classifier__criterion&#x27;: [&#x27;gini&#x27;, &#x27;entropy&#x27;],
                             &#x27;classifier__max_depth&#x27;: [4, 5, 6, 7, 8],
                             &#x27;classifier__max_features&#x27;: [&#x27;auto&#x27;, &#x27;sqrt&#x27;, &#x27;log2&#x27;],
                             &#x27;classifier__n_estimators&#x27;: [200, 500]})</pre></div> </div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-188" type="checkbox" ><label for="sk-estimator-id-188" class="sk-toggleable__label  sk-toggleable__label-arrow ">estimator: Pipeline</label><div class="sk-toggleable__content "><pre>Pipeline(steps=[(&#x27;preprocessor&#x27;,
                     ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                                      Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                                       SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                                     strategy=&#x27;constant&#x27;)),
                                                                      (&#x27;onehot&#x27;,
                                                                       OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                                      [&#x27;state&#x27;, &#x27;gender&#x27;]),
                                                     (&#x27;numerical&#x27;,
                                                      Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                                       SimpleImputer()),
                                                                      (&#x27;scaler&#x27;,
                                                                       StandardScaler())]),
                                                      [&#x27;age&#x27;, &#x27;weight&#x27;])])),
                    (&#x27;classifier&#x27;, RandomForestClassifier())])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-189" type="checkbox" ><label for="sk-estimator-id-189" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;preprocessor: ColumnTransformer<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.compose.ColumnTransformer.html">?<span>Documentation for preprocessor: ColumnTransformer</span></a></label><div class="sk-toggleable__content "><pre>ColumnTransformer(transformers=[(&#x27;categorical&#x27;,
                                     Pipeline(steps=[(&#x27;imputation_constant&#x27;,
                                                      SimpleImputer(fill_value=&#x27;missing&#x27;,
                                                                    strategy=&#x27;constant&#x27;)),
                                                     (&#x27;onehot&#x27;,
                                                      OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),
                                     [&#x27;state&#x27;, &#x27;gender&#x27;]),
                                    (&#x27;numerical&#x27;,
                                     Pipeline(steps=[(&#x27;imputation_mean&#x27;,
                                                      SimpleImputer()),
                                                     (&#x27;scaler&#x27;, StandardScaler())]),
                                     [&#x27;age&#x27;, &#x27;weight&#x27;])])</pre></div> </div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-190" type="checkbox" ><label for="sk-estimator-id-190" class="sk-toggleable__label  sk-toggleable__label-arrow ">categorical</label><div class="sk-toggleable__content "><pre>[&#x27;state&#x27;, &#x27;gender&#x27;]</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-191" type="checkbox" ><label for="sk-estimator-id-191" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;SimpleImputer<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.impute.SimpleImputer.html">?<span>Documentation for SimpleImputer</span></a></label><div class="sk-toggleable__content "><pre>SimpleImputer(fill_value=&#x27;missing&#x27;, strategy=&#x27;constant&#x27;)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-192" type="checkbox" ><label for="sk-estimator-id-192" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;OneHotEncoder<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.OneHotEncoder.html">?<span>Documentation for OneHotEncoder</span></a></label><div class="sk-toggleable__content "><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div> </div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-193" type="checkbox" ><label for="sk-estimator-id-193" class="sk-toggleable__label  sk-toggleable__label-arrow ">numerical</label><div class="sk-toggleable__content "><pre>[&#x27;age&#x27;, &#x27;weight&#x27;]</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-194" type="checkbox" ><label for="sk-estimator-id-194" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;SimpleImputer<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.impute.SimpleImputer.html">?<span>Documentation for SimpleImputer</span></a></label><div class="sk-toggleable__content "><pre>SimpleImputer()</pre></div> </div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-195" type="checkbox" ><label for="sk-estimator-id-195" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;StandardScaler<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html">?<span>Documentation for StandardScaler</span></a></label><div class="sk-toggleable__content "><pre>StandardScaler()</pre></div> </div></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator  sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-196" type="checkbox" ><label for="sk-estimator-id-196" class="sk-toggleable__label  sk-toggleable__label-arrow ">&nbsp;RandomForestClassifier<a class="sk-estimator-doc-link " rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html">?<span>Documentation for RandomForestClassifier</span></a></label><div class="sk-toggleable__content "><pre>RandomForestClassifier()</pre></div> </div></div></div></div></div></div></div></div></div></div></div>
    </div>
    <br />
    <br />


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.. _sphx_glr_download_auto_examples_miscellaneous_plot_pipeline_display.py:

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

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

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


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.. only:: html

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

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