:orphan:
:html_theme.sidebar_secondary.remove:

.. This document is auto-generated by the altair-gallery extension. Do not modify directly.

.. _gallery_normed_parallel_coordinates:


Normalized Parallel Coordinates
-------------------------------
A `Parallel Coordinates <https://en.wikipedia.org/wiki/Parallel_coordinates>`_
chart is a chart that lets you visualize the individual data points by drawing
a single line for each of them.

Such a chart can be created in Altair by first transforming the data into a
suitable representation.

This example shows a modified parallel coordinates chart with the Iris dataset,
where the y-axis shows the value after min-max rather than the raw value. It's a
simplified Altair version of `the VegaLite version <https://vega.github.io/vega-lite/examples/parallel_coordinate.html>`_


.. altair-plot::
    :remove-code:
    


    import altair as alt
    from vega_datasets import data
    from altair import datum

    source = data.iris()

    alt.Chart(source).transform_window(
        index='count()'
    ).transform_fold(
        ['petalLength', 'petalWidth', 'sepalLength', 'sepalWidth']
    ).transform_joinaggregate(
         min='min(value)', 
         max='max(value)',
         groupby=['key']
    ).transform_calculate(
        minmax_value=(datum.value-datum.min)/(datum.max-datum.min), 
        mid=(datum.min+datum.max)/2
    ).mark_line().encode(
        x='key:N',
        y='minmax_value:Q',
        color='species:N',
        detail='index:N',
        opacity=alt.value(0.5)
    ).properties(width=500)


    # No channel encoding options are specified in this chart
    # so the code is the same as for the method-based syntax.


.. tab-set::

    .. tab-item:: Method syntax
        :sync: method

        .. code:: python


            import altair as alt
            from vega_datasets import data
            from altair import datum

            source = data.iris()

            alt.Chart(source).transform_window(
                index='count()'
            ).transform_fold(
                ['petalLength', 'petalWidth', 'sepalLength', 'sepalWidth']
            ).transform_joinaggregate(
                 min='min(value)', 
                 max='max(value)',
                 groupby=['key']
            ).transform_calculate(
                minmax_value=(datum.value-datum.min)/(datum.max-datum.min), 
                mid=(datum.min+datum.max)/2
            ).mark_line().encode(
                x='key:N',
                y='minmax_value:Q',
                color='species:N',
                detail='index:N',
                opacity=alt.value(0.5)
            ).properties(width=500)




    .. tab-item:: Attribute syntax
        :sync: attribute

        .. code:: python


            import altair as alt
            from vega_datasets import data
            from altair import datum

            source = data.iris()

            alt.Chart(source).transform_window(
                index='count()'
            ).transform_fold(
                ['petalLength', 'petalWidth', 'sepalLength', 'sepalWidth']
            ).transform_joinaggregate(
                 min='min(value)', 
                 max='max(value)',
                 groupby=['key']
            ).transform_calculate(
                minmax_value=(datum.value-datum.min)/(datum.max-datum.min), 
                mid=(datum.min+datum.max)/2
            ).mark_line().encode(
                x='key:N',
                y='minmax_value:Q',
                color='species:N',
                detail='index:N',
                opacity=alt.value(0.5)
            ).properties(width=500)


            # No channel encoding options are specified in this chart
            # so the code is the same as for the method-based syntax.