:orphan:
:html_theme.sidebar_secondary.remove:

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

.. _gallery_scatter_with_loess:


Scatter Plot with LOESS Lines
-----------------------------
This example shows how to add a trend line to a scatter plot using 
the LOESS transform (LOcally Estimated Scatter Plot Smoothing).


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



    import altair as alt
    import pandas as pd
    import numpy as np

    np.random.seed(1)

    source = pd.DataFrame({
        'x': np.arange(100),
        'A': np.random.randn(100).cumsum(),
        'B': np.random.randn(100).cumsum(),
        'C': np.random.randn(100).cumsum(),
    })

    base = alt.Chart(source).mark_circle(opacity=0.5).transform_fold(
        fold=['A', 'B', 'C'], 
        as_=['category', 'y']
    ).encode(
        alt.X('x:Q'), 
        alt.Y('y:Q'), 
        alt.Color('category:N')
    )

    base + base.transform_loess('x', 'y', groupby=['category']).mark_line(size=4)
    # 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
            import pandas as pd
            import numpy as np

            np.random.seed(1)

            source = pd.DataFrame({
                'x': np.arange(100),
                'A': np.random.randn(100).cumsum(),
                'B': np.random.randn(100).cumsum(),
                'C': np.random.randn(100).cumsum(),
            })

            base = alt.Chart(source).mark_circle(opacity=0.5).transform_fold(
                fold=['A', 'B', 'C'], 
                as_=['category', 'y']
            ).encode(
                alt.X('x:Q'), 
                alt.Y('y:Q'), 
                alt.Color('category:N')
            )

            base + base.transform_loess('x', 'y', groupby=['category']).mark_line(size=4)


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

        .. code:: python



            import altair as alt
            import pandas as pd
            import numpy as np

            np.random.seed(1)

            source = pd.DataFrame({
                'x': np.arange(100),
                'A': np.random.randn(100).cumsum(),
                'B': np.random.randn(100).cumsum(),
                'C': np.random.randn(100).cumsum(),
            })

            base = alt.Chart(source).mark_circle(opacity=0.5).transform_fold(
                fold=['A', 'B', 'C'], 
                as_=['category', 'y']
            ).encode(
                alt.X('x:Q'), 
                alt.Y('y:Q'), 
                alt.Color('category:N')
            )

            base + base.transform_loess('x', 'y', groupby=['category']).mark_line(size=4)
            # No channel encoding options are specified in this chart
            # so the code is the same as for the method-based syntax.