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).

Method syntax

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)

Attribute syntax

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.