Scatter Plot with LOWESS Regression — Altair

A scatter plot with a LOWESS (Locally Weighted Scatterplot Smoothing) regression curve overlaid. LOWESS is a non-parametric method that fits smooth curves by performing local weighted regressions at each point, adapting to local data patterns without assuming a specific functional form. This makes it ideal for exploring complex relationships where the underlying pattern is unknown or varies across the data range.

Scatter Plot with LOWESS Regression rendered with Altair

Python source (Altair)

""" anyplot.ai
scatter-regression-lowess: Scatter Plot with LOWESS Regression
Library: altair 6.1.0 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-14
"""

import os
import sys

import numpy as np
import pandas as pd
from statsmodels.nonparametric.smoothers_lowess import lowess


# Handle module name conflict by removing current directory from import path
original_path = sys.path[:]
sys.path = [p for p in sys.path if p not in ("", ".")]
import altair as alt


sys.path = original_path


# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"

# Data - complex non-linear relationship
np.random.seed(42)
n = 200
x = np.linspace(0, 10, n)
# Non-linear pattern: sine wave with trend and noise
y = 2 * np.sin(x * 0.8) + 0.5 * x + np.random.normal(0, 0.8, n)

# Create DataFrame for scatter points
df = pd.DataFrame({"x": x, "y": y})

# Compute LOWESS smoothed values
lowess_result = lowess(y, x, frac=0.3, return_sorted=True)
df_lowess = pd.DataFrame({"x": lowess_result[:, 0], "y_lowess": lowess_result[:, 1]})

# Scatter points layer with filled markers and tooltips
scatter = (
    alt.Chart(df)
    .mark_circle(size=100, opacity=0.6, color="#009E73")
    .encode(
        x=alt.X("x:Q", title="Independent Variable (meters)"),
        y=alt.Y("y:Q", title="Dependent Variable (kg)"),
        tooltip=["x:Q", "y:Q"],
    )
)

# LOWESS curve layer
lowess_line = (
    alt.Chart(df_lowess).mark_line(strokeWidth=4, color="#FFD43B").encode(x=alt.X("x:Q"), y=alt.Y("y_lowess:Q"))
)

# Combine layers and apply theme-adaptive styling
chart = (
    (scatter + lowess_line)
    .properties(
        width=1600,
        height=900,
        background=PAGE_BG,
        title=alt.Title("scatter-regression-lowess · altair · anyplot.ai", fontSize=28),
    )
    .configure_axis(
        domainColor=INK_SOFT,
        tickColor=INK_SOFT,
        gridColor=INK,
        gridOpacity=0.10,
        labelColor=INK_SOFT,
        titleColor=INK,
        labelFontSize=18,
        titleFontSize=22,
    )
    .configure_view(fill=PAGE_BG, stroke=INK_SOFT, strokeWidth=0)
    .configure_title(color=INK)
)

# Save with theme-suffixed filenames
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")

Part of Scatter Plot with LOWESS Regression on anyplot.ai.

Scatter Plot with LOWESS Regression — Altair

Python source (Altair)

Other implementations