Histogram with KDE Overlay — Altair

A histogram with kernel density estimate (KDE) overlay combines discrete binning with continuous density estimation to visualize the distribution of continuous data. The histogram bars show frequency counts in each bin while the smooth KDE curve reveals the underlying probability density, making it easier to perceive the true shape of the distribution without binning artifacts.

Histogram with KDE Overlay rendered with Altair

Python source (Altair)

""" anyplot.ai
histogram-kde: Histogram with KDE Overlay
Library: altair 6.1.0 | Python 3.13.13
Quality: 93/100 | Updated: 2026-05-06
"""

import os

import altair as alt
import numpy as np
import pandas as pd
from scipy.stats import gaussian_kde


# Theme-adaptive 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"

# Okabe-Ito palette
BRAND = "#009E73"  # Position 1 - first series
ACCENT = "#954477"  # Position 7 - for KDE line

# Data - bimodal distribution for interesting KDE demonstration
np.random.seed(42)
values = np.concatenate([np.random.normal(loc=45, scale=8, size=300), np.random.normal(loc=72, scale=10, size=200)])

# Calculate histogram bins for density
hist, bin_edges = np.histogram(values, bins=30, density=True)
hist_df = pd.DataFrame({"bin_start": bin_edges[:-1], "bin_end": bin_edges[1:], "density": hist, "base": 0.0})

# Calculate KDE
kde = gaussian_kde(values, bw_method="scott")
x_kde = np.linspace(values.min() - 5, values.max() + 5, 200)
y_kde = kde(x_kde)
kde_df = pd.DataFrame({"x": x_kde, "density": y_kde})

# Histogram bars using Okabe-Ito brand color
histogram = (
    alt.Chart(hist_df)
    .mark_bar(opacity=0.6, color=BRAND)
    .encode(
        x=alt.X("bin_start:Q", title="Test Score", scale=alt.Scale(zero=False)),
        x2="bin_end:Q",
        y=alt.Y("density:Q", title="Density"),
        y2="base:Q",
    )
)

# KDE line using Okabe-Ito position 7
kde_line = alt.Chart(kde_df).mark_line(color=ACCENT, strokeWidth=4).encode(x=alt.X("x:Q"), y=alt.Y("density:Q"))

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

# Save PNG and HTML with theme suffix
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")

Part of Histogram with KDE Overlay on anyplot.ai.

Histogram with KDE Overlay — Altair

Python source (Altair)

Other implementations