Overlapping Histograms — Altair

Overlapping histograms display multiple distributions on the same axes using semi-transparent bars, enabling direct visual comparison between groups. This technique reveals differences in central tendency, spread, and shape across categories while maintaining the familiar histogram format. The transparency allows viewers to see where distributions overlap and diverge.

Overlapping Histograms rendered with Altair

Python source (Altair)

""" anyplot.ai
histogram-overlapping: Overlapping Histograms
Library: altair 6.1.0 | Python 3.13.13
Quality: 88/100 | Updated: 2026-05-08
"""

import os
import sys


sys.path.insert(0, os.path.dirname(sys.executable) + "/../lib/python3.13/site-packages")

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


# Theme tokens (see prompts/default-style-guide.md "Background" + "Theme-adaptive Chrome")
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 (first series is ALWAYS #009E73)
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477"]

# Data: Employee response times (ms) by department
np.random.seed(42)

engineering = np.random.normal(loc=350, scale=80, size=150)
sales = np.random.normal(loc=420, scale=100, size=150)
support = np.random.normal(loc=280, scale=60, size=150)

df = pd.DataFrame(
    {
        "Response Time (ms)": np.concatenate([engineering, sales, support]),
        "Department": ["Engineering"] * 150 + ["Sales"] * 150 + ["Support"] * 150,
    }
)

# Plot - overlapping histograms with semi-transparent bars
chart = (
    alt.Chart(df)
    .mark_bar(opacity=0.5, binSpacing=0)
    .encode(
        x=alt.X(
            "Response Time (ms):Q",
            bin=alt.Bin(maxbins=25),
            title="Response Time (ms)",
            axis=alt.Axis(labelFontSize=18, titleFontSize=22),
        ),
        y=alt.Y("count():Q", title="Frequency", stack=None, axis=alt.Axis(labelFontSize=18, titleFontSize=22)),
        color=alt.Color(
            "Department:N",
            scale=alt.Scale(domain=["Engineering", "Sales", "Support"], range=IMPRINT[:3]),
            legend=alt.Legend(
                title="Department",
                titleFontSize=20,
                labelFontSize=18,
                orient="right",
                symbolSize=300,
                symbolStrokeWidth=0,
            ),
        ),
        tooltip=[alt.Tooltip("Department:N"), alt.Tooltip("count():Q", title="Count")],
    )
    .properties(
        width=1600,
        height=900,
        background=PAGE_BG,
        title=alt.Title("histogram-overlapping · altair · anyplot.ai", fontSize=28, anchor="middle", color=INK),
    )
    .configure_axis(
        domainColor=INK_SOFT, tickColor=INK_SOFT, gridColor=INK, gridOpacity=0.1, labelColor=INK_SOFT, titleColor=INK
    )
    .configure_view(fill=PAGE_BG, stroke=INK_SOFT)
    .configure_legend(fillColor=ELEVATED_BG, strokeColor=INK_SOFT, labelColor=INK_SOFT, titleColor=INK)
)

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

Part of Overlapping Histograms on anyplot.ai.

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