Stacked Histogram — Seaborn

A histogram showing multiple groups stacked on top of each other within each bin. The total bar height represents the combined frequency, while colored segments show individual group contributions.

Stacked Histogram rendered with Seaborn

Python source (Seaborn)

""" anyplot.ai
histogram-stacked: Stacked Histogram
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 89/100 | Updated: 2026-05-12
"""

import os

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns


# Get theme from environment
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"

# Set theme-aware colors
sns.set_theme(
    style="ticks",
    rc={
        "figure.facecolor": PAGE_BG,
        "axes.facecolor": PAGE_BG,
        "axes.edgecolor": INK_SOFT,
        "axes.labelcolor": INK,
        "text.color": INK,
        "xtick.color": INK_SOFT,
        "ytick.color": INK_SOFT,
        "grid.color": INK,
        "grid.alpha": 0.10,
        "legend.facecolor": ELEVATED_BG,
        "legend.edgecolor": INK_SOFT,
    },
)

# Data - Response times (ms) from three different server regions
np.random.seed(42)

# Generate response times for three server regions with different characteristics
region_a = np.random.normal(loc=45, scale=12, size=150)  # US East - faster
region_b = np.random.normal(loc=60, scale=15, size=180)  # Europe - medium
region_c = np.random.normal(loc=75, scale=18, size=120)  # Asia Pacific - slower

# Combine into DataFrame
df = pd.DataFrame(
    {
        "Response Time (ms)": np.concatenate([region_a, region_b, region_c]),
        "Region": (["US East"] * len(region_a) + ["Europe"] * len(region_b) + ["Asia Pacific"] * len(region_c)),
    }
)

# Plot
fig, ax = plt.subplots(figsize=(16, 9))

# Okabe-Ito palette for stacked histogram
IMPRINT = ["#009E73", "#C475FD", "#4467A3"]

# Stacked histogram using histplot with multiple='stack'
sns.histplot(
    data=df,
    x="Response Time (ms)",
    hue="Region",
    hue_order=["US East", "Europe", "Asia Pacific"],
    multiple="stack",
    bins=20,
    palette=IMPRINT,
    edgecolor="white",
    linewidth=0.8,
    alpha=0.9,
    ax=ax,
)

# Styling
ax.set_xlabel("Response Time (ms)", fontsize=20)
ax.set_ylabel("Frequency", fontsize=20)
ax.set_title("histogram-stacked · seaborn · anyplot.ai", fontsize=24)
ax.tick_params(axis="both", labelsize=16)
ax.grid(True, alpha=0.1, linestyle="-", axis="y")

# Adjust legend styling
legend = ax.get_legend()
legend.set_title("Server Region")
legend.get_title().set_fontsize(16)
for text in legend.get_texts():
    text.set_fontsize(14)

plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)

Part of Stacked Histogram on anyplot.ai.

Other implementations