Stacked Bar Chart — plotnine

A stacked bar chart that displays multiple data series stacked on top of each other within each category, showing both individual component values and their cumulative totals. This visualization excels at revealing part-to-whole relationships while maintaining the ability to compare totals across categories. Stacked bar charts are particularly effective for composition analysis, where understanding how different components contribute to a whole is as important as comparing totals.

Stacked Bar Chart rendered with plotnine

Python source (plotnine)

""" anyplot.ai
bar-stacked: Stacked Bar Chart
Library: plotnine 0.15.4 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-09
"""

import os
import pathlib
import sys

import pandas as pd


# Remove local module from path to avoid shadowing the plotnine library
sys.path = [p for p in sys.path if "bar-stacked/implementations/python" not in p]

from plotnine import (
    aes,
    element_line,
    element_rect,
    element_text,
    geom_bar,
    geom_text,
    ggplot,
    labs,
    position_stack,
    scale_fill_manual,
    theme,
    theme_minimal,
)


# 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"

# Okabe-Ito palette (first series always #009E73)
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233"]

# Data - Quarterly sales by product category
data = {
    "Quarter": ["Q1", "Q2", "Q3", "Q4"] * 4,
    "Category": ["Electronics"] * 4 + ["Clothing"] * 4 + ["Home"] * 4 + ["Sports"] * 4,
    "Sales": [45, 52, 48, 68, 32, 38, 55, 42, 28, 31, 35, 38, 18, 22, 28, 25],
}

df = pd.DataFrame(data)

# Order categories for consistent stacking (largest at bottom)
category_order = ["Sports", "Home", "Clothing", "Electronics"]
df["Category"] = pd.Categorical(df["Category"], categories=category_order, ordered=True)

# Plot
plot = (
    ggplot(df, aes(x="Quarter", y="Sales", fill="Category"))
    + geom_bar(stat="identity", position="stack", width=0.7)
    + geom_text(aes(label="Sales"), position=position_stack(vjust=0.5), size=12, color="white", fontweight="bold")
    + scale_fill_manual(values=IMPRINT)
    + labs(title="bar-stacked · plotnine · anyplot.ai", x="Quarter", y="Sales (thousands USD)", fill="Category")
    + theme_minimal()
    + theme(
        figure_size=(16, 9),
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG),
        panel_grid_major=element_line(color=INK, size=0.3, alpha=0.10),
        panel_grid_minor=element_line(color=INK, size=0.2, alpha=0.05),
        panel_border=element_rect(color=INK_SOFT, fill=None),
        plot_title=element_text(size=24, weight="bold", color=INK),
        axis_title=element_text(size=20, color=INK),
        axis_text=element_text(size=16, color=INK_SOFT),
        legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
        legend_title=element_text(size=18, color=INK),
        legend_text=element_text(size=16, color=INK_SOFT),
        legend_position="right",
    )
)

# Save
output_dir = pathlib.Path(__file__).parent
plot.save(output_dir / f"plot-{THEME}.png", dpi=300, verbose=False)

Part of Stacked Bar Chart on anyplot.ai.

Other implementations