Stacked Bar Chart — lets-plot

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 lets-plot

Python source (lets-plot)

""" anyplot.ai
bar-stacked: Stacked Bar Chart
Library: letsplot 4.9.0 | Python 3.13.13
Quality: 88/100 | Updated: 2026-05-09
"""

import os

import pandas as pd
from lets_plot import *


LetsPlot.setup_html()

# 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"
RULE = "rgba(26,26,23,0.15)" if THEME == "light" else "rgba(240,239,232,0.15)"

# Okabe-Ito palette
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233"]

# Data: Quarterly sales by product category
data = {
    "quarter": ["Q1", "Q2", "Q3", "Q4"] * 4,
    "product": ["Electronics"] * 4 + ["Furniture"] * 4 + ["Clothing"] * 4 + ["Office Supplies"] * 4,
    "sales": [
        120,
        145,
        165,
        190,  # Electronics
        85,
        92,
        78,
        110,  # Furniture
        65,
        88,
        95,
        72,  # Clothing
        45,
        52,
        48,
        58,  # Office Supplies
    ],
}
df = pd.DataFrame(data)

# Create stacked bar chart with refined visual presentation
plot = (
    ggplot(df, aes(x="quarter", y="sales", fill="product"))
    + geom_bar(
        stat="identity",
        position="stack",
        width=0.65,
        color="white",
        size=0.3,
        tooltips=layer_tooltips().title("@product").line("Sales: @sales K$").format("sales", ".0f"),
    )
    + scale_fill_manual(values=IMPRINT)
    + labs(title="bar-stacked · letsplot · anyplot.ai", x="Quarter", y="Sales (Thousands $)", fill="Product")
    + theme(
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG),
        panel_grid_major_y=element_line(color=RULE, size=0.25),
        panel_grid_major_x=element_blank(),
        panel_grid_minor=element_blank(),
        axis_title=element_text(size=20, color=INK),
        axis_text=element_text(size=16, color=INK_SOFT),
        axis_ticks=element_blank(),
        axis_line_y=element_line(color=INK_SOFT, size=0.3),
        axis_line_x=element_line(color=INK_SOFT, size=0.3),
        plot_title=element_text(size=24, color=INK),
        legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT, size=0.3),
        legend_text=element_text(size=16, color=INK_SOFT),
        legend_title=element_text(size=16, color=INK),
        legend_position="right",
    )
    + ggsize(1600, 900)
)

# Save PNG (scale 3x for 4800 × 2700 px)
ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)

# Save HTML
ggsave(plot, f"plot-{THEME}.html", path=".")

Part of Stacked Bar Chart on anyplot.ai.

Stacked Bar Chart — lets-plot

Python source (lets-plot)

Other implementations