Grouped Bar Chart — plotnine

A grouped bar chart that displays multiple bars side-by-side for each category, enabling direct comparison of values across different groups within the same categorical dimension. This visualization excels at showing how different groups perform relative to each other across multiple categories, making patterns and differences immediately apparent. Grouped bar charts are essential for comparative analysis where you need to track multiple series against the same set of categories.

Grouped Bar Chart rendered with plotnine

Python source (plotnine)

""" anyplot.ai
bar-grouped: Grouped Bar Chart
Library: plotnine 0.15.4 | Python 3.13.13
Quality: 83/100 | Updated: 2026-05-06
"""

import os

import pandas as pd
from plotnine import (
    aes,
    element_line,
    element_rect,
    element_text,
    geom_bar,
    ggplot,
    ggsave,
    labs,
    position_dodge,
    scale_fill_manual,
    theme,
)


# 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"]

# Data - Quarterly revenue by product line
data = {
    "Quarter": ["Q1", "Q1", "Q1", "Q2", "Q2", "Q2", "Q3", "Q3", "Q3", "Q4", "Q4", "Q4"],
    "Product": [
        "Software",
        "Hardware",
        "Services",
        "Software",
        "Hardware",
        "Services",
        "Software",
        "Hardware",
        "Services",
        "Software",
        "Hardware",
        "Services",
    ],
    "Revenue": [120, 85, 45, 135, 92, 52, 148, 78, 61, 165, 88, 70],
}
df = pd.DataFrame(data)

# Ensure categorical order matches Okabe-Ito palette order
df["Product"] = pd.Categorical(df["Product"], categories=["Software", "Hardware", "Services"], ordered=True)

# Theme-adaptive chrome
anyplot_theme = theme(
    plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
    panel_background=element_rect(fill=PAGE_BG),
    panel_grid_major=element_line(color=INK_SOFT, size=0.3, alpha=0.10),
    panel_border=element_rect(color=INK_SOFT, fill=None),
    axis_title=element_text(size=20, color=INK),
    axis_text=element_text(size=16, color=INK_SOFT),
    axis_line=element_line(color=INK_SOFT),
    plot_title=element_text(size=24, color=INK),
    legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
    legend_text=element_text(size=16, color=INK_SOFT),
    legend_title=element_text(size=18, color=INK),
    figure_size=(16, 9),
)

# Plot
plot = (
    ggplot(df, aes(x="Quarter", y="Revenue", fill="Product"))
    + geom_bar(stat="identity", position=position_dodge(width=0.8), width=0.7)
    + scale_fill_manual(values=IMPRINT)
    + labs(x="Quarter", y="Revenue ($ millions)", title="bar-grouped · plotnine · anyplot.ai", fill="Product Line")
    + anyplot_theme
)

# Save
ggsave(plot, filename=f"plot-{THEME}.png", dpi=300, width=16, height=9)

Part of Grouped Bar Chart on anyplot.ai.

Other implementations