A stacked area chart displays multiple data series as areas stacked on top of each other, with each series starting where the previous one ends. This visualization emphasizes both individual contributions and cumulative totals over a continuous axis (typically time). It is ideal for showing how parts contribute to a whole while tracking changes over time, making patterns of composition and overall trends immediately visible.
""" anyplot.ai
area-stacked: Stacked Area Chart
Library: altair 6.1.0 | Python 3.13.13
Quality: 92/100 | Updated: 2026-05-07
"""
import os
import altair as alt
import numpy as np
import pandas as pd
# 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"
# Data: Monthly revenue by product category over two years
np.random.seed(42)
months = pd.date_range("2023-01", periods=24, freq="MS")
# Generate realistic revenue data with trends
base_software = 120 + np.cumsum(np.random.randn(24) * 5)
base_hardware = 80 + np.cumsum(np.random.randn(24) * 4)
base_services = 50 + np.cumsum(np.random.randn(24) * 3)
base_support = 30 + np.cumsum(np.random.randn(24) * 2)
# Ensure all values are positive
software = np.maximum(base_software, 20)
hardware = np.maximum(base_hardware, 15)
services = np.maximum(base_services, 10)
support = np.maximum(base_support, 5)
# Create long-form data for Altair
df = pd.DataFrame(
{
"Month": list(months) * 4,
"Revenue": np.concatenate([software, hardware, services, support]),
"Category": (["Software"] * 24 + ["Hardware"] * 24 + ["Services"] * 24 + ["Support"] * 24),
}
)
# Define category order (largest at bottom for easier reading)
# Stack order: 1=bottom, 4=top
category_order = ["Software", "Hardware", "Services", "Support"]
stack_order = {"Software": 1, "Hardware": 2, "Services": 3, "Support": 4}
df["StackOrder"] = df["Category"].map(stack_order)
# Okabe-Ito palette: first series ALWAYS #009E73
colors = ["#009E73", "#C475FD", "#4467A3", "#BD8233"]
# Create stacked area chart
chart = (
alt.Chart(df)
.mark_area(opacity=0.85, line=alt.MarkConfig(strokeWidth=2))
.encode(
x=alt.X(
"Month:T",
title="Month",
axis=alt.Axis(
labelFontSize=18, titleFontSize=22, format="%b %Y", labelAngle=-45, labelColor=INK_SOFT, titleColor=INK
),
),
y=alt.Y(
"Revenue:Q",
title="Revenue ($ thousands)",
stack="zero",
axis=alt.Axis(labelFontSize=18, titleFontSize=22, labelColor=INK_SOFT, titleColor=INK),
),
color=alt.Color(
"Category:N",
scale=alt.Scale(domain=category_order, range=colors),
legend=alt.Legend(
title="Product Category",
titleFontSize=20,
labelFontSize=18,
orient="right",
symbolSize=300,
symbolStrokeWidth=0,
labelColor=INK_SOFT,
titleColor=INK,
fillColor=ELEVATED_BG,
strokeColor=INK_SOFT,
),
),
order=alt.Order("StackOrder:Q", sort="ascending"),
tooltip=[
alt.Tooltip("Month:T", title="Month", format="%B %Y"),
alt.Tooltip("Category:N", title="Category"),
alt.Tooltip("Revenue:Q", title="Revenue ($k)", format=".1f"),
],
)
.properties(
width=1600,
height=900,
background=PAGE_BG,
title=alt.Title("area-stacked · altair · anyplot.ai", fontSize=28, anchor="middle", color=INK),
)
.configure_axis(domainColor=INK_SOFT, tickColor=INK_SOFT, grid=True, gridColor=INK, gridOpacity=0.10)
.configure_view(stroke=None, fill=PAGE_BG)
)
# Save as PNG (1600 * 3 = 4800, 900 * 3 = 2700)
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
# Save as HTML for interactivity
chart.interactive().save(f"plot-{THEME}.html")
Part of Stacked Area Chart on anyplot.ai.