Subplot Grid Layout — Altair

A customizable grid of multiple subplots allowing different plot types in each cell, with shared or independent axes. Unlike faceted plots that repeat the same visualization for data subsets, subplot grids enable combining distinct visualizations (scatter, line, bar, histogram, etc.) into a cohesive multi-panel figure for comprehensive data presentation.

Subplot Grid Layout rendered with Altair

Python source (Altair)

""" anyplot.ai
subplot-grid: Subplot Grid Layout
Library: altair 6.1.0 | Python 3.13.13
Quality: 98/100 | Updated: 2026-05-13
"""

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"

# Okabe-Ito palette (first series always #009E73)
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD"]
BRAND = IMPRINT[0]
SECONDARY = IMPRINT[1]

# Data
np.random.seed(42)

# Panel 1: Scatter plot - Product metrics
n_products = 50
products_df = pd.DataFrame(
    {
        "Units Sold": np.random.randint(100, 1000, n_products),
        "Revenue ($K)": np.random.uniform(10, 100, n_products),
        "Product": [f"P{i}" for i in range(n_products)],
    }
)

# Panel 2: Line plot - Monthly performance
months = pd.date_range("2024-01", periods=12, freq="ME")
monthly_df = pd.DataFrame(
    {"Month": months, "Sales": np.cumsum(np.random.normal(50, 15, 12)) + 500, "Target": np.linspace(500, 700, 12)}
)
monthly_df = monthly_df.melt(id_vars=["Month"], var_name="Metric", value_name="Value")

# Panel 3: Bar plot - Regional performance
regions_df = pd.DataFrame(
    {"Region": ["North", "South", "East", "West", "Central"], "Performance": [85, 72, 91, 68, 79]}
)

# Panel 4: Histogram - Distribution of order values
order_values = np.random.lognormal(mean=4.5, sigma=0.5, size=200)
histogram_df = pd.DataFrame({"Order Value ($)": order_values})

# Chart 1: Scatter plot
scatter = (
    alt.Chart(products_df)
    .mark_circle(size=120, opacity=0.7)
    .encode(
        x=alt.X("Units Sold:Q", title="Units Sold"),
        y=alt.Y("Revenue ($K):Q", title="Revenue ($K)"),
        color=alt.value(BRAND),
        tooltip=["Product", "Units Sold", "Revenue ($K)"],
    )
    .properties(width=750, height=420, title=alt.Title("Product Performance", fontSize=22, anchor="start"))
)

# Chart 2: Line plot
line = (
    alt.Chart(monthly_df)
    .mark_line(strokeWidth=3)
    .encode(
        x=alt.X("Month:T", title="Month"),
        y=alt.Y("Value:Q", title="Sales ($K)", scale=alt.Scale(zero=False)),
        color=alt.Color(
            "Metric:N",
            scale=alt.Scale(domain=["Sales", "Target"], range=[BRAND, SECONDARY]),
            legend=alt.Legend(title="Metric", titleFontSize=16, labelFontSize=14),
        ),
        strokeDash=alt.StrokeDash(
            "Metric:N", scale=alt.Scale(domain=["Sales", "Target"], range=[[0], [5, 5]]), legend=None
        ),
    )
    .properties(width=750, height=420, title=alt.Title("Monthly Sales Trend", fontSize=22, anchor="start"))
)

# Chart 3: Bar plot
bar = (
    alt.Chart(regions_df)
    .mark_bar(size=60)
    .encode(
        x=alt.X("Region:N", title="Region", axis=alt.Axis(labelAngle=0)),
        y=alt.Y("Performance:Q", title="Performance Score", scale=alt.Scale(domain=[0, 100])),
        color=alt.condition(alt.datum.Performance >= 80, alt.value(BRAND), alt.value(SECONDARY)),
        tooltip=["Region", "Performance"],
    )
    .properties(width=750, height=420, title=alt.Title("Regional Performance", fontSize=22, anchor="start"))
)

# Chart 4: Histogram
histogram = (
    alt.Chart(histogram_df)
    .mark_bar(opacity=0.8)
    .encode(
        x=alt.X("Order Value ($):Q", bin=alt.Bin(maxbins=25), title="Order Value ($)"),
        y=alt.Y("count():Q", title="Frequency"),
        color=alt.value(BRAND),
        tooltip=[alt.Tooltip("count()", title="Count")],
    )
    .properties(width=750, height=420, title=alt.Title("Order Value Distribution", fontSize=22, anchor="start"))
)

# Combine into 2x2 grid
row1 = alt.hconcat(scatter, line, spacing=60)
row2 = alt.hconcat(bar, histogram, spacing=60)

chart = (
    alt.vconcat(row1, row2, spacing=60)
    .properties(
        background=PAGE_BG,
        title=alt.Title("subplot-grid · altair · anyplot.ai", fontSize=28, anchor="middle", offset=20),
    )
    .configure_axis(
        labelFontSize=16,
        titleFontSize=18,
        gridOpacity=0.10,
        domainColor=INK_SOFT,
        tickColor=INK_SOFT,
        gridColor=INK,
        labelColor=INK_SOFT,
        titleColor=INK,
    )
    .configure_view(strokeWidth=0, fill=PAGE_BG)
    .configure_title(color=INK, fontSize=22)
    .configure_legend(
        fillColor=ELEVATED_BG,
        strokeColor=INK_SOFT,
        labelColor=INK_SOFT,
        titleColor=INK,
        titleFontSize=16,
        labelFontSize=14,
    )
)

# Save outputs
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")

Part of Subplot Grid Layout on anyplot.ai.

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