Density Contour Plot — Seaborn

A density contour plot (also known as a 2D KDE contour plot) displays the concentration of points in a 2D scatter plot using contour lines. The contours connect points of equal density, revealing clusters, patterns, and the overall bivariate distribution shape.

Density Contour Plot rendered with Seaborn

Renders

Python source (Seaborn)

""" anyplot.ai
contour-density: Density Contour Plot
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-16
"""

import os

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns


# Theme tokens (see prompts/default-style-guide.md)
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"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
SCATTER_COLOR = "#4A4A44" if THEME == "light" else "#9A9A94"

# Data - bivariate normal distributions with two clusters
np.random.seed(42)

# Main cluster
n1 = 300
x1 = np.random.normal(loc=5, scale=1.5, size=n1)
y1 = np.random.normal(loc=5, scale=1.5, size=n1)

# Secondary cluster
n2 = 150
x2 = np.random.normal(loc=9, scale=1.0, size=n2)
y2 = np.random.normal(loc=8, scale=1.0, size=n2)

# Combine clusters
x = np.concatenate([x1, x2])
y = np.concatenate([y1, y2])

# Configure seaborn theme with theme-adaptive colors
sns.set_theme(
    style="ticks",
    rc={
        "figure.facecolor": PAGE_BG,
        "axes.facecolor": PAGE_BG,
        "axes.edgecolor": INK_SOFT,
        "axes.labelcolor": INK,
        "text.color": INK,
        "xtick.color": INK_SOFT,
        "ytick.color": INK_SOFT,
        "grid.color": INK,
        "grid.alpha": 0.10,
    },
)

# Create figure
fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)

# Density contour plot using seaborn's kdeplot (filled with viridis)
sns.kdeplot(x=x, y=y, ax=ax, levels=10, fill=True, cmap="viridis", alpha=0.8)

# Add contour lines for clarity (using INK_SOFT for theme-adaptive color)
sns.kdeplot(x=x, y=y, ax=ax, levels=10, color=INK_SOFT, linewidths=1.5, alpha=0.6)

# Scatter plot overlay for context (theme-adaptive color, semi-transparent)
ax.scatter(x, y, s=15, color=SCATTER_COLOR, alpha=0.25, edgecolors="none")

# Styling
ax.set_xlabel("X Variable (units)", fontsize=20, color=INK)
ax.set_ylabel("Y Variable (units)", fontsize=20, color=INK)
ax.set_title("contour-density · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK)
ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)

# Remove top and right spines
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
for spine in ["left", "bottom"]:
    ax.spines[spine].set_color(INK_SOFT)
    ax.spines[spine].set_linewidth(0.8)

# Subtle grid
ax.yaxis.grid(True, alpha=0.10, linewidth=0.8, color=INK)

plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)

Retrieve this implementation

Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/contour-density/seaborn/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.

{
  "spec_id": "contour-density",
  "language": "python",
  "library": "seaborn",
  "page": "https://anyplot.ai/contour-density/python/seaborn",
  "hub": "https://anyplot.ai/contour-density",
  "code_json": "https://api.anyplot.ai/specs/contour-density/seaborn/code",
  "spec_json": "https://api.anyplot.ai/specs/contour-density",
  "render_light_png": "https://storage.googleapis.com/anyplot-images/plots/contour-density/python/seaborn/plot-light.png",
  "render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/contour-density/python/seaborn/plot-dark.png",
  "quality_score": 90.0,
  "license": "MIT",
  "guide": "https://anyplot.ai/llms.txt"
}

Part of Density Contour Plot on anyplot.ai.

Other implementations