Basic Area Chart — Seaborn

An area chart showing quantitative data over a continuous axis with the area below the line filled. It emphasizes the magnitude of values over time by filling the space between the line and axis, creating visual weight that helps readers understand volume and trends. Particularly effective for showing cumulative totals, resource consumption, or any data where the "amount" is as important as the trend.

Basic Area Chart rendered with Seaborn

Python source (Seaborn)

""" anyplot.ai
area-basic: Basic Area Chart
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-28
"""

import os

import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import numpy as np
import pandas as pd
import seaborn as sns


# 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"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
BRAND = "#009E73"

# Data - daily website visitors over a month
np.random.seed(42)
dates = pd.date_range(start="2024-03-01", periods=30, freq="D")
base_visitors = 8000
trend = np.linspace(0, 2000, 30)
weekly_pattern = np.array([1.0, 1.1, 1.15, 1.2, 1.1, 0.7, 0.65] * 5)[:30]
noise = np.random.randn(30) * 350
visitors = (base_visitors + trend) * weekly_pattern + noise
visitors[9:12] *= 0.22  # Planned maintenance window (days 10–12)
visitors = np.maximum(visitors, 100)

df = pd.DataFrame({"date": dates, "visitors": visitors})
avg_visitors = df["visitors"].mean()
y_max = df["visitors"].max() * 1.18

# Configure seaborn theme (theme-adaptive chrome)
sns.set_theme(
    style="white",
    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": 0.15,
        "axes.spines.top": False,
        "axes.spines.right": False,
    },
)

fig, ax = plt.subplots(figsize=(8, 4.5), dpi=400, facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)

# Layered gradient fill using seaborn's light_palette — 3 layers at higher alpha
# for stronger area visual weight than the previous 5-layer faint approach
palette_colors = sns.light_palette(BRAND, n_colors=5)
for i in range(3):
    frac = (i + 1) / 3
    ax.fill_between(df["date"], 0, df["visitors"] * frac, color=palette_colors[i + 2], alpha=0.28, linewidth=0)

# Seaborn lineplot for the area boundary line
sns.lineplot(data=df, x="date", y="visitors", ax=ax, color=BRAND, linewidth=2.5)

# Annotate the scheduled maintenance dip (days 10–12)
maint_idx = 10
maint_val = df["visitors"].iloc[maint_idx]
ax.annotate(
    "Scheduled\nmaintenance",
    xy=(df["date"].iloc[maint_idx], maint_val + 80),
    xytext=(df["date"].iloc[maint_idx + 6], maint_val + 4200),
    fontsize=8,
    fontweight="semibold",
    color=INK,
    arrowprops={"arrowstyle": "->", "color": INK_SOFT, "lw": 1.2, "connectionstyle": "arc3,rad=0.2"},
    ha="center",
    va="bottom",
)

# Monthly average reference line
ax.axhline(y=avg_visitors, color=INK_SOFT, linestyle="--", linewidth=1.0, alpha=0.6, zorder=1)
ax.text(
    df["date"].iloc[-1],
    avg_visitors + y_max * 0.012,
    f"Avg: {avg_visitors:,.0f}",
    fontsize=8,
    color=INK_MUTED,
    ha="right",
    va="bottom",
    fontstyle="italic",
)

# Labels and title
title = "area-basic · python · seaborn · anyplot.ai"
n = len(title)
ratio = 67 / n if n > 67 else 1.0
title_fontsize = max(8, round(12 * ratio))

ax.set_xlabel("Date", fontsize=10, color=INK)
ax.set_ylabel("Visitors / day", fontsize=10, color=INK)
ax.set_title(title, fontsize=title_fontsize, fontweight="medium", color=INK, pad=8)
ax.tick_params(axis="both", labelsize=8, colors=INK_SOFT)

# Spine, grid, and axes styling
sns.despine(ax=ax)
ax.yaxis.grid(True, alpha=0.15, linewidth=0.8, color=INK)
ax.set_axisbelow(True)
ax.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, _: f"{x:,.0f}"))
ax.xaxis.set_major_locator(mdates.WeekdayLocator(byweekday=mdates.MO))
ax.xaxis.set_minor_locator(mdates.DayLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %d"))
plt.setp(ax.get_xticklabels(), rotation=30, ha="right")
ax.set_ylim(bottom=0, top=y_max)

plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)

Part of Basic Area Chart on anyplot.ai.

Other implementations