Bollinger Bands Indicator Chart — Matplotlib

A Bollinger Bands chart displays price data with a volatility envelope consisting of three lines: a middle band (simple moving average), an upper band (SMA plus 2 standard deviations), and a lower band (SMA minus 2 standard deviations). This technical indicator helps traders identify overbought/oversold conditions, volatility patterns, and potential price breakouts by showing how prices relate to their recent statistical range.

Bollinger Bands Indicator Chart rendered with Matplotlib

Python source (Matplotlib)

""" anyplot.ai
indicator-bollinger: Bollinger Bands Indicator Chart
Library: matplotlib 3.10.9 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-17
"""

import os

import matplotlib.pyplot as plt
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 color is always brand green
BRAND = "#009E73"
SECONDARY = "#C475FD"
TERTIARY = "#4467A3"

# Data - Generate realistic stock price data with Bollinger Bands
np.random.seed(42)
n_days = 120

# Generate realistic price movement using random walk
dates = pd.date_range("2024-01-01", periods=n_days, freq="B")
returns = np.random.normal(0.0005, 0.015, n_days)
price_base = 150
close = price_base * np.cumprod(1 + returns)

# Calculate Bollinger Bands (20-period SMA, 2 standard deviations)
window = 20
sma = pd.Series(close).rolling(window=window).mean()
std = pd.Series(close).rolling(window=window).std()
upper_band = sma + 2 * std
lower_band = sma - 2 * std

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

# Plot the filled area between bands (volatility envelope)
ax.fill_between(dates, lower_band, upper_band, alpha=0.15, color=TERTIARY, label="Volatility Band (±2σ)")

# Plot upper and lower bands
ax.plot(dates, upper_band, color=TERTIARY, linewidth=2, alpha=0.7)
ax.plot(dates, lower_band, color=TERTIARY, linewidth=2, alpha=0.7)

# Plot middle band (SMA) as dashed line
ax.plot(dates, sma, color=SECONDARY, linewidth=2.5, linestyle="--", label="SMA (20-day)")

# Plot closing price prominently in brand color
ax.plot(dates, close, color=BRAND, linewidth=3, label="Close Price")

# Style
ax.set_xlabel("Date", fontsize=20, color=INK)
ax.set_ylabel("Price ($)", fontsize=20, color=INK)
ax.set_title("indicator-bollinger · matplotlib · anyplot.ai", fontsize=24, fontweight="medium", color=INK)
ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)

# Format x-axis dates
fig.autofmt_xdate(rotation=30)
ax.xaxis.set_major_locator(plt.MaxNLocator(8))

# Spines
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
for s in ("left", "bottom"):
    ax.spines[s].set_color(INK_SOFT)

# Grid - subtle y-axis only
ax.yaxis.grid(True, alpha=0.1, linewidth=0.8, color=INK_SOFT)

# Legend
leg = ax.legend(fontsize=16, loc="upper left", framealpha=0.95)
if leg:
    leg.get_frame().set_facecolor(ELEVATED_BG)
    leg.get_frame().set_edgecolor(INK_SOFT)
    leg.get_frame().set_linewidth(0.8)
    plt.setp(leg.get_texts(), color=INK_SOFT)

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

Part of Bollinger Bands Indicator Chart on anyplot.ai.

Bollinger Bands Indicator Chart — Matplotlib

Python source (Matplotlib)

Other implementations