Basic Stem Plot — Matplotlib

A stem plot displays data points as markers connected to a baseline by vertical lines (stems). Each data point is represented by a marker at the data value with a thin line extending down to a baseline, making it ideal for visualizing discrete or sequential data where individual values matter. This plot type is particularly useful in signal processing and scientific applications where the discrete nature of measurements needs emphasis.

Basic Stem Plot rendered with Matplotlib

Python source (Matplotlib)

""" anyplot.ai
stem-basic: Basic Stem Plot
Library: matplotlib 3.11.1 | Python 3.13.14
Quality: 96/100 | Updated: 2026-07-25
"""

import os

import matplotlib.pyplot as plt
import numpy as np


# Theme tokens (see prompts/default-style-guide.md "Background" + "Theme-adaptive Chrome")
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"
POSITIVE = "#009E73"  # Imprint palette position 1 — semantic exception: positive polarity
NEGATIVE = "#AE3030"  # Imprint palette position 5 — semantic exception: negative polarity

# Data - discrete damped oscillation signal
np.random.seed(42)
sample_index = np.arange(0, 30)
decay = np.exp(-sample_index / 10)
amplitude = decay * np.cos(sample_index * 0.8) + np.random.randn(30) * 0.05
is_positive = amplitude >= 0

# Plot — see default-style-guide.md "Visual Sizing Defaults" for the canvas + sizing values
fig, ax = plt.subplots(figsize=(8, 4.5), dpi=400, facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)

# Decay envelope — matplotlib-distinctive overlay tracing the exponential bound
# that governs the oscillation, drawn on a fine grid for a smooth dashed curve.
envelope_x = np.linspace(0, 29, 300)
envelope_y = np.exp(-envelope_x / 10)
ax.plot(envelope_x, envelope_y, linestyle="--", linewidth=1.2, color=INK_SOFT, alpha=0.6, zorder=1)
ax.plot(envelope_x, -envelope_y, linestyle="--", linewidth=1.2, color=INK_SOFT, alpha=0.6, zorder=1)

markerline_pos, stemlines_pos, _ = ax.stem(sample_index[is_positive], amplitude[is_positive], basefmt=" ")
markerline_neg, stemlines_neg, _ = ax.stem(sample_index[~is_positive], amplitude[~is_positive], basefmt=" ")
ax.axhline(0, linewidth=1.5, color=INK_SOFT, zorder=1)

plt.setp(stemlines_pos, linewidth=2, color=POSITIVE, alpha=0.8, zorder=2)
plt.setp(markerline_pos, markersize=12, color=POSITIVE, markeredgecolor=PAGE_BG, markeredgewidth=2, zorder=3)
plt.setp(stemlines_neg, linewidth=2, color=NEGATIVE, alpha=0.8, zorder=2)
plt.setp(markerline_neg, markersize=12, color=NEGATIVE, markeredgecolor=PAGE_BG, markeredgewidth=2, zorder=3)

# Peak annotation — calls out the decay envelope's starting amplitude at n=0
ax.annotate(
    f"Peak {amplitude[0]:.2f} V",
    xy=(sample_index[0], amplitude[0]),
    xytext=(sample_index[0] + 6, amplitude[0] - 0.35),
    fontsize=8,
    color=INK,
    arrowprops={"arrowstyle": "->", "color": INK_SOFT, "linewidth": 1.2},
    bbox={"boxstyle": "round,pad=0.3", "facecolor": ELEVATED_BG, "edgecolor": INK_SOFT, "alpha": 0.9},
    zorder=4,
)

# Style
title = "stem-basic · python · matplotlib · anyplot.ai"
ax.set_xlabel("Sample Index (n)", fontsize=10, color=INK)
ax.set_ylabel("Amplitude (V)", fontsize=10, color=INK)
ax.set_title(title, fontsize=11, fontweight="medium", color=INK)
ax.tick_params(axis="both", labelsize=8, colors=INK_SOFT)
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
for s in ("left", "bottom"):
    ax.spines[s].set_color(INK_SOFT)
ax.yaxis.grid(True, alpha=0.12, linewidth=0.8, color=INK)

# Save
plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)  # bbox_inches MUST stay default (None)

Part of Basic Stem Plot on anyplot.ai.

Other implementations