Basic Stem Plot — lets-plot

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 lets-plot

Python source (lets-plot)

""" anyplot.ai
stem-basic: Basic Stem Plot
Library: letsplot 4.11.0 | Python 3.13.14
Quality: 94/100 | Updated: 2026-07-25
"""
# ruff: noqa: F405

import os

import numpy as np
import pandas as pd
from lets_plot import *


LetsPlot.setup_html()

# 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"
MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
RULE = "rgba(26,26,23,0.15)" if THEME == "light" else "rgba(240,239,232,0.15)"

# Imprint palette — first series is always #009E73
BRAND = "#009E73"

# Data - discrete samples of a damped oscillation (impulse response)
np.random.seed(42)
n = 30
x = np.arange(n)
envelope = np.exp(-x / 10)
y = envelope * np.cos(x * 0.8) + np.random.randn(n) * 0.05
# Fade the stems once the envelope decays past ~0.1 to sharpen the visual hierarchy
alpha = np.where(envelope >= 0.1, 1.0, 0.4)

df = pd.DataFrame({"x": x, "y": y, "y_base": 0.0, "alpha": alpha})
envelope_df = pd.DataFrame({"x": x, "upper": envelope, "lower": -envelope})

plot = (
    ggplot(df)
    + geom_line(aes(x="x", y="upper"), data=envelope_df, color=MUTED, size=1.0, linetype="dashed", alpha=0.7)
    + geom_line(aes(x="x", y="lower"), data=envelope_df, color=MUTED, size=1.0, linetype="dashed", alpha=0.7)
    + geom_hline(yintercept=0, color=INK_SOFT, size=0.5)
    + geom_segment(aes(x="x", y="y_base", xend="x", yend="y", alpha="alpha"), color=BRAND, size=1.2)
    + geom_point(
        aes(x="x", y="y", alpha="alpha"),
        color=BRAND,
        fill=BRAND,
        size=3.5,
        stroke=1.2,
        shape=21,
        tooltips=layer_tooltips().title("Sample @x").line("Amplitude|@y"),
    )
    + scale_alpha_identity()
    + labs(x="Sample Index", y="Amplitude (a.u.)", title="stem-basic · python · letsplot · anyplot.ai")
    + theme(
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_border=element_blank(),
        panel_grid_major=element_line(color=RULE, size=0.3),
        panel_grid_minor=element_blank(),
        axis_title=element_text(size=12, color=INK),
        axis_text=element_text(size=10, color=INK_SOFT),
        axis_ticks=element_line(color=INK_SOFT),
        axis_line_x=element_line(color=INK_SOFT, size=0.4),
        axis_line_y=element_line(color=INK_SOFT, size=0.4),
        plot_title=element_text(size=16, color=INK),
    )
    + ggsize(800, 450)
)

# Save PNG (scale 4x for 3200 x 1800 px)
ggsave(plot, f"plot-{THEME}.png", path=".", scale=4)

# Save HTML
ggsave(plot, f"plot-{THEME}.html", path=".")

Part of Basic Stem Plot on anyplot.ai.

Other implementations