Basic Strip Plot — lets-plot

A strip plot displays individual data points for each category along a single axis, with random horizontal jitter applied to reduce overplotting. Unlike box plots or violin plots that show summary statistics, strip plots reveal every observation, making them ideal for small to medium datasets where individual values matter. The random jitter spreads points horizontally within each category to show density through point accumulation.

Basic Strip Plot rendered with lets-plot

Python source (lets-plot)

""" anyplot.ai
strip-basic: Basic Strip Plot
Library: letsplot 4.9.0 | Python 3.13.13
Quality: 83/100 | Updated: 2026-05-06
"""

import os

import numpy as np
import pandas as pd
from lets_plot import (
    LetsPlot,
    aes,
    element_blank,
    element_line,
    element_rect,
    element_text,
    geom_jitter,
    ggplot,
    ggsave,
    ggsize,
    labs,
    theme,
    theme_minimal,
)


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"

BRAND = "#009E73"  # Okabe-Ito position 1

# Data - Survey response scores by department
np.random.seed(42)

departments = ["Marketing", "Engineering", "Sales", "Support"]
data = []

distributions = {"Marketing": (72, 12), "Engineering": (78, 8), "Sales": (68, 15), "Support": (75, 10)}

for dept in departments:
    n_points = np.random.randint(25, 45)
    mean, std = distributions[dept]
    scores = np.clip(np.random.normal(mean, std, n_points), 40, 100)
    for score in scores:
        data.append({"Department": dept, "Score": score})

df = pd.DataFrame(data)

# Plot
plot = (
    ggplot(df, aes(x="Department", y="Score"))
    + geom_jitter(color=BRAND, size=4, alpha=0.65, width=0.25, height=0, seed=42)
    + labs(x="Department", y="Survey Score (points)", title="strip-basic · letsplot · anyplot.ai")
    + ggsize(1600, 900)
    + theme_minimal()
    + theme(
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG),
        axis_title=element_text(color=INK, size=20),
        axis_text=element_text(color=INK_SOFT, size=16),
        plot_title=element_text(color=INK, size=24),
        panel_grid_major_x=element_blank(),
        panel_grid_minor=element_blank(),
        panel_grid_major_y=element_line(color=INK_SOFT, size=0.3),
    )
)

# Save
ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)
ggsave(plot, f"plot-{THEME}.html", path=".")

Part of Basic Strip Plot on anyplot.ai.

Basic Strip Plot — lets-plot

Python source (lets-plot)

Other implementations