A combined visualization that overlays individual data points (strip plot) on top of a box plot. This provides both summary statistics (median, quartiles, whiskers) and visibility of the actual data distribution.
""" anyplot.ai
cat-box-strip: Box Plot with Strip Overlay
Library: pygal 3.1.0 | Python 3.13.13
Quality: 92/100 | Updated: 2026-05-13
"""
import os
import numpy as np
import pygal
from pygal.style import Style
# Theme tokens from environment
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
# Okabe-Ito palette (colorblind-safe, first series is brand green #009E73)
IMPRINT = ("#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477")
# Data - Test scores across education levels
np.random.seed(42)
categories = ["High School", "Bachelor's", "Master's", "PhD"]
data = {
"High School": np.random.normal(68, 12, 45),
"Bachelor's": np.random.normal(78, 10, 50),
"Master's": np.random.normal(82, 8, 38),
"PhD": np.random.normal(85, 7, 42),
}
# Add realistic outliers
data["High School"] = np.append(data["High School"], [95, 48])
data["Bachelor's"] = np.append(data["Bachelor's"], [58, 98])
data["Master's"] = np.append(data["Master's"], [62, 95])
data["PhD"] = np.append(data["PhD"], [65, 100])
# Clamp all values to 0-100 range
for key in data:
data[key] = np.clip(data[key], 0, 100)
# Color sequence: 6 colors for box plot elements + 4 for strip points (one per category)
color_sequence = []
for i in range(4):
color_sequence.extend([IMPRINT[i]] * 6) # 6 box elements per category
for i in range(4):
color_sequence.append(IMPRINT[i]) # 1 strip series per category
# Custom style for 4800x2700 px canvas with theme-adaptive colors
custom_style = Style(
background=PAGE_BG,
plot_background=PAGE_BG,
foreground=INK,
foreground_strong=INK,
foreground_subtle=INK_MUTED,
colors=tuple(color_sequence),
title_font_size=28,
label_font_size=22,
major_label_font_size=18,
legend_font_size=16,
value_font_size=14,
opacity=0.7,
)
# Create XY chart for combined box plot with strip overlay
chart = pygal.XY(
width=4800,
height=2700,
style=custom_style,
title="cat-box-strip · pygal · anyplot.ai",
x_title="Education Level",
y_title="Test Score",
show_legend=False,
stroke=True,
fill=True,
dots_size=0,
show_x_guides=True,
show_y_guides=True,
xrange=(0, 5),
range=(0, 105),
margin=100,
explicit_size=True,
)
# Layout parameters
box_width = 0.25
cap_width = 0.15
# Pre-compute box plot components and strip points
strip_data = []
box_data = []
for i, (category, values) in enumerate(data.items()):
center_x = i + 1 # X position for this group (1, 2, 3, 4)
values = np.array(values)
# --- Box Plot Statistics ---
median = float(np.median(values))
q1 = float(np.percentile(values, 25))
q3 = float(np.percentile(values, 75))
iqr = q3 - q1
whisker_low = float(max(values.min(), q1 - 1.5 * iqr))
whisker_high = float(min(values.max(), q3 + 1.5 * iqr))
box_data.append((center_x, median, q1, q3, whisker_low, whisker_high))
# --- Strip Points with Jitter ---
np.random.seed(42 + i)
jitter = np.random.uniform(-0.12, 0.12, len(values))
strip_points = [(center_x + j, float(v)) for j, v in zip(jitter, values, strict=True)]
strip_data.append((category, strip_points))
# Draw box plots first (so strip points appear on top)
for center_x, median, q1, q3, whisker_low, whisker_high in box_data:
# IQR box (filled rectangle)
quartile_box = [
(center_x - box_width, q1),
(center_x - box_width, q3),
(center_x + box_width, q3),
(center_x + box_width, q1),
(center_x - box_width, q1),
]
chart.add("", quartile_box, stroke=True, fill=True, show_dots=False, stroke_style={"width": 6})
# Median line (horizontal line within box)
median_line = [(center_x - box_width * 1.1, median), (center_x + box_width * 1.1, median)]
chart.add("", median_line, stroke=True, fill=False, show_dots=False, stroke_style={"width": 10})
# Whiskers (vertical lines from box to caps)
whisker_bottom = [(center_x, q1), (center_x, whisker_low)]
whisker_top = [(center_x, q3), (center_x, whisker_high)]
chart.add("", whisker_bottom, stroke=True, fill=False, show_dots=False, stroke_style={"width": 6})
chart.add("", whisker_top, stroke=True, fill=False, show_dots=False, stroke_style={"width": 6})
# Whisker caps (horizontal lines at ends)
cap_bottom = [(center_x - cap_width, whisker_low), (center_x + cap_width, whisker_low)]
cap_top = [(center_x - cap_width, whisker_high), (center_x + cap_width, whisker_high)]
chart.add("", cap_bottom, stroke=True, fill=False, show_dots=False, stroke_style={"width": 6})
chart.add("", cap_top, stroke=True, fill=False, show_dots=False, stroke_style={"width": 6})
# Add strip points on top with transparency
for _category, strip_points in strip_data:
chart.add("", strip_points, stroke=False, fill=False, dots_size=16)
# X-axis labels for categories
chart.x_labels = [
{"value": 0, "label": ""},
{"value": 1, "label": "High School"},
{"value": 2, "label": "Bachelor's"},
{"value": 3, "label": "Master's"},
{"value": 4, "label": "PhD"},
{"value": 5, "label": ""},
]
# Save outputs
chart.render_to_file(f"plot-{THEME}.html")
chart.render_to_png(f"plot-{THEME}.png")
Part of Box Plot with Strip Overlay on anyplot.ai.