A raincloud plot combines three visualization elements—a half-violin (the "cloud"), jittered strip points (the "rain"), and a box plot—to provide a comprehensive view of data distribution. This hybrid approach shows distribution shape, summary statistics, and individual observations simultaneously, addressing the limitation of box plots that can hide multimodal distributions. Often called the "gold standard" for transparent statistical visualization in scientific publications.
""" anyplot.ai
raincloud-basic: Basic Raincloud Plot
Library: letsplot 4.10.1 | Python 3.13.13
Quality: 94/100 | Updated: 2026-05-26
"""
import os
import numpy as np
import pandas as pd
from lets_plot import (
LetsPlot,
aes,
arrow,
element_blank,
element_line,
element_rect,
element_text,
geom_boxplot,
geom_jitter,
geom_segment,
geom_text,
geom_violin,
ggplot,
ggsave,
ggsize,
labs,
position_nudge,
scale_color_manual,
scale_fill_manual,
scale_x_continuous,
scale_y_discrete,
theme,
)
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"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
RULE = "rgba(26,26,23,0.15)" if THEME == "light" else "rgba(240,239,232,0.15)"
# anyplot categorical palette (canonical order, first series ALWAYS #009E73)
BRAND = "#009E73"
LAVENDER = "#C475FD"
BLUE = "#4467A3"
# Data — reaction times (ms) for three experimental conditions
np.random.seed(42)
control = np.random.normal(450, 60, 80)
treatment_a = np.random.normal(380, 50, 80)
treatment_b = np.concatenate([np.random.normal(300, 30, 50), np.random.normal(540, 35, 30)])
df = pd.DataFrame(
{
"condition": ["Control"] * len(control)
+ ["Treatment A"] * len(treatment_a)
+ ["Treatment B"] * len(treatment_b),
"reaction_time": np.concatenate([control, treatment_a, treatment_b]),
}
)
palette = {"Control": BRAND, "Treatment A": LAVENDER, "Treatment B": BLUE}
# Display order (bottom to top of y-axis): Treatment B, Treatment A, Control
cat_order = ["Treatment B", "Treatment A", "Control"]
plot = (
ggplot(df, aes(x="reaction_time", y="condition", fill="condition", color="condition"))
# Half-violin (cloud) — nudged above the category baseline
+ geom_violin(trim=False, show_half=1, size=0.8, alpha=0.7, position=position_nudge(y=0.12))
# Boxplot on the baseline with elevated-bg fill for contrast in both themes
+ geom_boxplot(
width=0.18,
outlier_size=0,
outlier_alpha=0,
fill=ELEVATED_BG,
color=INK,
size=0.8,
alpha=0.95,
show_legend=False,
)
# Rain — jittered points below the baseline
+ geom_jitter(
width=0,
height=0.05,
size=4.0,
alpha=0.5,
shape=21,
stroke=0.3,
show_legend=False,
position=position_nudge(y=-0.16),
)
# Annotation: Treatment A faster mean — text on the right (off the cloud), arrow lands just above the peak top
+ geom_text(
x=690, y=1.55, label="~70ms faster mean\nthan Control", size=13, color=INK_SOFT, fontface="italic", hjust=1
)
+ geom_segment(x=550, y=1.45, xend=400, yend=1.70, color=INK_SOFT, size=0.5, arrow=arrow(length=8, type="closed"))
# Annotation: Treatment B bimodal — text on the right, arrows land just above each peak top
+ geom_text(
x=690, y=0.55, label="Two distinct\nresponse clusters", size=13, color=INK_SOFT, fontface="italic", hjust=1
)
+ geom_segment(x=550, y=0.45, xend=310, yend=0.55, color=INK_SOFT, size=0.5, arrow=arrow(length=8, type="closed"))
+ geom_segment(x=620, y=0.30, xend=555, yend=0.40, color=INK_SOFT, size=0.5, arrow=arrow(length=8, type="closed"))
+ scale_fill_manual(values=palette)
+ scale_color_manual(values=palette)
+ scale_y_discrete(limits=cat_order)
+ scale_x_continuous(limits=[200, 700])
+ labs(x="Reaction Time (ms)", y="Experimental Condition", title="raincloud-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),
plot_title=element_text(size=16, face="bold", color=INK),
axis_title_x=element_text(size=12, color=INK, margin=[12, 0, 0, 0]),
axis_title_y=element_text(size=12, color=INK, margin=[0, 12, 0, 0]),
axis_text_x=element_text(size=10, color=INK_SOFT),
axis_text_y=element_text(size=12, color=INK, face="bold"),
axis_ticks=element_blank(),
axis_line_x=element_blank(),
axis_line_y=element_blank(),
legend_position="none",
panel_grid_major_y=element_blank(),
panel_grid_minor=element_blank(),
panel_grid_major_x=element_line(color=RULE, size=0.4),
plot_margin=[40, 40, 30, 20],
)
+ ggsize(800, 450)
)
ggsave(plot, f"plot-{THEME}.png", path=".", scale=4)
ggsave(plot, f"plot-{THEME}.html", path=".")
Part of Basic Raincloud Plot on anyplot.ai.