A three-dimensional scatter plot that displays the relationship between three numeric variables by plotting points in 3D space. This visualization extends the classic 2D scatter plot to reveal patterns, clusters, and correlations across three dimensions simultaneously, making it invaluable for multivariate data exploration.
""" anyplot.ai
scatter-3d: 3D Scatter Plot
Library: plotly 6.7.0 | Python 3.13.13
Quality: 85/100 | Updated: 2026-05-08
"""
import os
import numpy as np
import plotly.graph_objects as go
# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
# Data - Molecular compound properties (3D chemical space)
np.random.seed(42)
# Three distinct clusters representing different compound families
# X: Molecular Weight (g/mol), Y: LogP (lipophilicity), Z: Tpsa (polar surface area)
cluster1_x = np.random.normal(320, 40, 50) # Heavy molecules
cluster1_y = np.random.normal(3.5, 0.8, 50)
cluster1_z = np.random.normal(60, 15, 50)
cluster2_x = np.random.normal(180, 30, 50) # Light molecules
cluster2_y = np.random.normal(1.2, 0.6, 50)
cluster2_z = np.random.normal(40, 10, 50)
cluster3_x = np.random.normal(250, 35, 50) # Medium molecules
cluster3_y = np.random.normal(2.8, 0.7, 50)
cluster3_z = np.random.normal(80, 12, 50)
x = np.concatenate([cluster1_x, cluster2_x, cluster3_x])
y = np.concatenate([cluster1_y, cluster2_y, cluster3_y])
z = np.concatenate([cluster1_z, cluster2_z, cluster3_z])
# Use molecular weight for color (continuous dimension)
color = x
# Create 3D scatter plot with turbo colormap for library differentiation
fig = go.Figure(
data=[
go.Scatter3d(
x=x,
y=y,
z=z,
mode="markers",
marker=dict(
size=12,
color=color,
colorscale="Turbo",
opacity=0.8,
colorbar=dict(
title=dict(text="Molecular Weight (g/mol)", font=dict(size=22)),
tickfont=dict(size=16),
thickness=25,
len=0.7,
x=1.02,
xpad=15,
),
),
hovertemplate="<b>Compound Analysis</b><br>"
"Molecular Weight: %{marker.color:.1f} g/mol<br>"
"LogP (Lipophilicity): %{y:.2f}<br>"
"Polar Surface Area: %{z:.1f} Ų<br>"
"<extra></extra>",
)
]
)
# Update layout with theme-adaptive styling
fig.update_layout(
title=dict(text="scatter-3d · plotly · anyplot.ai", font=dict(size=32, color=INK), x=0.5, xanchor="center"),
scene=dict(
xaxis=dict(
title=dict(text="Molecular Weight (g/mol)", font=dict(size=22, color=INK)),
tickfont=dict(size=16, color=INK_SOFT),
gridcolor="rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)",
showbackground=True,
backgroundcolor=PAGE_BG,
),
yaxis=dict(
title=dict(text="LogP (Lipophilicity)", font=dict(size=22, color=INK)),
tickfont=dict(size=16, color=INK_SOFT),
gridcolor="rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)",
showbackground=True,
backgroundcolor=PAGE_BG,
),
zaxis=dict(
title=dict(text="Polar Surface Area (Ų)", font=dict(size=22, color=INK)),
tickfont=dict(size=16, color=INK_SOFT),
gridcolor="rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)",
showbackground=True,
backgroundcolor=PAGE_BG,
),
camera=dict(eye=dict(x=1.5, y=1.5, z=1.2)),
bgcolor=PAGE_BG,
),
paper_bgcolor=PAGE_BG,
plot_bgcolor=PAGE_BG,
font=dict(color=INK),
margin=dict(l=60, r=100, t=120, b=60),
)
# Save outputs (theme-suffixed filenames)
fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")
Part of 3D Scatter Plot on anyplot.ai.