A line plot rendered in polar coordinates, where data points are connected with lines around a circular axis. The angle (theta) typically represents a cyclical variable while the radius shows magnitude.
""" anyplot.ai
polar-line: Polar Line Plot
Library: altair 6.1.0 | Python 3.13.13
Quality: 92/100 | Updated: 2026-05-12
"""
import os
import sys
# Remove current directory from path to avoid importing this file as altair
cwd = os.getcwd()
if cwd in sys.path:
sys.path.remove(cwd)
script_dir = os.path.dirname(os.path.abspath(__file__))
if script_dir in sys.path:
sys.path.remove(script_dir)
import altair as alt
import numpy as np
import pandas as pd
# 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"
# Okabe-Ito palette (positions 1-2 for two series)
IMPRINT = ["#009E73", "#C475FD"]
# Data - Seasonal temperature pattern (cyclical)
np.random.seed(42)
months = np.arange(0, 360, 30) # 12 months as degrees
month_names = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
# Two cities with different seasonal patterns
city_a_temp = np.array([5, 7, 12, 18, 24, 28, 30, 29, 24, 17, 10, 6])
city_b_temp = np.array([28, 27, 24, 18, 12, 8, 7, 9, 14, 20, 24, 27])
# Normalize temperatures to 0-1 range for polar visualization
city_a_norm = (city_a_temp - city_a_temp.min()) / (city_a_temp.max() - city_a_temp.min()) * 0.4 + 0.3
city_b_norm = (city_b_temp - city_b_temp.min()) / (city_b_temp.max() - city_b_temp.min()) * 0.4 + 0.3
# Convert polar to cartesian for Altair
theta_rad_months = np.radians(months)
theta_rad_closed = np.append(theta_rad_months, theta_rad_months[0])
city_a_closed = np.append(city_a_norm, city_a_norm[0])
city_b_closed = np.append(city_b_norm, city_b_norm[0])
x_a = city_a_closed * np.cos(theta_rad_closed)
y_a = city_a_closed * np.sin(theta_rad_closed)
x_b = city_b_closed * np.cos(theta_rad_closed)
y_b = city_b_closed * np.sin(theta_rad_closed)
df = pd.DataFrame(
{
"x": np.concatenate([x_a, x_b]),
"y": np.concatenate([y_a, y_b]),
"order": list(range(len(x_a))) + list(range(len(x_b))),
"city": ["Northern City"] * len(x_a) + ["Southern City"] * len(x_b),
}
)
# Create polar grid - concentric circles
grid_circles = []
for r in [0.2, 0.4, 0.6, 0.8]:
theta_circle = np.linspace(0, 2 * np.pi, 100)
x_c = r * np.cos(theta_circle)
y_c = r * np.sin(theta_circle)
for i in range(len(x_c)):
grid_circles.append({"x": x_c[i], "y": y_c[i], "r": str(r), "order": i})
grid_df = pd.DataFrame(grid_circles)
# Create radial lines
radials = []
for angle in months:
angle_rad = np.radians(angle)
radials.append({"x": 0, "y": 0, "x2": 0.85 * np.cos(angle_rad), "y2": 0.85 * np.sin(angle_rad)})
radials_df = pd.DataFrame(radials)
# Month labels
labels = []
for angle, name in zip(months, month_names, strict=True):
angle_rad = np.radians(angle)
labels.append({"x": 0.95 * np.cos(angle_rad), "y": 0.95 * np.sin(angle_rad), "label": name})
labels_df = pd.DataFrame(labels)
# Concentric grid circles
circles_chart = (
alt.Chart(grid_df)
.mark_line(strokeWidth=1.5, opacity=0.5)
.encode(
x=alt.X("x:Q", axis=None, scale=alt.Scale(domain=[-1.1, 1.1])),
y=alt.Y("y:Q", axis=None, scale=alt.Scale(domain=[-1.1, 1.1])),
detail="r:N",
order="order:O",
color=alt.value(INK_SOFT),
)
)
# Radial grid lines
radials_chart = (
alt.Chart(radials_df)
.mark_rule(strokeWidth=1.5, opacity=0.5)
.encode(x="x:Q", y="y:Q", x2="x2:Q", y2="y2:Q", color=alt.value(INK_SOFT))
)
# Month labels
labels_chart = (
alt.Chart(labels_df)
.mark_text(fontSize=22, fontWeight="bold")
.encode(x="x:Q", y="y:Q", text="label:N", color=alt.value(INK))
)
# Data lines
lines_chart = (
alt.Chart(df)
.mark_line(strokeWidth=4, opacity=0.9)
.encode(
x="x:Q",
y="y:Q",
color=alt.Color(
"city:N",
scale=alt.Scale(domain=["Northern City", "Southern City"], range=IMPRINT),
legend=alt.Legend(
title="City",
titleFontSize=20,
labelFontSize=18,
orient="bottom",
direction="horizontal",
fillColor=ELEVATED_BG,
strokeColor=INK_SOFT,
titleColor=INK,
labelColor=INK_SOFT,
),
),
order="order:O",
)
)
# Data points
points_chart = (
alt.Chart(df)
.mark_point(size=250, filled=True, opacity=0.9)
.encode(
x="x:Q",
y="y:Q",
color=alt.Color(
"city:N", scale=alt.Scale(domain=["Northern City", "Southern City"], range=IMPRINT), legend=None
),
)
)
# Combine all layers
chart = (
alt.layer(circles_chart, radials_chart, labels_chart, lines_chart, points_chart)
.properties(
width=1200,
height=1200,
title=alt.Title(
text="polar-line · altair · anyplot.ai",
subtitle="Monthly Temperature Patterns",
fontSize=28,
subtitleFontSize=22,
anchor="middle",
color=INK,
subtitleColor=INK_SOFT,
),
background=PAGE_BG,
)
.configure_view(strokeWidth=0, fill=PAGE_BG)
)
# Save (1200 * 3 = 3600 for square format)
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")
Part of Polar Line Plot on anyplot.ai.