🌈 Day 34: Polar Area Chart in Python

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🔹 What is a Polar Area Chart?

A Polar Area Chart (also called Coxcomb Chart) is a circular chart where:

• Each category has an equal angle

• Radius (distance from center) represents the value

• Larger values extend further outward

It looks like a mix of a bar chart + pie chart in polar form.

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🔹 When Should You Use It?

Use a polar area chart when:

• Comparing categorical magnitudes

• You want a visually engaging circular design

• Showing seasonal or cyclic patterns

• Creating modern dashboard visuals

Avoid it when precise numeric comparison is critical.

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🔹 Example Scenario

Suppose you want to compare:

• Category A

• Category B

• Category C

• Category D

• Category E

• Category F

The chart makes it easy to see which category dominates.

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🔹 Key Idea Behind It

👉 All slices have equal angle
👉 Radius determines size
👉 Larger value = longer outward bar
👉 Circular layout improves visual appeal

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🔹 Python Code (Interactive Polar Area Chart – Plotly)

import plotly.express as px

# 1. Minimal Data
 data = dict(values=[10, 35, 15, 25, 45, 20],  
             names=['A', 'B', 'C', 'D', 'E', 'F'])

# 2. Aesthetic Chart Creation 
fig = px.bar_polar(     data,
    r="values",
    theta="names",
    color="values",
    template="plotly_dark",
    color_continuous_scale="Edge"
)

# 3. Quick Polish
fig.update_layout( 
    showlegend=False, 
 margin=dict(t=50, b=20, l=20, r=20)
)

fig.show()

📌 Install Plotly if needed:

pip install plotly

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🔹 Output Explanation

• Each segment represents a category

• All segments have equal angle

• Category E (45) extends the furthest

• Dark theme gives modern dashboard feel

• Interactive hover shows exact values

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🔹 Polar Area vs Pie Chart

Aspect	Polar Area	Pie Chart
Angle size	Equal	Varies
Value representation	Radius	Angle
Visual impact	High	Moderate
Precision	Medium	Low

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🔹 Key Takeaways

• Great alternative to pie charts

• More visually engaging

• Best for categorical comparisons

• Ideal for dashboards & presentations