📊 Day 19: Contour Plot in Python

 

📊 Day 19: Contour Plot in Python

🔹 What is a Contour Plot?

A Contour Plot is used to represent 3D data on a 2D plane.
It shows lines (or filled regions) where the value of a third variable remains constant—similar to a topographic map.

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🔹 When Should You Use It?

Use a contour plot when:

• Working with three continuous variables

• Visualizing surfaces or gradients

• Understanding peaks, valleys, and transitions

• Analyzing density or mathematical functions

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🔹 Example Scenario

Suppose you are analyzing:

• Elevation levels on a map

• Probability density surfaces

• Loss functions in machine learning

A contour plot helps you quickly identify:

• High and low regions

• Sharp or smooth changes

• Overall surface behavior

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🔹 Key Idea Behind It

👉 Each contour line represents the same Z value
👉 Closely spaced lines = steep change
👉 Wider spacing = gradual change

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🔹 Python Code (Contour Plot)

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(-3, 3, 100) 
y = np.linspace(-3, 3, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(X) * np.cos(Y)

plt.contour(X, Y, Z)
plt.xlabel("X Axis")
plt.ylabel("Y Axis")
plt.title("Contour Plot Example")

plt.show()

🔹 Output Explanation

• Lines connect points of equal value

• Peaks and valleys are easily visible

• Dense contours show steep regions

• Helps visualize complex surfaces clearly

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🔹 Contour Plot vs Heatmap

Feature	Contour Plot	Heatmap
Representation	Lines / levels	Color blocks
Precision	High	Medium
Gradients	Very clear	Less clear
Best use	Surface analysis	Pattern spotting

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🔹 Key Takeaways

• Contour plots visualize 3D data in 2D

• Excellent for surface & gradient analysis

• Widely used in science, ML & engineering

• Ideal when exact value levels matter