Animated Charts

Advanced

Learning Objectives

After completing this recipe, you will be able to:

Understand changes over time through animation
Understand the concepts of Matplotlib Animation

Note: This document is a static page, so we show a single frame (snapshot) of the animation as an example. When actually running the code, you can see the dynamically moving chart.

0. Setup


import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
 
# Generate data: moving sine wave
x = np.linspace(0, 2*np.pi, 100)

1. Frame Visualization

Let’s visualize a specific point in time of the animation.


plt.figure(figsize=(10, 6))
y = np.sin(x) # t=0
plt.plot(x, y, label='Time=0')
 
y2 = np.sin(x + np.pi/2) # t=1
plt.plot(x, y2, '--', label='Time=1')
 
plt.title('Wave Movement Snapshot')
plt.legend()
plt.show()

Wave Snapshot

2. Comparing Multiple Time Points


plt.figure(figsize=(10, 6))
for t in np.linspace(0, np.pi, 5):
    plt.plot(x, np.sin(x + t), alpha=0.5, label=f't={t:.2f}')
 
plt.title('Multiple Time Steps')
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
plt.tight_layout()
plt.show()

Multiple Time Steps