Creating Animated GIF Charts with Python and Matplotlib

Today we share how to make visualizations look appealing by creating GIF charts with Python and matplotlib.

If ImageMagick is not installed on your computer, download the appropriate version for your operating system first, because matplotlib's save method for GIF animation requires ImageMagick.

Note that in the GIF the scatter points remain static while the line moves, and the X‑axis label changes on each frame.

Below is the Python code used to produce the GIF:

<code>import sys
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

fig, ax = plt.subplots()
fig.set_tight_layout(True)

# inquire figure size and DPI
print('fig size: {0} DPI, size in inches {1}'.format(fig.get_dpi(), fig.get_size_inches()))

# draw static scatter and initial line
x = np.arange(0, 20, 0.1)
ax.scatter(x, x + np.random.normal(0, 3.0, len(x)))
line, = ax.plot(x, x - 5, 'r-', linewidth=2)

def update(i):
    label = 'timestep {0}'.format(i)
    print(label)
    # update line and axis with new X label
    line.set_ydata(x - 5 + i)
    ax.set_xlabel(label)
    return line, ax

if __name__ == '__main__':
    # FuncAnimation will call update for each frame; 10 frames, 200ms interval
    anim = FuncAnimation(fig, update, frames=np.arange(0, 10), interval=200)
    if len(sys.argv) > 1 and sys.argv[1] == 'save':
        anim.save('line.gif', dpi=80, writer='imagemagick')
    else:
        plt.show()</code>

If you want a more stylish theme you can import the seaborn library with import seaborn .

A reminder: although this example uses only ten frames and simple graphics, each frame is about 160 KB because GIF does not use inter‑frame compression; therefore, reducing the number of frames and lowering the figure size or DPI in matplotlib can help keep the file size manageable.

Original source: https://jizhi.im/blog/post/pytogif