各国和地区疫情动态增长图，附python实例代码

用python制作了动态的gif图，可以直观的感受过去2个多月来，各国和地区的累计确诊人数变化趋势。

目前各国疫情态势逐渐明朗，有的已经成功守住底线，还有的苦苦挣扎，还有的前景不明朗。不过，终究是one world one fight。相信这是黎明前的黑暗。

用python制作动态图其实很简单，下面是一个简单示范代码：

import matplotlib

import matplotlib.pyplot as plt

import numpy as np

import imageio

def plot_for_offset(power, y_max):

# Data for plotting

t = np.arange(0.0, 100, 1)

s = t**power

fig, ax = plt.subplots(figsize=(10,5))

ax.plot(t, s)

ax.grid()

ax.set(xlabel='X', ylabel='x^{}'.format(power),title='Powers of x')

# Used to keep the limits constant

ax.set_ylim(0, y_max)

# Used to return the plot as an image rray

fig.canvas.draw()

image = np.frombuffer(fig.canvas.tostring_rgb(), dtype='uint8')

image = image.reshape(fig.canvas.get_width_height()[::-1] + (3,))

return image

#fps控制每秒播放图片数量快慢

kwargs_write = {'fps':1.0, 'quantizer':'nq'}

imageio.mimsave('test.gif', [plot_for_offset(i/4, 100) for i in range(10)], fps=1)

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import matplotlib