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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