python绘制动态图形是数据可视化更直观、更好看的一种方式，matplotlib工具包是常用的绘图工具，也可以用来绘制动态图形。本文介绍四种绘制动态图形的方法，包括生成图形的代码和动态图形演示示例。

用matplotlib工具包创建动画图有两种方法：

• 使用 pause() 函数
• 使用 FuncAnimation() 函数

代码如下：

from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation, writers
import numpy as np
  
fig = plt.figure(figsize = (7,5))
axes = fig.add_subplot(1,1,1)
axes.set_ylim(0, 300)
palette = ['blue', 'red', 'green', 
           'darkorange', 'maroon', 'black']
  
y1, y2, y3, y4, y5, y6 = [], [], [], [], [], []
  
def animation_function(i):
    y1 = i
    y2 = 5 * i
    y3 = 3 * i
    y4 = 2 * i
    y5 = 6 * i
    y6 = 3 * i
  
    plt.xlabel("Country")
    plt.ylabel("GDP of Country")
      
    plt.bar(["India", "China", "Germany", 
             "USA", "Canada", "UK"],
            [y1, y2, y3, y4, y5, y6],
            color = palette)
  
plt.title("Bar Chart Animation")
  
animation = FuncAnimation(fig, animation_function, 
                          interval = 50)
plt.show()

如下图：

横向柱状跑图 （Horizontal Bar Chart Race），使用FuncAnimation() 函数

以下代码是绘制世界1500年-2018年主要城市人口变化横向柱状跑图，需要数据集文件city_populations.csv评论区留言。

程序代码如下：

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
from matplotlib.animation import FuncAnimation

df = pd.read_csv('city_populations.csv',
				usecols=['name', 'group', 'year', 'value'])

colors = dict(zip(['India','Europe','Asia',
				'Latin America','Middle East',
				'North America','Africa'],
					['#adb0ff', '#ffb3ff', '#90d595',
					'#e48381', '#aafbff', '#f7bb5f',
					'#eafb50']))

group_lk = df.set_index('name')['group'].to_dict()

def draw_barchart(year):
	dff = df[df['year'].eq(year)].sort_values(by='value',
											ascending=True).tail(10)
	ax.clear()
	ax.barh(dff['name'], dff['value'],
			color=[colors[group_lk[x]] for x in dff['name']])
	dx = dff['value'].max() / 200
	
	for i, (value, name) in enumerate(zip(dff['value'],
										dff['name'])):
		ax.text(value-dx, i,	 name,		
				size=14, weight=600,
				ha='right', va='bottom')
		ax.text(value-dx, i-.25, group_lk[name],
				size=10, color='#444444',
				ha='right', va='baseline')
		ax.text(value+dx, i,	 f'{value:,.0f}',
				size=14, ha='left', va='center')
		
	# polished styles
	ax.text(1, 0.4, year, transform=ax.transAxes,
			color='#777777', size=46, ha='right',
			weight=800)
	ax.text(0, 1.06, 'Population (thousands)',
			transform=ax.transAxes, size=12,
			color='#777777')
	
	ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
	ax.xaxis.set_ticks_position('top')
	ax.tick_params(axis='x', colors='#777777', labelsize=12)
	ax.set_yticks([])
	ax.margins(0, 0.01)
	ax.grid(which='major', axis='x', linestyle='-')
	ax.set_axisbelow(True)
	ax.text(0, 1.12, 'The most populous cities in the world from 1500 to 2018',
			transform=ax.transAxes, size=24, weight=600, ha='left')
	
	ax.text(1, 0, ' ',
			transform=ax.transAxes, ha='right', color='#777777',
			bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
	plt.box(False)
	plt.show()

fig, ax = plt.subplots(figsize=(15, 8))
animator = FuncAnimation(fig, draw_barchart,
						frames = range(1990, 2019))
plt.show()

散点图动画，使用FuncAnimation()函数

在本例中, 使用random 数据和自定义函数animation_func()

from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
import random
import numpy as np

x = []
y = []
colors = []
fig = plt.figure(figsize=(7,5))

def animation_func(i):
	x.append(random.randint(0,100))
	y.append(random.randint(0,100))
	colors.append(np.random.rand(1))
	area = random.randint(0,30) * random.randint(0,30)
	plt.xlim(0,100)
	plt.ylim(0,100)
	plt.scatter(x, y, c = colors, s = area, alpha = 0.5)

animation = FuncAnimation(fig, animation_func,
						interval = 100)
plt.show()

如下图：

使用 pause() 函数绘制动态直线

matplotlib工具包的pyplot模块中有pause()函数，可用来设置时间间隔参数，达到绘制直线的动画效果。

代码如下：

from matplotlib import pyplot as plt

x = []
y = []

for i in range(100):
	x.append(i)
	y.append(i)

	# Mention x and y limits to define their range
	plt.xlim(0, 100)
	plt.ylim(0, 100)
	
	# Ploting graph
	plt.plot(x, y, color = 'green')
	plt.pause(0.01)

plt.show()

如下图：

使用 FuncAnimation() 绘制动态直线

FuncAnimation() 函数本身并不能创建动画效果，而是通过生成一系列不同参数的图片来实现动画效果.

Syntax: FuncAnimation(figure, animation_function, frames=None, init_func=None, fargs=None, save_count=None, *, cache_frame_data=True, **kwargs)

在这个实例代码中，使用FuncAnimation函数创建一条直线的简单动画效果，只需要调整参数即刻。

from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
import numpy as np
  
x = []
y = []
  
figure, ax = plt.subplots()
  
# Setting limits for x and y axis
ax.set_xlim(0, 100)
ax.set_ylim(0, 12)
  
# Since plotting a single graph
line,  = ax.plot(0, 0) 
  
def animation_function(i):
    x.append(i * 15)
    y.append(i)
  
    line.set_xdata(x)
    line.set_ydata(y)
    return line,
  
animation = FuncAnimation(figure,
                          func = animation_function,
                          frames = np.arange(0, 10, 0.1), 
                          interval = 10)
plt.show()

如下图：