Python数据可视化：使用 Matplotlib 绘制人口变化趋势

1. 导入 NumPy 和 Matplotlib 库，读取 'chapter3 populations.npz' 文件中的数据并命名为 data:

import numpy as np
import matplotlib.pyplot as plt

data = np.load('chapter3 populations.npz')

2. 分别定义变量保存 data 中的数组，并输出:

year = data['year']
population = data['population']
male_population = data['male_population']
female_population = data['female_population']
urban_population = data['urban_population']
rural_population = data['rural_population']

print(year)
print(population)
print(male_population)
print(female_population)
print(urban_population)
print(rural_population)

3. 定义画布大小 figsize=(15,5)，创建 1行2 列的子图: 利用散点图画出 1996-2015 年人口变化，第一幅子图绘制出男性人口和女性人口随时间的变化，第二幅子图绘制出城镇人口和乡村人口随时间的变化:

fig, axes = plt.subplots(1, 2, figsize=(15, 5))

axes[0].scatter(year, male_population, label='Male Population')
axes[0].scatter(year, female_population, label='Female Population')
axes[0].set_xlabel('Year')
axes[0].set_ylabel('Population')
axes[0].set_title('Male and Female Population')
axes[0].legend()

axes[1].scatter(year, urban_population, label='Urban Population')
axes[1].scatter(year, rural_population, label='Rural Population')
axes[1].set_xlabel('Year')
axes[1].set_ylabel('Population')
axes[1].set_title('Urban and Rural Population')
axes[1].legend()

plt.show()