官方示例
import numpy as np
import matplotlib.pyplot as plt
# 创建模拟数据
t = np.arange(0.01, 10.0, 0.01)
data1 = np.exp(t)
data2 = np.sin(2 * np.pi * t)
fig, ax1 = plt.subplots()
color = 'tab:red'
ax1.set_xlabel('time (s)')
ax1.set_ylabel('exp', color=color)
ax1.plot(t, data1, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax2 = ax1.twinx() # 创建共用x轴的第二个y轴
color = 'tab:blue'
ax2.set_ylabel('sin', color=color)
ax2.plot(t, data2, color=color)
ax2.tick_params(axis='y', labelcolor=color)
fig.tight_layout()
plt.show()
结果如下图：
封装成函数
为了便于使用封装成函数，代码如下：
import matplotlib.pyplot as plt
def plot_twin(_y1, _y2, _ylabel1, _ylabel2):
fig, ax1 = plt.subplots()
color = 'tab:blue'
ax1.set_xlabel('time')
ax1.set_ylabel(_ylabel1, color=color)
ax1.plot(_y1, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax2 = ax1.twinx() # 创建共用x轴的第二个y轴
color = 'tab:red'
ax2.set_ylabel(_ylabel2, color=color)
ax2.plot(_y2, color=color)
ax2.tick_params(axis='y', labelcolor=color)
fig.tight_layout()
plt.show()
if __name__ == '__main__':
import numpy as np
# 创建模拟数据
t = np.arange(0.01, 10.0, 0.01)
data1 = np.exp(t)
data2 = np.sin(2 * np.pi * t)
plot_twin(data1, data2, 'exp', 'sine')