python可视化分析（八）-绘制双坐标系时间序列图

实现功能：

python绘制双坐标系（双变量）时间序列图。

实现代码：

import pandasas pd

import numpyas np

import matplotlib.pyplotas plt

# Import Data

df = pd.read_csv("F:\数据杂坛\datasets\economics.csv")

x = df['date']

y1 = df['psavert']

y2 = df['unemploy']

# Plot Line1 (Left Y Axis)

fig, ax1 = plt.subplots(1, 1, figsize=(12, 6), dpi=100)

ax1.plot(x, y1, color='tab:red')

# Plot Line2 (Right Y Axis)

ax2 = ax1.twinx()# instantiate a second axes that shares the same x-axis

ax2.plot(x, y2, color='tab:blue')

# Decorations

# ax1 (left Y axis)

ax1.set_xlabel('Year', fontsize=18)

ax1.tick_params(axis='x', rotation=70, labelsize=12)

ax1.set_ylabel('Personal Savings Rate', color='#dc2624', fontsize=16)

ax1.tick_params(axis='y', rotation=0, labelcolor='#dc2624')

ax1.grid(alpha=.4)

# ax2 (right Y axis)

ax2.set_ylabel("Unemployed (1000's)", color='#01a2d9', fontsize=16)

ax2.tick_params(axis='y', labelcolor='#01a2d9')

ax2.set_xticks(np.arange(0, len(x), 60))

ax2.set_xticklabels(x[::60], rotation=90, fontdict={'fontsize':10})

ax2.set_title(

"Personal Savings Rate vs Unemployed: Plotting in Secondary Y Axis",

    fontsize=18)

fig.tight_layout()

plt.show()

实现效果：

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