时间序列的类型与应用

Python 中的时间序列机器学习

Chris Holdgraf

Fellow, Berkeley Institute for Data Science

时间序列

时间序列的要素是什么？

Datapoint	Datapoint	Datapoint	Datapoint	Datapoint	Datapoint
1	34	12	54	76	40

Timepoint	Timepoint	Timepoint	Timepoint	Timepoint	Timepoint
2:00	2:01	2:02	2:03	2:04	2:05

Timepoint	Timepoint	Timepoint	Timepoint	Timepoint	Timepoint
Jan	Feb	March	April	May	Jun

Timepoint	Timepoint	Timepoint	Timepoint	Timepoint	Timepoint
1e-9	2e-9	3e-9	4e-9	5e-9	6e-9

用 Pandas 读取时间序列

import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv('data.csv')
data.head()

          date symbol       close       volume
0   2010-01-04   AAPL  214.009998  123432400.0
46  2010-01-05   AAPL  214.379993  150476200.0
92  2010-01-06   AAPL  210.969995  138040000.0
138 2010-01-07   AAPL  210.580000  119282800.0
184 2010-01-08   AAPL  211.980005  111902700.0

绘制 pandas 时间序列

import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(12, 6))
data.plot('date', 'close', ax=ax)
ax.set(title="AAPL daily closing price")

时间序列图

为何使用机器学习？

我们可以处理非常大且复杂的数据

为何使用机器学习？

我们可以：

预测未来
将此过程自动化

为何将二者结合？

机器学习流程

特征提取
模型拟合
预测与验证

让我们来练习！

Python 中的时间序列机器学习