時間序列的種類與應用

Python 的時間序列資料機器學習

Chris Holdgraf

Fellow, Berkeley Institute for Data Science

時間序列

什麼構成時間序列？

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 讀取時間序列

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

繪製 pandas 時間序列

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")

時間序列圖

為什麼要用機器學習？

我們可以處理非常大的資料與非常複雜的資料

為什麼要用機器學習？

我們可以：

預測未來
自動化這個流程

為什麼要結合這兩者？

機器學習流程

特徵擷取
模型擬合
預測與驗證

一起來練習吧！

Python 的時間序列資料機器學習