July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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386
11
章 時系列データ
2001Q4 0.046303 0.163344 0.251503 -0.157276
期間は一定の間隔を表すものなので、アップサンプリングとダウンサンプリングのルールはより厳格
になります。
●
ダウンサンプリングにおいて、変換後の頻度は、変換前の頻度に基づいた長い期間でなければ
ならない。
●
アップサンプリングにおいて、変換後の頻度は、変換前の頻度に基づいた短い期間でなければ
ならない。
これらのルールが満たされない場合は、例外が発生します。これは主に、四半期、年次、週次の
頻度において影響があります。例えば、変換後を
Q-MAR
の頻度にする場合は、変換前の頻度が
A-MAR
、
A-JUN
、
A-SEP
、
A-DEC
である必要があります
＊
1
。
In [234]: annual_frame.resample('Q-MAR').ffill()
Out[234]:
Colorado Texa
s New York Ohio
2000Q4 0.556703 0.016631 0.111873 -0.027445
2001Q1 0.556703 0.016631 0.111873 -0.027445
2001Q2 0.556703 0.016631 0.111873 -0.027445
2001Q3 0.556703 0.016631 0.111873 -0.027445
2001Q4 0.046303 0.163344 0.251503 -0.157276
2002Q1 0.046303 0.163344 ...
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