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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360
11
章 時系列データ
文字 オフセットクラス 説明
A-JAN, A-FEB, ... YearEnd
1
年に
1
度、指定した月の暦通りの月末ごと：
JAN
（
1
月）、
FEB
（
2
月）、
MAR
（
3
月）、
APR
（
4
月）、
MAY
（
5
月）、
JUN
（
6
月）、
JUL
（
7
月）、
AUG
（
8
月）、
SEP
（
9
月）、
OCT
（
10
月）、
NOV
（
11
月）、
DEC
（
12
月）。
BA-JAN, BA-FEB, ... BusinessYearEnd
1
年に
1
度、指定した月の最終営業日ごと。
AS-JAN, AS-FEB, ... YearBegin
1
年に
1
度、指定した月の暦通りの月初ごと。
BAS-JAN, BAS-FEB, ... BusinessYearBegin
1
年に
1
度、指定した月の営業開始日ごと。
date_range
は、デフォルトでは開始と終了のタイムスタンプを（もしあれば）保存します。
In [79]: pd.date_range('2012-05-02 12:56:31', periods=5)
Out[79]:
DatetimeIndex(['2012-05-02 12:56:31', '2012-05-03 12:56:31',
'2012-05-04 12:56:31', '2012-05-05 12:56:31',
'2012-05-06 12:56:31'],
dtype='datetime64[ns]', freq='D')
開始日と終了日に時刻の情報を追加したいものの、タイムスタンプとしては午前零 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.