如何在 Pandas 中获取数据帧的移位索引值?
how to get the shifted index value of a dataframe in Pandas?
考虑下面的简单示例:
date = pd.date_range('1/1/2011', periods=5, freq='H')
df = pd.DataFrame({'cat' : ['A', 'A', 'A', 'B',
'B']}, index = date)
df
Out[278]:
cat
2011-01-01 00:00:00 A
2011-01-01 01:00:00 A
2011-01-01 02:00:00 A
2011-01-01 03:00:00 B
2011-01-01 04:00:00 B
我想创建一个包含索引 lagged/lead 值的变量。那是这样的:
df['index_shifted']=df.index.shift(1)
因此,例如,在时间 2011-01-01 01:00:00
我希望变量 index_shifted
为 2011-01-01 00:00:00
我该怎么做?
谢谢!
df['index_shifted']=df.index.shift(-1)
怎么了?
(正版问题,不知道有没有遗漏)
我认为你需要 Index.shift
和 -1
:
df['index_shifted']= df.index.shift(-1)
print (df)
cat index_shifted
2011-01-01 00:00:00 A 2010-12-31 23:00:00
2011-01-01 01:00:00 A 2011-01-01 00:00:00
2011-01-01 02:00:00 A 2011-01-01 01:00:00
2011-01-01 03:00:00 B 2011-01-01 02:00:00
2011-01-01 04:00:00 B 2011-01-01 03:00:00
对我来说,它可以在没有 freq
的情况下工作,但在实际数据中可能是必要的:
df['index_shifted']= df.index.shift(-1, freq='H')
print (df)
cat index_shifted
2011-01-01 00:00:00 A 2010-12-31 23:00:00
2011-01-01 01:00:00 A 2011-01-01 00:00:00
2011-01-01 02:00:00 A 2011-01-01 01:00:00
2011-01-01 03:00:00 B 2011-01-01 02:00:00
2011-01-01 04:00:00 B 2011-01-01 03:00:00
编辑:
如果DatetimeIndex
的freq
是None
,您需要将freq
添加到shift
:
import pandas as pd
date = pd.date_range('1/1/2011', periods=5, freq='H').union(pd.date_range('5/1/2011', periods=5, freq='H'))
df = pd.DataFrame({'cat' : ['A', 'A', 'A', 'B',
'B','A', 'A', 'A', 'B',
'B']}, index = date)
print (df.index)
DatetimeIndex(['2011-01-01 00:00:00', '2011-01-01 01:00:00',
'2011-01-01 02:00:00', '2011-01-01 03:00:00',
'2011-01-01 04:00:00', '2011-05-01 00:00:00',
'2011-05-01 01:00:00', '2011-05-01 02:00:00',
'2011-05-01 03:00:00', '2011-05-01 04:00:00'],
dtype='datetime64[ns]', freq=None)
df['index_shifted']= df.index.shift(-1, freq='H')
print (df)
cat index_shifted
2011-01-01 00:00:00 A 2010-12-31 23:00:00
2011-01-01 01:00:00 A 2011-01-01 00:00:00
2011-01-01 02:00:00 A 2011-01-01 01:00:00
2011-01-01 03:00:00 B 2011-01-01 02:00:00
2011-01-01 04:00:00 B 2011-01-01 03:00:00
2011-05-01 00:00:00 A 2011-04-30 23:00:00
2011-05-01 01:00:00 A 2011-05-01 00:00:00
2011-05-01 02:00:00 A 2011-05-01 01:00:00
2011-05-01 03:00:00 B 2011-05-01 02:00:00
2011-05-01 04:00:00 B 2011-05-01 03:00:00
考虑下面的简单示例:
date = pd.date_range('1/1/2011', periods=5, freq='H')
df = pd.DataFrame({'cat' : ['A', 'A', 'A', 'B',
'B']}, index = date)
df
Out[278]:
cat
2011-01-01 00:00:00 A
2011-01-01 01:00:00 A
2011-01-01 02:00:00 A
2011-01-01 03:00:00 B
2011-01-01 04:00:00 B
我想创建一个包含索引 lagged/lead 值的变量。那是这样的:
df['index_shifted']=df.index.shift(1)
因此,例如,在时间 2011-01-01 01:00:00
我希望变量 index_shifted
为 2011-01-01 00:00:00
我该怎么做? 谢谢!
df['index_shifted']=df.index.shift(-1)
怎么了?
(正版问题,不知道有没有遗漏)
我认为你需要 Index.shift
和 -1
:
df['index_shifted']= df.index.shift(-1)
print (df)
cat index_shifted
2011-01-01 00:00:00 A 2010-12-31 23:00:00
2011-01-01 01:00:00 A 2011-01-01 00:00:00
2011-01-01 02:00:00 A 2011-01-01 01:00:00
2011-01-01 03:00:00 B 2011-01-01 02:00:00
2011-01-01 04:00:00 B 2011-01-01 03:00:00
对我来说,它可以在没有 freq
的情况下工作,但在实际数据中可能是必要的:
df['index_shifted']= df.index.shift(-1, freq='H')
print (df)
cat index_shifted
2011-01-01 00:00:00 A 2010-12-31 23:00:00
2011-01-01 01:00:00 A 2011-01-01 00:00:00
2011-01-01 02:00:00 A 2011-01-01 01:00:00
2011-01-01 03:00:00 B 2011-01-01 02:00:00
2011-01-01 04:00:00 B 2011-01-01 03:00:00
编辑:
如果DatetimeIndex
的freq
是None
,您需要将freq
添加到shift
:
import pandas as pd
date = pd.date_range('1/1/2011', periods=5, freq='H').union(pd.date_range('5/1/2011', periods=5, freq='H'))
df = pd.DataFrame({'cat' : ['A', 'A', 'A', 'B',
'B','A', 'A', 'A', 'B',
'B']}, index = date)
print (df.index)
DatetimeIndex(['2011-01-01 00:00:00', '2011-01-01 01:00:00',
'2011-01-01 02:00:00', '2011-01-01 03:00:00',
'2011-01-01 04:00:00', '2011-05-01 00:00:00',
'2011-05-01 01:00:00', '2011-05-01 02:00:00',
'2011-05-01 03:00:00', '2011-05-01 04:00:00'],
dtype='datetime64[ns]', freq=None)
df['index_shifted']= df.index.shift(-1, freq='H')
print (df)
cat index_shifted
2011-01-01 00:00:00 A 2010-12-31 23:00:00
2011-01-01 01:00:00 A 2011-01-01 00:00:00
2011-01-01 02:00:00 A 2011-01-01 01:00:00
2011-01-01 03:00:00 B 2011-01-01 02:00:00
2011-01-01 04:00:00 B 2011-01-01 03:00:00
2011-05-01 00:00:00 A 2011-04-30 23:00:00
2011-05-01 01:00:00 A 2011-05-01 00:00:00
2011-05-01 02:00:00 A 2011-05-01 01:00:00
2011-05-01 03:00:00 B 2011-05-01 02:00:00
2011-05-01 04:00:00 B 2011-05-01 03:00:00