python – 如何在Pandas中获取数据帧的移位索引值？

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的滞后/超前值的变量.这就是：

df['index_shifted']=df.index.shift(1)

因此,例如,在时间2011-01-01 01:00:00我期望变量index_shifted为2011-01-01 00:00:00

我怎样才能做到这一点？
谢谢！

解决方法:

我认为你需要Index.shift与-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

对我来说它没有频率工作,但也许在实际数据中是必要的：

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为None,则需要添加freq to 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

标签：shift,date-range,python,pandas,dataframe
来源： https://codeday.me/bug/20190722/1502731.html