如何獲得Pandas中數據框的移位索引值？

Question

考慮以下這個簡單的例子：

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 

我希望創建一個包含索引的滯後/鉛值的變量。這是一樣的東西：

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

所以，舉例來說，在時間2011-01-01 01:00:00我希望變量index_shifted是2011-01-01 00:00:00

我怎麼能這樣做？ 謝謝！

Answer 1

我認爲你需要Index.shift與-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 

對我來說，工作沒有freq，但也許它是在真實的數據需要：

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 

編輯：

如果DatetimeIndexfreq爲None，你需要添加freq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 

Answer 2

df['index_shifted']=df.index.shift(-1)有什麼問題？

（正品的問題，不知道如果我錯過了什麼）