df2.combine_first(df1)
（文档）似乎可以满足您的要求；PFB代码段和输出
import pandas as pdprint 'pandas-version: ', pd.__version__df1 = pd.Dataframe.from_records([('2015-07-09 12:00:00',1,1,1),('2015-07-09 13:00:00',1,1,1),('2015-07-09 14:00:00',1,1,1),('2015-07-09 15:00:00',1,1,1)], columns=['Dt', 'A', 'B', 'C']).set_index('Dt')# print df1df2 = pd.Dataframe.from_records([('2015-07-09 14:00:00',2,2,2,2),('2015-07-09 15:00:00',2,2,2,2),('2015-07-09 16:00:00',2,2,2,2),('2015-07-09 17:00:00',2,2,2,2),], columns=['Dt', 'A', 'B', 'C', 'D']).set_index('Dt')res_combine1st = df2.combine_first(df1)print res_combine1st
输出
pandas-version: 0.15.2 A B C DDt 2015-07-09 12:00:00 1 1 1 NaN2015-07-09 13:00:00 1 1 1 NaN2015-07-09 14:00:00 2 2 2 22015-07-09 15:00:00 2 2 2 22015-07-09 16:00:00 2 2 2 22015-07-09 17:00:00 2 2 2 2
