如何使用日期時間索引搜索日期時間索引

Question

給定一個DataFrame，其中索引是Datetime，如何通過只匹配日期部分來檢索行？

例如：

df1 = 

        A B C D 
2011-01-13 16:00:00 344 144 616 73 
2011-01-14 16:00:00 346 145 624 74 
2011-01-18 16:00:00 339 146 639 77 
... 

並考慮：

df2['Date'] = 

0 2011-01-13 
1 2011-01-13 
2 2011-01-26 
3 2011-02-02 
4 2011-02-10 
5 2011-03-03 
6 2011-03-03 
7 2011-06-03 
8 2011-05-03 
9 2011-06-10 
10 2011-08-01 
11 2011-08-01 
12 2011-12-20 

我想是這樣的：

for indx, row in df2.iterrows(): 
    print df1.loc[df1.index.date() == row['Date'].date()] 

Answer 1

您可以使用to_series，date和isin：

print df1.index.to_series().dt.date 
2011-01-13 16:00:00 2011-01-13 
2011-01-14 16:00:00 2011-01-14 
2011-01-18 16:00:00 2011-01-18 
dtype: object 

print df1.index.to_series().dt.date.isin(df2['Date'].dt.date) 
Name: Date, dtype: object 
2011-01-13 16:00:00  True 
2011-01-14 16:00:00 False 
2011-01-18 16:00:00 False 
dtype: bool 

print df1[df1.index.to_series().dt.date.isin(df2['Date'].dt.date)] 
         A B C D 
2011-01-13 16:00:00 344 144 616 73 

或者，也許你需要：

print df1.index.date 
[datetime.date(2011, 1, 13) datetime.date(2011, 1, 14) 
datetime.date(2011, 1, 18)] 

print df2['Date'].dt.date.isin(df1.index.date) 
0  True 
1  True 
2  False 
3  False 
4  False 
5  False 
6  False 
7  False 
8  False 
9  False 
10 False 
11 False 
12 False 
Name: Date, dtype: bool 

print df2[df2['Date'].dt.date.isin(df1.index.date)] 
     Date 
0 2011-01-13 
1 2011-01-13 

Answer 2

可以在df1創建日期列，然後將該表合併df2（假定在df2日期類型datetime.date的）：

df1['Date'] = [d.date() for d in df1.index] 
>>> df2.merge(df1, how='left', on='Date'] 
      Date A B C D 
0 2011-01-13 344 144 616 73 
1 2011-01-13 344 144 616 73 
2 2011-01-26 NaN NaN NaN NaN 
3 2011-02-02 NaN NaN NaN NaN 
4 2011-02-10 NaN NaN NaN NaN 
5 2011-03-03 NaN NaN NaN NaN 
6 2011-03-03 NaN NaN NaN NaN 
7 2011-06-03 NaN NaN NaN NaN 
8 2011-05-03 NaN NaN NaN NaN 
9 2011-06-10 NaN NaN NaN NaN 
10 2011-08-01 NaN NaN NaN NaN 
11 2011-08-01 NaN NaN NaN NaN 
12 2011-12-20 NaN NaN NaN NaN