Python Pandas：如何根据日期组合或合并两个不同大小的数据帧

Question

我喜欢根据日期范围合并或组合两个不同大小的数据帧 df1 和 df2，例如：

df1:

Date        Open  High  Low
2021-07-01  8.43  8.44  8.22 
2021-07-02  8.36  8.4   8.28
2021-07-06  8.22  8.23  8.06
2021-07-07  8.1   8.19  7.98
2021-07-08  8.07  8.1   7.91
2021-07-09  7.97  8.11  7.92
2021-07-12  8     8.2   8
2021-07-13  8.15  8.18  8.06
2021-07-14  8.18  8.27  8.12
2021-07-15  8.21  8.26  8.06
2021-07-16  8.12  8.23  8.07

df2：

Day of month   Revenue   Earnings
01             45000     4000
07             43500     5000
12             44350     6000
15             39050     7000

结果应该是这样的：

组合：

Date        Open  High  Low   Earnings
2021-07-01  8.43  8.44  8.22  4000
2021-07-02  8.36  8.4   8.28  4000
2021-07-06  8.22  8.23  8.06  4000
2021-07-07  8.1   8.19  7.98  5000
2021-07-08  8.07  8.1   7.91  5000
2021-07-09  7.97  8.11  7.92  5000
2021-07-12  8     8.2   8     6000
2021-07-13  8.15  8.18  8.06  6000
2021-07-14  8.18  8.27  8.12  6000
2021-07-15  8.21  8.26  8.06  7000
2021-07-16  8.12  8.23  8.07  7000

收益列是根据日期范围合并的，我如何在 python pandas 中执行此操作？

Answer 1

尝试merge_asof

#df1.date=pd.to_datetime(df1.date)
df1['Day of month'] = df1.Date.dt.day 
out = pd.merge_asof(df1, df2, on ='Day of month', direction = 'backward')
out
Out[213]: 
         Date  Open  High   Low  Day of month  Revenue  Earnings
0  2021-07-01  8.43  8.44  8.22           1    45000      4000
1  2021-07-02  8.36  8.40  8.28           2    45000      4000
2  2021-07-06  8.22  8.23  8.06           6    45000      4000
3  2021-07-07  8.10  8.19  7.98           7    43500      5000
4  2021-07-08  8.07  8.10  7.91           8    43500      5000
5  2021-07-09  7.97  8.11  7.92           9    43500      5000
6  2021-07-12  8.00  8.20  8.00          12    44350      6000
7  2021-07-13  8.15  8.18  8.06          13    44350      6000
8  2021-07-14  8.18  8.27  8.12          14    44350      6000
9  2021-07-15  8.21  8.26  8.06          15    39050      7000
10 2021-07-16  8.12  8.23  8.07          16    39050      7000