我在2018年1月1日创建了一个只有datetime列且间隔为1秒的数据框，如下面的代码所示。
i = pd.date_range(start='2018-01-01 00:00:00', end='2018-01-01 23:59:00', freq="1S")
ts = pd.DataFrame(index=i)
ts = ts.reset_index()
ts = ts.rename(columns={'index': 'datetime'})`
df1：
datetime
0 2018-01-01 00:00:00
1 2018-01-01 00:00:01
2 2018-01-01 00:00:02
3 2018-01-01 00:00:03
4 2018-01-01 00:00:04
5 2018-01-01 00:00:05
6 2018-01-01 00:00:06
7 2018-01-01 00:00:07
8 2018-01-01 00:00:08
9 2018-01-01 00:00:09
10 2018-01-01 00:00:10
11 2018-01-01 00:00:11
12 2018-01-01 00:00:12
13 2018-01-01 00:00:13
14 2018-01-01 00:00:14
15 2018-01-01 00:00:15
16 2018-01-01 00:00:16
17 2018-01-01 00:00:17
18 2018-01-01 00:00:18
19 2018-01-01 00:00:19
20 2018-01-01 00:00:20
21 2018-01-01 00:00:21
22 2018-01-01 00:00:22
23 2018-01-01 00:00:23
24 2018-01-01 00:00:24
25 2018-01-01 00:00:25
26 2018-01-01 00:00:26
27 2018-01-01 00:00:27
28 2018-01-01 00:00:28
29 2018-01-01 00:00:29`
我有另一个日期时间列和其他列的数据框
df2：
datetime a b c d e
0 2018-01-01 00:00:04 0.9
1 2018-01-01 00:00:06 0.6 0.7
2 2018-01-01 00:00:09 0.5 0.7 0.8
3 2018-01-01 00:00:16 2.3 3.6 4.9 5.0
4 2018-01-01 00:00:17 0.9 3.5 5.5
5 2018-01-01 00:00:23 0.1 0.6 0.0 1.7
6 2018-01-01 00:00:29 2.7 5.5 4.3 `
现在，我尝试使用pandas外连接映射df1和df2的日期时间列，我希望我的预期结果看起来像
datetime a b c d e
0 2018-01-01 00:00:00
1 2018-01-01 00:00:01
2 2018-01-01 00:00:02
3 2018-01-01 00:00:03
4 2018-01-01 00:00:04 0.9
5 2018-01-01 00:00:05
6 2018-01-01 00:00:06 0.6 0.7
7 2018-01-01 00:00:07
8 2018-01-01 00:00:08
9 2018-01-01 00:00:09 0.5 0.7 0.8
10 2018-01-01 00:00:10
11 2018-01-01 00:00:11
12 2018-01-01 00:00:12
13 2018-01-01 00:00:13
14 2018-01-01 00:00:14
15 2018-01-01 00:00:15
16 2018-01-01 00:00:16 2.3 3.6 4.9 5.0
17 2018-01-01 00:00:17 0.9 3.5 5.5
18 2018-01-01 00:00:18
19 2018-01-01 00:00:19
20 2018-01-01 00:00:20
21 2018-01-01 00:00:21
22 2018-01-01 00:00:22
23 2018-01-01 00:00:23 0.1 0.6 0.0 1.7
24 2018-01-01 00:00:24
25 2018-01-01 00:00:25
26 2018-01-01 00:00:26
27 2018-01-01 00:00:27
28 2018-01-01 00:00:28
29 2018-01-01 00:00:29 2.7 5.5 4.3 `
但是我的输出看起来像这样
datetime a b c d e
0 2018-01-01 00:00:00
1 2018-01-01 00:00:01
2 2018-01-01 00:00:02
3 2018-01-01 00:00:03
4 2018-01-01 00:00:04
5 2018-01-01 00:00:05
6 2018-01-01 00:00:06
7 2018-01-01 00:00:07
8 2018-01-01 00:00:08
9 2018-01-01 00:00:09
10 2018-01-01 00:00:10
11 2018-01-01 00:00:11
12 2018-01-01 00:00:12
13 2018-01-01 00:00:13
14 2018-01-01 00:00:14
15 2018-01-01 00:00:15
16 2018-01-01 00:00:16
17 2018-01-01 00:00:17
18 2018-01-01 00:00:18
19 2018-01-01 00:00:19
20 2018-01-01 00:00:20
21 2018-01-01 00:00:21
22 2018-01-01 00:00:22
23 2018-01-01 00:00:23
24 2018-01-01 00:00:24
25 2018-01-01 00:00:25
26 2018-01-01 00:00:26
27 2018-01-01 00:00:27
28 2018-01-01 00:00:28
29 2018-01-01 00:00:29
30 2018-01-01 00:00:04 0.9
31 2018-01-01 00:00:06 0.6 0.7
32 2018-01-01 00:00:09 0.5 0.7 0.8
33 2018-01-01 00:00:16 2.3 3.6 4.9 5.0
34 2018-01-01 00:00:17 0.9 3.5 5.5
35 2018-01-01 00:00:23 0.1 0.6 0.0 1.7
36 2018-01-01 00:00:29 2.7 5.5 4.3 `
我用于执行该操作的代码是：
test = pandas.merge(df1, df2, on = ['datetime'], how= 'outer')我不太确定如何解决此问题，如果能得到一些帮助，我将不胜感激。
最佳答案
将ts与datetime索引保持一致，并按照评论中提到的@Scott Boston使用Reindex，
i = pd.date_range(start='2018-01-01 00:00:00', end='2018-01-01 23:59:00', freq="1S")
ts = pd.DataFrame(index=i)
df['datetime'] = pd.to_datetime(df['datetime'])
df.set_index('datetime').reindex(ts.index)
a b c d e
2018-01-01 00:00:00 NaN NaN NaN NaN NaN
2018-01-01 00:00:01 NaN NaN NaN NaN NaN
2018-01-01 00:00:02 NaN NaN NaN NaN NaN
2018-01-01 00:00:03 NaN NaN NaN NaN NaN
2018-01-01 00:00:04 0.9
2018-01-01 00:00:05 NaN NaN NaN NaN NaN
2018-01-01 00:00:06 0.6 0.7
2018-01-01 00:00:07 NaN NaN NaN NaN NaN
2018-01-01 00:00:08 NaN NaN NaN NaN NaN
2018-01-01 00:00:09 0.5 0.7 0.8
2018-01-01 00:00:10 NaN NaN NaN NaN NaN
2018-01-01 00:00:11 NaN NaN NaN NaN NaN
2018-01-01 00:00:12 NaN NaN NaN NaN NaN
2018-01-01 00:00:13 NaN NaN NaN NaN NaN
2018-01-01 00:00:14 NaN NaN NaN NaN NaN
2018-01-01 00:00:15 NaN NaN NaN NaN NaN
2018-01-01 00:00:16 2.3 3.6 4.9 5.0
2018-01-01 00:00:17 0.9 3.5 5.5
选项2：连拍
pd.concat([ts, df.set_index('datetime')], axis = 1)
关于python - 映射两个表的日期时间列，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/54009571/