<p>我试图重复这个问题。希望这对你有用</p>
<pre><code>import io, pandas as pd
file1 = io.StringIO('''
evt_gts evt_id
01-07-2019 16:42:00 976162O
01-07-2019 16:42:30 976162O
04-07-2019 15:03:20 976162O
04-07-2019 15:03:25 976162O
05-07-2019 10:20:00 976162O
''')
file2= io.StringIO('''
timestamp variable
01-07-2019 13:25:03 RefSpd
01-07-2019 13:25:10 EffRealized
01-07-2019 13:25:30 ABHPosition
01-07-2019 13:25:35 LinkVolt
01-07-2019 13:25:36 BCPress
01-07-2019 23:18:00 speed
01-07-2019 23:18:05 temperature
01-07-2019 23:31:00 speed
01-07-2019 23:31:04 temperature
01-07-2019 23:43:00 speed
01-07-2019 23:43:05 temperature
''')
df1 = pd.read_csv(file1, delim_whitespace=True).reset_index()
df2 = pd.read_csv(file2, delim_whitespace=True).reset_index()
df1['date'] = pd.to_datetime(df1['index'] + " " + df1['evt_gts'])
df1 = df1[['date', 'evt_id']]
df1.columns = ['date', 'variable']
df2['date'] = pd.to_datetime(df2['index'] + " " + df2['timestamp'])
df2 = df2[['date', 'variable']]
df = pd.concat([df1, df2]).sort_values('date')
print(df)
</code></pre>
<p>结果</p>
<pre><code> date variable
0 2019-01-07 13:25:03 RefSpd
1 2019-01-07 13:25:10 EffRealized
2 2019-01-07 13:25:30 ABHPosition
3 2019-01-07 13:25:35 LinkVolt
4 2019-01-07 13:25:36 BCPress
0 2019-01-07 16:42:00 976162O
1 2019-01-07 16:42:30 976162O
5 2019-01-07 23:18:00 speed
6 2019-01-07 23:18:05 temperature
7 2019-01-07 23:31:00 speed
8 2019-01-07 23:31:04 temperature
9 2019-01-07 23:43:00 speed
10 2019-01-07 23:43:05 temperature
2 2019-04-07 15:03:20 976162O
3 2019-04-07 15:03:25 976162O
4 2019-05-07 10:20:00 976162O
</code></pre>
