Python 如何根据数据范围最好地合并两个数据框

我正在try 合并两个数据帧.On有一个包含事件的日期范围列，另一个包含值的列.我想将这一事件添加到测量值和各自的日期中.

import pandas as pd

df_1 = pd.DataFrame(
    columns=["timestamp", "measured value"],
    data=[
        (pd.to_datetime("2012-07-16 23:23:50"), 2.1),
        (pd.to_datetime("2012-08-16 02:23:50"), 4),
        (pd.to_datetime("2015-07-16 12:23:50"), 2),
        (pd.to_datetime("2018-08-16 20:23:50"), 1.2),
    ],
)
df_2 = pd.DataFrame(
    columns=["start", "end", "event"],
    data=[
        
        (
            pd.to_datetime("2015-06-16 12:23:50"),
            pd.to_datetime("2015-08-16 12:23:50"),
            True,
        ),
       
    ],
)

我try 了以下几种方法:

df_2.index = pd.IntervalIndex.from_arrays(df_2["start"], df_2["end"], closed="both")
df_1.assign(events = df_2['event'])

 timestamp  measured value events
0 2012-07-16 23:23:50    2.1    NaN
1 2012-08-16 02:23:50    4.0    NaN
2 2015-07-16 12:23:50    2.0    NaN
3 2018-08-16 20:23:50    1.2    NaN

所需输出:

 timestamp  measured value event
0 2012-07-16 23:23:50    2.1   NaN
1 2012-08-16 02:23:50    4.0   NaN
2 2015-07-16 12:23:50    2.0  True
3 2018-08-16 20:23:50    1.2   NaN