Python Pandas：两个不同数据帧中的日期时间比较以找到最接近的匹配项

考虑以下两个数据帧:

date,price
2022-07-23 02:00:00,22834.24
2022-07-23 03:00:00,22808.55
2022-07-23 04:00:00,22895.41
2022-07-23 05:00:00,22902.46
2022-07-23 06:00:00,22827.46
2022-07-23 19:00:00,22272.57
2022-07-23 20:00:00,22325.82
2022-07-23 21:00:00,22243.32
2022-07-23 22:00:00,22469.08
2022-07-23 23:00:00,22451.07
2022-07-24 00:00:00,22549.18
2022-07-24 01:00:00,22423.58
2022-07-24 02:00:00,22469.09
2022-07-24 04:00:00,22396.51
2022-07-24 05:00:00,22749.98
2022-07-24 06:00:00,22679.01
2022-07-24 07:00:00,22701.61

date,price,passed_bars
2022-07-23 02:00:00,22834.24,30.0
2022-07-23 19:00:00,22272.57,13.0
2022-07-24 04:00:00,22396.51,4.0

我们可以使用以下代码片段重新生成数据帧:

import pandas as pd

li1 = [{'date': '2022-07-23 02:00:00', 'price': 22834.24}, {'date': '2022-07-23 03:00:00', 'price': 22808.55},
       {'date': '2022-07-23 04:00:00', 'price': 22895.41}, {'date': '2022-07-23 05:00:00', 'price': 22902.46},
       {'date': '2022-07-23 06:00:00', 'price': 22827.46}, {'date': '2022-07-23 19:00:00', 'price': 22272.57},
       {'date': '2022-07-23 20:00:00', 'price': 22325.82}, {'date': '2022-07-23 21:00:00', 'price': 22243.32},
       {'date': '2022-07-23 22:00:00', 'price': 22469.08}, {'date': '2022-07-23 23:00:00', 'price': 22451.07},
       {'date': '2022-07-24 00:00:00', 'price': 22549.18}, {'date': '2022-07-24 01:00:00', 'price': 22423.58},
       {'date': '2022-07-24 02:00:00', 'price': 22469.09}, {'date': '2022-07-24 04:00:00', 'price': 22396.51},
       {'date': '2022-07-24 05:00:00', 'price': 22749.98}, {'date': '2022-07-24 06:00:00', 'price': 22679.01},
       {'date': '2022-07-24 07:00:00', 'price': 22701.61}]

li2 = [{'date': '2022-07-23 02:00:00', 'price': 22834.24, 'passed_bars': 30.0},
       {'date': '2022-07-23 19:00:00', 'price': 22272.57, 'passed_bars': 13.0},
       {'date': '2022-07-24 04:00:00', 'price': 22396.51, 'passed_bars': 4.0}]

df1 = pd.DataFrame.from_records(li1)

df2 = pd.DataFrame.from_records(li2)

目标是向第一个数据帧df1添加新列，其中每个值必须根据以下逻辑计算:

这个新列是df1中的当前记录和df2中最近的记录之间的时间距离，即df1.date.iloc[i] >= nearest_to_current(df2.date).

基于上述逻辑，所需的数据帧应该如下所示:

date,price, passed_time
2022-07-23 02:00:00,22834.24, 0 hours
2022-07-23 03:00:00,22808.55, 1 hours
2022-07-23 04:00:00,22895.41, 2 hours
2022-07-23 05:00:00,22902.46, 3 hours
2022-07-23 06:00:00,22827.46, 4 hours
2022-07-23 19:00:00,22272.57, 0 hours
2022-07-23 20:00:00,22325.82, 1 hours
2022-07-23 21:00:00,22243.32, 2 hours
2022-07-23 22:00:00,22469.08, 3 hours
2022-07-23 23:00:00,22451.07, 4 hours
2022-07-24 00:00:00,22549.18, 5 hours
2022-07-24 01:00:00,22423.58, 6 hours
2022-07-24 02:00:00,22469.09, 7 hours
2022-07-24 04:00:00,22396.51, 0 hours
2022-07-24 05:00:00,22749.98, 1 hours
2022-07-24 06:00:00,22679.01, 2 hours
2022-07-24 07:00:00,22701.61, 3 hours