在python中增加24小时到负时差

2024-02-27 22:45:39

我正在使用python计算两个事件之间的时间间隔.每个事件都有一个“开始时间”和“结束时间”.我在新列“时间间隔”中发现了两者之间的区别,但是当开始和结束时间在不同的日期时(例如,开始时间23:46:00和结束时间00:21:00给出了-23) ：25：00).我想创建一个if语句来运行“时间间隔”列,并将24小时添加到任何负值中.但是,我在将“间隔”值增加24小时时遇到了问题.目前,我的“间隔” dtype = timedelta64 [ns].

这是表格的一部分,以澄清问题：

        CallDate      BeginningTime        EndingTime            Interval
    75  1/8/2009    1900-01-01 07:49:00  1900-01-01 08:19:00     00:30:00
    76  1/11/2009   1900-01-01 14:37:00  1900-01-01 14:59:00     00:22:00
    77  1/9/2009    1900-01-01 09:29:00  1900-01-01 09:56:00     00:27:00
    78  1/11/2009   1900-01-01 09:20:00  1900-01-01 10:13:00     00:53:00
    79  1/16/2009   1900-01-01 15:11:00  1900-01-01 15:50:00     00:39:00
    80  1/17/2009   1900-01-01 22:52:00  1900-01-01 23:26:00     00:34:00
    81  1/19/2009   1900-01-01 05:48:00  1900-01-01 06:32:00     00:44:00
    82  1/20/2009   1900-01-01 23:46:00  1900-01-01 00:21:00     -23:25:00
    83  1/20/2009   1900-01-01 21:29:00  1900-01-01 22:08:00     00:39:00
    84  1/23/2009   1900-01-01 07:33:00  1900-01-01 07:55:00     00:22:00
    85  1/30/2009   1900-01-01 19:33:00  1900-01-01 20:01:00     00:28:00

更新：这是导致我到这一点的代码

   df['BeginningTime']=pd.to_datetime(df['BeginningTime'], format='%H:%M')
   df['EndingTime']=pd.to_datetime(df['EndingTime'], format='%H:%M')

   df['Interval']=df['EndingTime']-df['BeginningTime']

   df[['CallDate','BeginningTime','EndingTime','Interval']]

解决方法:

如果您只想将1天作为负数添加到时间增量中,请执行以下操作：

df['Interval']=df['Interval'].apply(lambda x: x + Timedelta(days=1) if x < 0 else x)

如果可以确定结束时间将在24小时之内,则可以检查结束时间是否早于开始时间,并使用timedelta将结束时间增加一天,而不是间隔时间.

from datetime import datetime, timedelta

d1 = datetime.strptime( "1900-01-01 23:46:00", "%Y-%m-%d %H:%M:%S" )
d2 = datetime.strptime( "1900-01-01 00:21:00", "%Y-%m-%d %H:%M:%S" )

if d2 < d1:
    d2 += timedelta(days=1)

print d2 - d1

# 0:35:00

使用熊猫,您可以执行以下操作：

import pandas as pd
from pandas import Timedelta

d = {
    "CallDate": [
        "1/8/2009",
        "1/11/2009",
        "1/9/2009",
        "1/11/2009",
        "1/16/2009",
        "1/17/2009",
        "1/19/2009",
        "1/20/2009",
        "1/20/2009",
        "1/23/2009",
        "1/30/2009"
    ],
    "BeginningTime": [
        "1900-01-01 07:49:00",
        "1900-01-01 14:37:00",
        "1900-01-01 09:29:00",
        "1900-01-01 09:20:00",
        "1900-01-01 15:11:00",
        "1900-01-01 22:52:00",
        "1900-01-01 05:48:00",
        "1900-01-01 23:46:00",
        "1900-01-01 21:29:00",
        "1900-01-01 07:33:00",
        "1900-01-01 19:33:00"
    ],
    "EndingTime": [
        "1900-01-01 08:19:00",
        "1900-01-01 14:59:00",
        "1900-01-01 09:56:00",
        "1900-01-01 10:13:00",
        "1900-01-01 15:50:00",
        "1900-01-01 23:26:00",
        "1900-01-01 06:32:00",
        "1900-01-01 00:21:00",
        "1900-01-01 22:08:00",
        "1900-01-01 07:55:00",
        "1900-01-01 20:01:00"
    ]
}

df = pd.DataFrame(data=d)

df['BeginningTime']=pd.to_datetime(df['BeginningTime'], format="%Y-%m-%d %H:%M:%S")
df['EndingTime']=pd.to_datetime(df['EndingTime'], format="%Y-%m-%d %H:%M:%S")

def interval(x):
    if x['EndingTime'] < x['BeginningTime']:
        x['EndingTime'] += Timedelta(days=1)
    return x['EndingTime'] - x['BeginningTime']

df['Interval'] = df.apply(interval, axis=1)

In [2]: df
Out[2]:
         BeginningTime   CallDate          EndingTime  Interval
0  1900-01-01 07:49:00   1/8/2009 1900-01-01 08:19:00  00:30:00
1  1900-01-01 14:37:00  1/11/2009 1900-01-01 14:59:00  00:22:00
2  1900-01-01 09:29:00   1/9/2009 1900-01-01 09:56:00  00:27:00
3  1900-01-01 09:20:00  1/11/2009 1900-01-01 10:13:00  00:53:00
4  1900-01-01 15:11:00  1/16/2009 1900-01-01 15:50:00  00:39:00
5  1900-01-01 22:52:00  1/17/2009 1900-01-01 23:26:00  00:34:00
6  1900-01-01 05:48:00  1/19/2009 1900-01-01 06:32:00  00:44:00
7  1900-01-01 23:46:00  1/20/2009 1900-01-01 00:21:00  00:35:00
8  1900-01-01 21:29:00  1/20/2009 1900-01-01 22:08:00  00:39:00
9  1900-01-01 07:33:00  1/23/2009 1900-01-01 07:55:00  00:22:00
10 1900-01-01 19:33:00  1/30/2009 1900-01-01 20:01:00  00:28:00

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