如何将时间四舍五入到下一刻钟？答案

【问题标题】：How can I round up time to the following quarter of the hour?如何将时间四舍五入到下一刻钟？
【发布时间】：2019-07-25 15:24:14
【问题描述】：

我想将 HH:MM:SS 向上舍入到下一个季度。举几个例子：

我有以下数据：

12:25:00 PM
03:33:00 PM
03:36:00 PM
03:48:00 PM

我想得到以下结果：

12:30:00 PM
03:45:00 PM
03:45:00 PM
04:00:00 PM

【问题讨论】：

标签： python timestamp rounding

【解决方案1】：

只需添加一个timedelta 15 的最接近的下一个倍数与当前分钟之间的差异

>>> from datetime import datetime,timedelta
>>> time_lst = ['12:25:00 PM', '03:33:00 PM', '03:36:00 PM', '03:48:00 PM']
>>>
>>> dt_list = [datetime.strptime(time, "%H:%M:%S %p") for time in time_lst]
>>> [(dt + timedelta(minutes=15*(int(dt.minute/15)+1) - dt.minute)).strftime("%H:%M:%S %p") for dt in dt_list]
['12:30:00 PM', '03:45:00 AM', '03:45:00 AM', '04:00:00 AM']
>>>

【讨论】：

【解决方案2】：

import time
from math import floor, ceil

SECONDS_PER_15MIN = 15 * 60;

time_now = time.time() # somehow get your time in seconds
print("now", time.asctime(time.localtime(time_now)))

# Count how often 15minutes fits in there
count = time_now/SECONDS_PER_15MIN
# Round it down or up and multiply with the number of seconds in 15 minutes again to get the total number of seconds
time_rounded_down = floor(count) * SECONDS_PER_15MIN
time_rounded_up = ceil(count) * SECONDS_PER_15MIN
print("down", time.asctime(time.localtime(time_rounded_down)))
print("up", time.asctime(time.localtime(time_rounded_up)))

【讨论】：

【解决方案3】：

类似的东西

import math

lst = ['12:25:00 PM',
       '03:33:00 PM',
       '03:36:00 PM',
       '03:48:00 PM']
new_time_lst = []

for entry in lst:
    elements = entry.split(':')
    hours = int(elements[0])
    minutes = int(elements[1])
    q = math.floor(minutes / 15)
    if q < 3:
        q += 1
    else:
        q = 0
        hours += 1
    hours_str = '0' + str(hours) if hours < 10 else str(hours)
    q_str = str(q * 15)
    elements[0] = hours_str
    elements[1] = q_str
    new_time = ':'.join(elements)
    new_time_lst.append(new_time)

print(new_time_lst)

输出

['12:30:00 PM', '03:45:00 PM', '03:45:00 PM', '04:0:00 PM']

【讨论】：

【解决方案4】：

感谢您的帮助。

我找到了一种更简单的方法，我想在这里分享：

In [1]:df['Times']

0   2019-08-07 12:25:00
1   2019-08-07 15:33:00
2   2019-08-07 15:36:00
3   2019-08-07 15:48:00


df['Times'].apply(lambda x: pd.Timestamp(x).ceil('15T'))

0   2019-08-07 12:30:00
1   2019-08-07 15:45:00
2   2019-08-07 15:45:00
3   2019-08-07 16:00:00

【讨论】：