有没有办法在python中列出2个数据时间之间的日期时间范围？

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我在不同的列中有2组datetime数据，我想列出同一行的2个日期和时间范围内的范围。

例如，我尝试下面的输出不显示日期时间范围

import pandas as pd

a = '2020-11-17 13:35:18'   
b = '2020-11-17 13:36:09'

tt= pd.date_range(start=a,end=b)
print(tt)

OUTPUT:
DatetimeIndex(['2020-11-17 13:35:18'], dtype='datetime64[ns]', freq='D')

预期输出为：

['2020-11-17 13:35:18','2020-11-17 13:35:19',,'2020-11-17 13:35:20','2020-11-17 13:35:21','2020-11-17 13:35:22','2020-11-17 13:35:23','2020-11-17 13:35:24','2020-11-17 13:35:25',
'2020-11-17 13:35:26','2020-11-17 13:35:27','2020-11-17 13:35:28','2020-11-17 13:35:29','2020-11-17 13:35:30','2020-11-17 13:35:31','2020-11-17 13:35:32','2020-11-17 13:35:33',
'2020-11-17 13:35:34','2020-11-17 13:35:35','2020-11-17 13:35:36','2020-11-17 13:35:37','2020-11-17 13:35:38','2020-11-17 13:35:39','2020-11-17 13:35:40','2020-11-17 13:35:41',
'2020-11-17 13:35:42','2020-11-17 13:35:43','2020-11-17 13:35:44','2020-11-17 13:35:45','2020-11-17 13:35:46','2020-11-17 13:35:47','2020-11-17 13:35:48','2020-11-17 13:35:49',
'2020-11-17 13:35:50','2020-11-17 13:35:51','2020-11-17 13:35:52','2020-11-17 13:35:53','2020-11-17 13:35:54','2020-11-17 13:35:55','2020-11-17 13:35:56','2020-11-17 13:35:57',
'2020-11-17 13:35:58','2020-11-17 13:35:59','2020-11-17 13:36:00','2020-11-17 13:36:01','2020-11-17 13:36:02','2020-11-17 13:36:03','2020-11-17 13:36:04','2020-11-17 13:36:05',
'2020-11-17 13:36:06','2020-11-17 13:36:07','2020-11-17 13:36:08','2020-11-17 13:36:09']

耶斯列尔

您输出的原因是如果未设置freq参数，则使用默认值。

因此，设置S秒频率：

tt = pd.date_range(start=a,end=b, freq='S')
print(tt)
DatetimeIndex(['2020-11-17 13:35:18', '2020-11-17 13:35:19',
               '2020-11-17 13:35:20', '2020-11-17 13:35:21',
               '2020-11-17 13:35:22', '2020-11-17 13:35:23',
               '2020-11-17 13:35:24', '2020-11-17 13:35:25',
               '2020-11-17 13:35:26', '2020-11-17 13:35:27',
               '2020-11-17 13:35:28', '2020-11-17 13:35:29',
               '2020-11-17 13:35:30', '2020-11-17 13:35:31',
               '2020-11-17 13:35:32', '2020-11-17 13:35:33',
               '2020-11-17 13:35:34', '2020-11-17 13:35:35',
               '2020-11-17 13:35:36', '2020-11-17 13:35:37',
               '2020-11-17 13:35:38', '2020-11-17 13:35:39',
               '2020-11-17 13:35:40', '2020-11-17 13:35:41',
               '2020-11-17 13:35:42', '2020-11-17 13:35:43',
               '2020-11-17 13:35:44', '2020-11-17 13:35:45',
               '2020-11-17 13:35:46', '2020-11-17 13:35:47',
               '2020-11-17 13:35:48', '2020-11-17 13:35:49',
               '2020-11-17 13:35:50', '2020-11-17 13:35:51',
               '2020-11-17 13:35:52', '2020-11-17 13:35:53',
               '2020-11-17 13:35:54', '2020-11-17 13:35:55',
               '2020-11-17 13:35:56', '2020-11-17 13:35:57',
               '2020-11-17 13:35:58', '2020-11-17 13:35:59',
               '2020-11-17 13:36:00', '2020-11-17 13:36:01',
               '2020-11-17 13:36:02', '2020-11-17 13:36:03',
               '2020-11-17 13:36:04', '2020-11-17 13:36:05',
               '2020-11-17 13:36:06', '2020-11-17 13:36:07',
               '2020-11-17 13:36:08', '2020-11-17 13:36:09'],
              dtype='datetime64[ns]', freq='S')

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