熊猫read_csv parse_dates格式“％m /％d /％Y％H：％M：％S”仅在列中解析日期，缺少时间

Question

我在csv文件中有一个统计信息，有些是具有数千行的巨大文件。结构是：

"Result  :  Stat01"
"Save Time: 09/23/2019 19:01:27"

"User Name:admin"

"Total 1,365    Records"

"Start Time","Period","Messages Received","Messages Sent"
09/23/2019 01:30:00,5,114,57
09/23/2019 01:30:00,5,0,0
09/23/2019 01:30:00,5,47493,46911
09/23/2019 01:30:00,5,47772,46347
09/23/2019 01:30:00,5,0,0
09/23/2019 01:35:00,5,32990,34652
09/23/2019 01:35:00,5,142,63
09/23/2019 01:35:00,5,0,0
09/23/2019 01:35:00,5,47379,46297
09/23/2019 01:35:00,5,46324,45750
09/23/2019 01:35:00,5,0,0
09/23/2019 01:40:00,5,31974,33969
09/23/2019 01:40:00,5,114,57
09/23/2019 01:40:00,5,0,0
09/23/2019 01:40:00,5,44701,43845
09/23/2019 01:40:00,5,44903,43770
09/23/2019 01:40:00,5,0,0
09/23/2019 01:45:00,5,33531,35274
09/23/2019 01:45:00,5,126,63
09/23/2019 01:45:00,5,0,0
09/23/2019 01:45:00,5,45821,43960
09/23/2019 01:45:00,5,44988,45120
09/23/2019 01:45:00,5,0,0
09/23/2019 01:50:00,5,32544,33804
09/23/2019 01:50:00,5,112,56
09/23/2019 01:50:00,5,0,0
09/23/2019 01:50:00,5,45645,44609
09/23/2019 01:50:00,5,44878,44628

我尝试使用 parse_dates 和 date_parser 在熊猫中进行解析，但是pandas DataFrame中的结果只是日期，它跳过了时间。统计信息有5分钟的频率，需要时间。 使用的代码是

mydateparser = lambda x: pd.datetime.strptime(x, "%m/%d/%Y %H:%M:%S")
sta = pd.read_csv('Export.csv',skiprows=7,parse_dates=["Start Time"],date_parser= mydateparser)
sta.head()

输出没有时间：

Start Time  Period  Messages Received   Messages Sent
0   2019-09-23  5   46803   49665
1   2019-09-23  5   112 56
2   2019-09-23  5   0   0
3   2019-09-23  5   66647   65771
4   2019-09-23  5   67151   65191

感谢您的帮助

Answer 1

索引的显示减少为%m-%d-%Y，但是也没有显示时间。 谢谢大家

Answer 2

“时间”似乎是包含时间的列。您仅在解析“开始时间”。解析两者或将两者组合成一列。