Pandas read\u csv parse\u dates格式“%m/%d/%Y%H:%m:%S”位于仅分析日期列中，缺少tim

Question

我有一个统计在csv文件，一些是巨大的文件与数千行。结构为：

"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

我尝试在pandas中用parse\u dates和date\u parser进行解析，但是在pandas数据帧中的结果只是日期，它跳过了时间。统计有5分钟的频率，它需要时间。 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

谢谢你的帮助

Answer 1

“Period”似乎是包含时间的列。您只解析“开始时间”。分析两者或将两者合并为一列。你知道吗

Answer 2

索引的表示形式被缩减为%m-%d-%Y，但是它也有时间没有显示。 谢谢你们