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首页 > 解决方案 > Pandas read_csv parse_dates format "%m/%d/%Y %H:%M:%S" 在列中仅解析日期，缺少时间

python - Pandas read_csv parse_dates format "%m/%d/%Y %H:%M:%S" 在列中仅解析日期，缺少时间

问题描述

我在 csv 文件中有一个统计数据，有些是包含数千行的大文件。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解析 pandas，但 pandas DataFrame 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

感谢您的帮助

标签： pythonpandasdatedatetime

解决方案

索引的显示减少到%m-%d-%Y但它也没有显示时间。多谢你们

解析日期

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