我似乎无法将to_datetime应用于pandas数据帧列，尽管我过去曾做过几十次。下面的代码告诉我，在我尝试将其转换为时间戳之后，“Date Time”列中的任何随机值都是一个字符串。 'errors=coerce'应将任何解析错误转换为'NaT'，但我仍然将'2015-10-10 12:31:04'作为字符串。
import pandas as pd
df=pd.read_csv(...)
df["Date Time"]=pd.to_datetime(df["Date Time"],errors="coerce")
print str(type(df["Date Time"][9]))+" 1"##########
为什么pandas不会引发错误，或者不会将解析错误转换为'NaT'？
以下是csv的几行。真实文件有来自不同来源的一百万行，因此日期格式可能不一致，但在这种情况下，我希望datetime返回'NaT'或引发错误，具体取决于错误参数。
Accuracy,Activity,Altitude,Bearing,Date Time,Date(GMT),Description,Distance,Latitude,Longitude,Name,Speed,_FileNames,datenum
,,null,,,,,,sj,,,,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/aacy.csv,17054710926
0.0,,0.0,0.0,,,,0.00292115,50.67713796,4.61960233,,4.5,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/aars.csv,17054710926
0.0,,0.0,0.0,2015-01-31 15:10:,,,0.00404488,39.91572515,116.43714731,,5.4,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/abch.csv,17054710926
0.0,Walk/Run,0.0,0.0,2015-01-11 10:36:22,,,0,39.94002308,116.43548671,tfdeddd,0.0,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/abbj.csv,20150111
0.0,Walk/Run,0.0,0.0,2015-01-11 10:36:24,,,0.00968132,39.93998097,116.43558673,,2.7,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/abbj.csv,20150111
0.0,Walk/Run,0.0,0.0,2015-01-11 10:36:26,,,0.00768588,39.94003147,116.43552386,,4.5,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/abbj.csv,20150111
0.0,Walk/Run,0.0,0.0,2015-01-11 10:36:28,,,0.00239565,39.94007265,116.43551403,,3.6,C:/Users/Alexis/Dropbox/Location/Path Tracking Lite/abbj.csv,20150111