如何從Python中的變量中刪除/去除行號

Question

import csv 
import pandas as pd 
from datetime import datetime,time,date 
from pandas.io.data import DataReader 

fd = pd.read_csv('c:\\path\\to\\file.csv') 

fd.columns = ['Date','Time'] 

datex = fd.Date 
timex = fd.Time 

timestr = datetime.strptime (str(datex+" "+timex) , "%m/%d/%Y %H:%M") 

所以，我想要做的是將日期和時間列傳遞給datetime。有兩列，日期和時間顯然包含日期和時間。但是，當我嘗試了上面的方法，我收到此錯誤：

\n35760 08/07/2015 04:56\n35761 08/07/2015 04:57\n35762 08/07/2015 04:58\n35763 08/07/2015 04:59\ndtype: object' does not match format '%m/%d/%Y %H:%M' 

那麼，如何做我要麼帶或DATEX和天美時刪除\ nXXXXX？或以其他方式匹配格式？

Answer 1

# concatenate two columns (date and time) into one column that represent date time now into one columns 
datetime = datex + timex 
# remove additional characters and spaces from newly created datetime colummn 
datetime = datetime.str.replace('\n\d+' , '').str.strip() 
# then string should be ready to be converted to datetime easily 
pd.to_datetime(datetime , format='%m/%d/%Y%H:%M') 

Answer 2

使用熊貓內置parse_dates功能:)

pd.read_csv('c:\\path\\to\\file.csv', parse_dates=True)