Python 3基于日期列(字符串格式)从CSV删除行

Question

我试图适合以下情况 - 但失败

pandas -python，基于日期列删除行

我有一个带有以下列的output.csv文件

Customer, Alertkey, Node, Alertgroup, FirstOccurrence,
TKT_Flag, X733SpecificProb, TKT_TicketNumber, TKT_Keyword

最近7天数据将每7天从数据库中更新该文件

因此，理想情况下，我必须从文件本身中删除数据的前7天。

我可以在下面写下，但是获取类型错误" typeError：字符串索引必须是整数"

import pandas as pd
from dateutil.relativedelta import relativedelta
from dateutil import parser

df=pd.read_csv('output.csv', usecols=['FirstOccurrence'],parse_dates=[0])
df=df['FirstOccurrence'].iloc[0]
dt = parser.parse(df)
SevenDays = dt + relativedelta( days = +7 )
df=df[(parser.parse(df['FirstOccurrence']) < SevenDays)].drop(df.columns)

将有数百万行。我将从2016年1月1日开始复制前几行。但是它将从2016年1月1日到迄今为止。每周都会附加并应删除前7天的记录 - 即首次应从1月1日至1月6日删除记录，等等

Customer,Alertkey,Node,Alertgroup,FirstOccurrence,TKT_Flag,X733SpecificProb,TKT_TicketNumber,TKT_Keyword
Cust1,Cust1_11_53_Services_Warning,Node_Cust1,ITM_K53_SERVICEMON,2016-01-01 00:12:59,1005,TOLPUKC_OS:25223174,INC000014799786,CGMIDDLEWARE_MEDIUM_CONNECTDIRECT
Cust1,Cust1_11_53_Services_Warning,Node1_Cust1,ITM_K53_SERVICEMON,2016-01-01 00:12:59,1005,TOLPUKC_OS:25223175,INC000014799785,CGMIDDLEWARE_MEDIUM_CONNECTDIRECT
Cust2,Cust2_21_NT_System_CPU_Critical,Cust2_Node8,ITM_NT_System,2016-01-01 00:15:48,101,PARPFRC_OS:21192843,INC000000628410,WINDOWS_MEDIUM_DEFPRODUCTSILVER
Cust3,Cust3_10352_LZ_TDW_DISK_Critica,Cust3_Node22,ITM_Linux_Disk,2016-01-01 00:17:05,200,TOLPUKC_OS:25223370,INC000001412280,CGMOM_HIGH_DEFPRODUCT
Cust6,Cust6_11_53_Services_Warning,Cust6_Node700,ITM_K53_SERVICEMON,2016-01-01 00:22:36,22,TOLPUKC_OS:25223601,INC000002250120,CGIOWINTELIMOC_MEDIUM_DEFPRODUCT

Answer 1

替换以下内容： df=df[(parser.parse(df['FirstOccurrence']) < SevenDays)].drop(df.columns)

with： df = df.drop(df[(parser.parse(df['FirstOccurrence']) < SevenDays)].index, inplace=True)

尝试这个希望对您有帮助。