Python 有没有办法跳过熊猫的行列,直到csv说;航班表;?

Python 有没有办法跳过熊猫的行列,直到csv说;航班表;?,python,pandas,csv,Python,Pandas,Csv,这是我的CSV,虽然我希望它跳过字符串“Flight Table”之前的多行,但这是否可能?我使用了skiprows,但我需要更多的变通能力 手动计算行数并使用skiprows 如果行不断变化-请使用readline,直到找到字符串并以编程方式计算行数,然后将行数输入skiprows skiprows:类似列表、int或可调用、可选 文件开头要跳过的行号(0索引)或要跳过的行数(int)。我会: 打开CSV文件 将其作为迭代器循环 如果一行以您的魔术字符串开头,请将剩余的行传递给pandas.r

这是我的CSV,虽然我希望它跳过字符串“Flight Table”之前的多行,但这是否可能?我使用了skiprows,但我需要更多的变通能力 手动计算行数并使用skiprows

如果行不断变化-请使用readline,直到找到字符串并以编程方式计算行数,然后将行数输入skiprows

skiprows:类似列表、int或可调用、可选 文件开头要跳过的行号(0索引)或要跳过的行数(int)。

我会:

  • 打开CSV文件
  • 将其作为迭代器循环
  • 如果一行以您的魔术字符串开头,请将剩余的行传递给pandas.read\u csv

  • 预期产量是多少?
    N11682,aircraft,C172,,Cessna,C172SP,airplane,airplane_single_engine_land,fixed_tricycle,Piston,false,false,false,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
    ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
    Flights Table,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
    Date,AircraftID,From,To,Route,TimeOut,TimeOff,TimeOn,TimeIn,OnDuty,OffDuty,TotalTime,PIC,SIC,Night,Solo,CrossCountry,Distance,DayTakeoffs,DayLandingsFullStop,NightTakeoffs,NightLandingsFullStop,AllLandings,ActualInstrument,SimulatedInstrument,HobbsStart,HobbsEnd,TachStart,TachEnd,Holds,Approach1,Approach2,Approach3,Approach4,Approach5,Approach6,DualGiven,DualReceived,SimulatedFlight,GroundTraining,InstructorName,InstructorComments,Person1,Person2,Person3,Person4,Person5,Person6,FlightReview,Checkride,IPC,PilotComments
    2020-11-01,N172TG,KSFM,KSFM,,,,,,,,0.8,0.8,0.0,0.0,0.0,0.0,0.00,0,0,0,0,0,0.0,0.0,0.00,0.00,0.00,0.00,0,,,,,,,0.8,0.0,0.0,0.0,,,,,,,,,false,false,false
    2020-11-01,N916BA,KSFM,KSFM,,,,,,,,0.5,0.5,0.0,0.0,0.0,0.0,0.00,0,0,0,0,0,0.0,0.0,0.00,0.00,0.00,0.00,0,,,,,,,0.5,0.0,0.0,0.0,,,,,,,,,false,false,false31,N172TG,KSFM,KSFM,KASH,,,,,,,1.7,1.7,0.0,0.0,0.0,1.7,0.00,0,0,0,0,0,0.0,0.0,0.00,0.00,0.00,0.00,0,,,,,,,1.7,0.0,0.0,0.0,,,,,,,,,false,false,false
    
    with open(mycsv, 'r') as fobj:
        for line in fobj:
            if line.startswith('Flights Table'):
                df = pandas.read_csv(fobj)