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  • pandas df

    import numpy as np
    import pandas as pd
    
    s = pd.Series([1, 3, 5, np.nan, 6, 8])
    # print(s)
    dates = pd.date_range('20130101', periods=6)
    # print(dates)
    df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
    print(df)
    
    a = list(df.itertuples(index=False))
    print(a[0].A)
    # print(df.iloc[0])
    # for i in range(0,len(df)):
    #     print(df.iloc[i])
    # df.apply(lambda row: print(row), axis=1)
    # for index, row in df.iteritems():
    #     print(row) # 输出列名
    #     print(row[0]) # 输出列名
    #     print(row[1]) # 输出列名
        # print(getattr(row[1],'A')) # 输出列名
    """
    一,
    for  row in df.iteritems():
        print(row) # 输出列名
        ('D', 2013-01-01   -0.055828
    2013-01-02    0.084284
    2013-01-03    0.100456
    2013-01-04   -1.974011
    2013-01-05    0.389353
    2013-01-06   -0.481591
    Freq: D, Name: D, dtype: float64)
    print(row[0]) # 输出列名
    D
    print(row[1]) # 输出列名
    2013-01-01   -0.055828
    2013-01-02    0.084284
    2013-01-03    0.100456
    2013-01-04   -1.974011
    2013-01-05    0.389353
    2013-01-06   -0.481591
    
    for index, row in df.iteritems():
        print(index) 
        A
        print(row)  
    2013-01-01   -1.484969
    2013-01-02   -0.867084
    2013-01-03    0.056310
    2013-01-04   -0.455150
    2013-01-05    0.407460
    2013-01-06    2.217088
    
     print(row[0])
       -1.484968691334848
    
    二,
    def xxx(row):
        print(row)
    df.apply(lambda row: xxx(row), axis=1)
    
    Name: 2013-01-05 00:00:00, dtype: float64
    A    0.744318
    B   -0.408481
    C   -1.112620
    D   -0.777420
    Name: 2013-01-06 00:00:00, dtype: float64
    
    df.apply(lambda row: print(row['A']), axis=1)
    1.0063752461677924
    -0.13564652552723439
    -0.18798539100536096
    -0.5690084386213422
    -0.13362146127312274
    0.2806066279622273
    
    三,
    print(df.iloc[0])
    A   -0.472537
    B    0.332931
    C    0.843660
    D    1.418739
    for i in range(0,len(df)):
        print(df.iloc[i])
    A    0.746477
    B    1.179014
    C    1.064718
    D    0.566558
    Name: 2013-01-01 00:00:00, dtype: float64
    .....
    .....
    A    1.528804
    B   -1.115476
    C   -1.977193
    D    0.198156
    Name: 2013-01-06 00:00:00, dtype: float64
    
    
    四
    a = list(df.itertuples(index=False))
    print(a)
    [Pandas(A=-1.1849829013487616, B=1.2936306177332026, C=0.502434532988977, D=-1.3271967698449694), Pandas(A=-0.5338415234544399, B=0.0007, D=0.7390005803766758), Pandas(A=0.4991051381749911, B=0.20302599765021992, C=0.9679266312234202, D=-0.9711976649303432), Panda752633523728, C=-0.7871250572578905, D=-0.8497460123073107)]
    print(a[0])
    Pandas(A=-0.5325202189360843, B=-0.6197580479253518, C=0.5830443356731136, D=-0.6202575921374842)
    print(a[0].A)
    1.736514718339463
     """
    

      

     

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  • 原文地址:https://www.cnblogs.com/Crius/p/15405657.html
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