Pandas-数据结构-DataFrame（八）：对齐【运算时自动按照列和索引（行标签）】

雨点打透心脏的1/2处 2023-09-29 10:09 4阅读 0赞

import numpy as np
    import pandas as pd
    
    df1 = pd.DataFrame(np.random.randn(10, 4), columns=['A', 'B', 'C', 'D'])
    df2 = pd.DataFrame(np.random.randn(7, 3), columns=['A', 'B', 'C'])
    print("df1 = \n", df1)
    print("-" * 50)
    print("df2 = \n", df2)
    print("-" * 100)
    
    # DataFrame对象之间的数据自动按照列和索引（行标签）对齐
    print("df1 + df2 = \n", df1 + df2)

打印结果：

df1 = 
               A         B         C         D
    0  0.429778  1.582570  0.131346  0.134428
    1  0.560277 -0.717356  1.644508 -0.878158
    2 -0.515847 -1.771639  2.269994 -0.085366
    3 -0.811989  0.218562 -0.780336  0.027762
    4 -0.632858 -1.030526  0.691704 -1.946222
    5 -0.024812 -1.186269  1.056239  0.697720
    6  0.654899 -1.376284 -0.068436  0.263064
    7 -1.638721 -0.747343 -1.256148 -1.731662
    8  0.610803  0.045523  1.284305 -0.170015
    9  0.299883  1.725392  1.414165  0.629212
    --------------------------------------------------
    df2 = 
               A         B         C
    0  0.544155  0.241862  0.805521
    1 -0.729923 -0.000557  0.315256
    2 -0.924674  0.628935 -0.756562
    3  0.259076  0.404369 -1.591667
    4  2.002728  0.513643  0.840330
    5  1.285893  0.487775 -0.432646
    6 -0.297986 -0.520492  1.960273
    ----------------------------------------------------------------------------------------------------
    df1 + df2 = 
               A         B         C   D
    0  0.973932  1.824432  0.936867 NaN
    1 -0.169646 -0.717913  1.959764 NaN
    2 -1.440521 -1.142704  1.513432 NaN
    3 -0.552913  0.622931 -2.372004 NaN
    4  1.369870 -0.516883  1.532035 NaN
    5  1.261082 -0.698494  0.623594 NaN
    6  0.356913 -1.896777  1.891836 NaN
    7       NaN       NaN       NaN NaN
    8       NaN       NaN       NaN NaN
    9       NaN       NaN       NaN NaN
    
    Process finished with exit code 0