合并数据框而无需在python pandas中复制行 [英] Merge dataframes without duplicating rows in python pandas

问题描述

我想使用两个相似的列"A"合并两个数据框:

I'd like to combine two dataframes using their similar column 'A':

>>> df1
    A   B
0   I   1
1   I   2
2   II  3

>>> df2
    A   C
0   I   4
1   II  5
2   III 6

为此，我尝试使用:

合并= pd.merge(df1，df2，on ='A'，how ='outer')

merged = pd.merge(df1, df2, on='A', how='outer')

哪个返回:

>>> merged
    A   B   C
0   I   1.0 4
1   I   2.0 4
2   II  3.0 5
3   III NaN 6

但是，由于df2仅包含A =='I'的一个值，因此我不希望在合并的数据帧中重复该值.相反，我想要以下输出:

However, since df2 only contained one value for A == 'I', I do not want this value to be duplicated in the merged dataframe. Instead I would like the following output:

>>> merged
    A   B   C
0   I   1.0 4
1   I   2.0 NaN
2   II  3.0 5
3   III NaN 6

做到这一点的最佳方法是什么?我是python的新手，但仍然对所有的join/merge/concatenate/append操作感到困惑.

What is the best way to do this? I am new to python and still slightly confused with all the join/merge/concatenate/append operations.

推荐答案

让我们通过 cumcount

df1['g']=df1.groupby('A').cumcount()
df2['g']=df2.groupby('A').cumcount()
df1.merge(df2,how='outer').drop('g',1)
Out[62]: 
     A    B    C
0    I  1.0  4.0
1    I  2.0  NaN
2   II  3.0  5.0
3  III  NaN  6.0

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