【问题标题】:how to find the complement of two dataframes如何找到两个数据帧的补码
【发布时间】:2016-12-18 19:00:24
【问题描述】:

给定两个大数据帧,是否有任何简洁高效的代码(避免直接使用任何for loop)让我获得这两个数据帧的补码?

对我来说最直接的方法是计算union-intersection,如下面的简单示例所示,但我不知道如何用pandasnp 的优雅语言来实现它

df1= pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],
                     'key2': ['K0', 'K1', 'K0', 'K1'],
                   'A': ['A0', 'A1', 'A2', 'A3'],
                    'B': ['B0', 'B1', 'B2', 'B3']})     
df2= pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],
                      'key2': ['K0', 'K0', 'K0', 'K0'],
                      'C': ['C0', 'C1', 'C2', 'C3'],
                      'D': ['D0', 'D1', 'D2', 'D3']})        
intersection= pd.merge(df1, df2, how='inner',on=['key1', 'key2'])
union=pd.merge(df1, df2, how='outer',on=['key1', 'key2'])       


complement=union-intersection

感谢任何cmets和答案

【问题讨论】:

标签: python pandas join merge


【解决方案1】:

从这里开始:

df1= pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],
                     'key2': ['K0', 'K1', 'K0', 'K1'],
                   'A': ['A0', 'A1', 'A2', 'A3'],
                    'B': ['B0', 'B1', 'B2', 'B3']})     
df2= pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],
                      'key2': ['K0', 'K0', 'K0', 'K0'],
                      'C': ['C0', 'C1', 'C2', 'C3'],
                      'D': ['D0', 'D1', 'D2', 'D3']})        
intersection  = pd.merge(df1, df2, how='inner',on=['key1', 'key2'])
union         = pd.merge(df1, df2, how='outer',on=['key1', 'key2'])       

打印联合

     A    B key1 key2    C    D
0   A0   B0   K0   K0   C0   D0
1   A1   B1   K0   K1  NaN  NaN
2   A2   B2   K1   K0   C1   D1
3   A2   B2   K1   K0   C2   D2
4   A3   B3   K2   K1  NaN  NaN
5  NaN  NaN   K2   K0   C3   D3

打印交点

    A   B key1 key2   C   D
0  A0  B0   K0   K0  C0  D0
1  A2  B2   K1   K0  C1  D1
2  A2  B2   K1   K0  C2  D2

联合路口试试这个:

union[union.isnull().any(axis=1)]

     A    B key1 key2    C    D
1   A1   B1   K0   K1  NaN  NaN
4   A3   B3   K2   K1  NaN  NaN
5  NaN  NaN   K2   K0   C3   D3

【讨论】:

  • 非常感谢,但我没有足够的声誉来支持你
  • 我给你点赞了!
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