数据帧的两列和三列的唯一列表的并集

联接列并删除重复项的方式 set s

df['Col1+Col2'] = (df['Col1 Extract'] + df['Col2 Extract']).apply(lambda x: list(set(x)))
df['Col1+Col2+Col3'] = (df['Col1 Extract'] + df['Col2 Extract'] + df['Col3 Extract']).apply(lambda x: list(set(x)))
print (df)
          Col1 Extract     Col2 Extract    Col3 Extract  \
0       [unclassified]   [sink, fridge]  [unclassified]   
1  [fridge, microwave]  [fridge, stove]          [sink]   
2       [unclassified]   [unclassified]  [unclassified]   

                      Col1+Col2                    Col1+Col2+Col3  
0  [fridge, unclassified, sink]      [fridge, unclassified, sink]  
1    [stove, fridge, microwave]  [stove, fridge, microwave, sink]  
2                [unclassified]                    [unclassified] 

如果订购是重要用途 dict.fromkeys 戏法

df['Col1+Col2'] = (df['Col1 Extract'] + df['Col2 Extract']).apply(lambda x: list(dict.fromkeys(x)))
df['Col1+Col2+Col3'] = (df['Col1 Extract'] + df['Col2 Extract'] + df['Col3 Extract']).apply(lambda x: list(dict.fromkeys(x)))
print (df)
          Col1 Extract     Col2 Extract    Col3 Extract  \
0       [unclassified]   [sink, fridge]  [unclassified]   
1  [fridge, microwave]  [fridge, stove]          [sink]   
2       [unclassified]   [unclassified]  [unclassified]   

                      Col1+Col2                    Col1+Col2+Col3  
0  [unclassified, sink, fridge]      [unclassified, sink, fridge]  
1    [fridge, microwave, stove]  [fridge, microwave, stove, sink]  
2                [unclassified]                    [unclassified]