基于另一列从熊猫数据框中的列中的每个列表中删除元素

Question

I'd like to remove values in list from column B based on column A, wondering how.

Given:

df = pd.DataFrame({
    'A': ['a1', 'a2', 'a3', 'a4'],
    'B': [['a1', 'a2'], ['a1', 'a2', 'a3'], ['a1', 'a3'], []]
})

I want:

result = pd.DataFrame({
    'A': ['a1', 'a2', 'a3', 'a4'],
    'B': [['a1', 'a2'], ['a1', 'a2', 'a3'], ['a1', 'a3'], []],
    'Output': [['a2'], ['a1', 'a3'], ['a1'], []]
})

Answer 1

一种方法是通过DataFrame.apply对每一行应用过滤函数：

df['Output'] = df.apply(lambda x: [i for i in x.B if i != x.A], axis=1)

Answer 2

Another solution using iterrows() :

for i,value in df.iterrows():
    try:
        value['B'].remove(value['A'])
    except ValueError:
        pass
print(df)

Output:

    A         B
0  a1      [a2]
1  a2  [a1, a3]
2  a3      [a1]
3  a4        []