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python函数中用于在其他两个条件中创建基于列的新条件的语法无效

syntax dataframe for-loop pandas python

JAG2024 · 技术社区 · 8 年前

我一直收到错误信息 SyntaxError: invalid syntax 我想知道(1)这是为什么,以及(2)如何修复我的函数,使它按我的要求工作。

d = {'Relationship': ['Male', 'Female','Spouse','Spouse','Male','Spouse','Male','Male','Male','Spouse','Female'], 'Sex': ['Male', 'Female','Female','Male','Male','Female','Male','Male','Male','Female','Female']}
df = pd.DataFrame(data=d)
df

Relationship    Sex
Male            Male
Female          Female
Spouse          Female
Spouse          Male
Male            Male
Spouse          Female
Male            Male
Male            Male
Male            Male
Spouse          Female
Female          Female

我想要的是 Spouse 填上所列的异性 df['Sex'] . 所以测向仪应该是这样的:

df

Relationship    Sex
Male            Male
Female          Female
Male            Female
Female          Male
Male            Male
Male            Female
Male            Male
Male            Male
Male            Male
Male            Female
Female          Female

def typex(column):
    if column['Relationship']!='Spouse' & column['Sex']! ='Female':
        return 'Male'
    elif column['Relationship']!='Spouse' & column['Sex']! ='Male':
        return 'Female'

df.loc[:,'Relationship'] = df.apply(typex, axis=1)

1 回复 | 直到 8 年前

JAG2024 8 年前

我建议使用 numpy.select

m1 = (df['Relationship']!='Spouse') & (df['Sex']!='Female')
m2 = (df['Relationship']!='Spouse') & (df['Sex']!='Male')

df['new'] = np.select([m1, m2], ['Male','Female'], default='not matched')

但是如果你想用你的代码改变 & 到 and because working with scalars

def typex(column):
    if (column['Relationship']=='Spouse') and (column['Sex']=='Female'):
        return 'Male'
    elif (column['Relationship']=='Spouse') and (column['Sex']='Male'):
        return 'Female'

df['new'] = df.apply(typex, axis=1)

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