如果无或nan,则合并pandas中的两行

对于给定的数据帧 df

df = pd.DataFrame({
    'id': [1, 2, 2], 
    'name': ['Peter', 'Max', None], 
    'age': [50.0, np.nan, 60.0]
})

我想 groupby 如果只有 None 或 nan 在分组行的列中,因此生成的df应如下所示

        age     id  name
id              
1   0   50.0    1   Peter
2   1   60.0    2   Max

有没有比这个矿山更好的整洁解决方案:

def f(df):
    names = set(df['name']) - {None}
    if len(names) == 1:
        df['name'] = names.pop()
    else:
        print('Error: Names are not mergeable:', names)

    ages = {age for age in df['age'] if ~np.isnan(age)}
    if len(ages) == 1:
        df['age'] = ages.pop()
    else:
        print('Error: Ages are not mergeable:', ages)

    df = df.drop_duplicates()
    return df

df.groupby('id').apply(f)