示例数据：

>>>name   food  beverage  age
0  Ruth   Burger Cola      23
1 Dina    Pasta  water     19
2 Joel    Tuna   water     28
3 Daniel  null   soda      30
4 Tomas   null   cola     10

使用一般方法实现，但不断出错(ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all())，具体逻辑如下：

if df[(df['food'].isna())]:
  df['beverage']=' '
  df['age']=' '

1、使用mask修改

df[['beverage','age']] = df[['beverage','age']].mask(df['food'].isna(),'')

输出结果：

     name    food beverage age
0    Ruth  Burger     Cola  23
1    Dina   Pasta    water  19
2    Joel    Tuna    water  28
3  Daniel     NaN             
4   Tomas     NaN      

2、使用loc修改

可以使用布尔索引来根据条件赋值:

df.loc[df['food'].isna(), ['age', 'beverage']] = ''

输出结果：

     name    food beverage age
0    Ruth  Burger     Cola  23
1    Dina   Pasta    water  19
2    Joel    Tuna    water  28
3  Daniel     NaN             
4   Tomas     NaN             

3、使用np.where修改

cols = ['beverage','age']
arr = np.where(df['food'].isna()[:,None],'',df[cols])
#for NaN : arr = np.where(df['food'].isna()[:,None],np.nan,df[cols])
df[cols] = arr

输出结果：

     name    food beverage age
0    Ruth  Burger     Cola  23
1    Dina   Pasta    water  19
2    Joel    Tuna    water  28
3  Daniel     NaN             
4   Tomas     NaN