change specific values in dataframe if one cell in a row is null

Try with mask

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

df
Out[86]: 
     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             

You can use boolean indexing to assign the values based on the condition:

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

---

     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             

You can use np.where:

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

---

     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