[USER (data scientist)]: Awesome! Now, I want to group the data by restaurant and food category, and then find the average nutritional values for each group. Please generate and display a DataFrame to visualize the average nutritional values (calories, total fat, sodium, sugar, protein) by restaurant and food category in the 'fastfood' dataset.
 My template of code snippet is:

---BEGIN CODE TEMPLATE--- 

import pandas as pd
import pickle

# Read the fastfood data 
fastfood = pd.read_csv("fastfood.csv")  

# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]
</code1>
# YOUR SOLUTION END: 

print(grouped_fastfood)
pickle.dump(grouped_fastfood,open("./pred_result/grouped_fastfood.pkl","wb"))

print(average_nutritional_values)
pickle.dump(average_nutritional_values,open("./pred_result/average_nutritional_values.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: No problem! You can use the groupby() function to group the data and then calculate the mean of the nutritional values. Here's the code for that:
