[USER (data scientist)]: Great, now that the dataset is sorted by health score, please select the top 5 healthiest options, ensuring that at least one vegetarian option is included. Provide a list of top 5 healthiest fast food options, including at least one vegetarian option. 

[YOU (AI assistant)]: To select the top 5 healthiest options, including at least one vegetarian option, I need to know the criteria to identify vegetarian items in the dataset. Please provide a condition or a list of keywords that can be used to filter vegetarian items. 

[USER (data scientist)]:Vegetarian: Menu items containing the words "chicken", "beef", "pork", "bacon", "fish", "shrimp", "turkey", or "sausage" are assumed to be non-vegetarian. All other items are assumed to be vegetarian.  Generate and filter a DataFrame to identify and combine the top vegetarian and non-vegetarian options from the 'sorted_fastfood' dataset, resulting in a DataFrame and a pickle file containing these selections.

[YOU (AI assistant)]: Sure, I can help you with that. 
'''
import pandas as pd 
import pickle  
  
# Load the dataset  
fastfood = pd.read_csv("fastfood.csv")

# Define the keywords to filter non-vegetarian items  
non_veg_keywords = ['chicken', 'beef', 'pork', 'bacon', 'fish', 'shrimp', 'turkey', 'sausage']  
  
# Make the filtering case-insensitive  
sorted_fastfood['item_lower'] = sorted_fastfood['item'].str.lower()  
  
# Filter vegetarian items  
sorted_fastfood['is_vegetarian'] = ~sorted_fastfood['item_lower'].str.contains('|'.join(non_veg_keywords))  
  
# Find the top vegetarian option  
top_vegetarian = sorted_fastfood[sorted_fastfood['is_vegetarian']].head(1)  
  
# Find the top 4 healthiest non-vegetarian options  
top_non_vegetarian = sorted_fastfood[~sorted_fastfood['is_vegetarian']].head(4)  
  
# Combine the top vegetarian and non-vegetarian options  
top_healthy_options = pd.concat([top_vegetarian, top_non_vegetarian])  
  
# Drop the 'item_lower' and 'is_vegetarian' columns as they are not needed anymore  
top_healthy_options = top_healthy_options.drop(columns=['item_lower', 'is_vegetarian'])  

print(top_healthy_options) 

# save data
pickle.dump(top_healthy_options, open("./pred_result/top_healthy_options.pkl","wb"))
'''

[USER (data scientist)]: The `sorted_fast_food` is sorted by ascending order of `health score`, why you use `head(`?
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd   
import pickle 
  
# Load the dataset  
fastfood = pd.read_csv("fastfood.csv")  

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

print(top_healthy_options) 

# save data
pickle.dump(top_healthy_options, open("./pred_result/top_healthy_options.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: I should have used the tail() function to get the top healthiest options from the sorted dataset without modifying it. Here's the corrected code:

 