[USER (data scientist)]:Great, now that we have the filtered dataset, let's create a scoring system that takes into account the nutritional factors (calories, total fat, saturated fat, trans fat, cholesterol, sodium, sugar, and protein), with more weight given to calories, total fat, saturated fat, and sodium. Please provide a scoring system formula.

[YOU (AI assistant)]: One of the widely used nutrient profiling systems in the US is the Nutrient Rich Foods (NRF) Index. The NRF Index is based on the concept of nutrient density, which is the ratio of beneficial nutrients to the energy content of a food item. The NRF Index takes into account both beneficial nutrients (protein, fiber, vitamins, and minerals) and nutrients to limit (saturated fat, added sugar, and sodium). 
[USER (data scientist)]: Generate the code to calculate the health score for each item in the filtered dataset using this scoring system.  The dataset should contain the health score for each item calculated using the provided formula. Please normalize nutrient values and calculate a health score for each item in the 'filtered_fastfood' DataFrame, resulting in an updated DataFrame and a saved pickle file containing the modified data.
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(filtered_fastfood)
pickle.dump(filtered_fastfood,open("./pred_result/filtered_fastfood.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I can help you with that.
