Food Menu Analysis

Project Overview

This project analyzes a food menu dataset using Python, Pandas, NumPy, and OpenPyXL. It categorizes menu items, calculates nutritional summaries, performs category-wise analysis, and exports the cleaned dataset to an Excel file.

Technologies Used

• Python
• Pandas
• NumPy
• OpenPyXL

Features

• Creates a structured food menu dataset
• Displays statistical summary using describe()
• Filters items by category
• Calculates category-wise totals
• Computes overall totals for:
  • Price
  • Protein
  • Calories
• Generates category summary using groupby()
• Creates indicator columns using NumPy
• Exports cleaned data to Excel

Categories Included

• Fried Chicken
• Burgers
• Rice & Rolls
• Sides
• Beverages
• Desserts
• Snacks/Popcorn

Output

📟 Output

Dataset Overview

• Total Items: 50
• Categories: 7
• Dataset contains:
  • Item ID
  • Item Name
  • Category
  • Price (INR)
  • Calories (kcal)
  • Protein (g)
  • Fat (g)
  • Carbohydrates (g)
  • Sodium (mg)

Analysis Performed

✅ Statistical Summary using describe()

✅ Category-wise Filtering:

• Fried Chicken
• Burgers
• Rice & Rolls
• Sides
• Beverages
• Desserts
• Snacks/Popcorn

✅ Category-wise Nutritional Summaries

✅ Total Price Calculation

✅ Total Protein Calculation

✅ Total Calories Calculation

✅ Grouped Category Analysis using groupby()

✅ New Classification Columns Created:

• Is_Fried
• Is_Burger
• Is_rice
• Is_sides
• Is_beverage
• Is_deserts
• Is_snacks

Generated Output File

📁 food_data_cleaned.xlsx

The cleaned dataset is successfully exported to an Excel file with additional category indicator columns.

Author

Varshini Nagarajan B.Tech Information Technology Aspiring Java Developer