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Nutritional analysis of McDonald’s menu using Python, focusing on calorie counts and health insights across various food categories.

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Satyam18g/McDonalds_Menu_Nutritional_Analysis--using_PYTHON

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McDonald's Menu Nutritional Analysis

Project Overview

McDonald's is a global fast-food chain known for its diverse menu offerings. This project aims to analyze the nutritional content of the menu items available at McDonald's outlets. The analysis will provide valuable insights into the calorie count and nutrition facts of various menu items.

Objectives

  • Extract meaningful information from the McDonald's menu nutritional dataset.
  • Perform exploratory data analysis to understand the nutritional distribution and trends.
  • Create visualizations to present the calorie count and nutrition facts of different menu items.
  • Identify healthy and less healthy menu options based on nutritional content.

Timeline

The project is expected to be completed within two weeks.

Deliverables

  1. Report (PDF):
    • Description of data analysis approach and methodology.
    • Exploratory data analysis findings and insights.
    • Visualizations depicting nutritional information.
    • Source code used for data preprocessing, analysis, and visualization.

Tasks/Activities List

Data Collection

  • Download the McDonald's menu nutritional dataset from this link.

Data Preprocessing

  • Load and inspect the dataset.
  • Handle missing values and perform data cleaning if necessary.

Exploratory Data Analysis (EDA)

  • Analyze the distribution of calorie counts across menu items.
  • Explore the nutritional content (e.g., fat, protein, carbohydrates) of different items.
  • Identify trends and patterns in the dataset.

Data Visualization

  • Create bar charts, histograms, and box plots to visualize calorie distribution and nutritional content.
  • Compare nutritional characteristics of different food categories (e.g., burgers, salads, desserts).

Nutrition-Based Insights

  • Identify menu items with the highest and lowest calorie counts.
  • Determine the average nutritional content of popular menu categories.

Documentation and Reporting

  • Summarize the findings and insights from the analysis.
  • Explain how the nutritional analysis could benefit McDonald's customers and the organization.

Recommendations

To improve the nutritional profile of their menu, McDonald's can consider the following recommendations:

  1. Increase Availability of Healthier Options

    • Expand salad and fresh vegetable offerings.
    • Incorporate whole grains.
  2. Modify Existing Menu Items

    • Reduce sodium content.
    • Lower saturated fats.
  3. Introduce Nutrient-Dense Ingredients

    • Offer more lean protein sources.
    • Incorporate sources of healthy fats.
  4. Reformulate Recipes

    • Cut down on added sugars.
    • Offer smaller portion sizes for high-calorie items.
  5. Enhance Transparency and Education

    • Ensure that nutritional information is easily accessible.
    • Launch health campaigns.
  6. Sustainable and Nutritious Ingredients

    • Source local and organic produce.
    • Expand plant-based alternatives.
  7. Customer Feedback and Continuous Improvement

    • Regularly update the menu based on customer feedback and nutritional research.
    • Test healthier menu items in select locations.

Success Metrics

  • The project should provide a comprehensive overview of the nutritional content of McDonald's menu items.
  • Visualizations should effectively convey calorie counts and nutritional information.
  • Insights should highlight healthy and less healthy food options.

How to Run the Project

  1. Clone the repository:
    git clone https://github.com/Satyam18g/mcdonalds-nutritional-analysis.git
    cd mcdonalds-nutritional-analysis

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