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An exploratory data analysis performed on data from McDonalds menu, focused mainly on fast food’s impact on people’s health and well-being.

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Tomaszlek/McDonaldsAnalysis

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McDonaldsAnalysis

Project Descripton

This project focuses on the nutritional analysis of McDonald's menu items. We explore various nutritional aspects, including calories, fats (including trans and saturated fats), vitamins, and mineral content such as iron, calcium, and sodium. The aim is to understand the nutritional profile of the available food options and investigate the impact of serving size and unhealthy fat content on the caloric value of these products. Additionally, this project includes a Power BI report to visualize findings dynamically and interactively.

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Installation

Download my project or clone the repository and then to run this project do the following steps:

  1. Run the .pbix report in Power BI, which you can then view and study various types of trends.
  2. Install Anaconda Navigator and run Jupyterlab. Open the .py file, and run the code.

Key findings

  • The average caloric content of products by category was examined.

  • The impact of serving size and total fat content on caloric value was analyzed and proven to be true.

  • A correlation between saturated fat content and caloric value was investigated and also proven to be true.

  • Data visualizations including bar charts, scatter plots, and pie charts were created to better understand the distribution of vitamins and microelements across the meal categories.

  • A Power BI report was developed to dynamically explore the nutritional content and trends within McDonald's menu items.

Data source

https://www.kaggle.com/datasets/mcdonalds/nutrition-facts

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An exploratory data analysis performed on data from McDonalds menu, focused mainly on fast food’s impact on people’s health and well-being.

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