The Principal Component Analysis is a Python program that performs dimensionality reduction on Starbucks nutrition data using PCA and visualizes the results in a 3D scatter plot. The code calculates the principal components, determines colors based on the axes values. It provides a concise representation of the nutritional characteristics of Starbucks products.
To use the program, first, download the scripts and the database and put them in the same folder. Then, execute the python script.
python principal_component_analysis.py
This work uses the Starbucks Nutrition Facts dataset, made available by Utkarsh Singh for the Advancement of Science and Art on Kaggle. Special thanks to Utkarsh Singh and the dataset creators for making this data available.
This program was created by Jonatas Fernandes Andrade and Gabriel Medina da Assunção.