Spotify Music Feature Analysis Project

My project explores the Spotify Track Dataset from Kaggle to understand how different audio features interact with each other to create a genre fingerprint and contribute to the popularity of a song.

Project Break down

• Project 1: initial overview of data and research question

• Project 2: EDA on dataset and investigating which features are important for the model

• Project 3: Model analysis

• Project 4: Monte Carlo Simulation: Experimenting with different proportions of classes within dataset

Environment

OS: macOS 14.6
Python: 3.11.11

Packages:
pandas==2.2.3
numpy==2.1.3
matplotlib==3.10.1
seaborn==0.13.2
scikit-learn==1.6.1
imbalanced-learn==0.13.0
imblearn==0.0
statsmodels==0.14.4

Steps to reproduce each project:

1. ensure proper packages are installed using virtual environemnt with the listed packages
2. run the qmd file

About Me

• student
  • Computer Science + Stats minor
  • 4th year
  • UCSC