Spotify 2023 Streaming Analysis

Author: ShiriCodes
Live Report: View Online

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📌 Overview

This project presents a statistical analysis of Spotify’s top-streamed songs in 2023, exploring:

• Danceability, energy, valence, BPM, and musical mode
• Temporal trends and correlations
• Streaming success patterns

The project also includes personal insights and product recommendations derived from the analysis, highlighting trends and patterns in Spotify's top-streamed songs. All analysis was performed in R and organized using RMarkdown, producing an interactive HTML report.

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🛠 Tools & Methods

• R packages: ggplot2, dplyr, e1071, knitr
• Statistical methods:
  • Descriptive stats (mean, median, std, skewness)
  • t-tests (e.g., before vs after 2020, major vs minor mode)
  • Bootstrap confidence intervals
  • Correlation analysis & multiple testing corrections

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🌟 HTML Report Features

• Interactive Table of Contents – Navigate easily
• Responsive Design – Works on desktop & mobile
• Dark Mode Support – Follows system preference
• Expandable Code Blocks – Click SHOW to view underlying R code

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🔹 Repository Contents

File	Description
Spotify-2023-Analysis.R	R script with all statistical calculations & plots
Spotify-2023-Analysis.Rmd	Full RMarkdown report with narrative + code
index.html	Knitted interactive HTML report
spotify-2023-clean.RData	Cleaned dataset used for analysis
LICENSE	MIT license

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⚡ Explore the Project

1. View the Live Report: Interactive HTML
2. RMarkdown Workflow: Open Spotify-2023-Analysis.Rmd in RStudio
3. Reproduce in R: Run Spotify-2023-Analysis.R with the dataset in your working directory

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🔗 Portfolio

Explore more of my projects: ShiriCodes GitHub