🎧 MGTA452: Final Project - Musical Analytics using Spotify Data 🎵

Welcome to our final project for MGTA452! This project dives deep into mustical characteristics from Spotify data to uncover potential correlations between top 50 songs and outside factors such as time, unemployment, inflation. 🌟

---

📝 Project Overview

We are interested in identifying trends in music over the past 10 years and extrapolate insights to promote innovation in industries that use music in their businesses to drive optimal decision making.

---

🎵 Data We’re Exploring

Historical and Financial Data

• We used financial data from https://fred.stlouisfed.org/docs/api/fred/. The data tracks levels on indicators like unemployment and inflation for each month in the past 10 years.

Spotify Data (from Kaggle and Spotify's API)

• We utilized musical data from https://www.kaggle.com/datasets/conorvaneden/best-songs-on-spotify-for-every-year-2000-2023. This data includes musical features for the top 50 songs on Spotify for each month in the past 10 years. From Spotify's API, we’ll analyze attributes of songs such as:
• Valence (emotional positivity) 😊
• Danceability 💃
• Liveness 🎤
• Key 🎼
• Tempo ⏱️
• Loudness 🔊
• Song Length ⏳
• Popularity 🌍
• Energy ⚡

---

📊 Methods & Visualizations

To uncover correlations and trends, we’ll experiment with:

• 🗺️ Line Graphs to show relationships between features.
• 📊 Histograms to compare attributes.
• 🚀 Tableau Charts to discover new insights.
• 🌍 Other Visualizations to explore relationships between our data.

---

🌟 Why This Matters

1. Enhanced User Engagement:
   • Streaming platforms can use our findings to personalize recommendations based on mood and external events. 🎶✨
2. Marketing & Advertising:
   • Marketers can tailor campaigns to align with audience mood and external factors. 📈🎯
3. Cultural Insights:
   • Understand how music choices intersect with outside influences, fostering innovation and connection. 🌍❤️

---

🚀 Our Goals

1. Explore correlations between music preferences and external factors using data analysis.
2. Identify trends in musical features and artists over time.
3. Support businesses and marketers in aligning strategies with audience trends and behaviors. 🌟
4. Generate actionable and cultural insights for creators to produce content that resonates with audiences.
   • Music Producers 🎧
   • Artists and Songwriters 🎤
   • Marketers and advertisers 💼
   • Cultural analysts 📖

---

🤝 Team Members

• Juan Hernandez Guizar 🌟
• Andrew Burda 🌟
• Melody Miu 🌟
• Jay Lee 🌟

---

Let’s uncover how 🎶 music connects with the 🌍 world around us!