🎵 Assignment 1 — Spotify Database

📌 Project Description

This project imports and analyzes Spotify data using PostgreSQL and Python.
Five CSV files are imported into the database:

• spotify_artists
• spotify_albums
• spotify_tracks
• spotify_features
• spotify_data

The data is then analyzed using basic and analytical SQL queries.

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🛠 Tools Used

• PostgreSQL — Database management system for data storage.
• Python (psycopg2, pandas) — For importing CSV files into the database and executing SQL queries.
• SQL — For data analysis (LIMIT, WHERE + ORDER BY, GROUP BY, JOIN, aggregations).
• (Optional) Apache Superset — For visualization (not required in this project).

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🚀 How to Run

1️⃣ Install dependencies

# 📦 Install dependencies
pip install pandas psycopg2

# ▶️ Run the script
python dv.py

# ✅ This will:
- Import CSV data into PostgreSQL
- Execute 4 basic queries
- Execute 10 analytical queries

# 🔍 Queries Implemented

🟢 Basic Queries
- LIMIT → First 10 albums
- WHERE + ORDER BY → Top 20 tracks by popularity
- GROUP BY → Average track popularity by album
- JOIN → Number of tracks per album

🔵 Analytical Queries
- Top 10 artists by number of followers
- Top albums by total track popularity
- Most energetic tracks
- Top albums by danceability
- Distribution of track duration (0–10 minutes)
- Fast and popular tracks (tempo + popularity)
- Artists ranked by number of tracks
- Top explicit tracks by popularity
- Number of tracks by release year
- Average energy by release year

📂 Project Structure
📦 Assignment 1 - Spotify Database  
├── dv.py            # Main Python script (import + queries)  
├── queries.sql      # Collection of SQL queries  
├── Assignment1.pdf  # Assignment description  
└── *.csv            # Spotify dataset files  
✨ Done — ready to explore Spotify with SQL!