Music Data Analysis

Uma associação de como o rock foi se modificando desde a década de 50 até os dias de hoje e como isso pode ser observado na prática nas músicas presentes na minha playlist de rock do Spotify, chamada "For Those About To Rock"

An exploratory data analysis and data visualization project using data from Spotify Web API

analysis of complete spotify streaming dataset (endsong_*.json)

An extended analysis of the evolution of American popular music from 1960 to 2017 using data from the Billboard Year-End Hot 100 charts, lyrics scraped from the web, and Spotify audio features.

Exploring Audio Features and building a Machine Learning Approach

An exploratory data analysis (EDA) and data visualization project using data from Spotify using Python.

Data Engineering project using Databricks PySpark & Spark SQL for analysing data from Spotify API and present in form of PowerBI report

Fetching & Statistical Analysis of Spotify Data

The Spotify Data Analysis Project showcases data's role in diverse fields, using Python and libraries like Pandas,Numpy,Seaborn and Matplotlib, within the Jupyter Notebook environment. It explores music-related datasets, highlighting data's influence on decisions, research, and prediction, while honing technical skills and industry insights.

Analyse Spotify playlists, albums and artists.

Waveform seekbar generated from Spotify audio analysis API.

A portable Python script to export your Spotify playlists' information to JSON files for learning, backups or analysis.

A Spotify Wrapped-style analysis of your iMessage history. Beautiful iOS-styled reports generated locally.

A in depth data analysis and visualization on spotify streaming history.

A data analysis project involving the saddest and happiest songs available at Spotify

Data analysis on my monthly playlists

Pulling data using both the Genius API and the Spotify API I've been able to analyze Jorge Drexler's music and get some insights and visualizations on his creative process and his songs in general; both from the lyrics side and the musical theory side. Wordcount, lexical and lyrical density, sentiment analysis and analysis of musical components like tempo, time signature and key are all taken into account. Also, in the end, gloom_index is used combining both lyrics and music.

project which uses Hooktheory and Spotify APIs to perform analysis of chord progressions of popular songs.

Analyzing Spotify Data with Pyspark and ETL Procedures

analysing my friend's music taste against each other using data collected from spotify.

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"Analyze your Spotify listening habits using Pandas, NumPy, Matplotlib, and Seaborn"

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This is an analysis of the data on Spotify tracks from 1921-2020 with Jupyter Notebook and Python Data Science tools.

Digging into Spotify's valence score

Classification & Time Series Analysis of Spotify Data using Grid Searched Random Forest & LSTM.

🎵 Transform Spotify playlists into a DJ-ready Rekordbox library. Automatic KEY detection (Camelot), BPM analysis, quality filtering, and smart organization. Perfect for harmonic mixing!

A machine learning exercise using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.

Personal Spotify Music Trend Analysis