🎤 Lyrics/associated NLP data for Billboard's Top 100, 1950-2015.

JSON files for every Billboard Hot 100 chart in history, updated daily.

🎧 Get json type billboard hot 100 chart

Python application that scrapes Billboard's Hot 100 Chart using BeautifulSoup

Racing bar chart animation of artists with the most Billboard Hot 100 Entries using the pandas and data visualization libraries in Python 3.

Simple API to access Billboard Charts

Hit Song Prediction Model - Master Thesis in Music and Acoustic Engineering - Politecnico di Milano

Machine Learning to Classify Songs as a Hit or a Flop according to the Billboard Hot 100

A musical time machine built with BeautifulSoup to create a playlist of top 100 songs on billboard in Spotify from a particular week in the past.

Visualizing music artist performance across genres (2010-2019) using Python and Tableau to uncover correlations and trends

Provide an overview of Billboard Chart for any week

Fetching data about billboard's charts and uploading it to kaggle

Taking an analytics approach, I aim to use information about a song's properties to predict its popularity.

Descubra como estava a Billboard Hot 100 no dia do seu aniversário!

This repository contains a Python script that creates a private Spotify playlist with the Top 100 songs from the Billboard website on a specified date. It uses the spotipy library to authenticate the user with Spotify, search for the songs on Spotify, and add the songs to the playlist.

Changes over time: Hiphop--solos and collaborations--on the Hot 100 Billboard Charts: https://maloriejhughes.github.io/HipHop-BillboardCharts-and-Collaborations/

Music Through The Ages: What Makes a Hit? - In this final data science project we attempt to find out the common characteristics between charting songs using Spotify and Billboard data.

Download billboard HOT 100 songs

Collect information on songs, analyze and build a recommender system with the help of Spotify API.

The Artist Success Trajectory Predictor is a data science project that forecasts artist success using historical chart performance and Spotify popularity. It generates visual insights to show trends and predict future success in the music industry. Key visualizations highlight the impact of different weighting strategies on prediction accuracy.

This Python script allows you to travel back in time and create a Spotify playlist of the Billboard Hot 100 songs for any specified date.

Based on Billboard, This will show K-Pop 100 Ranking.

This repository analyzes Taylor Swift’s songs and their performance on the Billboard Hot 100, using data from Billboard and Spotify. It includes data cleaning, feature engineering, and exploratory analysis to uncover insights into factors driving chart success.

Frequency analysis of historical Billboard Hot 100 lists based on an artist's supporting vs main artist numbers.

An UI version for billboard.py

Gets most used word in lyrics for Billboard's Top 100 using the Genius API. Plots to bar graph.

Simple webapp showing top 100 songs

Machine learning/deep learning approach to predict success of songs based on Spotify audio features and Billboard data

Dashboard to show data on music artists who appeared on BillBoard Top 100 Chart from 1999-2019, and created a machine learning algorithm to predict if the song will be a hit based on given attributes.

Billboard's Historical Ranking