Skip to content

We use a dataset of 18,403 music reviews scraped from Pitchfork in order to predict if an album will be a hit. Also, we study the Second Album Syndrome in order to determine if it exists, and how it manifests itself.

Notifications You must be signed in to change notification settings

Adam-Chellaoui/Data_analysis_Music_success_prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 

Repository files navigation

1. Context of the Project

Congratulations! You have just been hired as a data scientist at Piccardi Music, a promising new music label created by a mysterious Italian disc jockey "Signor Piccardi". The company hired you to carry out a variety of data-related tasks, which will be explained in further detail below.

For this homework you will use a dataset of 18,403 music reviews scraped from Pitchfork, including relevant metadata such as review author, review date, record release year, review score, and genre, along with the respective album's audio features pulled from Spotify's API.

We study two questions :

  • Will this album be a hit ?
  • Is the Second Album Syndrome real ?

2. Libraries used

  • pandas
  • numpy
  • seaborn
  • scipy
  • matplotlib
  • statsmodels
  • sklearn
  • scipy

About

We use a dataset of 18,403 music reviews scraped from Pitchfork in order to predict if an album will be a hit. Also, we study the Second Album Syndrome in order to determine if it exists, and how it manifests itself.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published