Name: Spotify-YouTube Data
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

Spotify-YouTube Data

Project Video available on YouTube - https://youtu.be/xqtbBosGMl0

Spotify YouTube Dataset: Music Trends Across Platforms

This dataset shows how popular songs perform on both Spotify and YouTube. It includes useful details about each song, like its name, artist, how many times it was played on Spotify, how many views it got on YouTube, and several audio features like danceability, energy, loudness, and tempo.

Using this dataset, we answered multiple questions with Python in our Project.

Q.1) Top 10 Artists - with the Highest Views on YouTube?
Q.2) Top 10 Tracks - with the Highest Streams on Spotify?
Q.3) What are the most common Album Types on Spotify? How many tracks belong to each album type?
Q.4) How do the Average Views, Likes, and Comments are compared between different Album Types?
Q.5) Top 5 YouTube Channels - based on the Views?
Q.6) The Top Most Track - based on Views?
Q.7) Which Top 7 Tracks have the highest Like-to-View ratio on YouTube?
Q.8) Top Albums having the Tracks with Maximum Danceability ?
Q.9) What is the Correlation between Views, Likes, Comments, and Stream?

These are the main Features/Columns available in the dataset :

Track: The name of the song
Artist: The person or band who performed the song
Stream: Total number of times the song was streamed on Spotify
Youtube Views: Total number of views the song has on YouTube
Danceability: Score showing how suitable the track is for dancing (0 to 1)
Energy: Score representing how energetic or intense the song is (0 to 1)
Key: The musical key of the track (number from 0 to 11)
Loudness: The loudness of the song in decibels (dB)
Speechiness: Tells how much spoken words are in the track
Acousticness: Tells if the track is mostly acoustic or not
Instrumentalness: Predicts if the song has no vocals
Liveness: Indicates if the song was recorded in front of a live audience
Valence: Measures how happy or positive the song sounds
Tempo: The speed of the song in beats per minute (BPM)
Duration_ms: Length of the track in milliseconds
Year: The year the song was released

Tables

Spotify Youtube Dataset

@kaggle.rohitgrewal_spotify_youtube_data.spotify_youtube_dataset

13.73 MB
20,718 rows
28 columns

CREATE TABLE spotify_youtube_dataset (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "artist" VARCHAR,
  "url_spotify" VARCHAR,
  "track" VARCHAR,
  "album" VARCHAR,
  "album_type" VARCHAR,
  "uri" VARCHAR,
  "danceability" DOUBLE,
  "energy" DOUBLE,
  "key" DOUBLE,
  "loudness" DOUBLE,
  "speechiness" DOUBLE,
  "acousticness" DOUBLE,
  "instrumentalness" DOUBLE,
  "liveness" DOUBLE,
  "valence" DOUBLE,
  "tempo" DOUBLE,
  "duration_ms" DOUBLE,
  "url_youtube" VARCHAR,
  "title" VARCHAR,
  "channel" VARCHAR,
  "views" DOUBLE,
  "likes" DOUBLE,
  "comments" DOUBLE,
  "description" VARCHAR,
  "licensed" VARCHAR,
  "official_video" VARCHAR,
  "stream" DOUBLE
);