Song Popularity (0-100) where higher is betterĭanceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. The metadata for these variables is provided below: Variable Name Now, we have shorten our variables list from 23 to 13. # "playlist_genre" "playlist_subgenre" "danceability" # "track_popularity" "track_album_name" "playlist_name" Sp_data$playlist_subgenre <- as.factor(sp_data$playlist_subgenre) #Selecting the interesting variables Sp_data$playlist_genre <- as.factor(sp_data$playlist_genre) Sp_data$playlist_name <- as.factor(sp_data$playlist_name) Sp_data$track_album_name <- as.factor(sp_data$track_album_name) Sp_data$track_name <- as.factor(sp_data$track_name) Sp_data$track_artist <- as.factor(sp_data$track_artist) Sp_data$track_id <- as.factor(sp_data$track_id) #Converting the non-numerical variables into categorical variables Hence, We will prune our variables’ list and explore the dataset further with respect to these variables only. The variable “playlist_genre” contains 6 distinct categories and “playlist_subgenre” contains 24 distinct categories respectively, so it converted to factor type it would be easier to analyze. Firstly, There are these 7 variables which should better be cast in factor datatypes for better analysis results. Not all of the 23 variables are relevant for our analysis. # "track_album_release_date" "playlist_name" Names of the variables are below: colnames(sp_data) # "track_id" "track_name" The dataset contains 32833 observations and 23 variables. #Loading the datasetĭata Description #Display the dimensions of raw dataset This package was authored to make it easily accesible for anyone to get their own data or general metadata around songs from the Spotify’s API. This dataset comes originally from spotifyr package. Thanks, Spotify, for making mood swings more fun.The spotify_songs data file can be downloaded directly from the Spotify. The next time you feel like listening to your favorite tunes without hearing both " WAP" and " Driver's License" back-to-back (such good songs, but such different vibes), all you have to do is tap into the playlist with the mood you're feeling and you'll be vibing in no time. Then, hop into the playlist and start listening! If your mood changes or you want to listen to a different genre, simply tap the "X" next to the genre or mood to disable the filter and you'll be returned to the "Liked Songs" library. The app will populate moods and genres based on the songs you like, so your headers might be different than someone else's. Once you have over 30 songs, go into your library and tap into where it says "Liked Songs." Then, tap one of the filters at the top of the playlist header to display all the tracks that fall under that mood or genre (you can swipe sideways on the horizontal list to see more). First, you have to have at least 30 tracks in your "liked" collection. Here's exactly how to sort your Spotify "liked" collection by mood and genre. If the question of "Where has this been all my life?" also flashed through your head, then same. Spotify released a new feature that lets users sort their "liked" songs by mood and genre, meaning you can now filter out songs that don't match your vibe. The app has debuted tons of great features that give users a seamless music-enjoying experience, and the latest launch just made that experience even better. Not only is it home to some of the best music, podcasts, and playlists, but it's also so easy to use. Spotify is a music-lover's must-have app for a multitude of reasons.
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