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Spotify Tracks Dataset

Hugging Face

Content This is a dataset of Spotify tracks over a range of 125 different genres. Each track has some audio features associated with it. The data is in CSV format which is tabular and can be loaded quickly. Usage The dataset can be used for: Building a Recommendation System based on some user input or preference Classification purposes based on audio features and available genres Any other application that you can think of. Feel free to discuss! Column… See the full description on the dataset page: https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset.

descriptionmaharshipandya--spotify-tracks-dataset.parquet view_list500 rows cloud_downloadmaharshipandya/spotify-tracks-dataset
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Data preview

500 rows · 20 columns · showing first 12
# track_id text artists text album_name text track_name text popularity integer duration_ms integer explicit boolean danceability float energy float key integer loudness float mode integer speechiness float acousticness float instrumentalness float liveness float valence float tempo float time_signature integer track_genre text
1 5SuOikwiRyPMVoIQDJUgSVGen HoshinoComedyComedy73230666False0.6760.4611-6.74600.1430.03221.01e-060.3580.71587.924acoustic
2 4qPNDBW1i3p13qLCt0Ki3ABen WoodwardGhost (Acoustic)Ghost - Acoustic55149610False0.420.1661-17.2310.07630.9245.56e-060.1010.26777.494acoustic
3 1iJBSr7s7jYXzM8EGcbK5bIngrid Michaelson;ZAYNTo Begin AgainTo Begin Again57210826False0.4380.3590-9.73410.05570.2100.1170.1276.334acoustic
4 6lfxq3CG4xtTiEg7opyCyxKina GrannisCrazy Rich Asians (Original Motion Picture Soundtrack)Can't Help Falling In Love71201933False0.2660.05960-18.5210.03630.9057.07e-050.1320.143181.73acoustic
5 5vjLSffimiIP26QG5WcN2KChord OverstreetHold OnHold On82198853False0.6180.4432-9.68110.05260.46900.08290.167119.94acoustic
6 01MVOl9KtVTNfFiBU9I7dcTyrone WellsDays I Will RememberDays I Will Remember58214240False0.6880.4816-8.80710.1050.28900.1890.66698.024acoustic
7 6Vc5wAMmXdKIAM7WUoEb7NA Great Big World;Christina AguileraIs There Anybody Out There?Say Something74229400False0.4070.1472-8.82210.03550.8572.89e-060.09130.0765141.33acoustic
8 1EzrEOXmMH3G43AXT1y7pAJason MrazWe Sing. We Dance. We Steal Things.I'm Yours80242946False0.7030.44411-9.33110.04170.55900.09730.7121514acoustic
9 0IktbUcnAGrvD03AWnz3Q8Jason Mraz;Colbie CaillatWe Sing. We Dance. We Steal Things.Lucky74189613False0.6250.4140-8.710.03690.29400.1510.669130.14acoustic
10 7k9GuJYLp2AzqokyEdwEw2Ross CoppermanHungerHunger56205594False0.4420.6321-6.7710.02950.4260.004190.07350.19678.94acoustic
11 4mzP5mHkRvGxdhdGdAH7EJZack TabudloEpisodeGive Me Your Forever74244800False0.6270.3638-8.12710.02910.27900.09280.30199.914acoustic
12 5ivF4eQBqJiVL5IAE9jRylJason MrazLove Is a Four Letter WordI Won't Give Up69240165False0.4830.3034-10.0610.04290.69400.1150.139133.43acoustic

Auto-generated charts

Spotify Tracks Dataset: 500 rows by 20 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Rows500
Columns20
Numeric cols13
Categorical cols2

Charts

Total popularity by explicit

Top explicit values ranked by summed popularity.

popularity vs duration_ms

popularity vs duration_ms, coloured by explicit.

Distribution of popularity

Histogram of popularity values.

Correlation of numeric columns

Pearson correlation between numeric columns.

popularity by explicit

Spread of popularity across explicit groups.

Interesting queries to try

Columns

  • Unnamed: 0 numeric
  • track_id text
  • artists text
  • album_name text
  • track_name text
  • popularity numeric
  • duration_ms numeric
  • explicit bool
  • danceability numeric
  • energy numeric
  • key numeric
  • loudness numeric
  • mode numeric
  • speechiness numeric
  • acousticness numeric
  • instrumentalness numeric
  • liveness numeric
  • valence numeric
  • tempo numeric
  • time_signature datetime
  • track_genre categorical

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