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Spotify Songs (Top 100 by Year)

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Spotify Songs (Top 100 by Year)

0 stars3🌍 Public
VVinayak Revankar
Last edited Sep 4, 2025
Created on Sep 1, 2025
Forked from Loading Data

The visualization displays the Top 100 Spotify songs from 2010–2019, parsed from a CSV file using `d3.csvParse`. It initially shows a loading state, then renders the raw data as JSON in a `<pre>` element after fetching, showcasing the song attributes like energy, danceability, and popularity. The code uses `d3.select` and `selectAll` to manage the DOM, with a state-based rendering loop for asynchronous loading.

AI-generated description

Spotify Top Songs (2010–2019)

This dataset contains information about the Top 100 Spotify songs for each year between 2010 and 2019.
It includes metadata such as song title, artist, genre, and a variety of musical/audio features such as tempo, danceability, and popularity.


Attribute Descriptions (VAD Framework)

Attribute Type Description
index Quantitative Row index (unique ID for each record)
title Categorical Title of the song
artist Categorical Performing artist
top genre Categorical Main genre of the song
year Ordered (Time) Release year (2010–2019)
bpm Quantitative Beats per minute (tempo)
nrgy Quantitative Energy score (0–100), higher = more energetic
dnce Quantitative Danceability score (0–100), higher = easier to dance to
dB Quantitative Loudness in decibels (negative values, closer to 0 = louder)
live Quantitative Liveness score (0–100), higher = more audience presence
val Quantitative Valence score (0–100), higher = more positive/happy mood
dur Quantitative Duration in seconds
acous Quantitative Acousticness score (0–100), higher = more acoustic
spch Quantitative Speechiness score (0–100), higher = more spoken words in track
pop Quantitative Popularity score (0–100), higher = more popular

Why This Dataset?

This dataset is interesting because it allows us to explore:

  • Trends in popular music across the decade
  • How audio features (energy, danceability, valence, acousticness) vary by year and genre
  • Correlations between tempo, mood, and popularity
  • Which artists or genres dominated specific years