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Spotify Songs (Top 100 by Year)
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 descriptionSpotify 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 track name, artist, release year, and musical features like danceability, energy, and tempo.
📑 Attribute Descriptions (VAD Framework)
| Attribute | Type | Description |
|---|---|---|
track_name |
Categorical | Title of the song |
artist_name |
Categorical | Performing artist |
year |
Ordered (Time) | Release year (2010–2019) |
genre |
Categorical | Main music genre of the song |
duration_ms |
Quantitative | Song duration in milliseconds |
danceability |
Quantitative | Score (0–1) measuring suitability for dancing |
energy |
Quantitative | Score (0–1) measuring intensity and activity |
valence |
Quantitative | Score (0–1) representing musical positivity (happy vs. sad mood) |
tempo |
Quantitative | Estimated tempo in beats per minute (BPM) |
🌟 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) vary by year/genre
- Correlations between tempo, mood, and popularity