Spotify Top 10,000 Most Streamed

Spotify Top 10000 Songs

This example displays the raw contents of a Spotify top 10,000 songs dataset as a JSON-formatted text dump. It uses D3 v7’s `csvParse` to load and parse a remote CSV file from a GitHub gist, then presents the resulting array of objects directly in a `<pre>` element. The visualization demonstrates a minimal data-loading workflow, with state management to show a “LOADING” placeholder before the fetched data appears. No charts or graphical encodings are rendered; the focus is purely on data ingestion and display.

84% match

Final Project: Spotify Top 10000 Streamed Songs

This interactive D3.js visualization explores the Spotify Top 10,000 Streamed Songs dataset from Kaggle, showing relationships between artist success metrics. Three coordinated views display a scatterplot of artists' peak positions versus song counts with dropdown filters, a horizontal bar chart comparing the top 10 artists by streams, and a third scatterplot of individual songs for selected artists. The visualization uses d3.scaleLog, d3.flatGroup for data aggregation, tooltips on hover, and multiple dropdown menus to switch between peak position, peak streams, and total streams metrics.

81% match

Spotify Tracks Dataset

This interactive histogram explores the distribution of numerical audio features and metadata from a Spotify tracks dataset. Users select an attribute (e.g., popularity, danceability, tempo) for the x-axis, choose between raw counts or percentages for the y-axis, and adjust the number of histogram bins via dropdown menus built with a local `dropdownMenu.js` module. The visualization is rendered as an SVG using D3 v5 APIs including `scaleBand`, `scaleLinear`, `axisBottom`, and `axisLeft`, with bars that highlight on mouseover. Data is loaded from a CSV file and processed with D3's `csv` function.

Ccindy203cc

76% match

Most streamed songs of all time

This visualization displays the most streamed songs of all time, plotting each track’s name against its duration in minutes using a simple scatterplot or bar layout. It loads data from a local CSV file with D3.js v7, using the `csv` and `select` APIs to parse the dataset and render the visual elements directly into the HTML page. The chart highlights how song lengths vary across popular hits.

GGogineni44

Spotify Tracks Dataset

This interactive histogram explores a Spotify tracks dataset, showing the distribution of a selected audio feature (such as popularity or energy) across user-defined bins. A dropdown menu switches the mode between absolute counts and percentages, while another controls the number of histogram sections. Built with D3 v5, the visualization uses `scaleBand` and `scaleLinear` for axes, and animated bar transitions via `transition().duration()` and `delay()` to reveal each segment sequentially, set against a radial gradient background.

AAmanda-Tai

Spotify Peak Position Transforming Data 2

This visualization analyzes the Spotify Top 10,000 Songs dataset, showing a ranked list of artists by how many songs each has reached the #1 peak position. The code uses `d3.flatGroup` to group records by artist, then computes the minimum `peak_position` per artist and counts songs at that maximum rank. Results are sorted in descending order using `d3.descending` and displayed as JSON text via `d3.select`. The data loads from an external CSV file using `d3.csvParse`.

Top 10 Artists Bar Chart - Spotify Peak Position

This visualization displays the top 10 artists on Spotify based on a user-selected metric, such as peak streams or total streams, using a horizontal bar chart with a logarithmic x-axis. Each bar’s length represents the aggregated value for that artist, and hovering over a bar reveals a tooltip with details like song counts and peak positions. The chart is built with D3 v7, using `scaleLog` and `scaleBand` for scales, `axisBottom` and `axisLeft` for axes, and a dropdown menu to switch between metrics. Data is sourced from a CSV file of Spotify’s top 10,000 songs and processed with `flatGroup`.

Loading data "Top 50 Spotify music from 2010 to 2019" by Enze Liu

This example demonstrates loading a CSV dataset of the top 50 Spotify songs from 2010 to 2019, reporting its size in kilobytes, row count, and column count. The visualization uses D3 v5’s `d3.csv` method to fetch and parse the data, then updates a large text element with the statistics. The dataset, sourced from Kaggle via a GitHub Gist, contains 603 rows and 14 columns. An alternative asynchronous approach using `fetch` and `d3.csvParse` is also shown in commented code.

Rrioto9858