Challenge

Example Spotify Songs Scatter Plot

This scatter plot maps 50 mock Spotify songs, with energy on the x-axis and popularity on the y-axis, while point color encodes valence using a three-shade blue palette. Both scales are constructed with `d3.scaleLinear` and `d3.extent`, and axes are rendered via the `@mjmacgregor/axis-labels` helper library for labeled ticks. The visualization is rendered as SVG circles with opacity, and the underlying data is generated randomly using `Math.random()` in the main script, mimicking song attributes without a real dataset.

Mmacgregorm01@gmail.com

87% match

SPOTIFY - Scatter Plot

This interactive scatter plot visualizes Spotify listening habits, mapping metrics like average listening time, total songs played, and mood score. Users switch X and Y axes via dropdown selectors, while circle color encodes Mood_Score through d3.interpolateTurbo, and size encodes New_Artists_Discovered via d3.scaleSqrt. Hovering reveals a tooltip and focus ring. The D3 v7 SVG chart includes gridlines, axes, transitions on points, and a custom CSV loader that flattens single-line data.

82% match

Spotify

This interactive scatterplot visualizes a dataset of Spotify tracks, plotting pairs of audio features such as acousticness, energy, and valence on x- and y-axes. Users select features from two dropdown menus, and the visualization updates the axes and data points accordingly. Rendered as an SVG using D3.js version 5, the chart uses `d3.scaleLinear` for both axes and draws semi-transparent circles to indicate track distributions. The code reads from a local CSV file and updates the chart dynamically via a polling function that checks selector changes.

Gginnyching

82% match

SPOTIFY - Scatter Plot

This scatter plot visualizes Spotify listening habits by plotting numeric columns from a CSV dataset, with axes automatically selected based on the most complete fields. The visualization loads data via `d3.csv` and uses reusable `d3.scaleLinear` scales, `d3.axisLeft` and `d3.axisBottom` for axes, and SVG circles for marks. It responsively redraws on window resize, applying custom margins and labels. The chart highlights relationships between behavioral metrics like newly discovered artists and mood scores, rendered with the D3 v6 library.

Spotify_D3ScatterPlot

This animated scatter plot visualizes Spotify listening habits, showing the relationship between total songs played and several rotating attributes including average listening time, new artists discovered, skipped songs, and mood score. Built with D3.js 6.7.0, it uses `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to map data from a CSV file loaded via `csv()`. The visualization cycles through four x-axis variables every two seconds using `setInterval`, redrawing circles with updated `cx` positions as the x-axis changes.

SCATTER-PLOT

This example visualizes listening time versus songs played from a Spotify habits dataset, plotting each week as a circle where size reflects artists discovered and color indicates mood score. It uses D3.js’s `scaleLinear`, `scaleSequential`, `interpolateTurbo`, `axisLeft`, and `axisBottom` to construct the scatter plot. The data loads from a GitHub Gist CSV file, and the reusable `scatterPlot` module renders SVG circles with hover tooltips.

music vis

This interactive scatterplot maps Spotify track attributes against one another, letting users select any two numeric columns from the dataset to compare on the x- and y-axes. The visualization updates dynamically through D3 v7's `scaleLinear`, `axisBottom`, and `axisLeft` APIs, rendering circles positioned by the chosen metrics. The code assigns CSS classes to each point based on a track genre field, although the dataset’s example rows lack a genre column, so the legend and color-coding rely on that optional data. The SVG plot includes labeled axes and a title reflecting the current variable pair.

Aa15923647