SCATTER-PLOT

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.

91% 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.

88% 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.

88% 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

310553047-HW1

This interactive scatter plot visualizes a Spotify dataset, allowing users to compare any two musical attributes by selecting them from dropdown menus for the x- and y-axes. The visualization shows how the chosen variables correlate across tracks, with each data point represented as a semi-transparent blue circle. The code uses D3 v5’s `select`, `csv`, `scaleLinear`, `scaleBand`, `axisLeft`, `axisBottom`, and `format` APIs to load data, render the SVG, and update the chart dynamically. Axis labels and gridlines are included, and the plot refreshes whenever the user changes the selected attributes.

Yyujun12689

areaChart-spotify

This area chart visualizes Spotify listening habits, showing total songs played per week. The visualization combines a filled area with a line overlay and circular data points, using steelblue for the area and line with tomato-colored points. Tooltips provide exact values on hover. Built with D3 v7, the chart employs `scaleLinear`, `axisBottom`, `axisLeft`, `area()`, and `line()` with `curveMonotoneX` smoothing. Data comes from a Gist-hosted CSV file displayed in an SVG rendered at 900×520 pixels.

Spotify Songs Scatterplot

This scatter plot visualizes the relationship between tempo and valence for a dataset of Spotify songs, where each circle represents a track’s musical attributes. The visualization uses D3’s `scaleLinear` and `axisLeft` to map the data, with circles colored by opacity to reveal density in overlapping regions. The chart is built via the reusable `viz` function, which handles axes, labels, and the plotting of points. The underlying data comes from the `@mjmacgregor/spotifysongs` package, and the example is intended as a template for adapting to other datasets.

Mmacgregorm01@gmail.com

Spotify Dataset Basic Scatter Plot with React & D3

This example shows a basic scatter plot of Spotify track data, mapping song duration in milliseconds along the x-axis against track popularity on the y-axis. Each circle represents one of 500 songs from a Kaggle dataset subset. Using React hooks to load the CSV file, the rendering delegates to a D3 function that applies `scaleLinear` and `extent` to compute the scales. The D3 `select` and `join` methods create the circle elements.

JJose Morales