Hair Metal Conclusion

100%

Hair Metal Conclusion

✓ Published0🌍 Public

Last edited Dec 22, 2020

Created on Dec 22, 2020

This interactive scatterplot charts hair length and album count against Billboard hits for 1980s hair metal bands, with pink circles representing each band. Clicking the x-axis labels switches the independent variable between hair length and number of albums, triggering a smooth transition of the axis and circles via d3 transitions. The visualization uses d3.csv to load the data, d3.scaleLinear for both axes, d3.axisBottom for the x-axis, and d3-tip for hover tooltips that display the band’s age and the selected metric.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

Similar vizzes

Loading thumbnail…

Data

This example presents an interactive scatter plot of Spotify song attributes, allowing users to compare musical features such as Tempo, Energy, and Danceability across tracks from 2010 to 2020. A year slider filters the dataset, while dropdown menus let users select which attributes to plot on the x- and y-axes and which categorical field, either Top Genre or Artist, to use for color encoding. The visualization is built with React, using D3 v6 and v5 APIs including `scaleLinear` and `scaleOrdinal` for axes and color, alongside ReactDropdown for menu selection, and it renders SVG circles with native tooltips. Data is loaded via `d3.csv` from a GitHub gist containing the yearly music trend dataset.

Nnikki81140

65% match

Loading thumbnail…

Fork of TP_dataviz Projet

This bar chart displays the number of Deezer fans for each album by the band Metallica, retrieved from the Wasabi API. Users can click the Ascending and Descending buttons to re-sort the bars by fan count or release date. The visualization uses D3 v4 with SVG and animated transitions, featuring a tooltip that shows album titles and fan numbers on hover. Data loads asynchronously via `fetch` and is processed with `scaleBand` and `scaleLinear` axes.

BBaptisteJarry

64% match

Loading thumbnail…

Fork of TP_dataviz

This interactive visualization explores the music of Metallica through two synchronized views: a radial stacked bar chart showing the top genres by song count, and a zoomable timeline plotting album releases. The radial chart uses D3’s scaleBand, scaleRadial, and arc generators, with hover and click interactions revealing songs via custom tooltips. The timeline, built with d3.scaleTime and d3.zoom, filters data from a local CSV or API fetch. D3 version 4 and 5 are loaded via CDN, with data sourced from the Wasabi API.

Eemilienbf

64% match

Loading thumbnail…

D3 Interactive plot

This interactive line chart lets users explore musical trends across different artists by clicking buttons to switch datasets, which are loaded from CSV files hosted on GitHub. Built with D3.js v6, the visualization uses `d3.csv()` to fetch data and renders an SVG with a single line per playlist genre. The chart includes a color-coded legend for six genres—pop, rap, rock, latin, r&b, and edm—using an ordinal color scale. Clicking a button updates the chart by removing existing line elements and redrawing them with the new data, providing a dynamic way to compare genre patterns across artists.

Vvedant74

64% match

Loading thumbnail…

Line Chart - Lignes ok

This line chart displays the number of songs per music genre over time, with separate colored lines for Country, Pop, and Metal. The visualization uses d3.nest to group data by genre and d3.line to generate paths, with d3.scaleTime and d3.scaleLinear mapping dates and counts to SVG coordinates. It loads data from a JSON file via d3.json, which is sorted chronologically before rendering. Axes and labels are created using d3.axisBottom and d3.axisLeft, with a categorical color scale distinguishing genres.

EElodie31190

64% match

Loading thumbnail…

Untitled

This stacked bar chart displays eye color frequencies across four hair color categories. The visualization uses d3.csv to load the dataset, d3.stack() to compute stacked segments, and d3.scaleBand/d3.scaleLinear for axes. Each bar segment is colored via a d3.scaleOrdinal palette, with a legend added in the second implementation. The SVG rendering relies on d3.axisBottom, d3.axisLeft, and nested data joins to append rectangles per subgroup.

CCo10

64% match

Loading thumbnail…

data vis hw3

This interactive dashboard explores a Spotify dataset, displaying a genre treemap alongside a bar chart of track counts for the top 10 artists within a selected genre. The interface includes 64 small scatter plots comparing musical attributes for the chosen genre, with a highlighted overlay for a selected artist. Built with React and D3 v7, the visualization uses SVG rendering, d3.treemap for the genre hierarchy, d3.scaleBand for the bar chart, and d3.scaleLinear for the scatter plots. Users can click the treemap to change genres and bar chart bars to filter artists.

Yyeeet0421

64% match

Loading thumbnail…

D3 Starter Updating bar chart + Interaction

This example demonstrates an interactive bar chart that visualizes movie metrics—revenue, budget, or popularity—for titles released between 2000 and 2009. Users click buttons to switch metrics, triggering animated updates to bar lengths and axes through D3’s general update pattern with transition delays. Hovering over a bar displays a tooltip with details like profit, ratings, and genre. The code uses d3.scaleBand, d3.scaleLinear, d3.axisTop, d3.axisLeft, and d3.transition, with SVG rendering and data parsed from a CSV file.

Mmaxthamt

63% match