Spotify_PieChart

PIE-CHART

A donut chart displays the distribution of Spotify listening weeks into three buckets based on skipped songs: low (≤5), medium (6–10), and high (≥11). The visualization uses d3.pie, d3.arc, and d3.scaleOrdinal to render slices with percentage labels, leader lines, and a legend. Data is loaded from a Gist-hosted CSV file using d3.csv, and the chart is rendered as an SVG. The component is reusable, with setters for width, height, and radii.

92% match

piechart

This visualization displays the genre distribution of Spotify’s Top 50 songs as a pie chart, with percentage labels on each slice and a color-coded legend. It loads CSV data via `d3.csv`, aggregates counts with `d3.rollup`, and renders SVG paths using `d3.pie` and `d3.arc`. The chart applies a Tableau10 color scheme from `d3.scaleOrdinal` and positions text labels at arc centroids.

Sshivadeclare2@gmail.com

84% match

Assignment2-1

A pie chart visualizes the distribution of Spotify's Top 50 songs from 2019 by genre. It fetches CSV data from a GitHub gist, uses `d3.rollup` to count songs per genre, and computes percentages for labels on each slice. The chart renders as SVG, using `d3.pie` and `d3.arc` for the sectors, a categorical color scheme, and includes a legend positioned to the right. A bold title and percentage labels are added directly on the arcs.

Sshivadeclare2@gmail.com

81% match

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.

80% match

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.

Pie Chart Artistes

A donut chart breaks down music genres by count, with each slice labeled and colored to show the proportion of artists per category. The visualization uses D3’s `pie` and `arc` generators to compute slice geometry and paths, while `scaleOrdinal` maps genre names to a custom color palette from `d3-scale-chromatic`. Hovering over a slice reveals a tooltip with the exact percentage, calculated using `sum` over the CSV data. The code reads from `data.csv` and renders the chart as SVG elements with mouseover and mouseout event handlers.

AAnissa Belkelfa

Fork of Pie Chart Artistes

A donut chart displays the distribution of music genres by percentage, with each slice labeled and colored distinctly. The visualization uses D3.js to load CSV data and render an SVG, employing `d3.pie` and `d3.arc` for the donut geometry, `d3.scaleOrdinal` with a custom color range, and d3-scale-chromatic for color handling. Hovering over a slice reveals a tooltip showing the precise percentage, calculated with `d3.sum`, while mouse events and CSS transitions manage tooltip visibility.

AAnissa Belkelfa

Spotify_LineChart

This line chart visualizes weekly song counts from a Spotify listening history dataset, using a reusable D3 line chart module. The chart plots total songs played across weeks, with steelblue lines and tomato-colored points marking each data value. It uses d3.scalePoint and d3.scaleLinear to map the axes, d3.axisBottom and d3.axisLeft for ticks, and d3.line to generate the path. Tooltips appear on hover via SVG `<title>` elements, while the data loads from a CSV file fetched with d3.csv.