vgsales.csv with brushing

D3 Scatter Plot: vgsales.csv

This scatter plot visualizes video game sales data from the vgsales.csv dataset, plotting each game’s release year on the x-axis against its global sales on the y-axis. Rendered as an SVG using D3 v6, the code applies `d3.scaleLinear` for both axes and draws semi-transparent circles with a radius of 4. The data is loaded via `d3.csv`, and axes are generated with `d3.axisLeft` and `d3.axisBottom`, with tick formatting modified to prevent commas in the year labels.

82% match

Game sale with Brushing

This scatter plot visualizes video game sales data from Kaggle, plotting global sales against year of release. Users can brush a rectangular region over the plot to select and highlight specific data points in pink, while unselected points dim to gray. Upon brush completion, a table appears listing the game name, year, and global sales for all highlighted entries. The visualization leverages d3.brush for interaction, d3.csv for data loading, and standard d3.scaleLinear, d3.axisBottom, and d3.axisLeft for the axes and scales.

RRochelle

81% match

Game sale >5 Million with Brushing

A D3 scatter plot displays video game sales over time, plotting each game's release year against its global sales figures. Users drag a rectangular brush across the chart to highlight selected points in pink while dimming others, and a hidden table populates with the game name, year, and sales data for brushed points. The visualization uses d3.brush for selection, d3.axisBottom and axisLeft for scales, and loads CSV data from a GitHub-hosted Kaggle dataset.

RRochelle

80% match

Refactored Iteration Line Graph: vgsales.csv

This interactive small-multiple chart displays video game sales over time across five regional markets, with each facet corresponding to a sales category (global, North America, Japan, EU, and other). A legend color-codes twelve genres, allowing users to hover to highlight a genre’s lines or click to toggle its visibility. Built with D3 v6, the SVG visualization fetches data from a GitHub gist and aggregates sales by year and genre via `d3.flatRollup` and `d3.sum`. Users can pan by dragging, zoom with the mouse wheel, and reset the view, while axes dynamically redraw their domains using `d3.axisBottom` and `d3.axisLeft`.

3rd Iteration Line Graph: vgsales.csv

This visualization displays a small-multiple line graph of video game sales over time, broken down by genre for global, North American, Japanese, EU, and other regional markets. Built with D3 v6 in SVG, it uses d3.flatRollup and d3.sum to aggregate the vgsales.csv data. Users can hover over the legend to highlight genres, click to toggle their visibility, and drag crosshairs across charts to compare values. The axes and line weight scale with zoom, and a reset button restores the view.

Iterating Line Graph: vgsales.csv

This interactive multi-line chart uses D3.js (v6) to display video game sales data from a GitHub-hosted CSV across five regions, with each graph showing sales for twelve genres over time. A color-coded legend maps genres to lines, where hovering highlights a genre by thickening its strokes and clicking toggles its visibility. The visualization aggregates the data once before rendering, and includes crosshair functionality for comparing values across the regional charts.

Line Graph: vgsales.csv

This visualization displays video game sales over time, broken into five small multiples by region: global, North America, Japan, the EU, and other sales. Each chart plots genre-specific sales as colored polylines and circles, using d3.flatRollup to aggregate the data from the vgsales.csv dataset. The graphs use d3.scaleLinear, axisLeft, and axisBottom to render axes, with a click handler that draws a crosshair across all charts for comparison.