rithwikjadala2003@gmail.com

@rithwikjadala2003·3 public vizzes

Q1c

This 3D scatter plot maps countries by GDP per capita, CO2 emissions per capita, and the percentage of energy from renewable sources, with each point colored by region. Using Plotly’s `scatter3d` trace type, the visualization plots the parsed CSV data from 2018 to 2023. Hovering over a point reveals the country name and year, allowing exploration of how these three variables relate across different global regions.

Oct 5, 2026

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assignment 6

This interactive D3.js visualization explores relationships between GDP per capita, CO2 emissions per capita, population, and renewable energy adoption across countries from 2018–2023. Three modes—a 2D scatterplot, small multiples by region, and animated year-by-year transitions—allow comparison of temporal trends. The SVG rendering uses d3.scaleOrdinal, d3.scaleSqrt, and d3.extent for consistent scales, with tooltips featuring configurable delay and a race timer animation. Data comes from a CSV file loaded via d3.csv.

Oct 5, 2026

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HW5 — Video Game Marks and Channels

A scatterplot displays video games from a CSV dataset, plotting critic scores against release years. Each point is colored by genre and its size encodes millions of units sold. The chart uses D3 v7 APIs including `d3.csv`, `d3.select`, `d3.scaleLinear`, and `d3.extent` to load and process data, map quantitative and categorical variables to position, hue, and area, and render the marks as SVG shapes.

Oct 1, 2026