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@mounikanarra123·4 public vizzes

HW6 — Year Comparison

This interactive D3.js visualization compares simulated car fuel efficiency (MPG) across years 2019–2024, using engine size and vehicle type as axes and color categories. It offers two views: an animated year-by-year transition and a side-by-side small multiples comparison, synchronized with a timed trial feature. The chart uses `d3.csv` to load data, `d3.scaleOrdinal` for color mapping, and SVG rendering with buttons for animation playback and timing. Both views share identical axis ranges and vehicle-type colors, helping users identify upward shifts in MPG for vehicle categories.

Oct 8, 2026

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HW6 — 3D Car Chart

This 3D scatter plot visualizes relationships between engine size, fuel efficiency, and horsepower across simulated car models from 2019–2024, with color encoding vehicle type. Users can drag to rotate the Plotly chart, which is built with the `scatter3d` trace type, and button presets switch between two camera perspectives. Data loads from a CSV using D3's `d3.csv` method, and preprocessing validates required columns and numeric fields before rendering.

Oct 8, 2026

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HW6 — Car Data Visualization

This scatter plot shows simulated car data from 2019–2024, mapping engine size on the x-axis against combined fuel efficiency on the y-axis. Each circle represents a model-year combination, with circle area encoding horsepower and color distinguishing vehicle type. The visualization uses D3 v7 with SVG rendering, employing d3.scaleLinear for axes and d3.scaleOrdinal for categorical coloring. Interactive features include hover tooltips and click-to-select highlighting, implemented through d3.select and event listeners. Data comes from a CSV file loaded via d3.csv.

Oct 8, 2026

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CSCE 5320 HW5 - Cars - Mounika Narra

This scatterplot displays 2025 vehicle models by engine size and combined fuel economy, with point size encoding annual fuel cost. A single Kia Niro (ID 34779) appears highlighted in purple. The visualization uses D3 v7 with SVG rendering, loading CSV data from a GitHub gist and parsing numeric columns via `d3.csv`. Linear scales (`d3.scaleLinear`) map the axes, while a summary panel reports dataset statistics, and axes are drawn with `d3.axisBottom` and `d3.axisLeft`.

Sep 30, 2026