Manoja T9 Q2

AREA CHART

This area chart displays monthly revenue trends from a CSV dataset, filling the area beneath the line with light steelblue and outlining it in steelblue. The visualization uses D3 v7’s `d3.area()` generator, with a `scalePoint` for months on the x-axis and a `scaleLinear` for revenue on the y-axis. Axes are rendered using `d3.axisLeft` and `d3.axisBottom`, with labels added for both dimensions. The chart is drawn as an SVG element within a `div` container, with the data loaded asynchronously from a GitHub-hosted CSV file.

PP Manisha

76% match

Mano T9 - Q1

This example shows a pie chart of social media platform usage percentages, with a legend displaying each platform’s name and share. The visualization is rendered as an SVG and uses D3’s `pie` and `arc` generators to compute and draw the segments, while `scaleOrdinal` with `schemeCategory10` assigns colors. Data is loaded via D3’s `csv` function from a GitHub gist, and the legend is built manually with appended `rect` and `text` elements.

76% match

Man SDV Task 8 Q3

This scatter plot visualizes the relationship between the width and length of items from a CSV dataset, with points colored and shaped by category. The visualization uses D3.js v7 to create SVG marks, axes, and a shape legend that maps ordinal categories to distinct symbols. The plot updates dynamically to fill the browser window, with axes labeled “Width” and “Length” and hover effects increasing point opacity. It is built using modular D3 components like `scaleLinear`, `scaleOrdinal`, `symbols`, `axisLeft`, and `axisBottom`, applying a joined subchart approach.

75% match

area chart

This area chart visualizes yearly data from a CSV file, showing how values change over time. It loads the dataset via `d3.csv` from a GitHub Gist, parses the year and value columns, and renders a filled steelblue area using the `d3.area` generator. The chart uses linear scales for both axes, with an x-axis formatted to show integer years and labeled "Year," while the y-axis is labeled "Value." Axes are drawn using `d3.axisBottom` and `d3.axisLeft` within an SVG container, demonstrating basic data loading, scaling, and shape generation in D3 v7.

Rr79162810@gmail.com

75% match

Sshanmukhivasa@my.unt.edu

Fork of T9 - Area chart

This area chart visualizes yearly price data from a CSV file, displaying the trend as a semi-transparent steelblue region. The code loads the data using `d3.text` and parses it with `d3.csvParseRows`. It builds the chart with `d3.select`, `d3.scaleLinear`, and `d3.area`, rendering the area path and axes via `d3.axisBottom` and `d3.axisLeft` within an SVG.

Manoja Q3

This scatter plot visualizes the relationship between the height and weight of different dog breeds, with each point colored by species using a fixed color mapping. The chart uses D3.js v6 APIs including `d3.csv`, `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, and `d3.axisBottom` to load data from a remote CSV, compute scales, and render SVG circles within a full-window canvas. Axis labels are added as rotated SVG text elements, and the point radius is constant at five pixels.

area chart

This area chart displays yearly values loaded from a remote CSV file, using a steelblue filled path to visualize trends over time. Built with D3 v7, the code uses `d3.csv` to fetch data, `d3.scaleLinear` for both axes, `d3.area` to generate the area path, and `d3.axisBottom`/`d3.axisLeft` for the labeled axes. The SVG output includes custom margins, axis titles, and tick formatting.

Vvishnupriya eupuri

Man SDV Activity6_Task2

This stacked bar chart displays sales performance across five product categories—Electronics, Clothing, Books, Furniture, and Toys—for four regions (North, South, East, West), with percentages derived from the CSV dataset. The visualization uses D3.js v7 to render an SVG, employing d3.stack() to compute stacked series, d3.scaleOrdinal for category colors, and d3.scaleBand with d3.scaleLinear for axes. Interactive tooltips show exact category percentages on mouseover, while hover effects change bar opacity, and a legend identifies each category.