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Question 3

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Sshivakumarganji@my.unt.edu
Last edited Apr 5, 2024
Created on Apr 5, 2024
Forked from Hello VizHub

This scatter plot displays the Iris dataset, plotting weight against height for individual data points. The visualization uses colored circles, with categories A, B, and other points rendered in skyblue, lightgreen, and orange respectively. The chart is built with D3 v7, using `scaleLinear`, `axisLeft`, and `axisBottom` for axes, while data is loaded via `csv` from a remote GitHub source. Axis labels for Weight and Height are styled with green Times New Roman font.

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We are Displaying the IRIS dataset using Scatter plot.

MIT Licensed

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Question 3

This scatter plot displays the Iris dataset, plotting weight against height for individual data points. The visualization uses colored circles, with categories A, B, and other points rendered in skyblue, lightgreen, and orange respectively. The chart is built with D3 v7, using `scaleLinear`, `axisLeft`, and `axisBottom` for axes, while data is loaded via `csv` from a remote GitHub source. Axis labels for Weight and Height are styled with green Times New Roman font.

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question3

This scatter plot visualizes the relationship between height and weight, with data points colored by category (A, B, or C) from the IRIS dataset, which is loaded via `d3.csv`. It uses `d3.scaleLinear` for the x- and y-axes, rendered using `axisBottom` and `axisLeft` in an SVG. Points are drawn as circles positioned using `cx` and `cy` attributes, colored by a custom marker function. Axis labels are styled with CSS, and the chart fills the browser window with margins for the title and axes.

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This scatter plot visualizes the relationship between height and weight, with data points colored by category (A, B, or other). The visualization uses a D3.js (v7) SVG rendering pipeline, reading a CSV dataset of weights and heights. The code leverages several D3 APIs, including `d3.csv`, `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, `d3.axisBottom`, and `d3.select` to build the chart, with axis labels styled via CSS and rendered as SVG text elements.

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This example visualizes a scatter plot of height and weight data, with points colored by category using skyblue, lightgreen, and orange. The SVG rendering uses D3 v7 APIs including `csv`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to map the data to axes and draw circles. The code loads data from a GitHub Gist URL and applies a custom parsing function to convert numeric fields. Axis labels are styled with green Times New Roman text, and the plot fills the browser window.

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This visualization plots the IRIS dataset as a scatter plot, using a CSV of heights and weights with category labels. The code loads the data from a remote URL via `d3.csv`, maps the rows to numeric height and weight values, and computes the scales with `d3.scaleLinear` and `d3.extent`. Circles are drawn in SVG with different fill colors—skyblue, lightgreen, or orange—assigned per category, while `d3.axisLeft` and `d3.axisBottom` create the labeled axes. The visualization displays the distribution of height and weight across the three categories.

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This scatter plot visualizes the relationship between height and weight, with points colored by category to reveal grouping patterns. The visualization renders as an SVG generated with D3.js v7, using `d3.csv` to load data from a remote GitHub repository and `d3.scaleLinear` for axis scaling. Points are drawn as SVG circles and colored via `d3.scaleOrdinal`, with interactive tooltips appearing on mouseover. The chart includes axes and a legend created through custom drawing functions, all styled through a separate CSS file.

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