Fork of D3 Scatter Plot

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Fork of D3 Scatter Plot

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Last edited Mar 7, 2022

Created on Mar 7, 2022

This scatter plot visualizes the Iris Dataset, mapping petal length on the x-axis against sepal length on the y-axis for individual flower specimens. The code loads raw CSV data from a GitHub gist, parses numeric fields, and uses D3 v6 scales, axes, and SVG circle elements to render the points across a full-window canvas. Axis tick labels are styled at 32 pixels for improved readability.

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A vanilla HTML implementation of a D3 scatter plot. Shows the Iris Dataset.

MIT Licensed

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Fork of D3 Scatter Plot

This example visualizes the Iris Dataset as a scatter plot, mapping petal length to the x-axis and sepal length to the y-axis. Built with D3 v6 and rendered as SVG, it loads data via `d3.csv`, scales positions using `d3.scaleLinear` with `d3.extent` domains, and draws circles for each observation. Axes are generated with `d3.axisLeft` and `d3.axisBottom`. The chart fills the browser window, with margins and a fixed point radius, highlighting the distribution of flower measurements.

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This visualization displays the Iris Dataset as a scatter plot, mapping petal length on the x-axis and sepal length on the y-axis. Each of the 150 flowers appears as a circle with a fixed radius of 5 pixels. The code uses d3.csv to load the data, d3.scaleLinear and d3.extent to set the scales, and d3.axisLeft and d3.axisBottom to render the axes. The SVG rendering fills the entire browser window, and circles are drawn using d3.selectAll and the .join method.

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This example displays the Iris Dataset as an interactive scatter plot, mapping petal length and sepal length for each specimen on a full-window SVG. It uses the D3.js v6 library, specifically importing functions like `csv`, `select`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom`. The code asynchronously fetches CSV data from a remote Gist, parses numeric fields, then binds circles to the data points at computed x and y positions. Axes are rendered with D3’s standard axis components, and the chart automatically resizes to fill the browser viewport.

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This scatter plot visualizes the Iris Dataset, plotting petal length against sepal length for individual flowers. The visualization uses D3 version 6, loading the data via the `csv` function and parsing numeric fields. The code employs `scaleLinear` to map data domains to pixel ranges, `extent` to calculate domains, and `axisLeft` and `axisBottom` to render the y- and x-axes. Data points are drawn as SVG circles using the `.join` operator, while axis labels are added as SVG text elements.

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This scatter plot visualizes the Iris Dataset, mapping petal length to the x-axis and sepal length to the y-axis. D3 code uses `csv` to load data, `scaleLinear` and `extent` to set scales, and `axisLeft` and `axisBottom` for axes. Each flower is rendered as an SVG circle with a fixed radius. The visualization fills the browser window using `window.innerWidth` and `window.innerHeight`.

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This scatter plot visualizes the Iris Dataset, plotting petal length against sepal length for individual flowers. The visualization is built with D3 version 6, using `scaleLinear` for both axes, `extent` to compute data domains, and `axisLeft`/`axisBottom` for tick marks. The code retrieves data from a CSV file via `d3.csv`, then renders circles with a fixed radius of 5 pixels. The SVG canvas fills the entire browser window, with axes labeled at 24-pixel font size.

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This scatter plot visualizes the Iris Dataset, plotting petal length against sepal length for individual flower samples. Each circle represents a data point, with axes labeled using D3's scaleLinear, axisLeft, and axisBottom APIs, and tick text styled at 24px. The visualization fills the browser window by setting SVG dimensions to window.innerWidth and innerHeight, reading the dataset from data.csv via d3.csv. Circle positions are computed by mapping data values through linear scales with defined margins and a fixed radius of 5 pixels.

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A D3 scatter plot displays the Iris dataset, mapping petal length on the x-axis and sepal length on the y-axis for individual flower specimens. Each data point is rendered as a fixed-radius SVG circle, with axes scaled using `d3.scaleLinear`. The code loads the CSV data via `d3.csv`, parses numeric fields, and appends an SVG canvas sized to the browser viewport. Axes are generated with `d3.axisLeft` and `d3.axisBottom`, while the circles are bound to data and added using `d3.selectAll` and `.join`.

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