Skip to main content
SimilarExport ZIP
100%

D3 Scatter Plot

✓ Published0🌍 Public
JJetlinZ
Last edited Jun 6, 2022
Created on Jun 6, 2022
Forked from D3 Scatter Plot

This scatter plot visualizes the classic Iris dataset by mapping petal length to the x-axis and sepal length to the y-axis, using D3 v6’s `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` functions. Circles are rendered as SVG elements with a fixed radius of 5 pixels, positioned via `cx` and `cy` attributes. The chart fills the browser window by setting width and height to `window.innerWidth` and `window.innerHeight`, with margins applied to the scales. The code fetches the data as CSV from a GitHub gist, parses numeric fields, and applies a data join with `selectAll` and `.join`.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

See also React Starter.

MIT Licensed

Similar vizzes

Loading thumbnail…

D3 Scatter Plot

This D3 scatter plot visualizes the classic Iris dataset, plotting sepal length against petal length for each flower specimen. The visualization uses D3 v7 APIs including `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to map data coordinates to SVG circle positions with a fixed radius of 5 pixels. Circles are rendered via SVG `<circle>` elements appended through D3's selection and join operations, with axes positioned using margin-based transforms. The chart fills the browser window, with data loaded asynchronously from a remote CSV file using `d3.csv`.

Aalexscott-untitled
96% match
Loading thumbnail…

D3 Scatter Plot

This D3 scatter plot visualizes the classic Iris dataset, mapping petal length on the x-axis against sepal length on the y-axis for each flower sample. The visualization uses D3 v7's `csv` loader to fetch and parse the remote dataset, then applies `scaleLinear` and `extent` to compute the axis domains from the numeric columns. SVG circles are drawn using a data join, with axes generated via `axisLeft` and `axisBottom`. The chart is rendered in vanilla HTML and JavaScript, filling the browser viewport dynamically.

Ccharlieronchetti@gmail.com
96% match
Loading thumbnail…

D3 Scatter Plot

This example visualizes the classic Iris dataset as a scatter plot, mapping petal width to the x-axis and sepal length to the y-axis. Circles represent individual flowers, with axes labeled via D3’s `scaleLinear`, `axisLeft`, and `axisBottom` APIs. The code loads CSV data using `d3.csv`, parses numerical fields, and renders the plot as SVG circles sized with a fixed radius. The visualization fills the browser window, using viewport dimensions for the chart’s width and height, and demonstrates a straightforward data-joining workflow with `selectAll` and `join`.

Lliu yang
95% match
Loading thumbnail…

D3 Scatter Plot

This scatter plot visualizes the Iris dataset, mapping petal length on the x-axis and sepal length on the y-axis. It displays each data point as a circle in an SVG rendered at full window size. The code uses d3.csv to load the data, d3.scaleLinear with d3.extent for axes, and d3.axisLeft and d3.axisBottom to draw the scales.

Sshmouelsamares
95% match
Loading thumbnail…

D3 Scatter Plot

This example displays the classic Iris dataset as a scatter plot, with petal length on the x-axis and sepal length on the y-axis. It loads data from a GitHub Gist using `d3.csv` and parses numeric fields. The visualization is built with React and rendered as SVG, using `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, and `d3.axisBottom` to construct the axes and points. The plot is generated by a custom `scatterPlot` function that sets the width based on the window size, with margins and a fixed point radius of 5.

JJetlinZ
95% match
Loading thumbnail…

D3 Scatterplot

This visualization displays the classic Iris dataset, plotting petal length against sepal length. Each flower sample is rendered as a fixed-radius circle in an SVG canvas that fills the browser viewport. The code uses D3 v7's `csv` loader to fetch data from a GitHub gist, then employs `scaleLinear` with `extent` to compute domains for both axes. Axis ticks are generated using `axisLeft` and `axisBottom`, with the categorical iris species left uncolored in this minimal example. The rendering relies on D3's declarative selection-based joins to bind data to SVG circle elements, with dimensions set to the window's inner height and width.

Mmegan-grannan
95% match
Loading thumbnail…

D3 Scatter Plot

This example displays the classic Iris dataset as a scatter plot, mapping petal length on the x-axis and sepal length on the y-axis. The visualization uses D3 v7’s `select`, `csv`, `scaleLinear`, `extent`, `axisBottom`, and `axisLeft` APIs to load the data, compute scales, and render SVG circles and axes. The plot fills the browser window, with bold tick labels, and the code demonstrates a straightforward data-ink pipeline from CSV parsing to interactive-free SVG rendering.

WWaseem Medhat
94% match
Loading thumbnail…

D3 Scatter Plot

This example visualizes the classic Iris dataset as a D3.js scatter plot, mapping sepal length on the y-axis and petal length on the x-axis. The chart renders as an SVG with circles positioned via linear scales, while axes are drawn using `d3.axisLeft` and `d3.axisBottom`. The code fetches CSV data asynchronously, parses numeric columns, and dynamically resizes the plot to the full window. It customizes tick label styling through CSS and uses a React starter environment.

TTheo-0201
94% match