3D Scatter Plot

100%

3D Scatter Plot

✓ Published2🌍 Public

Last edited Jul 7, 2022

Created on Jul 6, 2022

Forked from 3D Scatter Plot with Iris Dataset

This example shows a 3D scatter plot of wheat dataset attributes, with two traces comparing relationships between Area, Perimeter, and both Kernel_Length and Kernel_Width. The Plotly.js library renders the interactive visualization, while d3.csv loads the data from a GitHub-hosted CSV file. The code defines trace-specific marker styles, including sizes, colors, and opacity, and uses a minimal layout with all margins set to zero.

AI-generated description

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

Similar vizzes

Loading thumbnail…

3D Scatter Plot

This example visualizes the Wheat kernel dataset as a 3D scatter plot, displaying Area, Perimeter, and Kernel Length as markers in three-dimensional space. It also includes a second trace that combines Area, Perimeter, and Kernel Width, using distinct colors and marker symbols to differentiate the two series. The visualization is built with Plotly’s `scatter3d` and `scatter2d` types, with data loaded via D3’s `d3.csv` and rendered into a `div` using `Plotly.newPlot`. The layout margins are set to zero for a clean, full-bleed presentation.

Ssuchitra2602

95% match

Loading thumbnail…

3D Scatter plot using D3.js

This example presents an interactive 3D scatter plot built with Plotly.js and D3.js, visualizing agricultural crop data. It renders two marker traces from a CSV file: one mapping crop type, production, and district, the other correlating crop year, season, and area. The code uses `d3.csv` to load the dataset and `Plotly.newPlot` to draw the scatter3d traces within a DIV element. The visualization employs 3D markers with custom opacity and line styling to distinguish the two datasets, with the layout margins set to zero.

Ggayathrikavya

83% match

Loading thumbnail…

3D Scatter Plot

This 3D scatter plot visualizes the Iris dataset, displaying three dimensions (Area, Perimeter, and Kernel Length) as one series, with a second series replacing Kernel Length with Kernel Width. The plot uses the Plotly JavaScript library via the `Plotly.newPlot` function to render interactive 3D markers in a web page. Data is loaded asynchronously using D3's `d3.csv` to fetch a remote CSV, and the marker styles (size, opacity, and colors) are configured per series. The layout margins are zeroed to maximize the chart area.

Ssuchitra2602

83% match

Loading thumbnail…

3D Scatter Plot

This 3D scatter plot visualizes the relationship between length, breadth, and the resulting area and volume for squares and rectangles. Two sets of markers are rendered: red circles for area and green diamonds for volume, each positioned in three-dimensional space based on the CSV data. The example uses Plotly’s `Plotly.newPlot` method to create the `scatter3d` traces, with data loaded via D3’s `d3.csv` function. Axis titles and marker styling are configured through the layout object.

Aanushaanumula

82% match

Loading thumbnail…

3D Scatter Plot

This example shows a 3D scatter plot comparing anthropometric measurements—height, weight, age, and body fat—from a CSV dataset. Two overlapping sets of markers display different variable combinations, with semi-transparent circles highlighting the relationships among these dimensions. The visualization uses Plotly's `scatter3d` type through the `Plotly.newPlot` API, while D3's `d3.csv` loads and parses the external data file. A custom layout removes the chart margins to maximize the plotting area.

Ssaijahnaviappineni

80% match

Loading thumbnail…

Reusable Scatter plot Archana Goli

This reusable D3.js scatter plot visualizes the dimensions of wheat kernels, with each circle representing a sample. The plot cycles through four variables—Perimeter, Kernel_Width, Area, and Kernel_Length—on the x-axis every two seconds, while the y-axis remains Kernel_Length. Built with D3’s `scaleLinear`, `axisLeft`, and `axisBottom` APIs, the SVG visualization updates dynamically via a `setInterval` function. The code loads CSV data from a GitHub gist and renders animated, resizable scatter plots based on the browser window’s dimensions.

Aarchanagoli@my.unt.edu

80% match

Loading thumbnail…

Fork of 3D Scatter Plot

This interactive 3D scatter plot visualizes two sets of coordinates from a CSV dataset, using height, length, and corner positions as the three axes. Each of the two traces appears as a cluster of markers, with different colors, sizes, and opacities to distinguish the data groups. The visualization is built with Plotly’s `scatter3d` trace type and rendered via `Plotly.newPlot`, while the data loading and parsing rely on D3’s `d3.csv` function. The chart updates dynamically in response to the user’s rotation and zoom controls.

KKeerthipriyaBankuru

79% match

Loading thumbnail…

3D Bar Plot

This example displays two sets of three-dimensional scatter points from a CSV file, using colored markers to distinguish between datasets. The visualization leverages the Plotly JavaScript library through the `Plotly.newPlot` function to render an interactive 3D scene. The data is loaded remotely via `d3.csv`, and the visualization employs a scatter3d trace type with configurable marker size, opacity, and line properties. The scene is presented with zero margins to maximize the plotting area, and the renderable is provided through an SVG or web-based rendering approach.

Ssaijahnaviappineni

78% match