Fork of 3D Scatter Plot with Iris Dataset

100%

Fork of 3D Scatter Plot with Iris Dataset

✓ Published6🌍 Public

Last edited Mar 12, 2022

Created on Mar 12, 2022

Forked from 3D Scatter Plot with Iris Dataset

This example shows a 3D scatter plot of the Iris dataset, with two traces comparing sepal and petal measurements. The first trace uses sepal length, sepal width, and petal length as axes, while the second uses petal width in place of petal length, rendering both with circular markers and adjustable opacity. It loads CSV data via D3’s `d3.csv` and creates the interactive 3D visualization using Plotly’s `Plotly.newPlot` with a `scatter3d` trace type. The layout removes all margins, and the code relies on Plotly 2.9.0 and D3 3.5.17 from CDNs.

AI-generated description

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

Similar vizzes

Loading thumbnail…

Fork of 3D Scatter Plot

This example visualizes the Iris dataset in a 3D scatter plot, comparing sepal and petal measurements across two marker groups. The first trace plots sepal length, sepal width, and petal length, while the second trace uses petal width instead, with distinct marker styling and opacity. Built with Plotly.js via `Plotly.newPlot`, the code loads the CSV data using `d3.csv` and organizes columns into x, y, and z coordinates. The layout removes all margins to maximize the plotting area, and the chart renders inside a designated `div` element.

SsreepavanKothapalli

96% match

Loading thumbnail…

Fork of 3D Scatter Plot with Iris Dataset

This interactive 3D scatter plot visualizes the Iris dataset, displaying sepal length, sepal width, and petal length as coordinates in three-dimensional space. Each flower specimen appears as a marker, with a second trace plotting the same sepal dimensions against petal width in a 2D scatter overlay, both using semi-transparent styling to reveal overlapping points. The visualization is built with Plotly’s JavaScript library, specifically using `Plotly.newPlot` to render the chart into a dedicated div, while data is loaded asynchronously via `d3.csv` from a remote GitHub-hosted CSV file. The code defines two traces—one `scatter3d` and one `scatter2d`—with custom marker sizes, colors, and opacity, and removes all layout margins for a clean presentation.

JJyothicherukuri

95% match

Loading thumbnail…

Fork of Fork of 3D Scatter Plot with Iris Dataset

This example visualizes the Iris dataset as a 3D scatter plot, mapping sepal length, sepal width, and petal length for one trace, and petal width for another. The visualization uses Plotly’s `scatter3d` and `scatter2d` trace types, rendered inside a `myDiv` element via `Plotly.newPlot`. Data is loaded asynchronously from a GitHub-hosted CSV file using `d3.csv`, while marker styles, colors, and opacity are configured through Plotly’s marker properties. The layout removes all margins to maximize the plot area.

PPujitha14challagulla

95% match

Loading thumbnail…

Fork of 3D Scatter Plot

This visualization displays the Iris dataset as a 3D scatter plot, comparing sepal and petal measurements across different species. The first trace uses petal length as the z-axis with a colormap, while the second uses petal width, both with semi-transparent markers. The code loads the CSV data using `d3.csv`, parses it with custom `unpack` functions, and renders the plot using Plotly's `Plotly.newPlot` API with `scatter3d` traces. The layout removes all margins for a clean presentation.

SsreepavanKothapalli

95% match

Loading thumbnail…

Fork of 3D Scatter Plot with Iris Dataset

This example shows a 3D scatter plot of the Iris dataset, visualizing sepal and petal measurements from the data loaded via a CSV file. It renders two traces: one as a flat scatter2d layer and another as a scatter3d layer, both using markers with varying colors and opacity. The code uses the Plotly.js library to create the chart inside a div with the ID `myDiv`, while D3.js handles CSV parsing and data unpacking. The layout margins are set to zero to maximize the plot area.

JJyothicherukuri

95% match

Loading thumbnail…

Fork of Fork of 3D Scatter Plot with Iris Dataset

This example visualizes the classic Iris dataset as an interactive 3D scatter plot, displaying two traces that map sepal and petal measurements against different axes. The plot uses Plotly’s `Plotly.newPlot` function to render scatter3d markers with adjustable size, opacity, and color, while D3’s `d3.csv` loads the dataset from a GitHub gist. The layout removes all margins, focusing attention on the three-dimensional point distribution.

MMgk1255

94% match

Loading thumbnail…

Fork of 3D Scatter Plot

This fork displays two 3D scatter plots of the Iris dataset, showing sepal length, sepal width, and petal length in one trace, and sepal length, sepal width, and petal width in another, using gray and translucent markers. The code loads the CSV data with `d3.csv` and renders the interactive chart via the Plotly `Plotly.newPlot` API, setting marker size, opacity, and line styling for each `scatter3d` trace.

VVAbhiram99

94% match

Loading thumbnail…

3D Scatter Plot

This 3D Scatter Plot visualizes the Iris dataset, plotting sepal length, sepal width, and petal length in one trace, and sepal length, sepal width, and petal width in another, using Plotly's `scatter3d` trace type. The markers are styled with size, opacity, and line properties, and rendered inside a `myDiv` container. The code loads data via `d3.csv` from a GitHub gist and creates the plot with `Plotly.newPlot`, using the Plotly CDN and D3 v3. The layout margins are set to zero for a full-bleed view.

SsreepavanKothapalli

93% match