Fork of 3D Scatter Plot with Iris Dataset

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

Fork of 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.

Bbhargavarathod

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

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

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

Fork of 3D Scatter Plot

This fork of a 3D scatter plot visualizes the Iris dataset, displaying two series of markers that map sepal length, sepal width, and either petal length or petal width. The visualization uses Plotly’s `Plotly.newPlot` to render a `scatter3d` chart inside a `div`, with data loaded via `d3.csv`. Each trace configures marker size, opacity, and line styling, while the layout removes all margins to focus on the plotted points.

VVineela Reddy

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

Fork of 3D Scatter Plot

This example renders a 3D scatter plot of the Iris dataset, comparing flower measurements across two traces: sepal dimensions against petal length in one trace, and sepal dimensions against petal width in another. The visualization uses Plotly’s `scatter3d` type via `Plotly.newPlot` to draw markers with customizable size, opacity, and line styling into a `div`. Data loading relies on D3’s `d3.csv` to fetch the dataset, while `unpack` extracts specific columns for each axis, presenting the multidimensional relationships in an interactive three-dimensional space.

Ppavan0828