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Gist 659920e73da6e8c3e3885700757a5f3d

✓ Published0🌍 Public
RRoxIv
Last edited Jul 20, 2018
Created on Jul 20, 2018

This visualization renders the classic Iris dataset, showing the relationship between sepal and petal measurements for three flower species. The D3.js force-directed layout algorithm (`d3.forceSimulation`) positions each data point as a node in a network, with species membership encoded by color. The drawing uses SVG paths rendered via `d3.geoPath` to create a Voronoi tessellation of the measurement space, visually partitioning regions by species. The dataset is loaded directly from the embedded CSV, with each flower’s four attributes mapped to spatial dimensions.

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Gist 0bd164d320049d1926cdb6310644fa40

This visualization uses the classic Iris dataset to display the relationships between sepal and petal measurements for three flower species. The code loads the CSV data and renders a scatter plot that maps sepal length and width on the axes, with each point colored by species. The implementation relies on the Plotly.js library's `Scatter` and `Layout` classes to generate the interactive chart, with species values driving both the color and legend entries for the setosa, versicolor, and virginica groups.

JJan0RodGar
88% match
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iris

This visualization displays the classic Iris flower dataset as a scatterplot, mapping sepal length and width to the x and y axes, petal length to point size, and species to color. The rendering uses D3 v4’s SVG output. Data loading relies on `d3.csv` for parsing the CSV file, while scales are built with `d3.scaleLinear`, `d3.scaleSqrt`, and `d3.scaleOrdinal`, plus axes from `d3.axisBottom` and `d3.axisLeft`. A categorical legend, built with circle elements, identifies the three species (setosa, versicolor, virginica), and a tooltip div is appended to the body but never made visible.

GGTHamonville
86% match
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Iris_scatterplot_sepal

This example visualizes the classic Iris dataset, plotting sepal length against sepal width for 150 flowers. Points are encoded with different shapes and colors to distinguish the three species: setosa (circles), versicolor (red squares), and virginica (black squares). The visualization includes axis labels, a categorical color legend, and interactive tooltips that display the species on hover. Built with D3 v4 using SVG, it also demonstrates the use of ordinal color scales, square-root size scaling, and filter-based shape encoding.

DDjokovalle
84% match
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Activity6_task3

This visualization shows the classic Iris dataset, displaying the relationships between sepal and petal measurements for three species. Using D3.js, it renders a scatter plot where each point represents a flower, with sepal length on the x-axis, petal length on the y-axis, and points colored by species. The code uses `d3.forceSimulation` to optimize the layout of data points, ensuring they are spread evenly while preserving the integrity of the underlying measurements, offering an interactive view into the dataset's structure.

Ssravani1969@gmail.com
83% match
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D3: Drawing with iris data

This example visualizes the classic Iris dataset by plotting sepal length against sepal width for three species of iris flowers. Each species is distinguished by a unique symbol shape and color: red triangles for setosa, orange crosses for virginica, and blue stars for versicolor. The visualization also overlays a least-squares regression line for each species, computed from the data, to show trends in the relationship. Built with D3 v4, the code loads the CSV data and uses `d3.scaleLinear`, `d3.axisBottom`, `d3.axisLeft`, and `d3.symbol` to render the SVG scatterplot and its axes.

MMathReynaud
83% match
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D3: Drawing with iris data

This example visualizes the classic Iris dataset by plotting sepal length against sepal width for three species of iris flowers. Each species is distinguished by a unique symbol shape and color: red triangles for setosa, orange crosses for virginica, and blue stars for versicolor. The visualization also overlays a least-squares regression line for each species, computed from the data, to show trends in the relationship. Built with D3 v4, the code loads the CSV data and uses `d3.scaleLinear`, `d3.axisBottom`, `d3.axisLeft`, and `d3.symbol` to render the SVG scatterplot and its axes.

MMathReynaud
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D3 scatter plot

This scatter plot visualizes the Iris dataset, mapping petal length on the x-axis and sepal length on the y-axis. Each flower is rendered as an SVG circle using D3 v7, with positions scaled linearly via `d3.scaleLinear` and extents computed from the data. The axes are drawn using `d3.axisLeft` and `d3.axisBottom`, and the visualization fills the browser window. Data is loaded asynchronously with `d3.csv` from a remote GitHub gist, and circles are joined to the SVG using `selection.join`.

Yyankesswang
83% match
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td3

This visualization displays two side-by-side scatterplots of the Iris dataset, plotting sepal length against sepal width. Each point is encoded with a symbol and color representing the flower species, while point size reflects petal length. Built with D3 v4, the code uses `d3.scaleLinear`, `d3.scaleOrdinal`, and `d3.symbol` to generate distinct patterns for setosa, versicolor, and virginica. The SVG renderings are created by appending paths to separate chart divs, with scales computed from the CSV data using `d3.extent` and `d3.axisBottom`/`d3.axisLeft` for axes.

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