[introd3] scatterplot

[introd3] scatterplot using iris dataset (template)

This scatterplot visualizes the classic Iris dataset, mapping sepal length to the x-axis, sepal width to the y-axis, and petal length to the circle radius, while species determines color via d3.schemeCategory10. Built with D3 v4 and rendered in SVG, it includes labeled axes for sepal length and width. Circles are interactive: clicking highlights a point with a red stroke, and hovering displays a large text label showing the point’s sepal coordinates. A legend for species is scaffolded but not implemented.

TTollyCoburn

93% match

Basic Scatter Plot

This example visualizes the classic Iris dataset, plotting sepal length on the x-axis against petal length on the y-axis for 150 flowers. The scatter plot uses semi-transparent circular marks colored by species, with a categorical color legend generated via the d3-legend plugin. Built with D3 v4, the visualization employs d3.scaleLinear for axes, d3.axisBottom and d3.axisLeft for ticks, and d3.scaleOrdinal with schemeCategory10 for color mapping. The SVG render includes labeled axes and a legend, with data loaded from a CSV file.

92% match

Scatterplot Iris (d3.v4)

This scatterplot visualizes the classic Iris dataset using D3.js v4, mapping sepal length and width to the x- and y-axes. Each flower is represented by a circle whose radius encodes petal length, while color distinguishes species (setosa, versicolor, virginica) via a categorical scale. The chart includes labeled axes, a legend, and hover tooltips that display the species of each point. Built with SVG and animation, the visualization offers an interactive overview of the dataset’s structure and species groupings.

BBerengerCunillera

92% match

Basic Scatter Plot

This example visualizes the classic Iris dataset, plotting sepal length against petal length for 150 flowers of three species. Using D3.v4, it constructs an SVG scatter plot with labeled, ticked axes, employing `d3.scaleLinear`, `d3.axisBottom`, and `d3.axisLeft` for coordinate mapping and axis generation. The visualization also demonstrates custom axis label styling and margin-based layout, with data loaded from a CSV file.

Basic Scatter Plot

This example visualizes the classic Iris dataset, plotting sepal length against petal length for 150 flower specimens. Built with D3 v4, it loads data from a CSV file and uses linear scales with the margin convention to position circles in an SVG. The axis constraints are omitted, but the scatter plot effectively reveals the clustering of the three iris species based on their measured botanical dimensions.

scatterplot_iris

This scatterplot, built with D3 v4, visualizes the classic Iris dataset, plotting sepal length on the x-axis and sepal width on the y-axis. Each circle represents an iris flower, with its radius proportional to petal length. The visualization uses color to distinguish the three iris species, and it includes a legend for identification. Interactive tooltips appear on mouseover, showing the species of each point. Axes are labeled for sepal length and width, and the plot is rendered as an SVG with smooth transitions on hover.

DDjokovalle

scatterplot in progress

This example visualizes the classic Iris dataset as a scatterplot, mapping sepal length and sepal width to the x- and y-axes while encoding petal length in the radius of each circle and species in color. Built with D3 v4 and rendered as SVG, the chart loads iris.csv and applies linear scales for all three variables, with the radius scale bounded between 2 and 15 pixels. The visualization uses a categorical color scheme (d3.schemeCategory20) to distinguish the three iris species, and axes are drawn on the bottom and left edges of the plotting area.

BBerengerCunillera

Basic Scatter Plot

This example visualizes the classic Iris dataset with a basic scatter plot, using D3 v4 to render circles in SVG that map sepal length and width. Each circle’s fill encodes the flower species via a color legend, generated with the d3-legend plugin. Axis ticks and labels are customized with scales, and the plot is fully responsive to the viewport.