Fork of Fork of Fork of ICE7

Fork of Fork of Fork of ICE7

100% match

Fork of ICE7

This visualization displays a scatterplot of gladiolus flower measurements, with colored circles representing species and axes that cycle through different corolla and calyx dimensions every few seconds. The animation updates the x-axis variable in sequence while keeping the y-axis fixed, and a legend identifies each species by color. The code uses D3 v6 modules like `scatterPlot`, `scaleLinear`, `axisBottom`, and `axisLeft` to construct the chart, while `setInterval` drives the periodic axis changes. Data is loaded from a remote CSV file, and the points are rendered as SVG circles with custom radii.

91% match

Fork of Fork of ICE7

This animated scatterplot visualizes measurements of gladiolus flower species, comparing petal dimensions across four feature pairs. The visualization cycles through different x-axis variables—corolla width, calyx width, corolla length, and calyx length—while keeping y-axis fixed to calyx length. Data points are colored by species, with red, blue, and yellow marking three distinct gladiolus varieties. Built with D3 v6, the example uses `d3.scaleLinear`, `d3.axisLeft`, and `d3.axisBottom` for axes, `setInterval` for animation, and SVG circles with custom `rx` and `ry` attributes to render elliptical markers. The code appears to fork an existing D3 scatterplot example, adapting it to flower morphology data from a CSV source.

90% match

Fork of Fork of ICE7

This animated scatter plot cycles through four Iris flower measurements—petal width, sepal width, petal length, and sepal length—updating the x-axis every 10 seconds while keeping sepal length on the y-axis. It uses the D3 v6 library with SVG rendering, featuring pink circles and white axis labels on a pink background, and reads the ICE-7 dataset from a GitHub CSV URL via d3.csv. The plot is built with a custom scatterPlot function using d3.scaleLinear, d3.extent, d3.axisLeft, and d3.axisBottom.

Aajaysonu

87% match

Fork of Reusable D3 Scatter Plot- ICE7

This animated scatter plot cycles through four different Iris flower measurements on the x-axis while keeping sepal length fixed on the y-axis, revealing changing species clusters. The visualization uses D3 v6 modules including `csv`, `scaleLinear`, `axisBottom`, and `axisLeft` to render SVG circles colored by species, with a custom legend and rotating axis labels. Data comes from a remote iris dataset, and the animation uses `setInterval` to swap the x-value mapping every few seconds.

Bbhargavarathod

Fork of Fork of Fork of Reusable D3 Scatter Plot- ICE7

This visualization shows an animated scatter plot of iris data, cycling through four different yield measurements on the x-axis while the y-axis remains fixed. Colored circles represent three sites (StPaul, Duluth, and Morris) with distinct colors, and the chart includes a legend, axis labels, and a title. The plot updates every few seconds using `setInterval`, swapping the x-value mapping among the dataset columns. It uses D3 v6 with the `csv` loader, `scaleLinear`, `axisLeft`, `axisBottom`, and custom reusable chart functions from `scatterPlot.js`, rendering SVG elements with animated transitions.

Fork of ice - 7-1

This animated scatter plot cycles through four Iris dataset measurements on the x-axis every two seconds, using D3’s `scaleLinear`, `axisBottom`, and `axisLeft` to render axes and colored circles by species. The reusable `scatterPlot` function updates via `setInterval`, while D3’s `csv` loads the data and SVG selection joins drive the dynamic transitions.

AAmar09nath

Fork of Fork of fork of iCE - 7 Reusable Scatter Plot

This example shows an animated scatter plot of the Iris dataset, cycling through different pairs of flower measurements every two seconds. Data points are colored by species (blue, red, yellow) and rendered as SVG circles with white strokes. The visualization uses D3 v6 modules including `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to compute scales and draw axes, while a reusable `scatterPlot` function manages the chart configuration and updates. The code loads data from a CSV file hosted on GitHub and animates by changing the x-axis variable in a `setInterval` loop.

DDivyaVellanki