Polished Scatter Plot with Menus

Polished Scatter Plot with Menus

A scatter plot of the Iris dataset displays four numeric attributes and species, with interactive dropdown menus that select which attribute maps to the x and y axes. The SVG visualization uses React for component structure, d3.scaleLinear for axis scaling, and d3.csv for data loading. Each circle represents a flower sample, with tooltips showing formatted values via a D3 format specifier.

CChongho Lee

Polished Scatter Plot with Menus

This interactive scatter plot explores the classic Iris dataset, displaying measurements like sepal width and petal length as circles colored by species. Users select which attributes to plot on the X and Y axes via ReactDropdown menus, with d3.scaleLinear and d3.extent defining the scales. The visualization uses React hooks and components like AxisBottom, AxisLeft, and Marks to render SVG elements, with tooltips and formatted tick labels from d3.format.

WWolfgang

Polished Scatter Plot with Menus and Color

This interactive scatter plot visualizes the Iris dataset, showing relationships between four flower measurements with points colored by species. Users can switch the X and Y axes via dropdown menus powered by ReactDropdown. Built with React and D3 v5, the visualization uses d3.scaleLinear for axes, d3.scaleOrdinal for species colors, and scales computed with d3.extent and d3.nice. SVG circles include tooltip titles, while axis components render ticks and labels.

LLisa Wagner

Polished Scatter Plot with Menus

This example presents an interactive scatter plot of the Iris flower dataset, allowing users to select which numeric attributes to plot on the x- and y-axes via dropdown menus. The visualization uses React for component-based UI and rendering, with D3 v5 utilities such as `scaleLinear`, `extent`, and `format` for scales and axis tick formatting. SVG circles represent data points, colored by species using `scaleOrdinal`, and include tooltips showing exact values. The code leverages a custom `useData` hook to load CSV data asynchronously.

Ppnlinyz

Polished Scatter Plot with Menus

This interactive scatter plot displays the Iris flower dataset, allowing users to select which quantitative attributes to plot on the x- and y-axes via two dropdown menus built with React and the ReactDropdown component. The visualization is rendered as an SVG using D3 v7 scales (scaleLinear) and custom axis components, with circles colored in a teal tone and tooltips showing the formatted attribute values. The code loads CSV data via d3.csv and uses React hooks (useState, useEffect) to manage state and fetch the data.

Ddaneslutzky

Polished Scatter Plot with Menus

This interactive scatter plot visualizes the Iris flower dataset, allowing users to select which numeric attributes are plotted on the x- and y-axes via dropdown menus. The visualization uses React to manage component state and render SVG elements, with D3’s `scaleLinear`, `extent`, and `max` functions handling axis scaling and data mapping. Axis ticks and labels are generated through custom React components, while circles representing data points include tooltips using SVG `<title>` elements. The graph updates dynamically whenever the dropdown selections change.

AAudrey

Polished Scatter Plot with Menus

This interactive scatter plot displays the Iris dataset, allowing users to explore relationships between flower measurements by selecting different attributes for the x and y axes through dropdown menus. Built with React and rendered as SVG, the visualization uses D3.js functions such as `scaleLinear`, `extent`, and `format` to map data ranges and format tick labels. Each point is a circle with a native SVG `<title>` element for hover tooltips, positioned using computed coordinates from the D3 scales. The plot features labeled axes, styled tick marks, and a dark teal color scheme.

Jj-PGi

Polished Scatter Plot with Menus

This interactive scatter plot visualizes the Iris Dataset, displaying measurements from four flower attributes. Users select which attributes appear on the X and Y axes through two dropdown menus, with axis labels and scales updating accordingly. The visualization is built with React and D3 v7, using `scaleLinear`, `extent`, `max`, and `format` functions to position marks and format tick labels. SVG circles represent individual iris samples, with native `<title>` tooltips revealing exact values on hover. The example demonstrates a polished, reusable component architecture with axes, marks, and dropdowns split into separate functional components.

BBen Seebeck