Fork of Scatter Plot with Menus

Fork of Scatter Plot with Menus

This interactive scatter plot displays the classic Iris dataset, allowing users to explore relationships between sepal and petal measurements. Two dropdown menus let viewers independently select which attribute appears on the X and Y axes, with axes and labels updating dynamically. Built with React and D3 v5, the visualization uses d3.scaleLinear for scales, d3.extent for domain calculation, and d3.csv for data loading. SVG rendering draws the circular marks, while custom React components handle axis generation and menu controls, with d3.format applying abbreviated tick labels.

AAbin

Fork of Scatter Plot with Menus

This interactive scatter plot visualizes the Iris Dataset, displaying sepal and petal measurements as a series of circles. Two dropdown menus allow the user to independently select which quantitative or categorical attribute is plotted on the x- and y-axes. The visualization is built with React and D3 v5, using `d3.scaleLinear` and `d3.extent` to map data to SVG coordinates, while axis components and marks are rendered as reusable React functions. Data loading is handled asynchronously with `d3.csv`, and the chart updates dynamically when menu selections change.

Sshimos12468

Fork of Scatter Plot with Menus

This interactive scatter plot visualizes the Iris flower dataset, allowing viewers to explore relationships between sepal and petal measurements by swapping attributes on the x- and y-axes via dropdown menus. Built with React and D3 v5, it uses `scaleLinear` for axes, `csv` for data loading, and SVG circles rendered through React components for marks. At any moment, the graph displays one combination of the four numeric attributes, with axis labels updating dynamically to reflect the selected measures.

Mmartinbirch@outlook.dk

Fork of Scatter Plot with Menus

This interactive scatter plot of the classic Iris dataset lets users explore relationships between sepal and petal measurements. Two dropdown menus control which attribute is mapped to the x- and y-axes, updating the visualization in real time. Built with React and using d3's `scaleLinear` and `extent` for scaling, the SVG render shows circles colored teal, with labeled axes and tooltips. The data loads asynchronously from a GitHub-hosted CSV via d3's `csv` function.

Ppatty5531998

Fork of Scatter Plot with Menus

This interactive scatter plot displays the Iris Dataset, allowing users to explore relationships between sepal and petal measurements. Two dropdown menus, implemented with React state, dynamically select which numerical attributes map to the x and y axes. The visualization renders as an SVG using React with D3’s `scaleLinear` for axis scales and `extent` to compute domains from the CSV data. Circle marks use a tooltip via the `<title>` element.

Eevers-codeshop-ai

Fork of Scatter Plot with Menus

This interactive scatter plot explores the Iris Dataset, displaying sepal and petal measurements across four attributes. Users select which variables to plot on the X and Y axes through two dropdown menus, allowing arbitrary pairings of the dataset’s quantitative features. The visualization uses React with `useState` for menu state and D3’s `scaleLinear` for axes, rendered as SVG circles with tooltips showing axis values. The example demonstrates a classic approach to interactive multivariate exploration within a fixed canvas.

JJusung

Fork of Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing users to explore relationships between sepal and petal measurements by selecting which attributes are plotted on the x- and y-axes via dropdown menus. The chart renders data points as SVG circles with tooltips, using D3’s `scaleLinear`, `extent`, and `format` APIs for axes and tick labels. The visualization is built with React, managing state for axis selections, and a custom `useData` hook loads the CSV data using `d3.csv`.

GGeekboxer

Fork of Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing users to explore relationships between four numeric attributes through dropdown menus that dynamically reassign the x and y axes. The visualization uses React for component management and state, d3.v5 for scales and CSV parsing, and renders SVG circles with tooltips showing formatted values. Users can switch between sepal and petal measurements, with axis labels updating accordingly to reflect the selected variables.

EEugenio2192