Learn Scatter With Menu

Scatter Plot with Menu

This interactive scatter plot displays the Iris flower dataset, allowing users to explore relationships between sepal and petal measurements through two dropdown menus. Users select which attribute appears on each axis, and the SVG scatter plot updates the x and y scales accordingly. The visualization uses React hooks for state management, d3.scaleLinear for scaling, and d3.extent for domain calculations. Data is loaded asynchronously from a CSV file using d3.csv, with numeric values parsed on ingestion. The interface includes custom axis components with tick marks and axis labels.

SSam Hege

Scatter Plot with menus

This interactive scatter plot displays the Iris flower dataset, allowing users to explore relationships between four numeric measurements—sepal length, sepal width, petal length, and petal width—by selecting which attribute appears on each axis via two dropdown menus. The visualization renders data points as SVG circles, with scales created using d3.scaleLinear and extents computed via d3.extent. Axis components generate tick marks and labels, while React hooks manage the selected attributes and trigger re-renders upon menu changes. The data loads asynchronously from a CSV file using d3.csv.

KKolezhannochka

Learn Polished Scatter With Menu

This interactive scatter plot visualizes the Iris dataset, displaying sepal and petal measurements for individual flowers. Users can select which attributes to plot on the X and Y axes using drop-down menus, with both axes updating dynamically to reflect the chosen variables. The visualization is built with React and rendered as SVG, using D3's `scaleLinear` and `extent` functions to compute scales and domains. Axis components are custom React components that generate tick marks and labels, while the `Marks` component renders circles with tooltips for each data point.

TTsaiJie

menu iris scatter plot

This scatter plot visualizes the Iris dataset, allowing interactive exploration of relationships between different flower measurements (sepal length, sepal width, petal length, petal width) through two dropdown menus that control the x and y axes. The visualization uses React with D3 v5 for scales and axes, rendering SVG circles for data points. Axis components use D3's scaleLinear and extent functions to compute domains, while tooltips display formatted values. The data is loaded from a remote CSV file using D3's csv parsing utility.

GGuitong Li

Scatter plot with menu

This interactive scatter plot visualizes the Iris dataset, allowing users to select which flower measurements (sepal length/width, petal length/width) appear on each axis via dropdown menus. The chart uses React state to track selected attributes, updating the axes and circles accordingly. Built with D3 scales (d3.scaleLinear, d3.extent) and custom SVG axis components, each data point renders as a circle with a tooltip showing its x-value. The CSV data loads asynchronously via d3.csv from a GitHub gist.

Ccshm407

Scatter Plot with Menus

This interactive scatter plot displays the Iris dataset, allowing users to explore relationships between sepal and petal measurements by selecting which attributes appear on the X and Y axes via dropdown menus. The visualization renders each flower as an SVG circle, with tooltips showing exact values on hover. Built with React for the interface and D3 v5 for scales, axes, and data loading through `d3.csv`, the chart updates scales and labels dynamically when menu selections change. The code uses `scaleLinear` with `extent` for domain calculation and custom React components for the axes and dropdowns.

Wwinniepooh520

Scatter plot with menus

This interactive scatter plot displays the Iris dataset, allowing viewers to explore relationships between sepal and petal measurements by selecting which attribute appears on each axis through the dropdown menus. Built with React hooks and D3.js v5, the visualization uses `scaleLinear` to map data ranges to SVG coordinates and renders circles for individual specimens. The axis components dynamically update with `tickFormat` for readable labels, while hover tooltips reveal exact values. The code demonstrates a reusable pattern for building linked interactive visualizations from CSV data using `d3.csv` and React state management.

Ppatasky

scatter with menus

This interactive scatter plot displays the Iris flower dataset, letting users explore relationships between sepal and petal measurements through dropdown menus that control the x and y axes. The visualization, rendered with React and D3 v7, uses `scaleLinear` for axes, `scaleOrdinal` for species coloring, and SVG circles for data points. Hovering over the color legend highlights a selected species while dimming others, and tooltips reveal exact values via SVG `<title>` elements.

JJosh Zalcman