Fork of Scatter Plot with Menus

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

Fork of Scatter Plot with Menus

This interactive scatter plot displays the classic Iris dataset, allowing users to explore relationships between four measured attributes and species through dropdown menus that dynamically reassign the x- and y-axes. Built with React and rendered as SVG using D3 v5, the visualization updates scales and marks via state changes triggered by the dropdown selections. The code leverages `scaleLinear`, `extent`, and `csv` for data loading and scaling, with custom React components for axes, marks, and menu controls.

XXiaoyu Su

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 displays the Iris dataset, allowing users to select which quantitative attributes appear on the x- and y-axes through two dropdown menus built with React state. The visualization is rendered as an SVG, with axes and circles generated by D3 v5 scales and React components. Data is loaded asynchronously from a CSV file using d3.csv, and the plot updates dynamically when dropdown selections change.

EEdgar Alves

Fork of Scatter Plot with Menus

A scatter plot of the Iris dataset allows interactive selection of which measurement attributes (sepal length, sepal width, petal length, petal width, or species) appear on the X and Y axes via dropdown menus. The visualization is rendered as an SVG using React, with D3.js v5 functions like `csv` for data loading and `scaleLinear` for axis scales. Two dropdown components update the selected attributes, triggering re-renders of the axes and circles.

NNikithakatta30

Fork of Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing users to select which attributes to display on each axis via dropdown menus built with React state. The visualization uses D3 v5’s `scaleLinear`, `extent`, and `format` functions to map data values to SVG circle positions rendered through React components, with transitions applied when axes change. The chart includes labeled axes and tooltips showing the x-value for each point.

CChintan Sawla

Fork of Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, with dropdown menus controlling the attributes mapped to the x and y axes. The visualization is rendered using React and D3 v5, leveraging `d3.scaleLinear`, `d3.extent`, and `d3.format` to compute scales and tick formatting. Each data point is drawn as a circle with a tooltip showing its x-value. Selecting different attribute combinations updates the axes and marks dynamically, allowing exploration of relationships among sepal and petal measurements.

Rrajamrit-singh

Fork of Scatter Plot with Menus

This interactive scatter plot, built with React and D3.js v5, visualizes the classic Iris Dataset, which contains measurements of sepal and petal dimensions for three iris species. Two dropdown menus allow users to independently select which quantitative attribute is mapped to the x-axis and y-axis, dynamically updating the linear scales and the displayed points. The visualization renders as an SVG, with each data point drawn as a circle. The code uses `d3.csv` to load the data and `d3.scaleLinear` to generate the axes, with React's `useState` managing the selected attributes.

SSam