Dataviz 9 - Scatter plot with Menus (Coloured)

Dataviz 9 - Scatter plot with Menus

This interactive scatter plot explores the Iris Dataset, allowing users to dynamically select which flower measurements appear on the x- and y-axes via dropdown menus. Each point represents a flower specimen, positioned according to its sepal and petal dimensions. The visualization uses React for state management and rendering, while D3.js v5 handles data loading, linear scaling (scaleLinear), and SVG axis generation. The data is parsed from a CSV file using D3’s csv function, and axis labels update dynamically to reflect the selected attributes.

96% match

Dataviz 9 - Scatter plot with Menus (Interactive Colour Legend)

This interactive scatter plot displays the classic Iris dataset, letting users choose any two attributes for the x- and y-axes via React dropdown menus. The visualization uses an interactive color legend where hovering over a species name dims all other points, highlighting the selected species. Built with React and D3 v5, the chart uses `scaleLinear` and `scaleOrdinal` to map measurements and species to positions and colors, rendering all marks as SVG circles.

95% match

Dataviz 9 - Scatter plot with Menus (Polished)

This interactive scatter plot visualizes the classic Iris Dataset, displaying measurements of sepal and petal dimensions for three flower species. Dropdown menus on the left allow users to switch which quantitative attributes are plotted on the X and Y axes, with axis labels updating accordingly. Built with React and D3 v5, the visualization uses D3’s `scaleLinear` for axes, `extent` for domain calculation, and leverages SVG circles for each data point. Data is loaded asynchronously via D3’s `csv` function, with dropdowns implemented using the react-dropdown library.

Scatter Plot with Menus

This scatter plot visualizes the Iris Dataset, allowing users to explore relationships between four numeric flower measurements and species through interactive dropdown menus that control which attributes appear on the x and y axes. The visualization uses React to manage state for selected attributes, while D3.js handles the linear scales, axis generation, and data loading via `csv`. The SVG rendering displays circles colored teal, with axis labels updating dynamically based on menu selections.

Wwindwaver

Dataviz 9 - Scatter plot with Menus (Colour Legend)

This scatter plot displays the Iris dataset, showing relationships between sepal and petal measurements for three iris species. Users can select different attributes for the X and Y axes via dropdown menus, with species colors differentiated through an ordinal color legend using d3.scaleOrdinal. The visualization uses React with SVG rendering, importing axis components (AxisBottom, AxisLeft), a ColorLegend, and Marks that render circles with tooltips. Data loading relies on d3.csv from a CDN-hosted gist, with linear scales mapping the numeric measurements.

Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing users to select which flower measurements appear on the x and y axes via dropdown menus. The plot uses React dropdowns to control the axes, with d3.scaleLinear for positioning and d3.scaleOrdinal for species-based coloring. Hovering over the color legend highlights points of a selected species, using React’s useState to manage the hovered value, while SVG circles render each data point with tooltips.

CCatalina Vajiac

Scatter Plot with Menus and Colour

This scatter plot of the Iris dataset uses interactive dropdown menus to explore relationships between measurements. Users can select different attributes for the X and Y axes, and the visualization color-codes each point by species using a D3 ordinal scale. Built with React and rendered as SVG, it uses `scaleLinear` for axes, `scaleOrdinal` for colors, and custom React components for the dropdowns and marks. The plot includes axis labels and tick formatting via `format('.2s')`, with tooltips showing the x-value on hover.

NNikita Toropov

93% match