Scatter Plot Iris with Menus

Scatter Plot with Menus

This interactive scatter plot visualizes the Iris Dataset, allowing users to explore relationships between four numeric flower measurements by selecting which attributes appear on the x- and y-axes via dropdown menus. The visualization uses React with SVG rendering, leveraging d3.scaleLinear for coordinate mapping, d3.extent for domain calculation, and d3.csv for data loading. Each point is drawn as a circle with a tooltip showing its x-axis value, while axis labels update dynamically to reflect the selected measurements.

TTousifAhamed

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

Scatter Plot with Menus

This interactive scatter plot displays the Iris dataset, allowing users to explore relationships between different flower measurements by selecting which attributes appear on the x and y axes via two dropdown menus. The visualization is built using React with D3.js v6, rendering SVG circles with tooltips that show precise values on hover. The code uses D3's `scaleLinear`, `extent`, and `format` functions for axis scaling and tick formatting, while the custom `AxisBottom`, `AxisLeft`, `Marks`, and `Dropdown` components demonstrate a modular approach to building interactive charts within a React framework.

CCodeDuckie99

Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing users to explore relationships between four flower measurements. Two dropdown menus independently select the attributes plotted on the x and y axes, with axes and labels updating accordingly. Built with React and D3 v5, it uses `scaleLinear`, `extent`, and `csv` for data loading and scaling. Points are rendered as SVG circles, with tooltips showing formatted values. The interface demonstrates a simple pattern for linking dropdown controls to dynamic axis updates.

CCurran Kelleher

Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing viewers to explore relationships between different flower measurements by selecting which attributes to plot on the x- and y-axes via dropdown menus. The SVG rendering uses React to create axis components and circular marks, with D3's `scaleLinear` and `extent` functions managing the data domains. Hovering over a circle reveals a tooltip with its corresponding x-value, implemented through SVG `<title>` elements.

SSai Phaltankar

Scatter Plot With Menus

This scatter plot displays the Iris dataset, allowing users to explore correlations between four numeric flower measurements. Two dropdown menus, built with React, control which attributes appear on the x and y axes, dynamically updating the scales and axis labels. The visualization uses D3 v6 to load the CSV data, calculate linear scales, render SVG axes, and draw circles for each data point. A tooltip appears on hover, showing the formatted x-axis value.

MMonish Vassantrai

Scatter Plot with Menus

This interactive scatter plot visualizes the Iris flower dataset, letting users explore relationships between measurements by selecting which attributes appear on the x- and y-axes via dropdown menus. The visualization uses React with D3 v5 to render SVG circles, with scales and axes built through d3.scaleLinear and d3.axis components. Data is loaded asynchronously from a CSV file using d3.csv, and axis labels update dynamically based on menu selections.

Ccynichole

Scatter Plot with Menus

This interactive scatter plot visualizes the Iris dataset, allowing users to explore relationships between different flower measurements via dropdown menus. The chart displays data points as circles, with the x-axis and y-axis representing selected attributes like petal length or sepal width. Built with React and D3 utilities, the visualization uses d3.scaleLinear for axis scaling, d3.extent for domain calculation, and d3.csv for data loading. Users switch attributes through React state management, triggering real-time updates to the axes and marks rendered as SVG circles with tooltips.

LLaura Johnson