Interactive Color Legend on Graduate Admission dataset

Scatter Plot with Menus on Graduate Admission Dataset

This interactive scatter plot explores the Graduate Admission dataset, allowing users to compare any two attributes by selecting them from dropdown menus for the X and Y axes. The plot displays each admission record as a circle, with a tooltip showing the X-axis value. React manages the interactive state, while D3 v5 handles the linear scales and SVG rendering. The visualization is built with a React component structure, using D3's `scaleLinear` for axis scaling and `csv` for data loading.

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Graduate Admission

This scatter plot examines graduate school admission factors, plotting CGPA against GRE Score for individual applicants. Point color encodes University Rating, while point size reflects Research output, revealing potential correlations between academic metrics and university prestige. The visualization is built using the Vega-Lite API, with data fetched from a GitHub-hosted CSV via d3.csv. Custom configuration in config.js adjusts axis styling and tooltip fonts, and the chart auto-fits to the browser window dimensions.

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Interactive Color Legend with Menus

This interactive scatter plot visualizes the College Dataset, showing relationships between academic attributes such as applications, enrollment, and faculty credentials. Users select X and Y axes via dropdown menus, while a color legend distinguishes public from private institutions. Hovering over legend items highlights matching points and fades others using React state management. The visualization uses D3 scales and SVG rendering, with React components for axes, marks, and interactive controls, demonstrating a React-D3 integration pattern for exploratory data analysis.

Interactive Color Legend with Menus

This interactive scatter plot explores the College Dataset, showing relationships between academic metrics like enrollment, admissions, and faculty qualifications. Users dynamically select which attributes appear on the x and y axes using React dropdown menus, while the color legend distinguishes public versus private institutions. Built with React and D3 v5, the visualization uses `scaleLinear` and `scaleOrdinal` for positioning and coloring, rendering as SVG. Hovering over legend items filters the displayed points and fades non-matching data, providing an interactive way to compare institutional characteristics.

Interactive Color Legend with Menus

This interactive scatter plot visualizes the College Dataset, showing relationships between attributes like enrollment numbers and faculty PhD percentages, with points colored by public/private status. Users select X and Y axes from dropdown menus built with ReactDropdown, while hovering over the color legend highlights matching points and fades others. The visualization uses React for component composition, D3 scales for positioning and color mapping, and renders data as SVG circles with axis components from D3.

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Interactive Color Legend with Menus

This interactive scatter plot explores the relationship between two user-selected attributes from the College Dataset, showing each institution as a circle colored by its public or private status. Two dropdown menus, built with ReactDropdown, control which numeric columns (such as Enroll, PhD, or Outstate) appear on the x and y axes. A custom color legend, implemented as an SVG component, highlights points of one category on hover while fading the others, using d3.scaleOrdinal for color mapping and d3.scaleLinear for axis scales. All marks and axes render as React components with d3 scales, with data loaded asynchronously via d3.csv.

Interactive Color Legend with Menus

An interactive scatter plot of the College Dataset explores relationships among academic metrics. Dropdown menus switch the X and Y attributes, while hovering over the ordinal color legend highlights points from either public or private institutions by fading non-matching circles. The React and D3 v5 implementation uses `scaleLinear` for axes, `scaleOrdinal` for colors, and React state to manage selections and hover interactions, rendering the SVG marks with reusable axis and legend components.

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