ICE-5: The Shapes of Data

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This example loads a CSV dataset from a GitHub gist and presents a simple summary of its structure, including file size, row count, and column count, within a styled card layout. It then renders a minimal SVG visualization of bars representing the first ten rows of the data, using D3’s `csvParse` and basic selection/join methods (`selectAll`, `join`, `attr`). The page is built with plain HTML and JavaScript, relying on the D3 v7 library for data parsing and SVG manipulation, while the layout and styling are handled with inline CSS.

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This example displays a concise summary of a bird migration CSV dataset, showing file size, row count, and column count. A simple SVG path with a circle marker visually represents a migration route. The page loads data from a GitHub gist using `fetch` and parses it with `d3.csvParse`, while `d3.v7` is loaded via CDN. Styling relies on plain HTML and CSS, with no interactive elements beyond the static display.

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This example presents a small dashboard that loads a CSV dataset, displays summary statistics (approximate file size, row count, and column count), and renders a simple bar-chart-like SVG picture. The page uses D3’s `csvParse` to read the data from a GitHub Gist, then updates the HTML stat cards and draws rectangles with `d3.select`’s `.join` API. The SVG bars are based purely on row index, not on data values, making the visualization a generic shape demo. The code is plain JavaScript within an HTML file, using D3 v7.

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This example loads a CSV dataset from a GitHub gist and summarizes its file size, row count, and column count on a dashboard card. It then renders a simple SVG visualization of ten horizontal bars with row labels, using D3 v7’s `d3.csvParse` and selection joins via `join("rect")` and `join("text")`. The bars are based on row index rather than data values, acting as a generic placeholder. The code runs in a plain HTML page with inline CSS and JavaScript, using `fetch` to retrieve the data.

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This example summarizes a study-focus dataset by fetching a CSV from a GitHub gist and displaying the file size, row count, and column count as plain text using React state and `d3.csvParse`. Below the summary, a static SVG renders a lightblue circle and a lightgreen rectangle, both with black outlines, to demonstrate basic SVG markup within a React component. The visualization uses `fetch` to load the data and `useEffect` to parse it, with styling handled by external CSS that centers the content in a bordered card.

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This example fetches a CSV dataset about study focus logs and displays summary statistics for file size, row count, and column count. It renders a simple SVG visualization with horizontal bars representing the first ten rows of data. The code uses D3 v7's `csvParse` and `selectAll`/`join` methods, along with the Fetch API, to load and display the dataset. The visualization appears inside a pink card with a dashed-border SVG container.

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This example summarizes a study focus dataset by displaying its file size, row count, and column count in a styled React interface. The app fetches a remote CSV file from a GitHub gist and uses D3’s `csvParse` method to parse the text, then presents the metrics alongside a simple SVG containing a circle and rectangle. The visualization relies on React’s state management (`useState`) and `fetch` API, with D3 v7 loaded via script, and renders text and shapes using standard SVG markup.

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This example demonstrates how to load and summarize a CSV dataset using D3.js within a React application. It displays file size, row count, and column names by fetching the raw CSV text and parsing it with `d3.csvParse`. The page also renders basic SVG shapes—a circle, rectangle, line, and text—to illustrate static SVG output. The React component uses the `useRef` and `useEffect` hooks alongside `d3.select` to update the DOM.