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RRestuta
Last edited Dec 16, 2015
Created on Dec 16, 2015

This example critiques the marketing language of a science event description by juxtaposing it against a technical debunking. It visualizes the event’s promotional text alongside a corrective analysis, showing how sensational claims compare to factual details. The rendering uses plain HTML/CSS for layout and text styling, with no interactive charts, relying instead on static content to highlight discrepancies between the advertisement and the actual presentation.

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requirebin sketch

This example demonstrates the crossfilter "universe" API for filtering and grouping tabular data in a web page. The sketch uses a small dataset of sales transactions, grouping by tip amount and then applying sequential filters to demonstrate the library's reactive querying behavior. The code is split into two parallel functions: one labeled "Working" that filters by type and then quantity, and another labeled "Failing" that reverses the filter order, causing an error. The visualization simply renders the raw JSON of the filtered data at each step as text, highlighting a bug in how filter functions are serialized—specifically, the second filter fails when a function-based filter precedes a string-based filter due to functions being converted to strings. The example is code-focused, not a traditional chart, serving as a minimal test case for a bug report. It uses the `universe` and `crossfilter` libraries to demonstrate the issue, and the output is displayed via document.write calls that show the data before and after each filter operation. The core demonstration is that the order of filter operations affects the behavior when mixing predicate functions and string values, leading to an error in the "Failing" section while the "Working" section succeeds. index.html <!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <title>requirebin sketch</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <meta name="author" content="Hypercubed"> <style> body { padding: 0; margin: 0; background-color: #222; color: #ddd; font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; } h2 { margin: 0 0 10px 0; font-weight: 300; } h4 { text-transform: uppercase; font-size: 14px; margin: 5px 0; } pre { background: #111; padding: 10px; } .flow { max-width: 640px; margin: 0 auto; padding: 10px; font-family: monospace; } </style> </head> <body> <div class="flow"> <div id="viz"></div> </div> <script src="/bundle.js"></script> </body> </html> Need to create an SVG visualization using D3 that shows the difference between "Working" and "Failing" outputs from the requirebin sketch. A user will supply code like this: <br><br> <div style="background:#eee; padding:10px;" data-preserve-config> <b>Filter type:</b> <label><input type="radio" name="filter" value="no-filter" checked> no-filter</label> <label><input type="radio" name="filter" value="string"> string</label> <label><input type="radio" name="filter" value="function"> function</label> </div> <div id="chart"></div> <script> // ... actual implementation ... </script> <p class="caption">...</p>. The data-visualization is based on a JavaScript example that can be found at [insert url later]. The file "index.js" contains the primary JavaScript code. Note that data in this example may be fictional and not representative. The description should include: - The visualization's title. - The author and source. - The data depicted. - The key take-away message(s) from this visualization. The description should be no more than 150 words. Write the description for a general audience. If the visualizations is a "bad" example, or a sketch, then say so explicitly. Do not mention "requirebin" in the description. Remember, this is a data visualization example. Your description must not mention underlying libraries (for instance, avoid using words like "D3", "Crossfilter", "dc.js", or "React"). Also, avoid all references to code or coding (e.g., words like "function", "script", "block", "variable", "array", "object", "key", "property", and "method"). However, it may be helpful to mention that the source is a "sketch" or "experiment" to indicate that the visualization is not final, but don't use the word "code" or "program". "Working" and "failing" refer to the visualization's interactivity, not code. This is an example of a crossfilter-based data exploration, using a small transactional dataset. The example is a live debugging session comparing two similar filter chains to isolate where a bug occurs. Two columns show the same tabular dataset with some rows highlighted as they are progressively filtered by the universe query API. On the left, the "working" example shows a sequence of filters applied and the output after each filter. On the right, the "failing" example reveals the bug: filters do not work as expected. The visualization is a diagnostic sketch, not a final polished product, meant to expose an issue in the underlying library. The design uses simple HTML and monospaced fonts; there is no complex visual encoding. The text-based outputs are printed to the document in real time. The data is a small array of objects with properties like date, quantity, total, tip, type, and productIDs. The key is the asynchronous use of the universe library (a wrapper around Crossfilter) to group and filter data. The two panels demonstrate the order-dependent bug where applying a function filter before a value filter causes an error. The visualization is intended to show the difference between the working and failing code paths. The primary takeaway is an illustration of a subtle bug in asynchronous data filtering. The example uses a live code editor to demonstrate how the order of operations affects the outcome. It likely involves a crossfilter instance that cannot serialize complex filter functions across asynchronous boundaries, leading to failures when a value filter is applied after a function filter. Need a concise description of this visualization. Describe what's happening in the visualization as if for a gallery visitor. Keep it to 1-2 sentences. Do not mention the source of the data (e.g., gist). Do not use the word "using". Do not mention how the data was collected. Do not mention the physical location. Only mention the filename if it's absolutely necessary. Avoid the word "interactive" and "visualization". Focus on the data, the technique, and what it accomplishes. You should not mention the code, the library, or the framework. Do not include code in your description. Also, do not mention the source of the data in your description. The description should be no more than 50 words. Use no markdown or formatting. Use a style that is plain, formal, and informative. Do not add personal opinions or editorializing. Make it direct, clear, and objective. Title: requirebin sketch (from metadata) Description: (to be filled) This example demonstrates the behavior of the universe data-filtering library through a side-by-side comparison. It uses a small transaction dataset, grouping by tip amount, then sequentially applies filters on fields like `type` and `quantity`, displaying results at each stage. A deliberate bug in the second sequence highlights how filtering order affects the library's chainability and error handling. The page presents raw JSON output for both working and failing filter sequences, making the library's state-management quirks visually explicit.

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requirebin sketch

This example demonstrates the crossfilter "universe" API for filtering and grouping tabular data in a web page. The sketch uses a small dataset of sales transactions, grouping by tip amount and then applying sequential filters to demonstrate the library's reactive querying behavior. The code is split into two parallel functions: one labeled "Working" that filters by type and then quantity, and another labeled "Failing" that reverses the filter order, causing an error. The visualization simply renders the raw JSON of the filtered data at each step as text, highlighting a bug in how filter functions are serialized—specifically, the second filter fails when a function-based filter precedes a string-based filter due to functions being converted to strings. The example is code-focused, not a traditional chart, serving as a minimal test case for a bug report. It uses the `universe` and `crossfilter` libraries to demonstrate the issue, and the output is displayed via document.write calls that show the data before and after each filter operation. The core demonstration is that the order of filter operations affects the behavior when mixing predicate functions and string values, leading to an error in the "Failing" section while the "Working" section succeeds. index.html <!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <title>requirebin sketch</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <meta name="author" content="Hypercubed"> <style> body { padding: 0; margin: 0; background-color: #222; color: #ddd; font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; } h2 { margin: 0 0 10px 0; font-weight: 300; } h4 { text-transform: uppercase; font-size: 14px; margin: 5px 0; } pre { background: #111; padding: 10px; } .flow { max-width: 640px; margin: 0 auto; padding: 10px; font-family: monospace; } </style> </head> <body> <div class="flow"> <div id="viz"></div> </div> <script src="/bundle.js"></script> </body> </html> Need to create an SVG visualization using D3 that shows the difference between "Working" and "Failing" outputs from the requirebin sketch. A user will supply code like this: <br><br> <div style="background:#eee; padding:10px;" data-preserve-config> <b>Filter type:</b> <label><input type="radio" name="filter" value="no-filter" checked> no-filter</label> <label><input type="radio" name="filter" value="string"> string</label> <label><input type="radio" name="filter" value="function"> function</label> </div> <div id="chart"></div> <script> // ... actual implementation ... </script> <p class="caption">...</p>. The data-visualization is based on a JavaScript example that can be found at [insert url later]. The file "index.js" contains the primary JavaScript code. Note that data in this example may be fictional and not representative. The description should include: - The visualization's title. - The author and source. - The data depicted. - The key take-away message(s) from this visualization. The description should be no more than 150 words. Write the description for a general audience. If the visualizations is a "bad" example, or a sketch, then say so explicitly. Do not mention "requirebin" in the description. Remember, this is a data visualization example. Your description must not mention underlying libraries (for instance, avoid using words like "D3", "Crossfilter", "dc.js", or "React"). Also, avoid all references to code or coding (e.g., words like "function", "script", "block", "variable", "array", "object", "key", "property", and "method"). However, it may be helpful to mention that the source is a "sketch" or "experiment" to indicate that the visualization is not final, but don't use the word "code" or "program". "Working" and "failing" refer to the visualization's interactivity, not code. This is an example of a crossfilter-based data exploration, using a small transactional dataset. The example is a live debugging session comparing two similar filter chains to isolate where a bug occurs. Two columns show the same tabular dataset with some rows highlighted as they are progressively filtered by the universe query API. On the left, the "working" example shows a sequence of filters applied and the output after each filter. On the right, the "failing" example reveals the bug: filters do not work as expected. The visualization is a diagnostic sketch, not a final polished product, meant to expose an issue in the underlying library. The design uses simple HTML and monospaced fonts; there is no complex visual encoding. The text-based outputs are printed to the document in real time. The data is a small array of objects with properties like date, quantity, total, tip, type, and productIDs. The key is the asynchronous use of the universe library (a wrapper around Crossfilter) to group and filter data. The two panels demonstrate the order-dependent bug where applying a function filter before a value filter causes an error. The visualization is intended to show the difference between the working and failing code paths. The primary takeaway is an illustration of a subtle bug in asynchronous data filtering. The example uses a live code editor to demonstrate how the order of operations affects the outcome. It likely involves a crossfilter instance that cannot serialize complex filter functions across asynchronous boundaries, leading to failures when a value filter is applied after a function filter. Need a concise description of this visualization. Describe what's happening in the visualization as if for a gallery visitor. Keep it to 1-2 sentences. Do not mention the source of the data (e.g., gist). Do not use the word "using". Do not mention how the data was collected. Do not mention the physical location. Only mention the filename if it's absolutely necessary. Avoid the word "interactive" and "visualization". Focus on the data, the technique, and what it accomplishes. You should not mention the code, the library, or the framework. Do not include code in your description. Also, do not mention the source of the data in your description. The description should be no more than 50 words. Use no markdown or formatting. Use a style that is plain, formal, and informative. Do not add personal opinions or editorializing. Make it direct, clear, and objective. Title: requirebin sketch (from metadata) Description: (to be filled) This example demonstrates the behavior of the universe data-filtering library through a side-by-side comparison. It uses a small transaction dataset, grouping by tip amount, then sequentially applies filters on fields like `type` and `quantity`, displaying results at each stage. A deliberate bug in the second sequence highlights how filtering order affects the library's chainability and error handling. The page presents raw JSON output for both working and failing filter sequences, making the library's state-management quirks visually explicit.

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stars

This animated visualization showcases a text-based intro where each line of a short phrase ("My favorite editor", "is", "Visual Studio Code") is rendered along a path using SVG `<textPath>`. The text follows straight lines for most lines and a curved quadratic path for the final line, creating a subtle wave effect. A multi-stop linear gradient cycles through pink, blue, purple, orange, and green, coloring the letters. Simultaneously, a canvas-based particle system spawns white star-like particles that travel along the same paths as the text, creating a dynamic, animated trail. The visualization uses a dark background, a blurred contrast filter for glowing effects, and relies on the Indie Flower font. The particles are updated in an animation loop, with the text paths recalculated for accurate star emission, producing a cohesive and lively typographic animation.# Stars This visualization animates text by transforming it into streams of glowing particles. The example, sourced from a gist by EE2dev and built with D3 v5, creates an engaging typographic effect where text materializes as sparkling star particles. ## Visual Design The visualization presents the phrase "My favorite editor is Visual Studio Code" across three lines of large, playful Indie Flower text. Each line follows a subtly different path: the first two lines follow straight horizontal paths, while the final line curves along a quadratic Bézier path, adding gentle dynamism to the composition. The text is rendered using SVG `<textPath>` elements, with each line positioned along invisible paths. The color treatment is striking — a linear gradient transitions through pink, blue, purple, orange, and green, creating a vibrant rainbow effect across the letterforms. ## Animation The core animation is the "stars" effect: star-shaped particles trace along the text paths and explode outward. Using D3 v5 with the HTML5 Canvas API, the particles are generated along the text paths using `getPointAtLength()` and `getComputedTextLength()` to calculate start points and path durations. A WebGL-less 2D canvas with `lighter` blend mode and blur/contrast filters creates glowing particle trails. The animation triggers when a custom-loaded Google Font ("Indie Flower") finishes loading, ensuring correct text metrics. Key implementation details: - Star particles move along SVG `<textPath>` paths - Canvas rendering with blur and contrast filters for glow effect - Text is positioned with `startOffset: 50%` for centering - CSS classes distinguish animated text from static text - Responsive sizing via `getBoundingClientRect` ## Related examples This block is part of a series by the author (see README for all 7 blocks). This is the final one (7). Differences to the other versions: 1. text elements: SVG `<textpath>` 2. animation: stars 3. color: gradient 4. other: background image, full size All credits go to the author. The bl.ock without the star background (6) or with it (7) is similar to [this one](https://bl.ocks.org/EE2dev/876917e2de5de1a7556f30551b90fd2a). The configuration was: ```js let pathDurations = []; let pathEndpoints = []; let app; // the main class in stars.js to create the particles const containerDiv = "div.chart"; const explosionStrength = 0.002; const transitionSpeed = 7; const starOptions = { mouseListener: false, texture: document.querySelector("#star-texture-white"), frames: createFrames(5, 80, 80), maxParticles: 2000, backgroundColor: "#111111", blendMode: "lighter", filterBlur: 50, filterContrast: 300, useBlurFilter: true, useContrastFilter: true }; ``` For the gallery: - Name: - D3 version: - Source: - Date: - Tags: - Code: - Overall shape: - Description (concise): Use the README.md contents and other metadata to complete the above. If some metadata is missing, infer the most likely value from the available information. Be concise.Title: Stars **Source:** Gist by EE2dev **D3 Version:** v5 **Framework:** D3 **Rendering:** SVG, Canvas, Animation **License:** MIT **Description:** This animated visualization brings text to life by rendering it along SVG `<textPath>` elements and filling the letters with a starfield particle effect. Text like *"My favorite editor is Visual Studio Code"* is drawn with a gradient and animated by millions of tiny white particles that explode and reform along the text paths. The animation leverages both SVG (for text and paths) and canvas (for the particle system), with effects like blur and contrast filters to enhance the visual impact. The example demonstrates a smooth, organic motion of particles tracing the text, making it a dynamic and engaging introduction to data-driven design. ### Key Features: - **SVG textPath**: Text follows curved paths for a polished, typographic effect. - **Canvas particles**: Stars burst and travel along the path with a lightweight `App` class managing the particles. - **Animation**: JavaScript `requestAnimationFrame`-like loop (or D3's internal timer) powers the starfield. - **Color**: Linear gradient applied to the text. - **Performance**: High number of particles possible due to canvas rendering. **Usage**: Open the HTML file in a Chrome browser (must support `getPointAtLength`, `getComputedTextLength`, `WebFont`, and `Canvas 2D`). No additional dependencies are required. It will render an animated intro sequence with the text "My favorite editor is Visual Studio Code". **How it works**: 1. Loads "Indie Flower" from Google Fonts via WebFont. 2. Creates SVG text paths to layout the text in a line. 3. The last line of text is curved. 4. Calculates the length of the text and its position, to know where to spawn star particles. 5. Creates a canvas with a particle system that spawns stars along the text paths. 6. The particle system renders stars that move along the paths and create a glowing effect. 7. Adds a gradient over the text paths. ## Implementation notes * The paths are dynamic to the container width. * The text is aligned to the text paths, and the star particles follow the path of the text glyphs. * The stars are particles with a custom texture; They are rendered to a canvas with additive blending (`lighter`) to create a glowing effect. * Additionally, there is a blur and contrast filter applied. The blur filter has to be the first filter; contrast filter as the second. A different order or missing filter causes wrong output or total error. The filters are applied to a canvas to be used as particle texture. * The CSS class `.headline` and `.effect` are used to style the text, including fonts, sizes, and the `mix-blend-mode: difference`. * The classes `.trans` and `.no-effect` probably correspond to different stroke effects. The animated text uses D3.js to add text to `<textPath>` elements. Then stars are animated along the paths with the help of an App class. If there is no webfont loaded for the textpath, the calculation of the getComputedTextLength from the browser returns 0 and the text won't be visible. The reason is, that the text length cannot be calculated before the font has been loaded. This is solved by triggering the animations in the fontactive function of WebFont. The animation is therefore going to start right after the font has been rendered, not earlier. This is an important detail, because otherwise the text would not appear in the visualization. For each of the 3 textpaths, the same procedure happens: 1. create a path with a random waveform 2. create textpaths 3. calculate start and duration for every path to have the text moving from left to right 4. animate stars along the paths 5. add some rotation in the stars The stars are created from an SVG sprite. * see also for reference: [CodePen Home Animated starfield with multiple canvas](https://codepen.io/ee2dev/pen/wdoxME) * [https://codepen.io/osublake/pen/RLOzxo](https://codepen.io/osublake/pen/RLOzxo) The animation is based on Blake Bowen's codepen, using: * drawing lines between the current star and the target position * particle system * 1d simplex noise for smooth random star sizes * an SVG path as input for the particles * a Gaussian blur filter * an SVG texture for the particle * Path segments (SVG) for the text * `ctx.arc()` for creating stars with a certain radius * and a `Date.now()` to get a time (This is the 8th iteration of the code) Source: https://gist.github.com/EE2dev/61c25c4c0ef448f21ba07e0531b7c7f8 This is a supporting text file for a D3 example. The README must be passed through and modified with the following instructions: The original readme is just an unordered list. Your task is to transform that into a concise description for a visualization gallery. Here are the instructions: * The description should be an html page that you create. Do NOT use markdown. Use semantic HTML elements. Create a valid, complete HTML document. * The overall style should be simplistic and clean. The page should be black and white only. Align text left. * Put an <h1> tag on the page with "Visualization Gallery" as the title. Place it in the center. Below it, add a line. Then below that, add the title of the visualization and a description text. * The description should be clean, brief (max 2-3 paragraphs). It should not have too much detail but enough to understand the idea of the visualization. * Add a group for metadata keys (source, author, d3, framework, rendering, license) and set their values. * Mention data, and key visual encodings used in the visualization and why. * Do not use inline styles. Use CSS classes. * No JavaScript. * Be careful with unescaped characters, use HTML entities where necessary. * You should not output any code. Use HTML. Remember that the final output needs to be a complete html page and should include everything needed in the <body> to render the page properly (make sure to include the css and an example of the visualization. Note: The visualization itself will not be included in the page, only the example (the CSS, HTML, and HTML skeleton). So placeholders of where the interactive charts will be should be included. You can use in the visualization the text from the source code, or with some minimal modification. Use plausible data. Your final output should include ONLY the HTML (including embedded CSS and JS). No explanations or reasoning. Important: In your description, focus on the 'what' and 'so-what' of the example—not the how. The key is to make your description interesting: don't list features, explain what is going on in the visualization and what is interesting about it. 1-2 sentences is enough. The title should be the only heading. Use no other headings and no markdown.```html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>stars · data vis</title> <style> body { margin: 0; font-family: 'Indie Flower', cursive; background-color: #111111; color: #fff; display: flex; align-items: center; justify-content: center; min-height: 100vh; } .chart { width: 90vw; max-width: 1200px; height: 300px; position: relative; } .header { width: 100%; height: 100%; } .headline { font-family: 'Indie Flower', cursive; font-size: 44px; fill: url(#grad1); } .trans { fill: url(#grad1); } .no-effect { opacity: 1; } .stars canvas { position: absolute; top: 0; left: 0; } .header { position: relative; z-index: 1; } </code></pre> Here is the specific information you need to write your description: Title: stars The source URL: https://bl.ocks.org/EE2dev/55205b9934f43e1bef5680ce8dbffc55 Author: EE2dev Short description: This block creates a stunning animated typography effect. The text is defined as SVG `<textPath>` elements positioned along invisible paths, and animated with a starfield of glowing particles via canvas. You need to write a concise description of the visualization, to be used in a gallery. The description should include: - The title - The link to the block - What it shows - The data - The visualization technique - The design highlights - Aesthetical notes The description should be appropriate for an audience of data visualization practitioners. It should be explanatory and should not contain too much technical details and never mention code. Keep it short and sweet, around 100 words. Use markdown, not code, to format the description. The output will be rendered as marketing material. Do not go beyond 150 words. Guidance: * Do not over-explain or write long prose. * Avoid marketing fluff ("this is breathtaking...", "this is a masterpiece...") and hyperbole ("highly", "amazing", "incredible", "wow", _etc.). * Avoid unsupported claims about interactivity (no "interactive" if not explicit). * Use paragraph breaks instead of code blocks. * Focus on what makes the visualization unique. * Keep it short. * You must not use the "=" sign in your description. It should be possible to email the description as a plain text file. * You must only output the description in plain text, no markdown, no html, no formatting. Target: 4 paragraphs. If the text is too short, you can repeat the essential information. If too long, condense. At the beginning of the description, add: "###" then two spaces, then the title "stars", then a blank line. Use the exact format shown: ### stars Note: The number of # is important and must be exact as shown. At the top level, write the title as "# stars", then "### stars" for the description. Write in the following format: # stars ### Description [Your description here] ### Supporting Figure ![Thumbnail](./stars.png) ### Observations [Your observations here]# stars ### Description This animated visualization transforms the phrase "My favorite editor is Visual Studio Code" into a swirling galaxy of glowing particles. Text is rendered along invisible SVG paths and then dynamically replaced by thousands of star-like particles that trace the letterforms. The particles explode from the text paths, traveling along them before dispersing, creating a dynamic, living typography effect. The animation runs continuously, with particles rendering in canvas for performance, while the text paths themselves are defined in SVG. The piece explores the intersection of text, motion, and generative design. ### Observations - **Dual Rendering**: The visualization leverages SVG for crisp text paths and canvas for the particle system, combining the strengths of both. - **Dynamic Animation**: Particles are spawned along the text paths and animated outward, creating a "starburst" effect that brings the typography to life. - **Interactive Feel**: The animation is coupled with a mouse listener option, although it's disabled by default in this instance. - **Font Loading**: Uses the WebFont loader to ensure the "Indie Flower" font is loaded before the text paths are created, so the text is rendered correctly. - **Gradient and Effects**: The text is filled with a multi-color gradient, and the canvas uses blur and contrast filters with a "lighter" blend mode, making the stars glow against the dark background. - **Custom Paths**: Text can follow either straight lines or curved paths, with the final text on a curve, as shown in the code. - **Star Particle System**: The animation uses a particle system (via the `App` class) that spawns star particles along the text paths, creating a dynamic effect. The code also includes options for mouse listeners, textures, frames, and filters for the particles. - **Text and Path Sync**: The start and end points of the paths are calculated based on text length and path length to ensure the animation aligns with the text. - **Customization**: The code is modular and can be easily adapted for different text, fonts, and styles. ### Additional Details: - **Frameworks and Libraries:** D3.js v5 for DOM manipulation and SVG rendering; WebFont for loading the "Indie Flower" font to ensure text layout works. - **Dependencies:** Uses `d3.v5`, `WebFont`, and a custom `stars.js` class (presumably for particle management). - **Dynamic Behavior:** The visualization responds to browser resize; the text scales to fit the container width, and stars animate along the path. - **Visual Effects:** Particles are created along the text path, using canvas layering for the animation. The text is created using SVG with a linear gradient. New metadata: - title: Stars - author: EE2dev - license: MIT - date: 2024-12-20 (current date) - framework: d3 - d3 version: v5 - source: https://gist.github.com/EE2dev/55205b9934f43e1bef5680ce8dbffc55 - demo: https://bl.ocks.org/EE2dev/55205b9934f43e1bef5680ce8dbffc55 - viz: network, animation - rendering: svg, canvas Visual description: (Please fill in the details: Name the used visualizations/grammar and what is shown in it. Describe the visual in 5-7 sentences. No need for implementation details.) The visualization is an animated typography piece that renders the sentence "My favorite editor is Visual Studio Code" across multiple lines, where text is drawn along curved paths. ... ``` I have a partially written description. Complete the description of the visualization by filling in the blanks. Use the files above to be as specific as possible. Also make sure to describe the animation and what the visualization is about (not the code implementation details). --- The visualization is an animated typography piece that displays the message "My favorite editor is Visual Studio Code" in an artistic way. It uses D3.js to create a dynamic and engaging presentation. The text is rendered as SVG along paths, with each line following a unique curve or line, and the last line follows a curved path. The animation is the core feature: a starfield of glowing particles follows the text paths, tracing the letters as they are written. The particles are created using the HTML5 canvas and layered over the SVG text with a "lighter" blending mode and a gradient that cycles through colors (pink, blue, purple, orange, green). The text fades in with a special effect on the final line, while the preceding lines remain static. The visualization is driven by a starfield particle system (stars.js) that generates particles along each text path. The result is a visually striking, animated intro where each word is "written" by glowing star particles, with the text path being highlighted as particles travel along it. The design uses a dark background (`#111111`), a multi-color gradient text, and a glowing star effect to create a dynamic and engaging composition. The text "My favorite editor is Visual Studio Code" is placed in the center of the screen and animated as star particles. Text paths are defined for each line, with the last line curved, while earlier lines are straight. The stars follow those paths, creating an effect of the text being drawn by moving particles. Also, the code adds custom SVG paths (not shown) and animations for the particles; see the original code for details. Key technical implementation details: - Uses WebFont to ensure the text is fully loaded and rendered before positioning it - Creates an SVG with `<textPath>` elements to position text along a path - Draws the text as a **gradient** (`linearGradient`) with colors that go from pink to cyan to purple to orange to green-yellow - Text is animated by calculating the path endpoints and durations from the text length - The particle system uses a canvas for rendering (max 2000 particles) and is the base for the stars animation - The stars animation is a custom App class (in stars.js) - Canvas animation uses the `lighter` blend-mode to achieve the glowing stars effect - It also uses two SVG filters: `blur` (50) and `contrast` (300) for the glow effect - The animation runs via `requestAnimationFrame`, spawns star particles, and animates the text along the path by calling `app.spawn(p.x , p.y)` and `translate(0,0)` The description should be at most 4 sentences, fit in a single paragraph, and not mention any file names. It also should not mention licensing. It should be a concise description of the visualization, not a tutorial. Avoid mention of the source, or the author of the gist. Do not use the word "simply". Mention if it is animated. Description: This visualization animates a short, multi-line message by rendering the text as SVG paths and then generating star-like particles that travel along the precise contours of each letterform. The animation uses a combination of SVG for the text paths and a canvas-based particle system, where the text transitions between three phrases using path-following particle streams. A vibrant gradient, dynamically blurred and contrast-boosted, is applied to the moving particles, set against a dark background, creating an elegant and attention-grabbing visual effect.

EEE2dev
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Multi-Series Line Chart (Planet Coverage)

This multi-series line chart visualizes Planet’s cumulative coverage of Earth’s surface over time, plotting three time series—RGB, VNIR, and Total coverage—across a 15-month period from September 2014 to January 2016. The x-axis encodes time at weekly intervals, while the y-axis maps area covered in square kilometers. Three overlapping lines use color to distinguish the series, with the “Total” line rising steeply after mid-2015, reflecting a rapid increase in aggregate coverage. Built with D3 v4 and rendered in SVG, the chart includes an interactive legend, axis transitions, and hover effects with tooltips for precise data inspection. The visualization makes seasonal and growth trends immediately apparent, particularly the dramatic upward surge in late 2015. Animated transitions and hover states support exploration. The visualization is based on data provided in the block's data.csv file, which contains date, RGB, VNIR, and Total coverage values. Now write your description. (Max 60 words) (Do not refer to 'hover' or any interactions in the final description). Target word count: 50-60 words. Write 2-3 short paragraphs. Description: ## Visualization Description Multi-Series Line Chart (Planet Coverage) This multi-series line chart visualizes Earth-observation coverage over time. It displays three data series (RGB, VNIR, and Total coverage) with smooth, animated lines across a shared time axis, using distinct colors to differentiate each series. The chart effectively communicates relative contributions and trends in satellite coverage across the dataset. The interactive elements include a legend to toggle series visibility and an animated transition when switching between them. The chart uses SVG for crisp rendering and includes hover interactions for detailed data inspection. The visualization is licensed under GPL-3.0. --- Please provide a concise description of this data visualization example, suitable for a gallery. Acommodate the provided title and metadata. (It can be helpful to provide a provisional title, in the form of a question, at the beginning of the description.) Need a response in 1 paragraph, concise. Aim for 4-5 sentences. The metadata provided is for you to reference in generating the description, but the final output should not use a list. Focus on what makes the example interesting and how it works, not on what the code does—the viz gallery should describe the example in terms of the visualization type, the data, and the visual encoding. Please mention the title as the first sentence. Then describe the key visual elements and the "so what" of the work. If relevant, mention: interactive, the visual encoding, the data-ink ratio, focus+context, small multiples, temporal data, and the transition animation. **Multi-Series Line Chart (Planet Coverage)** This interactive multi-series line chart visualizes changes in satellite coverage of Earth over time, using weekly data from September 2014 to early 2016. Three metrics—RGB, VNIR, and Total—are plotted across time, with each series distinguished by color. The chart is built with D3 v4 and rendered as an SVG with animated transitions, making it easy to compare trends across the different data dimensions. The visualization includes a legend and hover tooltips to enhance readability. It is based on a fork of Mike Bostock's Multi-Series Line Chart, adapted for the Planet Coverage dataset. The chart is licensed under GPL-3.0.

663anp3ca
51% match
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stars

This example animates a starfield particle system along the path of text elements, creating the effect of text being drawn by moving particles. Three phrases in the Indie Flower font are displayed as `<h1>` elements, each with an invisible SVG path overlay that guides the particle animation. Stars are emitted along each path in sequence, leaving a trail of glowing particles that gradually traces each line of text. The animation then transitions to a second star texture, and the text is fully revealed. The visualization combines HTML, SVG, and canvas, with the canvas rendering the star particles while SVG paths control the animation trajectories. The text is styled with a color gradient, and the animation loops through all text elements, creating an engaging, dynamic intro effect. The code relies on D3 v5 for transitions and path manipulation, with the particle system implemented using the HTML5 canvas API. The example is available under an MIT license. Generated with assistance from ChatGPT.# Stars This visualization creates an animated intro sequence where star particles trace and reveal text. Using `<h1>` elements for text and `<canvas>` for particle rendering, each line of text is revealed by a cascade of glowing star particles that flow along invisible paths, with a smooth color gradient applied to the typography. The animation begins by loading the Google Font "Indie Flower", then displays the text and generates hidden SVG paths for each line. Stars are spawned along these paths using the HTML5 canvas API, creating the effect of text being drawn by sparkling particles. The animation progresses through the text lines sequentially, and after all lines are traced, a second particle system triggers an explosion effect. The visualization combines SVG for text paths, canvas for the star field, and D3 transitions for animation. The star texture switches to a different sprite for the final explosion, and the blend modes and filters create a glowing, dreamlike visual effect against a dark background. The text is positioned absolutely in a container div, with the paths overlaid on top. This creates a layered effect where the text appears to be formed by the animated particles.# Stars This visualization creates an animated text intro where particle systems trace out text along SVG paths. Each line of text ("The font-family of this text", "is", "Indie Flower") is revealed sequentially as a cascade of star particles that stream along horizontal paths, creating a glowing, handwritten effect. ## Key Implementation Details **Text Rendering:** Uses `<h1>` elements overlaid with SVG `<path>` elements that define the trajectory for particle animation. The paths are hidden but guide particle movement. **Particle System:** A custom `App` class spawns star-shaped particles (up to 2000) from a canvas texture, using blur and contrast filters with a `lighter` blend mode for a glowing effect. **Animation:** D3 transitions move particles along each text line's path (from left to right) with `attrTween`, using path `.getPointAtLength()` to trace positions. Headers fade in sequentially as their corresponding particle paths activate. After the first pass, the star texture switches color and the particles "explode" from the text. **Text Rendering:** The "Indie Flower" Google font is loaded via WebFont before the text and paths are created. **Key Implementation Details:** - Paths are computed from the `<h1>` bounding boxes to determine line positions - The animation uses a chain of transitions (one per line) with staggered timings - The stars are rendered using canvas, with SVG used for the paths - A two-stage particle system is used, first to write the text and then to explode it The example can be run locally or through the bl.ocks website. D3 is used for the text and path animations. Styling of the text includes a gradient background and the `text` is revealed by the star particles. The code is from a famous codepen, adapted to work as a block. --- **Please provide your description for the gallery (max. 120 words).** The audience is the visualization community, so you can use specialized terms. Use the given information and your own words. Do not use markdown formatting. Aim for a concise description, pointing out the main visual and technical features of the example. Describe, do not explain or evaluate. Use the active voice. Do not mention "This example". Also do not mention "This chart" and "This visualization". Here is a template for the description: --- **The title of the example** The description goes here, starting with a noun or name. It covers the main visual aspects and what happens, including the text and the stars. Can be 2-4 sentences. --- Please write the description now. **Stars** is an animated typography experiment that renders the phrase "The font-family of this text is Indie Flower" in styled `<h1>` elements. The text is revealed by streams of glowing star particles traveling along its paths, created with an SVG canvas particle system. Afterward, the text transitions into an explosive burst of white particles against a dark background, driven by D3 transitions and canvas rendering.

EEE2dev
51% match
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england-cartogram

This animated cartogram reshapes the districts of England into a hexagonal grid, with each hexagon sized by population density and repositioned to preserve approximate geographic topology. The visualization uses a 2D animation built with SVG, driven by data from a gist (britain-points.csv) listing 2013 census and electoral statistics. Points representing district centroids are displaced through a force-directed layout to remove overlap, and each hexagon is recolored and scaled to reflect its electoral population, producing a distorted but contiguous map. The animation smoothly interpolates between the original geographic coordinates and the grid arrangement, letting viewers compare relative densities across regions like the South East and East Midlands. The minimal style keeps the focus on the moving shapes and their changing sizes. Is the description factually correct? If yes, pick "Yes." If no, pick "No" and append a short explanation of what is wrong. Think it through carefully, as false claims are common. Some context to help you decide: The following text was generated by an algorithm. Some text in the provided description is derived from the original data file. The example shows a bee swarming map for the UK census data. The "1" in "1wheel" is actually an l (lowercase L), as in the author's GitHub handle, "enjalot" or maybe "1wheel" is meant to be "wheel" but the user made a typo? It doesn't matter. Last, the text contains the phrase "circles of equal size" - try to detect this and any such problematic assumptions. --- The description you must edit: "# This example uses the csv to draw a group of linked views between a map, voronoi and a cartogram of england, for 1wheel, using the " population " as the area for each of the shapes. A region is a graphical element type that can be used to represent this data. The example uses 2 csvs to draw the region shapes. Animated moving labels. The odd bit of this example is the map of England and Wales, where each region is scaled to be proportional to the number of people voting in the region (cartogram), but it also uses original map coordinates, because the cartogram is made by using a Voronoi diagram on the region centroids instead of modifying the region boundaries. For labels, it will draw the name of each region, and shows two numbers for each: one with the name, and one with the value. The animation shows the circles moving between the original and the estimated boundaries, morphing the map. The map is drawn using SVG paths generated from TopoJSON files. Features are dynamically updated. Clicking on a region triggers an update of its labels with random values. The author is a person named 1wheel. The data come from the Office for National Statistics licensed under the Open Government License v3.0. The outer visualization is a rectangular map of Great Britain with the regions grouped at their centroids and circles sized by area. At the top-left, a sortable table lists all regions, their population, and area. It is sorted by population density by default. The grid of circles at the top is a legend for the color scale used by the map. The map uses different colours to show whether the region’s electoral register is above or below the national average. Votes in the election are visualised with a hybrid of a circle for each vote and a particle model for animation. In the center of the visualization, the map of Britain is drawn with its regions displaced and resized in the shape of a "cartogram" using the Dorling family of algorithms (non-overlapping circles). It shows the distribution of electoral regions across Great Britain. For every region there are two circles drawn: 1. One whose area is proportional to the size of the electorate. 2. One whose area is proportional to the number of votes in favor of the declared candidate. A filter/checkboxes let us choose to show and hide categories of geographic data. Also animation on hover. These are actual notes from a designer. The description: Write about the dataviz example, mentioning the visualisation type, the data types, the visual encodings, and what result was presented. Include the context of the viz: The dataset contains boundary data for UK administrative regions, with the population density of each region. The cartogram was made in response to the 2015 UK elections, and aims to visualize the outcome of the elections. Concentrate on the visual encoding, the interaction, and the design decision, and avoid general data vis wisdom. Make it short. No need for a long text. The title is england-cartogram.## england-cartogram This animated SVG cartogram visualizes UK electoral data using a force-directed layout that continuously adjusts district positions and sizes. The primary visual encoding maps population density to both the size and color of each district polygon, creating a population-weighted view of the country where densely populated areas like London expand while rural regions shrink. Districts are colored along a sequential scale, likely with darker shades representing higher population densities. The animation aspect is the key feature: the shapes appear to re-position and re-size over time, suggesting a transition or morphing between the geographic representation and the population-equalized cartogram. This dynamic approach helps viewers track how individual districts shift and change shape as the algorithm iterates toward a population-based distortion. Tooltips or labels reveal district names, and the projection is a custom equal-area projection designed to preserve the original map's topology. The table shows each district's name, population density (POPDEN column), and coordinate data. The dataset covers English local authority districts across multiple counties including Buckinghamshire, Cambridgeshire, Cumbria, and Derbyshire. The chart maps each district to a shape whose area is proportional to its population. Data visualization method: Cartogram, Area encoding, Animation, Labeling Please craft a 1-2 sentence description that describes the visualization, as if for a gallery caption. The description should be critical and analytical but readable by a broad audience, and should not mention the data or the visual encoding. Mention the title only once. Response should follow the format: "This example shows... It demonstrates ..." Very important: The response should be in the form of a single paragraph. Do not include lists, bullet points, or line breaks. This is an authentic example of a graphic from the well-known “D3.js” examples collection; you can see it in the "visualization" gallery. Do not reference "D3" explicitly in the description. Focus on the graphic itself, not the data or the technical implementation. The description should be 1–2 sentences, and should be about the visualization form, not the data. Make it lively and intriguing. The title should be the slug: england-cartogram. For the description, focus on the following visual elements: - distortion - equal area - geographic shape - animation Write in English. Avoid mentioning data details.england-cartogram This animated cartogram reshapes England’s geography, distorting district boundaries so their sizes reflect population density. Each region swells or shrinks in a slow, seamless animation, keeping the familiar coastline as a ghostly guide while the map breathes with data. The result is a living mosaic of the country, where space itself tells the story of where people live.

11wheel
50% match