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@A1L9E9X9·16 public vizzes

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Temperature in San Francisco Line Chart

This line chart visualizes one week of temperature data in San Francisco, sourced from Data Canvas - Sense Your City. The chart maps timestamps to the x-axis and temperature in degrees Celsius to the y-axis, with a smooth curved line connecting the data points. The visualization includes labeled axes, grid lines, and a title. The code uses D3 v5 with `scaleTime`, `scaleLinear`, `axisBottom`, `axisLeft`, and `line` with `curveBasis` to generate the SVG rendering. Data is loaded via `csv` and processed by converting temperature to numbers and timestamps to `Date` objects before rendering.

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Responding to Resize

This example demonstrates how an SVG visualization can respond to browser resizing by recalculating its dimensions. A chart container fills the entire page using CSS, and a redraw function extracts the container’s clientWidth and clientHeight to update the SVG’s width and height attributes. Two semi-transparent green lines form an X across the viewport, with coordinates recomputed on each resize. The code uses D3 v5 with `selectAll` and data joins to merge entering and existing line elements, and listens for `window` resize events to trigger the redraw.

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Let's make a face with D3.js!

A yellow smiley face with moving eyebrows demonstrates D3.js v5 DOM manipulation. The code builds the face using SVG shapes, appending a circle for the head, two circles for eyes, rectangular eyebrows, and a path generated with the `arc()` function for the mouth. The eyebrows animate upward and downward over two seconds using chained `transition()` and `attr()` methods. This example highlights fundamental D3 selection, attribute setting, and transition functionality.

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Shapes and Colors with SVG and CSS

This example demonstrates how SVG shapes can be colored and styled through direct attributes and CSS rules. It shows circles, rectangles, and a polygonal path, with colors applied both explicitly (like a red circle and a green rectangle) and through inherited group properties. The SVG markup uses transform groups to scale and translate elements, while a separate stylesheet defines stroke properties for the path, including stroke-linejoin and stroke-linecap. The rendering is entirely SVG, with structure and styling separated between the HTML and CSS files.

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Temperature in San Francisco Line Chart

This line chart visualizes temperature over a week in San Francisco, with time on the x-axis and temperature on the y-axis. It uses d3.csv to load the data, d3.scaleTime and d3.scaleLinear for scales, and d3.line with d3.curveBasis to draw the smoothed path. Axes are rendered with d3.axisBottom and d3.axisLeft, removing domain lines and adding custom labels via appended text elements. The SVG rendering includes a title, gridlines via tickSize, and a maroon stroke for the line.

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Temperature in San Francisco Line Chart

This visualization displays a week of temperature readings in San Francisco as a smooth line chart. The code uses d3.scaleTime and d3.scaleLinear to map time and temperature data, with axes labeled "Time" and "Temperature." The line is generated with d3.line and curveBasis for smoothing, rendered as an SVG path with a maroon stroke. Data is loaded via d3.csv from a remote dataset, and the chart includes a title "A Week in San Francisco" with gridlines and axis labels styled via CSS.

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Temperature in San Francisco Line Chart

This line chart displays one week of temperature data in San Francisco, sourced from Data Canvas - Sense Your City, with time on the x-axis and degrees Celsius on the y-axis. The visualization uses D3 v5 with SVG rendering, employing `scaleTime` and `scaleLinear` for axes, `axisLeft` and `axisBottom` for tick marks, and `line` with `curveBasis` to create a smooth path. Grid lines and axis labels are styled via CSS, and the data is loaded asynchronously from a CSV file using `d3.csv`.

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Cars Report

This gallery example displays a minimal car report interface, demonstrating dynamic script loading through JavaScript. The page contains an empty body with a script that asynchronously injects an external JavaScript file using the `loadScript` function, which creates a `script` element and appends it to the document head. The example highlights basic SVG and HTML manipulations, though the rendered content relies entirely on the external `example.js` file, which currently contains only a commented-out alert. The CSS only resets body margins and hides overflow, leaving the visual outcome dependent on the loaded script’s behavior.

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Cars Report

This example displays a list of used cars with their year, make, model, and price, filtered to show only those priced under $2,000. The page initially shows “Loading...” for two seconds, simulating a delayed data fetch via a Promise and `setTimeout`. It then computes the report using `Array.filter`, `Array.map`, and `Array.join`, formatting each entry as a text string. Automatically generated from a JavaScript object parsed from embedded JSON, the visualization is built with React and plain DOM manipulation using `document.getElementById`.

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Cars Report

This example displays a text report of used cars from a hardcoded JSON array, listing each vehicle's year, make, model, and price. The React-based app simulates an asynchronous data fetch with a two-second delay, then filters the list to only show cars priced under $2,000. The visible output is plain text rendered inside an HTML `<pre>` element, with the initial "Loading..." state replaced once the promise resolves. The code demonstrates basic JavaScript promise handling and array filtering without any external visualization libraries.

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Cars Report

This example demonstrates loading a set of car records from an embedded JSON array, filtering those priced under $2,000, and displaying a formatted text report. It relies on JavaScript ES modules, with `getCars.js` returning a Promise that resolves after a simulated two-second delay, while `generateReport.js` uses `Array.filter`, `Array.map`, and `Array.join` to transform the data. The rendered output appears in an HTML `<pre>` element, initially showing a "Loading..." message before the final list is inserted.

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Cars Report

This example shows a text-based report of cars filtered by price, displaying each car’s year, make, model, and cost. It begins with a loading message, then uses asynchronous data retrieval via a Promise returned by getCars, which parses embedded JSON. The generateReport function filters cars under a specified price and formats each entry using formatCar. The page uses a plain HTML <pre> element and updates its textContent through DOM manipulation.

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Cars Report

This example demonstrates how to fetch and display a text report of used cars priced under $2,000. The page initially shows “Loading...” while a promise-based `getCars()` function simulates a two-second delay before resolving with a hardcoded JSON array. The `generateReport` function filters that array and applies `formatCar` to produce a formatted list with year, make, model, and price. It uses JavaScript ES6 modules, destructuring, `JSON.parse`, and `Promise` with `setTimeout` to mimic asynchronous data retrieval.

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Cars Report

This example demonstrates a simple text-based report of used cars, filtering a hardcoded list by price and displaying formatted results in a web page. It shows how JavaScript modules, arrays, and object destructuring work together to parse JSON data and generate a string output. The code uses `fetch`-style asynchronous loading via a custom Promise (`getCars`), array methods `filter` and `map`, and ES module exports/imports. The report is rendered into a `<pre>` element with no external libraries, relying on pure JavaScript and a Rollup-generated bundle.

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Cars Report

This example demonstrates loading a set of car records from an embedded JSON array, filtering those priced under $2,000, and displaying a formatted text report. It relies on JavaScript ES modules, with `getCars.js` returning a Promise that resolves after a simulated two-second delay, while `generateReport.js` uses `Array.filter`, `Array.map`, and `Array.join` to transform the data. The rendered output appears in an HTML `<pre>` element, initially showing a "Loading..." message before the final list is inserted.

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Cars Report

This example shows a text-based report of cars filtered by price, displaying each car’s year, make, model, and cost. It begins with a loading message, then uses asynchronous data retrieval via a Promise returned by getCars, which parses embedded JSON. The generateReport function filters cars under a specified price and formats each entry using formatCar. The page uses a plain HTML <pre> element and updates its textContent through DOM manipulation.