Cars Report

Cars Report

This example displays the make of the first car in a hardcoded JSON array of five vehicles, showing a simple text report. The page renders the message "Honda" in large, centered text within an HTML `<pre>` element. The visualization uses JavaScript to import the car data from a separate `cars.js` module, parse it as JSON, and assign the first record's make to the message element via the Document Object Model’s `getElementById` method. It demonstrates basic data handling and page updating without any charting library.

NNatália

EEmiliano de Jesús Gonzalez Rodriguez

Cars Report

A simple visualization displays the make of the first car in a hardcoded JSON dataset as plain text. The page renders the word "Honda" inside two large `<pre>` elements using vanilla JavaScript. The code defines and parses an embedded car dataset with native `JSON.parse` before accessing `cars[0].make` and assigning it to `textContent` for display. The example relies on no external libraries, using only standard DOM methods to update the HTML.

Cars Report

This example depicts a minimal cars report, displaying the make of the first vehicle from a hardcoded JSON array. A pre-formatted element renders the text "Honda" at a large font size. The implementation imports the parsed car data from a separate `cars.js` module, then uses the standard Document Object Model (DOM) API—specifically `document.getElementById` and `textContent`—to update the page. The visualization relies on D3 version 6 for data handling, though the core output is a simple text readout of the data.

AAndrew

Cars report

This example displays a one-word report, “Honda,” pulled from a hardcoded JSON dataset of five cars stored in `cars.js`. The page renders the first car’s make in large, styled text on a dark blue background. The code imports the parsed `cars` array and uses `document.getElementById` to set the text content of a `<pre>` element. Styling relies on CSS with a Google Fonts import, while D3 v5 is loaded via CDN but not used for visualization.

AAsperge-Atomique

Cars Report

This example displays the make of the first car in a hardcoded dataset, rendering the word "Honda" prominently on a dark, styled page. It loads a JSON array of car records via JavaScript’s `JSON.parse` and uses a simple DOM `textContent` assignment to update a `<pre>` element. The page’s visual design relies on an imported Google font (Ubuntu) and CSS for large, centered text. No interactive or charting library is used, focusing instead on minimal data extraction and static presentation.

RRod Potter

Cars report

This example displays the make of the first car in a small static dataset. It parses an embedded JSON string using `JSON.parse`, then renders the text `Honda` into an HTML `<pre>` element via the Document Object Model’s `textContent`. The page style uses an imported Google Font and CSS for a high-contrast presentation.

VVarun Khanna

Cars Report

This example displays the make of the first car in a hard-coded five-record dataset. The report presents the text “Honda” in a large <pre> element on a blank page. It imports the parsed `cars` array from a separate module, accesses its first object, and writes the `make` value to the DOM via `textContent`. The visualization relies on plain JavaScript and the `JSON.parse` API, with no external charting libraries.

Jjoalvarenga53

Cars Report

This example displays a single car make, “Honda,” from a small JSON dataset of five used cars, rendered as oversized text on a dark, centered page. The visualization uses a plain HTML `<pre>` element and JavaScript to parse the embedded `carsJSON` string, then writes the first record’s `make` property into the page via `document.getElementById`. Styling relies on CSS with the Ubuntu font, while data imports come from the `cars` module and rendering is handled by the browser’s DOM API, with no external visualization libraries.

RRod Potter