Cars report

Cars report

100% match

Cars report

This example displays the make of the first car in a hardcoded JSON array as large text on a webpage. The code imports the car data from a `cars.js` module, parses it with `JSON.parse`, and uses vanilla JavaScript to set the `textContent` of a `<pre>` element. Styling applies a custom Ubuntu font and a dark blue background via CSS, with no external visualization libraries involved.

93% match

Cars report

This example displays the make of the first car in a hardcoded JSON array. It uses a simple DOM API, `document.getElementById`, to insert the text "honda" into a preformatted element. The data is parsed with `JSON.parse` and styled with custom CSS, including a Google Fonts import, on a dark background.

92% match

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

92% match

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

The Cars Report displays the make of the first car in a small inline dataset, rendered as large text on a dark blue page. The example uses a plain JavaScript array of car objects defined in `cars.js` and parsed with `JSON.pars` (a typo for `JSON.parse`). Index.js accesses `cars[0].make` and updates the DOM via `document.getElementById("message-element").textContent`. Styling relies on the Ubuntu font from Google Fonts and a CSS background color, with no external visualization libraries.

Sselina-rudolph

Cars report

This example demonstrates how to display a car make from a static JSON dataset. The visualization imports a small array of car objects, accesses the first entry’s make property, and renders that text into a large HTML pre element. The page uses a custom Google Font and a dark blue background via CSS. The code relies on the cars module’s exported parsed JSON and manipulates the DOM with vanilla JavaScript through document.getElementById.

Cars Report

This example displays the make of the first car in a hardcoded JSON dataset, rendering it as large, styled text on a dark background. It loads an array of five car objects from `cars.js`, parses the JSON, and uses vanilla JavaScript to set the text content of a `<pre>` element via `document.getElementById`. The page’s styling comes from CSS, including the Ubuntu font, a navy background, and centered, 12em font size. No external visualization libraries are used; the focus is on a minimal DOM update.

Iimregan