Practic01 | Cars Report

Cars Report

This example displays a simple text report listing cars priced under $2,000, with each entry formatted as the year, make, model, and price. The report is generated by filtering a hardcoded JSON dataset of five used cars, then mapping each matching car through a formatting function. The code demonstrates modular JavaScript with ES6 imports and exports, using template literals for string construction and leveraging the `Array.filter` and `Array.map` methods. The resulting message is inserted into a `<pre>` element in the HTML via the Document Object Model.

AAparnaPSha

Practic02 | HTML

This example displays a simple text-based car report, listing vehicles under a specified price from an embedded JSON array. The page shows a static list and a dynamically generated report of five cars with prices below $2000, formatted as year, make, model, and cost. The code uses JavaScript’s native `JSON.parse` and array methods like `filter`, `map`, and `join` to process data, then updates the DOM via `document.getElementById().textContent`. Styling relies on plain CSS, with no D3.js functions applied in the visible implementation.

Hhimanshucse2012

Cars Report

This example displays a filtered list of cars priced under $2,000, formatted as a multi-line text report. It uses JavaScript array methods (`filter`, `map`, `join`) to process an embedded JSON dataset of car entries, extracting and formatting the year, make, model, and price into a readable string. The report is rendered to the page via `textContent` on a `<pre>` element, styled with a large Ubuntu font and a dark blue background from CSS, with ES6 module imports.

DDominika Modzelewska

Cars Report

This example displays a simple text report of car data, filtering a hardcoded JSON array to show only vehicles priced under $2000. The visualization uses D3 version 7 to parse the data, and JavaScript string formatting to display each car's year, make, model, and price. The page renders the result inside a `<pre>` element with large typography. The code demonstrates basic data manipulation and DOM text injection, relying on `JSON.parse` and standard document element selection.

MMFS-Dev

Cars Report

This visualization displays a plain-text report of cars priced under $2,000, listing each vehicle’s year, make, model, and price on separate lines. It filters an inline JSON array of car objects, then maps each entry through a `formatCar` function and joins the results with newline characters. The final message is rendered as text content inside a `<pre>` element using the DOM API `document.getElementById`. The code uses native JavaScript methods `JSON.parse`, `filter`, `map`, and `join` to process the static dataset embedded directly in the script.

KKinjal-Goyani

Cars Report

This example demonstrates a text-based report of cars filtered by price, showing a list of vehicles under $2,000. It uses JavaScript objects, arrays, and modules to parse embedded JSON data, format each car’s year, make, model, and price, and display the result in a large `<pre>` element. The code relies on standard ECMAScript features like `JSON.parse`, array filtering, and template literals, with a simulated asynchronous delay via `Promise` and `setTimeout`. No external libraries are used; the rendering is plain text output in an HTML page.

Ooxsrev

Cars Report

Ooxsrev

Cars Report

This example shows a plain-text report of five cars, listing each vehicle’s year, brand, model, and price, filtered to include only those priced under $2,000. The report is generated from an embedded JSON array parsed with `JSON.parse`, then processed through `Array.filter`, `Array.map`, and `Array.join` to produce formatted lines. The result is displayed inside a `<pre>` element by setting `textContent` via the DOM API, using a custom `formatCar` utility to assemble each line.

Yyouri7