Skip to main content
SimilarExport ZIP
100%

Cars Report

✓ Published0🌍 Public
Iidlevalor
Last edited Jul 23, 2021
Created on Jul 22, 2021
Forked from D3 Starter

This example demonstrates a simple text-based report generator that filters a list of used cars by price and formats the results. It uses static JSON data defined in the source code, containing five car objects with make, model, year, and price properties. The application filters for cars priced under $2,000, formats each entry using a custom `CarFormatter` utility, and displays the output in a large `<pre>` element. The code leverages ES6 modules and imports, along with JavaScript’s native `JSON.parse`, `filter`, and `map` methods, but does not use D3 or other visualization libraries.

AI-generated description

A demonstration of how to start using D3 version 6.

MIT Licensed

Similar vizzes

Loading thumbnail…

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
93% match
Loading thumbnail…

Cars Report

This example demonstrates a simple text-based car report generator. It filters a static JSON array of five used cars by price and formats matching entries as a readable list. The code uses native JavaScript array methods—`filter` and `map`—combined with a `formatCar` helper that leverages object destructuring and template literals. The final output is displayed in a `<pre>` element on the page, though the current script only assigns a "Hello World" message, leaving the report logic as a modular tutorial for data processing.

AAustin Krauss
93% match
Loading thumbnail…

Cars Report

This example generates a text report of used cars priced under $2,000. It filters a static JSON array of five car objects, formats each entry with its year, make, model, and price, and displays the resulting lines in a styled `<pre>` element. The code uses native JavaScript array methods, including `filter` and `map`, along with the `JSON.parse` API to load data and a template literal for string formatting.

RRod Potter
92% match
Loading thumbnail…

Cars Report

This example generates a text report of used cars priced under $2,000. It filters a static JSON array of five car objects, formats each entry with its year, make, model, and price, and displays the resulting lines in a styled `<pre>` element. The code uses native JavaScript array methods, including `filter` and `map`, along with the `JSON.parse` API to load data and a template literal for string formatting.

RRod Potter
92% match
Loading thumbnail…

Cars Report

This example demonstrates a text-based car report generated from an in-memory JSON dataset of five vehicles. It shows filtered results, listing cars priced under $2000 as formatted strings combining year, make, model, and price. The implementation uses JavaScript arrays, objects, destructuring, and template literals, with `Array.filter`, `Array.map`, and `Array.join` to transform the data. The report displays in an HTML `<pre>` element, while separate modules (`cars.js`, `formatCar.js`, `generateReport.js`, and `getCars.js`) illustrate modular code organization and a simulated asynchronous `getCars` promise.

Vvaynexie
92% match
Loading thumbnail…

Cars Report

This example demonstrates a simple text-based report of used cars, filtering a hard-coded JSON array of vehicle data to show only models priced under $2,000. The page renders a formatted list directly into a `<pre>` element using JavaScript’s native array methods `filter`, `map`, and `join`, along with a custom `formatCar` function that composes each line. It utilizes ES6 modules (`import`/`export`) to organize the formatting logic, data parsing via `JSON.parse`, and DOM manipulation through `document.getElementById`. No external visualization libraries are used; the output is plain text, not a chart.

Bbenoitgabrielleger
92% match
Loading thumbnail…

cars reports

This example demonstrates a simple text-based report of used car listings, filtering a small inline dataset by price and formatting each entry into a readable line. The code uses JavaScript modules (`cars.js`, `formatCar.js`, `generateReport.js`) to parse JSON with `JSON.parse`, filter the array, map cars into formatted strings, and join them with newlines. The generated report is displayed in a `<pre>` element via `document.getElementById` and `textContent`, showing only cars priced below 3000 dollars.

Nnightjean7
92% match
Loading thumbnail…

Cars Report

This example demonstrates a plain-text report generator that filters a small inline dataset of cars by price and formats the results into a readable list. The interface is a single `<pre>` element with large styled text, populated by writing the generated report’s string content into the DOM via `document.getElementById().textContent`. The code uses ES6 modules to separate data parsing with `JSON.parse`, a `formatCar` helper for string templating, and a `generateReport` function that chains `filter` and `map` before joining lines. No external libraries are used, relying only on core JavaScript and HTML.

WWMLek
92% match