Sample problems

Sample problems: objects and arrays

This example presents five JavaScript practice problems for manipulating data structures, using the D3 library (v4) within an HTML page. It demonstrates techniques like iterating through arrays with `forEach`, matching objects to copy properties, finding intersecting array elements with `includes`, and sorting an array of state objects by population using the `sort` method and `d3.ascending`. It also shows logging results to the console and using `d3.range` to create a numeric sequence for a modulus-based filtering exercise, though the final solution is left incomplete.

93% match

Sample problems 2: objects and arrays

This example presents four JavaScript practice problems focused on array and object manipulation, with output shown only in the browser’s developer console. It demonstrates techniques such as iterating with `forEach()`, filtering array elements using `includes()` for substring matching and set difference, sorting an array of objects by a string property with a custom comparator, and checking numeric properties with the modulo operator. The code uses the D3.js v4 library for loading, but the exercises themselves rely on core JavaScript APIs, including `console.log()`, and include sample datasets of U.S. states with their regions and populations.

Sample problems: objects and arrays

This example presents five JavaScript practice problems embedded in an HTML page, focusing on array and object manipulation rather than visual output. The exercises involve merging state names with their two-letter IDs, finding common elements between arrays, sorting state objects by population, and using the modulus operator to filter numbers. Built with D3 v4, the code uses `d3.range` to generate a sequence of integers, though all results are meant to be viewed in the browser’s developer console, as no SVG or graphical rendering is included.

Sample problems: objects and arrays

Sample problems: objects and arrays

This example presents five JavaScript practice problems focused on manipulating objects and arrays, with output intended for the browser’s developer console rather than SVG or other visual rendering. The code demonstrates basic data operations such as merging object properties by matching names, finding common elements between arrays using nested loops and the `includes` method, sorting an array of state objects by population, and using a loop with the modulus operator to filter numbers. It relies on vanilla JavaScript for most tasks and uses the D3 v4 library’s `d3.range` function to generate a sequence of integers from 1 to 10.

Sample problems: objects and arrays

This example presents five JavaScript practice problems that manipulate arrays and objects, with output visible only in the developer console. The problems demonstrate tasks such as merging object properties between arrays, finding common items, sorting objects by a numeric property, and filtering numbers using the modulus operator. The code uses D3 v4’s `d3.range` to generate an array of integers, while array methods like `forEach` and `sort` handle the core logic. No SVG or visual rendering is involved, as the focus is purely on algorithmic thinking with plain data structures.

90% match

Sample problems 2: objects and arrays

This example demonstrates four JavaScript practice problems for working with objects and arrays. The code uses a hardcoded array of state objects and a pair of simple arrays to test filtering, comparison, and sorting logic. It relies on the base JavaScript array methods `forEach`, `includes`, and `sort`, along with the d3 `ascending` comparator. All output is printed to the browser’s developer console using `console.log`, as the visualization itself displays only a static heading and instructions.

88% match

Sample problems 3: objects and arrays

This example presents four JavaScript practice problems centered on manipulating arrays of objects, specifically U.S. state data with name, ID, and population fields. The page instructs users to solve the problems in the browser console, as no SVG or visual output is generated. The first problem demonstrates using `d3.mean()` with an accessor function to calculate the average population, while subsequent problems require computing the same statistic manually without D3’s helper. The code relies on the D3 v4 library for the mean calculation and includes sample data hardcoded in the script.