Sample problems 3: objects and arrays

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.

96% match

Sample problems 3: objects and arrays

This example presents four JavaScript practice problems for manipulating arrays of objects, specifically a list of U.S. states with their names, IDs, and populations. The code demonstrates calculating the mean population using both D3’s `d3.mean()` aggregate function and manual iteration with `forEach` and a `while` loop. The visualization itself renders no graphics; instead, it instructs users to open the developer console to view computed results. The page uses D3 v4 and is forked from a series of related blocks by scresawn.

95% match

Sample problems 3: objects and arrays

This example presents four JavaScript practice problems focused on objects and arrays, using a small dataset of U.S. states with their populations. It shows how to compute the average population both with and without D3’s `d3.mean()` method, demonstrating iterative techniques like `forEach` and `while` loops. The code relies on D3 v4 for the `d3.mean()` call, while the rest uses vanilla JavaScript. No SVG or visual output is generated; instead, results are printed to the browser’s developer console, making the example a code-based exercise rather than a graphical visualization.

94% match

Sample problems 3: objects and arrays

This example presents four JavaScript practice problems for manipulating arrays of objects, using U.S. state population data. The page shows a static text heading but the core activity occurs in the developer console, where the user observes output. The code demonstrates computing an average both with the D3.js `d3.mean()` function and manually using `forEach` and `while` loops. The dataset is an in-code array of state objects containing name, ID, and population fields, with no SVG or visual rendering involved.

94% match

Sample problems 3: objects and arrays

This example presents two JavaScript practice problems for computing the mean population of a small array of U.S. states. The code uses D3 v4’s `d3.mean()` for the first solution, then demonstrates two alternative manual approaches—using `forEach` and a `while` loop—to calculate the same average. All results are printed to the browser’s developer console, as the page includes no SVG or visual output. The data is a hardcoded array of state objects containing name, ID, and population values.

94% match

Sample problems 3: objects and arrays

This example presents four JavaScript practice problems embedded in an HTML page, focusing on array and object manipulation with population data for four U.S. states. The first problem uses `d3.mean()` to calculate and log the average population, demonstrating D3 v4’s array statistics method. The second problem attempts the same calculation manually with a `while` loop, but contains an intentional infinite loop and redundant addition. No SVG or visual output is rendered; results appear only in the browser’s developer console. The code relies on the D3 v4 library’s `mean()` function and standard JavaScript array traversal.

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.

86% match

Sample problems 2: objects and arrays

This example presents four JavaScript practice problems that operate on arrays and objects, demonstrating data filtering, comparison, and sorting without any visual rendering. The code uses plain JavaScript methods such as `forEach`, `includes`, and `sort` to manipulate datasets like state objects with names, locations, and populations, and arrays of characters and numbers. It logs results to the browser’s developer console, including filtering states by location substrings, finding items unique to one array, sorting states alphabetically, and identifying even population values. The visualization relies entirely on the console output rather than D3 or SVG, though it is built within a D3 v4 environment.