Problems faced

Sample problems

This example presents five JavaScript practice problems focused on array and object manipulation. The code, built with D3 v4, demonstrates iterating through arrays to match objects, finding common elements, sorting an array by population, selecting a single object, and using a modulus operator within a loop. Since the problems do not involve SVG manipulation, users must open the developer console to see the output of each solution. The data are static, embedded within the `index.html` file.

LLaurynKW

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.

LLaurynKW

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 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.

Sample problems 3: objects and arrays

This example presents four JavaScript practice problems centered on arrays of objects, specifically U.S. state data with names, abbreviations, and populations. The visualization itself is minimal—a static HTML page with a heading and instructions—while the actual work happens in the console. The first problem demonstrates using `d3.mean()` with an accessor function to calculate the average population, while the second manually iterates through the array with `forEach` to sum populations and compute the mean. The code relies on the D3 v4 library and includes no SVG manipulation, focusing purely on data processing and console output.

HHeywhoyou22

61% match

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.

61% 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.