Introduction

In this blog post, we will explore how to solve the LeetCode problem "1996" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

You are playing a game that contains multiple characters, and each of the characters has two main properties: attack and defense. You are given a 2D integer array properties where properties[i] = [attacki, defensei] represents the properties of the ith character in the game. A character is said to be weak if any other character has both attack and defense levels strictly greater than this character's attack and defense levels. More formally, a character i is said to be weak if there exists another character j where attackj > attacki and defensej > defensei. Return the number of weak characters. Example 1: Input: properties = [[5,5],[6,3],[3,6]] Output: 0 Explanation: No character has strictly greater attack and defense than the other. Example 2: Input: properties = [[2,2],[3,3]] Output: 1 Explanation: The first character is weak because the second character has a strictly greater attack and defense. Example 3: Input: properties = [[1,5],[10,4],[4,3]] Output: 1 Explanation: The third character is weak because the second character has a strictly greater attack and defense. Constraints: 2 <= properties.length <= 105 properties[i].length == 2 1 <= attacki, defensei <= 105

Explanation

Here's a breakdown of the approach, complexity, and the Python code:

• High-Level Approach:

  • Sort the characters based on attack in descending order and in ascending order of defense for characters having same attack. This ordering ensures that when iterating, we only need to consider characters encountered so far to determine if a character is weak.
  • Iterate through the sorted characters, maintaining the maximum defense seen so far. A character is weak if its defense is less than the maximum defense seen so far.

• Complexity:

  • Runtime Complexity: O(N log N) due to sorting.
  • Storage Complexity: O(1) - excluding space used for sorting.

Code

    def numberOfWeakCharacters(properties):
    """
    Calculates the number of weak characters in a list of characters with attack and defense properties.

    Args:
        properties: A list of lists, where each inner list represents a character's [attack, defense].

    Returns:
        The number of weak characters.
    """
    properties.sort(key=lambda x: (-x[0], x[1]))  # Sort by attack descending, then defense ascending

    weak_count = 0
    max_defense = 0

    for attack, defense in properties:
        if defense < max_defense:
            weak_count += 1
        else:
            max_defense = defense

    return weak_count