LeetCode 2883: Drop Missing Data Solution

Problem Explanation

Explanation

To solve this problem, we need to iterate through the DataFrame and remove rows where the name column has missing values (e.g., None in Python). We can achieve this by checking each row and only keeping the rows where the name column is not missing.

Start by iterating through each row in the DataFrame.
Check if the name column in the current row is not missing.
If the name column is not missing, add the row to the result DataFrame.
Return the resulting DataFrame without the rows containing missing values in the name column.

Time Complexity

The time complexity of this solution is O(n), where n is the number of rows in the DataFrame.

Space Complexity

The space complexity of this solution is O(n) since we need to store the resulting DataFrame.

Solution Code

import java.util.ArrayList;
import java.util.List;

class Solution {
    public List<List<Object>> dropMissingData(List<List<Object>> data) {
        List<List<Object>> result = new ArrayList<>();
        
        for (List<Object> row : data) {
            if (row.get(1) != null) {
                result.add(row);
            }
        }
        
        return result;
    }
}

Frequently Asked Questions

How to solve LeetCode 2883 (Drop Missing Data)?

This page provides optimized solutions for LeetCode problem 2883 (Drop Missing Data) in Java, C++, and Python, along with a detailed explanation and an interactive code editor to test your code.

What is the time complexity of LeetCode 2883 (Drop Missing Data)?

The time complexity for LeetCode 2883 (Drop Missing Data) varies by solution. Check the detailed explanation section for specific complexities in Java, C++, and Python implementations.

Can I run code for LeetCode 2883 on DevExCode?

Yes, DevExCode provides an interactive code editor where you can write, test, and run your code for LeetCode 2883 in Java, C++, or Python.

2883. Drop Missing Data