Leetcode #531: Lonely Pixel I
In this guide, we solve Leetcode #531 Lonely Pixel I in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Given an m x n picture consisting of black 'B' and white 'W' pixels, return the number of black lonely pixels. A black lonely pixel is a character 'B' that located at a specific position where the same row and same column don't have any other black pixels.
Quick Facts
- Difficulty: Medium
- Premium: Yes
- Tags: Array, Hash Table, Matrix
Intuition
Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.
By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.
Approach
Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.
This keeps the solution linear while remaining easy to explain in an interview setting.
Steps:
- Initialize a hash map for seen items or counts.
- Iterate through the input, querying/updating the map.
- Return the first valid result or the final computed value.
Example
Input: picture = [["W","W","B"],["W","B","W"],["B","W","W"]]
Output: 3
Explanation: All the three 'B's are black lonely pixels.
Python Solution
class Solution:
def findLonelyPixel(self, picture: List[List[str]]) -> int:
rows = [0] * len(picture)
cols = [0] * len(picture[0])
for i, row in enumerate(picture):
for j, x in enumerate(row):
if x == "B":
rows[i] += 1
cols[j] += 1
ans = 0
for i, row in enumerate(picture):
for j, x in enumerate(row):
if x == "B" and rows[i] == 1 and cols[j] == 1:
ans += 1
return ans
Complexity
The time complexity is , and the space complexity is , where and are the number of rows and columns in the matrix respectively. The space complexity is , where and are the number of rows and columns in the matrix respectively.
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.