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Leetcode 3443. Maximum Manhattan Distance After K Changes | Greedy Path Optimization in Python
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In this video,
We solve Leetcode 3443: “Maximum Manhattan Distance After K Changes” using a Greedy + Manhattan Distance approach in Python.
You are given a string representing directions (N, S, E, W) and you're allowed to change up to K moves. The goal is to find the maximum Manhattan distance you can achieve after applying up to K changes.
We walk through:
✅ Step-by-step explanation
✅ Dry run with example
✅ Greedy insight
✅ Clean Python implementation
If you're preparing for coding interviews or aiming for Leetcode mastery, this problem enhances your spatial reasoning and greedy logic understanding.
📌 Don't forget to Like, Share, and Subscribe for more Leetcode in Python solutions!
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We solve Leetcode 3443: “Maximum Manhattan Distance After K Changes” using a Greedy + Manhattan Distance approach in Python.
You are given a string representing directions (N, S, E, W) and you're allowed to change up to K moves. The goal is to find the maximum Manhattan distance you can achieve after applying up to K changes.
We walk through:
✅ Step-by-step explanation
✅ Dry run with example
✅ Greedy insight
✅ Clean Python implementation
If you're preparing for coding interviews or aiming for Leetcode mastery, this problem enhances your spatial reasoning and greedy logic understanding.
📌 Don't forget to Like, Share, and Subscribe for more Leetcode in Python solutions!
🔖 Tags (YouTube Format, comma-separated):
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maximum manhattan distance
python greedy algorithm
directional string movement
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coordinate system
robot movement
string manipulation
distance calculation
coordinate update
grid traversal
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south move
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calculate final distance
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