Two city scheduling

Author: ramanaditya

leetcode/README.md

@@ -138,6 +138,7 @@
     | Sl No.| Level | Questions | Solution |
     | :---: | :---: | :--- | :--- |
     | 122. | <span style="color:green">Easy</span> | [Best Time to Buy and Sell Stock II](https://leetcode.com/problems/best-time-to-buy-and-sell-stock-ii/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/blob/master/leetcode/greedy/best-time-to-buy-and-sell-stock-ii.py) |
+    | 1029. | <span style="color:green">Easy</span> | [Two City Scheduling](https://leetcode.com/problems/two-city-scheduling/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/blob/master/leetcode/greedy/two-city-scheduling.py) |
     | 1046. | <span style="color:green">Easy</span> | [Last Stone Weight](https://leetcode.com/problems/last-stone-weight/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/blob/master/leetcode/greedy/last-stone-weight.py) |
     | 1196. | <span style="color:green">Easy</span> | [How Many Apples Can You Put into the Basket](https://leetcode.com/problems/how-many-apples-can-you-put-into-the-basket/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/blob/master/leetcode/greedy/how-many-apples-can-you-put-into-the-basket.py) |
 
@@ -304,5 +305,5 @@
     | :---: | :---: | :---: | :--- | :--- |
     | 1 | 226. | <span style="color:green">Easy</span> | [Invert Binary Tree](https://leetcode.com/problems/invert-binary-tree/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/tree/master/leetcode/tree/invert-binary-tree.py) |
     | 2 | 237. | <span style="color:green">Easy</span> | [Delete Node in a Linked List](https://leetcode.com/problems/delete-node-in-a-linked-list/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/tree/master/leetcode/linked-list/delete-node-in-a-linked-list.py) \| [C++](https://github.com/ramanaditya/data-structure-and-algorithms/tree/master/leetcode/linked-list/delete-node-in-a-linked-list.cpp) |
-    
+    | 3 | 1029. | <span style="color:green">Easy</span> | [Two City Scheduling](https://leetcode.com/problems/two-city-scheduling/) | [Python](https://github.com/ramanaditya/data-structure-and-algorithms/blob/master/leetcode/greedy/two-city-scheduling.py) | 
 

leetcode/greedy/two-city-scheduling.py

@@ -0,0 +1,57 @@
+"""
+## Questions
+
+### 1029. [Two City Scheduling](https://leetcode.com/problems/two-city-scheduling/)
+There are 2N people a company is planning to interview. The cost of flying the i-th person to city A is costs[i][0],
+and the cost of flying the i-th person to city B is costs[i][1].
+
+Return the minimum cost to fly every person to a city such that exactly N people arrive in each city.
+
+Example 1:
+Input: [[10,20],[30,200],[400,50],[30,20]]
+Output: 110
+Explanation:
+The first person goes to city A for a cost of 10.
+The second person goes to city A for a cost of 30.
+The third person goes to city B for a cost of 50.
+The fourth person goes to city B for a cost of 20.
+The total minimum cost is 10 + 30 + 50 + 20 = 110 to have half the people interviewing in each city.
+
+
+Note:
+1 <= costs.length <= 100
+It is guaranteed that costs.length is even.
+1 <= costs[i][0], costs[i][1] <= 1000
+"""
+
+## Solutions
+
+
+class Solution:
+    def lastStoneWeight(self, stones: List[int]) -> int:
+        """Slow using sort each time"""
+        if len(stones) <= 1:
+            return stones[0] if len(stones) == 1 else None
+        temp = sorted(stones, reverse=True)
+        while len(temp) > 2:
+            new_weight = abs(temp[0] - temp[1])
+            temp = sorted(temp[2:] + [new_weight], reverse=True)
+        return abs(temp[0] - temp[1])
+
+
+# Runtime: 32 ms, faster than 49.02% of Python3 online submissions
+# Memory Usage: 13.9 MB, less than 100.00% of Python3 online submissions
+
+
+# Solution
+
+
+class Solution:
+    def twoCitySchedCost(self, costs: List[List[int]]) -> int:
+        costA = [i for i, j in costs]
+        diff = [j - i for i, j in costs]
+        return sum(costA) + sum(sorted(diff)[: len(costs) // 2])
+
+
+# Runtime: 36 ms, faster than 90.00% of Python3 online submissions
+# Memory Usage: 13.8 MB, less than 7.69% of Python3 online submissions