398_Random_Pick_Index

Partho Biswas · Partho Biswas · commit 6217cdabd1a0 · 2020-06-05T11:31:36.000+06:00
diff --git a/README.md b/README.md
@@ -754,6 +754,7 @@ BFS, DFS, Dijkstra, Floyd–Warshall, Bellman-Ford, Kruskal, Prim's, Minimum Spa
 |09| **[307. Range Sum Query - Mutable](https://tinyurl.com/utc58vb)** | [Python](https://tinyurl.com/wu6rdaw/307_Range_Sum_Query_-_Mutable.py)| **[Vid 1](https://tinyurl.com/sumo5b6), [Art 1](https://tinyurl.com/r54yf9y), [Art 2](https://tinyurl.com/srucx8l)** | Medium | **Segment Tree Basics**. Very Important |
 |10| **[327. Count of Range Sum](https://tinyurl.com/ulofnqj)** | [Python](https://tinyurl.com/wu6rdaw/327_Count_of_Range_Sum.py)| **[Vid 1](https://tinyurl.com/sumo5b6), [Art 1](https://tinyurl.com/rlmha9k), [Art 2](https://tinyurl.com/qlqod4c)** | Hard | **Segment Tree Basics**. Very Important |
 |11| **[239. Sliding Window Maximum](https://tinyurl.com/rvhujl5)** | [Python](https://tinyurl.com/wu6rdaw/239_Sliding_Window_Maximum.py)| **[Video 1](https://tinyurl.com/v767bl3)**, [Official](https://tinyurl.com/www4np2), [Art 1](https://tinyurl.com/y8nbroux), [Art 2](https://tinyurl.com/s62fzls), **[Art 3](https://tinyurl.com/vd3dtch)**, **[Art 4](https://tinyurl.com/yx3sjp46)** | Hard | 📌 Here, I have specifically focused on solving it with AVL and Red-Black Tree. A "Queue" approach can be found o Queue section  |
+|12| **[398. Random Pick Index](https://tinyurl.com/ydf3t2ke)** | [Python](https://tinyurl.com/wu6rdaw/398_Random_Pick_Index.py)| **[Video 1](https://tinyurl.com/ycjk3gk6)**,  [Art 1](https://tinyurl.com/ych82hfp), [Art 2](https://tinyurl.com/y8hogyty), [Art 3](https://tinyurl.com/y7slu8x2), [Art 4](https://tinyurl.com/y896sqmt), [Art 5](https://tinyurl.com/yafb3esf) | Medium (Really!!??) | 📌 **Reservoir sampling**, What's the point of asking this into an interview!!?? |
 
 </p>
 </details>
diff --git a/leetcode.com/python/398_Random_Pick_Index.py b/leetcode.com/python/398_Random_Pick_Index.py
@@ -0,0 +1,20 @@
+# https://tinyurl.com/yafb3esf
+class Solution(object):
+
+    def __init__(self, nums):
+        self.nums = nums
+
+    def pick(self, target):
+        res = None
+        count = 0
+        for i, x in enumerate(self.nums):
+            if x == target:
+                count += 1
+                chance = random.randint(1, count)
+                if chance == count:
+                    res = i
+        return res
+
+# Your Solution object will be instantiated and called as such:
+# obj = Solution(nums)
+# param_1 = obj.pick(target)
