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import math def slidingWindowSpikes(measurements, measurementsLength, m, tolerance): sum_of_indices = 0 for i in range(measurementsLength - m + 1): window = measurements[i:i+m] mean = sum(window) / m variance = sum((x - mean) ** 2 for x in window) / m standard_error = math.sqrt(variance) if standard_error > tolerance: sum_of_indices += (i + 1) return sum_of_indices SLIDING WINDOW SPIKES ✅✅

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def find(parent, u): if parent[u] != u: parent[u] = find(parent, parent[u]) return parent[u] def unite(parent, rank, u, v): root_u = find(parent, u) root_v = find(parent, v) if root_u != root_v: if rank[root_u] > rank[root_v]: parent[root_v] = root_u elif rank[root_u] < rank[root_v]: parent[root_u] = root_v else: parent[root_v] = root_u rank[root_u] += 1 def solve(n, edges): edges.sort(key=lambda x: x[2]) parent = list(range(n + 1)) rank = [0] * (n + 1) cost = 0 edges_used = 0 for u, v, c in edges: if find(parent, u) != find(parent, v): unite(parent, rank, u, v) cost += c edges_used += 1 if edges_used == n - 1: break return cost Break and Add ✅ #Google

def findMinChanges(taskDependency):     n = len(taskDependency)     changes = 0     final_task = -1         for i in range(n):         if taskDependency[i] == i + 1:             final_task = i + 1             break         if final_task == -1:         final_task = n         changes += 1         visited = set()     for i in range(1, n + 1):         if i not in visited:             current = i             path = set()             while current not in visited:                 if current == final_task:                     break                 if current in path:                     # Found a cycle, break it                     changes += 1                     break                 path.add(current)                 visited.add(current)                 current = taskDependency[current - 1]     for i in range(1, n + 1):         if i != final_task and taskDependency[i - 1] == i:             changes += 1         return changes Taks Dependency ✅ #Gameskraft