Kth and closest points in Python

Questions 1 to 5 of 7

1. 1. A list of numbers arrives one at a time, and you cannot keep the whole list in memory. You want the 100th largest. Which method from the kth-largest lesson fits?

   Sort the whole list, then read index n - 100Quickselect on a full copy of the listA heapq min-heap that holds at most 100 numbersA heapq max-heap that holds every number seen
2. 2. In a sorted list of 10 numbers, which index holds the 3rd largest number? Indexes count from 0.

   8297
3. 3. Which statements about the three kth-largest methods are true? Choose all that apply.

   Pick every answer that is true.

   Sorting the whole list costs O(n log n) timeA min-heap of size k needs O(k) extra memoryQuickselect with a random pivot always runs in O(n) time, even in the worst caseQuickselect leaves the caller's list in its original order
4. 4. Which statements about squared distances in Python are true? Choose all that apply.

   Pick every answer that is true.

   Python's int arithmetic is exact, so 50000 * 50000 is 2500000000float(x * x) is exact for every whole number, so the conversion is always safeConverting a large squared distance to float can round it, so two different values can look equalComparing squared distances instead of real distances can change which points are closest
5. 5. What does this code print? ``python import heapq heap = [] for x in [7, 2, 9, 4, 5]: heapq.heappush(heap, x) if len(heap) > 3: heapq.heappop(heap) print(heap[0]) ``

   2957