Nice work! You’ve implemented a min-heap in Python, and that’s no small feat (although it could efficiently track the smallest feat).

To recap: `MinHeap`

tracks the minimum element as the element at index `1`

within an internal Python list.

When adding elements, we use `.heapify_up()`

to compare the new element with its parent, making swaps if it violates the heap property: **children must be greater than their parents**.

When removing the minimum element, we swap it with the last element in the list. Then we use `.heapify_down()`

to compare the new root with its children, swapping with the smaller child if necessary.

Heaps are so useful because they’re **efficient** in maintaining their heap properties. Building a heap using elements that decreased in value would ensure that we continually violated the heap property. How many swaps would that cause?

### Instructions

**1.**

Run the code in **script.py** to see how many swaps are made in a dataset of `10,000`

elements!