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Update Find Median from Data Stream.md #3

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Update Find Median from Data Stream.md #3

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4 changes: 2 additions & 2 deletions Solutions/Find Median from Data Stream.md
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Expand Up @@ -68,11 +68,11 @@ Instead of 2 heaps, you can use a self-balancing Binary Search Tree (like an AVL
1. Divide problem into 3 subproblems. Here are the groupings:
1. __Numbers < 0__: You have 2 options:
1. Use 2-heap solution (that we coded in original solution), or
1. Use 1 array, which represents 1 bucket
2. Use 1 array, which represents 1 bucket
1. __0 <= Numbers <= 100__: Use 100 buckets using an array of size 100
1. __100 < Numbers__: You have 2 options:
1. Use 2-heap solution (that we coded in original solution), or
1. Use 1 array, which represents 1 bucket
2. Use 1 array, which represents 1 bucket
1. For each number we get in the stream, insert it into 1 of the 3 groupings, keeping track of the count of numbers in each of these 3 groupings
1. To find the median, see which grouping the median must fall into and find it there.

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