# Posts tagged as “sorting”

Given an array of integers arr and an integer k.

A value arr[i] is said to be stronger than a value arr[j] if |arr[i] - m| > |arr[j] - m| where m is the median of the array.
If |arr[i] - m| == |arr[j] - m|, then arr[i] is said to be stronger than arr[j] if arr[i] > arr[j].

Return a list of the strongest k values in the array. return the answer in any arbitrary order.

Median is the middle value in an ordered integer list. More formally, if the length of the list is n, the median is the element in position ((n - 1) / 2) in the sorted list (0-indexed).

• For arr = [6, -3, 7, 2, 11]n = 5 and the median is obtained by sorting the array arr = [-3, 2, 6, 7, 11] and the median is arr[m] where m = ((5 - 1) / 2) = 2. The median is 6.
• For arr = [-7, 22, 17, 3]n = 4 and the median is obtained by sorting the array arr = [-7, 3, 17, 22] and the median is arr[m] where m = ((4 - 1) / 2) = 1. The median is 3.

Example 1:

Input: arr = [1,2,3,4,5], k = 2
Output: [5,1]
Explanation: Median is 3, the elements of the array sorted by the strongest are [5,1,4,2,3]. The strongest 2 elements are [5, 1]. [1, 5] is also accepted answer.
Please note that although |5 - 3| == |1 - 3| but 5 is stronger than 1 because 5 > 1.


Example 2:

Input: arr = [1,1,3,5,5], k = 2
Output: [5,5]
Explanation: Median is 3, the elements of the array sorted by the strongest are [5,5,1,1,3]. The strongest 2 elements are [5, 5].


Example 3:

Input: arr = [6,7,11,7,6,8], k = 5
Output: [11,8,6,6,7]
Explanation: Median is 7, the elements of the array sorted by the strongest are [11,8,6,6,7,7].
Any permutation of [11,8,6,6,7] is accepted.


Example 4:

Input: arr = [6,-3,7,2,11], k = 3
Output: [-3,11,2]


Example 5:

Input: arr = [-7,22,17,3], k = 2
Output: [22,17]


Constraints:

• 1 <= arr.length <= 10^5
• -10^5 <= arr[i] <= 10^5
• 1 <= k <= arr.length

## Solution 1: quick selection + sort

Step 1: find the median element m
Step 2: Sort the array according to m
Step 3: output the first k elements of the sorted array.

Time complexity: O(nlogn)
Space complexity: O(1)

## C++

In a special ranking system, each voter gives a rank from highest to lowest to all teams participated in the competition.

The ordering of teams is decided by who received the most position-one votes. If two or more teams tie in the first position, we consider the second position to resolve the conflict, if they tie again, we continue this process until the ties are resolved. If two or more teams are still tied after considering all positions, we rank them alphabetically based on their team letter.

Given an array of strings votes which is the votes of all voters in the ranking systems. Sort all teams according to the ranking system described above.

Return a string of all teams sorted by the ranking system.

Example 1:

Input: votes = ["ABC","ACB","ABC","ACB","ACB"]
Output: "ACB"
Explanation: Team A was ranked first place by 5 voters. No other team was voted as first place so team A is the first team.
Team B was ranked second by 2 voters and was ranked third by 3 voters.
Team C was ranked second by 3 voters and was ranked third by 2 voters.
As most of the voters ranked C second, team C is the second team and team B is the third.


Example 2:

Input: votes = ["WXYZ","XYZW"]
Output: "XWYZ"
Explanation: X is the winner due to tie-breaking rule. X has same votes as W for the first position but X has one vote as second position while W doesn't have any votes as second position.


Example 3:

Input: votes = ["ZMNAGUEDSJYLBOPHRQICWFXTVK"]
Output: "ZMNAGUEDSJYLBOPHRQICWFXTVK"
Explanation: Only one voter so his votes are used for the ranking.


Example 4:

Input: votes = ["BCA","CAB","CBA","ABC","ACB","BAC"]
Output: "ABC"
Explanation:
Team A was ranked first by 2 voters, second by 2 voters and third by 2 voters.
Team B was ranked first by 2 voters, second by 2 voters and third by 2 voters.
Team C was ranked first by 2 voters, second by 2 voters and third by 2 voters.
There is a tie and we rank teams ascending by their IDs.


Example 5:

Input: votes = ["M","M","M","M"]
Output: "M"
Explanation: Only team M in the competition so it has the first rank.


Constraints:

• 1 <= votes.length <= 1000
• 1 <= votes[i].length <= 26
• votes[i].length == votes[j].length for 0 <= i, j < votes.length.
• votes[i][j] is an English upper-case letter.
• All characters of votes[i] are unique.
• All the characters that occur in votes[0] also occur in votes[j] where 1 <= j < votes.length.

## Solution: Sort by rank

Time complexity: O(v*n + n^2*logn)
Space complexity: O(n*n)

## C++

Implement the class TweetCounts that supports two methods:

1. recordTweet(string tweetName, int time)

• Stores the tweetName at the recorded time (in seconds).

2. getTweetCountsPerFrequency(string freq, string tweetName, int startTime, int endTime)

• Returns the total number of occurrences for the given tweetName per minutehour, or day (depending on freq) starting from the startTime (in seconds) and ending at the endTime (in seconds).
• freq is always minutehour or day, representing the time interval to get the total number of occurrences for the given tweetName.
• The first time interval always starts from the startTime, so the time intervals are [startTime, startTime + delta*1>,  [startTime + delta*1, startTime + delta*2>, [startTime + delta*2, startTime + delta*3>, ... , [startTime + delta*i, min(startTime + delta*(i+1), endTime + 1)> for some non-negative number i and delta (which depends on freq).

Example:

Input
["TweetCounts","recordTweet","recordTweet","recordTweet","getTweetCountsPerFrequency","getTweetCountsPerFrequency","recordTweet","getTweetCountsPerFrequency"]
[[],["tweet3",0],["tweet3",60],["tweet3",10],["minute","tweet3",0,59],["minute","tweet3",0,60],["tweet3",120],["hour","tweet3",0,210]]

Output
[null,null,null,null,[2]
[2,1],null,[4]]

Explanation
TweetCounts tweetCounts = new TweetCounts();
tweetCounts.recordTweet("tweet3", 0);
tweetCounts.recordTweet("tweet3", 60);
tweetCounts.recordTweet("tweet3", 10);                             // All tweets correspond to "tweet3" with recorded times at 0, 10 and 60.
tweetCounts.getTweetCountsPerFrequency("minute", "tweet3", 0, 59); // return [2]. The frequency is per minute (60 seconds), so there is one interval of time: 1) [0, 60> - > 2 tweets.
tweetCounts.getTweetCountsPerFrequency("minute", "tweet3", 0, 60); // return [2, 1]. The frequency is per minute (60 seconds), so there are two intervals of time: 1) [0, 60> - > 2 tweets, and 2) [60,61> - > 1 tweet.
tweetCounts.recordTweet("tweet3", 120);                            // All tweets correspond to "tweet3" with recorded times at 0, 10, 60 and 120.
tweetCounts.getTweetCountsPerFrequency("hour", "tweet3", 0, 210);  // return [4]. The frequency is per hour (3600 seconds), so there is one interval of time: 1) [0, 211> - > 4 tweets.



Constraints:

• There will be at most 10000 operations considering both recordTweet and getTweetCountsPerFrequency.
• 0 <= time, startTime, endTime <= 10^9

## Solution: Hashtable + binary search

Time complexity:
Record: O(logn)
getCount: O(logn + |entries|)

Space complexity: O(n)

## C++

Given an array of integers nums, sort the array in ascending order.

Example 1:

Input: nums = [5,2,3,1]
Output: [1,2,3,5]


Example 2:

Input: nums = [5,1,1,2,0,0]
Output: [0,0,1,1,2,5]


Constraints:

• 1 <= nums.length <= 50000
• -50000 <= nums[i] <= 50000

Since n <= 50000, any O(n^2) won’t pass, we need O(nlogn) or better

## Solution 1: QuickSort

Time complexity: O(nlogn) ~ O(n^2)
Space complexity: O(logn) ~ O(n)

## Solution 2: Counting Sort

Time complexity: O(n)
Space complexity: O(max(nums) – min(nums))

## Solution 2: HeapSort

Time complexity: O(nlogn)
Space complexity: O(n)

## Solution 3: MergeSort

Time complexity: O(nlogn)
Space complexity: O(logn + n)

## Solution 4: BST

Time complexity: (nlogn)
Space complexity: O(n)

## C++

Given the array restaurants where  restaurants[i] = [idi, ratingi, veganFriendlyi, pricei, distancei]. You have to filter the restaurants using three filters.

The veganFriendly filter will be either true (meaning you should only include restaurants with veganFriendlyi set to true) or false (meaning you can include any restaurant). In addition, you have the filters maxPrice and maxDistance which are the maximum value for price and distance of restaurants you should consider respectively.

Return the array of restaurant IDs after filtering, ordered by rating from highest to lowest. For restaurants with the same rating, order them by id from highest to lowest. For simplicity veganFriendlyi and veganFriendly take value 1 when it is true, and 0 when it is false.

Example 1:

Input: restaurants = [[1,4,1,40,10],[2,8,0,50,5],[3,8,1,30,4],[4,10,0,10,3],[5,1,1,15,1]], veganFriendly = 1, maxPrice = 50, maxDistance = 10
Output: [3,1,5]
Explanation:
The restaurants are:
Restaurant 1 [id=1, rating=4, veganFriendly=1, price=40, distance=10]
Restaurant 2 [id=2, rating=8, veganFriendly=0, price=50, distance=5]
Restaurant 3 [id=3, rating=8, veganFriendly=1, price=30, distance=4]
Restaurant 4 [id=4, rating=10, veganFriendly=0, price=10, distance=3]
Restaurant 5 [id=5, rating=1, veganFriendly=1, price=15, distance=1]
After filter restaurants with veganFriendly = 1, maxPrice = 50 and maxDistance = 10 we have restaurant 3, restaurant 1 and restaurant 5 (ordered by rating from highest to lowest).


Example 2:

Input: restaurants = [[1,4,1,40,10],[2,8,0,50,5],[3,8,1,30,4],[4,10,0,10,3],[5,1,1,15,1]], veganFriendly = 0, maxPrice = 50, maxDistance = 10
Output: [4,3,2,1,5]
Explanation: The restaurants are the same as in example 1, but in this case the filter veganFriendly = 0, therefore all restaurants are considered.


Example 3:

Input: restaurants = [[1,4,1,40,10],[2,8,0,50,5],[3,8,1,30,4],[4,10,0,10,3],[5,1,1,15,1]], veganFriendly = 0, maxPrice = 30, maxDistance = 3
Output: [4,5]


Constraints:

• 1 <= restaurants.length <= 10^4
• restaurants[i].length == 5
• 1 <= idi, ratingi, pricei, distancei <= 10^5
• 1 <= maxPrice, maxDistance <= 10^5
• veganFriendlyi and veganFriendly are 0 or 1.
• All idi are distinct.

## Solution

Time complexity: O(nlogn)
Space complexity: O(n)

## C++

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