# Top k Frequent Words

Given a list of words, return the k most frequent elements. The answer should be sorted by frequency from highest to lowest. If two words have the same frequency, the word with the lower alphabetical order comes first. k is always valid, that is 1 <= k <= number of unique words.

For example, for the given list and k = 2,

["earth", "planet", "hello", "world", "hello", "world"]

Return ["hello", "world"] as they have the highest frequency and sorted according to the alphabetical order.

## Approach 1: Sorting

### Intuition

In a hashmap, keep the count of the words and then push the words along with their counts in a list and then sort the list. At last, return the first k elements. For the example above, the hashmap would be:

earth: 1
planet: 1
hello: 2
world: 2

After sorting (note the comparator function comp below):

hello: 2
world: 2
earth: 1
planet: 1

### Implementation

vector<string> topKFrequent(vector<string>& words, int k) {
unordered_map<string, int> frequency;
for (string &word: words) {
++frequency[word];
}
// word, frequency
vector<pair<string, int>> wordFreq;
for (const auto &[word, freq]: frequency) {
wordFreq.push_back({word, freq});
}
auto comp = [](const pair<string, int> &a, const pair<string, int> &b) {
return a.second > b.second || (a.second == b.second && a.first < b.first);
};
sort(wordFreq.begin(), wordFreq.end(), comp);
vector<string> ret;
for (int i = 0; i < k; ++i) {
ret.push_back(wordFreq[i].first);
}
return ret;
}

### Complexity Analysis

• Time complexity: $O(NlogN)$ due to sorting.
• Space complexity: $O(N)$.

## Approach 2: Priority Queue

### Using Custom Comparator in Priority Queue in C++ - A Primer

A priority queue is a queue where the elements stay in a certain sorted order. We can also provide a Compare type for custom ordering.

Defined in header queue

template<
class T,
class Container = std::vector<T>,
class Compare = std::less<typename Container::value_type>
> class priority_queue;

The compare type should provide strict weak ordering, that is, it should return true if the first argument comes before the second argument.

Since the priority queue outputs the largest elements first, the elements that “come before” are actually output last. That is, the front of the queue contains the “last” element according to the weak ordering imposed by Compare.

By default, in priority queue, the compare is less that is the largest element that appears at the top. Using greater we can make the smallest element appear at the top.

#include <bits/stdc++.h>
using namespace std;

template<typename T>
void printPriorityQueue(T &pq) {
while(!pq.empty()) {
cout << pq.top() << " ";
pq.pop();
}
cout << endl;
}

int main() {
priority_queue<int> pq1;
for (int x: {8, 0, 1, 2, 3, 7}) {
pq1.push(x);
}
printPriorityQueue(pq1); // prints "8 7 3 2 1 0"
priority_queue<int, vector<int>, greater<int>> pq2;
for (int x: {8, 0, 1, 2, 3, 7}) {
pq2.push(x);
}
printPriorityQueue(pq2); // prints "0 1 2 3 7 8"
return 0;
}

### Intuition

We have used sorting in approach - 1. Another efficient approach is using a priority queue. In the priority queue, we will always maintain the top k frequent words. Note the comp function below. If the priority queue size exceeds k, we will pop the topmost element (as it has the lowest count).

### Implementation

vector<string> topKFrequent(vector<string>& words, int k) {
unordered_map<string, int> frequency;
for (string &word: words) {
++frequency[word];
}

auto comp = [](const pair<string, int> &a, const pair<string, int> &b) {
return a.second > b.second || (a.second == b.second && a.first < b.first);
};

priority_queue<pair<string, int>, vector<pair<string, int>>, decltype(comp)> wordFreq (comp);

for (const auto &[word, freq]: frequency) {
wordFreq.push({word, freq});
if (wordFreq.size() > k) wordFreq.pop();
}

vector<string> ret;
while(!wordFreq.empty()) {
ret.push_back(wordFreq.top().first);
wordFreq.pop();
}
reverse(ret.begin(), ret.end());
return ret;
}

### Complexity Analysis

• Time complexity: $O(Nlogk)$ as the priority queue size never exceeds k.
• Space complexity: $O(N)$.