Medium
Top K Frequent Elements — Python
Full explanation · Time O(n) · Space O(n)
# Time: O(n)
# Space: O(n)
import collections
class Solution(object):
def topKFrequent(self, nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: List[int]
"""
counts = collections.Counter(nums)
buckets = [[] for _ in xrange(len(nums)+1)]
for i, count in counts.iteritems():
buckets[count].append(i)
result = []
for i in reversed(xrange(len(buckets))):
for j in xrange(len(buckets[i])):
result.append(buckets[i][j])
if len(result) == k:
return result
return result
# Time: O(n) ~ O(n^2), O(n) on average.
# Space: O(n)
# Quick Select Solution
from random import randint
class Solution2(object):
def topKFrequent(self, nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: List[int]
"""
counts = collections.Counter(nums)
p = []
for key, val in counts.iteritems():
p.append((-val, key))
self.kthElement(p, k-1)
result = []
for i in xrange(k):
result.append(p[i][1])
return result
def kthElement(self, nums, k):
def PartitionAroundPivot(left, right, pivot_idx, nums):
pivot_value = nums[pivot_idx]
new_pivot_idx = left
nums[pivot_idx], nums[right] = nums[right], nums[pivot_idx]
for i in xrange(left, right):
if nums[i] < pivot_value:
nums[i], nums[new_pivot_idx] = nums[new_pivot_idx], nums[i]
new_pivot_idx += 1
nums[right], nums[new_pivot_idx] = nums[new_pivot_idx], nums[right]
return new_pivot_idx
left, right = 0, len(nums) - 1
while left <= right:
pivot_idx = randint(left, right)
new_pivot_idx = PartitionAroundPivot(left, right, pivot_idx, nums)
if new_pivot_idx == k:
return
elif new_pivot_idx > k:
right = new_pivot_idx - 1
else: # new_pivot_idx < k.
left = new_pivot_idx + 1
# Time: O(nlogk)
# Space: O(n)
class Solution3(object):
def topKFrequent(self, nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: List[int]
"""
return [key for key, _ in collections.Counter(nums).most_common(k)]