如何在整数列表中找到重复项并创建重复项的另一个列表?
当前回答
我注意到大多数解决方案的复杂度为O(n * n),对于大型列表来说非常缓慢。所以我想分享一下我写的函数,它支持整数或字符串,在最好的情况下是O(n)。对于一个包含10万个元素的列表,最上面的解决方案需要超过30秒,而我的解决方案只需0.12秒
def get_duplicates(list1):
'''Return all duplicates given a list. O(n) complexity for best case scenario.
input: [1, 1, 1, 2, 3, 4, 4]
output: [1, 1, 4]
'''
dic = {}
for el in list1:
try:
dic[el] += 1
except:
dic[el] = 1
dupes = []
for key in dic.keys():
for i in range(dic[key] - 1):
dupes.append(key)
return dupes
list1 = [1, 1, 1, 2, 3, 4, 4]
> print(get_duplicates(list1))
[1, 1, 4]
或者获得唯一的副本:
> print(list(set(get_duplicates(list1))))
[1, 4]
其他回答
为了实现这个问题,我们可以使用多种不同的方法来解决它,这两种是常见的解决方案,但在实际场景中实现它们时,我们还必须考虑时间复杂性。
import random
import time
dupl_list = [random.randint(1,1000) for x in range(500)]
print("List with duplicate integers")
print (dupl_list)
#Method 1
print("******************Method 1 *************")
def Repeat_num(x):
_size = len(x)
repeated = []
for i in range(_size):
# print(i)
k = i + 1
for j in range(k, _size):
# print(j)
if x[i] == x[j] and x[i] not in repeated:
repeated.append(x[i])
return repeated
start = time.time()
print(Repeat_num(dupl_list))
end = time.time()
print("The time of execution of above program is :",(end-start) * 10**3, "ms")
print("***************Method 2****************")
#method 2 - using count()
def repeast_count(dup_list):
new = []
for a in dup_list:
# print(a)
# checking the occurrence of elements
n = dup_list.count(a)
# if the occurrence is more than
# one we add it to the output list
if n > 1:
if new.count(a) == 0: # condition to check
new.append(a)
return new
start = time.time()
print(repeast_count(dupl_list))
end = time.time()
print("The time of execution of above program is :",(end-start) * 10**3, "ms")
# #输出示例:
List with duplicate integers
[5, 45, 28, 81, 32, 98, 8, 83, 47, 95, 41, 49, 4, 1, 85, 26, 38, 82, 54, 11]
******************Method 1 *************
[]
The time of execution of above program is : 1.1069774627685547 ms
***************Method 2****************
[]
The time of execution of above program is : 0.1881122589111328 ms
对于一般的理解,方法1是好的,但是对于真正的实现,我更喜欢方法2,因为它比方法1花费的时间更少。
还有其他测试。当然要做……
set([x for x in l if l.count(x) > 1])
...代价太大了。使用下一个final方法大约快500倍(数组越长结果越好):
def dups_count_dict(l):
d = {}
for item in l:
if item not in d:
d[item] = 0
d[item] += 1
result_d = {key: val for key, val in d.iteritems() if val > 1}
return result_d.keys()
只有2个循环,没有非常昂贵的l.count()操作。
下面是一个比较方法的代码。代码如下,输出如下:
dups_count: 13.368s # this is a function which uses l.count()
dups_count_dict: 0.014s # this is a final best function (of the 3 functions)
dups_count_counter: 0.024s # collections.Counter
测试代码:
import numpy as np
from time import time
from collections import Counter
class TimerCounter(object):
def __init__(self):
self._time_sum = 0
def start(self):
self.time = time()
def stop(self):
self._time_sum += time() - self.time
def get_time_sum(self):
return self._time_sum
def dups_count(l):
return set([x for x in l if l.count(x) > 1])
def dups_count_dict(l):
d = {}
for item in l:
if item not in d:
d[item] = 0
d[item] += 1
result_d = {key: val for key, val in d.iteritems() if val > 1}
return result_d.keys()
def dups_counter(l):
counter = Counter(l)
result_d = {key: val for key, val in counter.iteritems() if val > 1}
return result_d.keys()
def gen_array():
np.random.seed(17)
return list(np.random.randint(0, 5000, 10000))
def assert_equal_results(*results):
primary_result = results[0]
other_results = results[1:]
for other_result in other_results:
assert set(primary_result) == set(other_result) and len(primary_result) == len(other_result)
if __name__ == '__main__':
dups_count_time = TimerCounter()
dups_count_dict_time = TimerCounter()
dups_count_counter = TimerCounter()
l = gen_array()
for i in range(3):
dups_count_time.start()
result1 = dups_count(l)
dups_count_time.stop()
dups_count_dict_time.start()
result2 = dups_count_dict(l)
dups_count_dict_time.stop()
dups_count_counter.start()
result3 = dups_counter(l)
dups_count_counter.stop()
assert_equal_results(result1, result2, result3)
print 'dups_count: %.3f' % dups_count_time.get_time_sum()
print 'dups_count_dict: %.3f' % dups_count_dict_time.get_time_sum()
print 'dups_count_counter: %.3f' % dups_count_counter.get_time_sum()
有点晚了,但可能对一些人有帮助。 对于一个比较大的列表,我发现这个方法很适合我。
l=[1,2,3,5,4,1,3,1]
s=set(l)
d=[]
for x in l:
if x in s:
s.remove(x)
else:
d.append(x)
d
[1,3,1]
显示正确和所有重复,并保持秩序。
使用sort()函数。重复项可以通过遍历它并检查l1[i] == l1[i+1]来识别。
另一种解决方案如下所示,不使用任何集合库。
a = [1,2,3,5,4,6,4,21,4,6,3,32,5,2,23,5]
duplicates = []
for i in a:
if a.count(i) > 1 and i not in duplicates:
duplicates.append(i)
print(duplicates)
输出是[2,3,5,4,6]
推荐文章
- 证书验证失败:无法获得本地颁发者证书
- 当使用pip3安装包时,“Python中的ssl模块不可用”
- 无法切换Python与pyenv
- Python if not == vs if !=
- 如何从scikit-learn决策树中提取决策规则?
- 为什么在Mac OS X v10.9 (Mavericks)的终端中apt-get功能不起作用?
- 将旋转的xtick标签与各自的xtick对齐
- 为什么元组可以包含可变项?
- 如何合并字典的字典?
- 如何创建类属性?
- 不区分大小写的“in”
- 在Python中获取迭代器中的元素个数
- 解析日期字符串并更改格式
- 使用try和。Python中的if
- 如何在Python中获得所有直接子目录