集合。Counter是python 2.7中的新功能:

Python 2.5.4 (r254:67916, May 31 2010, 15:03:39) 
[GCC 4.1.2 20080704 (Red Hat 4.1.2-46)] on linux2
a = [1,2,3,2,1,5,6,5,5,5]
import collections
print [x for x, y in collections.Counter(a).items() if y > 1]
Type "help", "copyright", "credits" or "license" for more information.
  File "", line 1, in 
AttributeError: 'module' object has no attribute 'Counter'
>>> 

在早期版本中，你可以使用传统的字典:

a = [1,2,3,2,1,5,6,5,5,5]
d = {}
for elem in a:
    if elem in d:
        d[elem] += 1
    else:
        d[elem] = 1

print [x for x, y in d.items() if y > 1]

使用Set函数 如:-

arr=[1,4,2,5,2,3,4,1,4,5,2,3]
arr2=list(set(arr))
print(arr2)

输出:- [1,2,3,4,5]

使用array删除副本

eg:-

arr=[1,4,2,5,2,3,4,1,4,5,2,3]
arr3=[]
for i in arr:
    if(i not in arr3):
     arr3.append(i)
print(arr3)

输出: [1,4,2,5,3]

使用Lambda函数

eg:-

rem_duplicate_func=lambda arr:set(arr)
print(rem_duplicate_func(arr))

输出: {1,2,3,4,5}

从字典中删除重复值

eg:-

dict1={
    'car':["Ford","Toyota","Ford","Toyota"],
    'brand':["Mustang","Ranz","Mustang","Ranz"] } dict2={} for key,value in dict1.items():
    dict2[key]=set(value) print(dict2)

输出: {“车”:{“丰田”、“福特”},“品牌”:{“主攻”、“野马”}}

对称差异-删除重复元素

eg:-

set1={1,2,4,5}
set2={2,1,5,7}
rem_dup_ele=set1.symmetric_difference(set2)
print(rem_dup_ele)

输出: {4 7}

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。

我没有看到一个纯粹使用迭代器的解决方案，所以我们开始吧

这需要对列表进行排序，这可能是这里的缺点。

a = [1,2,3,2,1,5,6,5,5,5]
a.sort()
set(map(lambda x: x[0], filter(lambda x: x[0] == x[1], zip(a, a[1:]))))

{1, 2, 5}

你可以用这段代码轻松检查你的机器有多快，有一百万潜在的重复:

首先生成数据

import random
from itertools import chain
a = list(chain(*[[n] * random.randint(1, 2) for n in range(1000000)]))

并运行测试:

set(map(lambda x: x[0], filter(lambda x: x[0] == x[1], zip(a, a[1:]))))

不用说，这个解决方案只在列表已经排序的情况下才有效。

简单地检查，对于所有列表项，如果一个项的第一个索引等于该项的最后一个索引:

>>> lastindex = lambda arr, el: len(arr) - arr[::-1].index(el) -1
>>> is_duplicate  = lambda arr, el: arr.index(el) != lastindex(arr, el)
>>> duplicates = lambda arr: [*set(x for x in arr if is_duplicate(arr, x))]
>>> 
>>> a=[2,3,5,7,11,13, 2,17,7,7,17,18,3,19,5,2,7,48,48,2,19]
>>> duplicates(a)
[2, 3, 5, 7, 48, 17, 19]
>>> 

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()