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
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]
其他回答
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()
list2 = [1, 2, 3, 4, 1, 2, 3]
lset = set()
[(lset.add(item), list2.append(item))
for item in list2 if item not in lset]
print list(lset)
我会用熊猫做这个,因为我经常用熊猫
import pandas as pd
a = [1,2,3,3,3,4,5,6,6,7]
vc = pd.Series(a).value_counts()
vc[vc > 1].index.tolist()
给了
[3,6]
可能不是很有效,但它肯定比许多其他答案的代码更少,所以我想我可以贡献一下
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]
如果你不关心自己编写算法或使用库,Python 3.8一行代码:
l = [1,2,3,2,1,5,6,5,5,5]
res = [(x, count) for x, g in groupby(sorted(l)) if (count := len(list(g))) > 1]
print(res)
打印项目和计数:
[(1, 2), (2, 2), (5, 4)]
groupby接受一个分组函数,因此您可以以不同的方式定义分组,并根据需要返回额外的Tuple字段。
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