在Python中使用循环在字典中计数元素的高效方法 [英] efficient way to count the element in a dictionary in Python using a loop
问题描述
我有一个值列表。我希望在循环期间计算每个类的元素数(即1,2,3,4,5)
I have a list of values. I wish to count during a loop the number of element for each class (i.e. 1,2,3,4,5)
mylist = [1,1,1,1,1,1,2,3,2,2,2,2,3,3,4,5,5,5,5]
mydict = dict()
for index in mylist:
mydict[index] = +1
mydict
Out[344]: {1: 1, 2: 1, 3: 1, 4: 1, 5: 1}
我希望得到这个结果
Out[344]: {1: 6, 2: 5, 3: 3, 4: 1, 5: 4}
推荐答案
对于你的小例子,使用有限的元素,你可以使用set和dict comprehension :
For your smaller example, with a limited diversity of elements, you can use a set and a dict comprehension:
>>> mylist = [1,1,1,1,1,1,2,3,2,2,2,2,3,3,4,5,5,5,5]
>>> {k:mylist.count(k) for k in set(mylist)}
{1: 6, 2: 5, 3: 3, 4: 1, 5: 4}
要将其分解, set(mylist)
compact:
To break it down, set(mylist)
uniquifies the list and makes it more compact:
>>> set(mylist)
set([1, 2, 3, 4, 5])
然后字典解析逐步通过唯一值并设置列表中的计数。
Then the dictionary comprehension steps through the unique values and sets the count from the list.
这也比使用计数器显着更快,而且比使用setdefault更快。
This also is significantly faster than using Counter and faster than using setdefault:
from __future__ import print_function
from collections import Counter
from collections import defaultdict
import random
mylist=[1,1,1,1,1,1,2,3,2,2,2,2,3,3,4,5,5,5,5]*10
def s1(mylist):
return {k:mylist.count(k) for k in set(mylist)}
def s2(mlist):
return Counter(mylist)
def s3(mylist):
mydict=dict()
for index in mylist:
mydict[index] = mydict.setdefault(index, 0) + 1
return mydict
def s4(mylist):
mydict={}.fromkeys(mylist,0)
for k in mydict:
mydict[k]=mylist.count(k)
return mydict
def s5(mylist):
mydict={}
for k in mylist:
mydict[k]=mydict.get(k,0)+1
return mydict
def s6(mylist):
mydict=defaultdict(int)
for i in mylist:
mydict[i] += 1
return mydict
def s7(mylist):
mydict={}.fromkeys(mylist,0)
for e in mylist:
mydict[e]+=1
return mydict
if __name__ == '__main__':
import timeit
n=1000000
print(timeit.timeit("s1(mylist)", setup="from __main__ import s1, mylist",number=n))
print(timeit.timeit("s2(mylist)", setup="from __main__ import s2, mylist, Counter",number=n))
print(timeit.timeit("s3(mylist)", setup="from __main__ import s3, mylist",number=n))
print(timeit.timeit("s4(mylist)", setup="from __main__ import s4, mylist",number=n))
print(timeit.timeit("s5(mylist)", setup="from __main__ import s5, mylist",number=n))
print(timeit.timeit("s6(mylist)", setup="from __main__ import s6, mylist, defaultdict",number=n))
print(timeit.timeit("s7(mylist)", setup="from __main__ import s7, mylist",number=n))
在打印(Python 3)的机器上:
On my machine that prints (Python 3):
18.123854104997008 # set and dict comprehension
78.54796334600542 # Counter
33.98185228800867 # setdefault
19.0563529439969 # fromkeys / count
34.54294775899325 # dict.get
21.134678319009254 # defaultdict
22.760544238000875 # fromkeys / loop
对于更大的列表,如10万个整数, ,在循环中使用defaultdict或fromkeys:
For Larger lists, like 10 million integers, with more diverse elements (1,500 random ints), use defaultdict or fromkeys in a loop:
from __future__ import print_function
from collections import Counter
from collections import defaultdict
import random
mylist = [random.randint(0,1500) for _ in range(10000000)]
def s1(mylist):
return {k:mylist.count(k) for k in set(mylist)}
def s2(mlist):
return Counter(mylist)
def s3(mylist):
mydict=dict()
for index in mylist:
mydict[index] = mydict.setdefault(index, 0) + 1
return mydict
def s4(mylist):
mydict={}.fromkeys(mylist,0)
for k in mydict:
mydict[k]=mylist.count(k)
return mydict
def s5(mylist):
mydict={}
for k in mylist:
mydict[k]=mydict.get(k,0)+1
return mydict
def s6(mylist):
mydict=defaultdict(int)
for i in mylist:
mydict[i] += 1
return mydict
def s7(mylist):
mydict={}.fromkeys(mylist,0)
for e in mylist:
mydict[e]+=1
return mydict
if __name__ == '__main__':
import timeit
n=1
print(timeit.timeit("s1(mylist)", setup="from __main__ import s1, mylist",number=n))
print(timeit.timeit("s2(mylist)", setup="from __main__ import s2, mylist, Counter",number=n))
print(timeit.timeit("s3(mylist)", setup="from __main__ import s3, mylist",number=n))
print(timeit.timeit("s4(mylist)", setup="from __main__ import s4, mylist",number=n))
print(timeit.timeit("s5(mylist)", setup="from __main__ import s5, mylist",number=n))
print(timeit.timeit("s6(mylist)", setup="from __main__ import s6, mylist, defaultdict",number=n))
print(timeit.timeit("s7(mylist)", setup="from __main__ import s7, mylist",number=n))
列印:
2825.2697427899984 # set and dict comprehension
42.607481333994656 # Counter
22.77713537499949 # setdefault
2853.11187016801 # fromkeys / count
23.241977066005347 # dict.get
15.023175164998975 # defaultdict
18.28165417900891 # fromkeys / loop
您可以看到,在计数
时间通过大列表将遭受严重/灾难性与其他解决方案相比。
You can see that solutions that relay on count
with a moderate number of times through the large list will suffer badly/catastrophically in comparison to other solutions.
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