给定一个无序的值列表,比如
a = [5, 1, 2, 2, 4, 3, 1, 2, 3, 1, 1, 5, 2]
我怎样才能得到出现在列表中的每个值的频率,就像这样?
# `a` has 4 instances of `1`, 4 of `2`, 2 of `3`, 1 of `4,` 2 of `5`
b = [4, 4, 2, 1, 2] # expected output
给定一个无序的值列表,比如
a = [5, 1, 2, 2, 4, 3, 1, 2, 3, 1, 1, 5, 2]
我怎样才能得到出现在列表中的每个值的频率,就像这样?
# `a` has 4 instances of `1`, 4 of `2`, 2 of `3`, 1 of `4,` 2 of `5`
b = [4, 4, 2, 1, 2] # expected output
当前回答
另一种方法是使用较重但功能强大的库——NLTK。
import nltk
fdist = nltk.FreqDist(a)
fdist.values()
fdist.most_common()
其他回答
您可以使用python中提供的内置函数
l.count(l[i])
d=[]
for i in range(len(l)):
if l[i] not in d:
d.append(l[i])
print(l.count(l[i])
上面的代码自动删除列表中的重复项,并打印原始列表和没有重复项的列表中每个元素的频率。
一枪双鸟!X维
还有一种方法是使用字典和列表。数数,下面一种幼稚的做法。
dicio = dict()
a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
b = list()
c = list()
for i in a:
if i in dicio: continue
else:
dicio[i] = a.count(i)
b.append(a.count(i))
c.append(i)
print (b)
print (c)
from collections import Counter
a=["E","D","C","G","B","A","B","F","D","D","C","A","G","A","C","B","F","C","B"]
counter=Counter(a)
kk=[list(counter.keys()),list(counter.values())]
pd.DataFrame(np.array(kk).T, columns=['Letter','Count'])
计算元素的频率可能最好使用字典:
b = {}
for item in a:
b[item] = b.get(item, 0) + 1
要删除重复项,请使用set:
a = list(set(a))
假设我们有一个列表:
fruits = ['banana', 'banana', 'apple', 'banana']
我们可以在列表中找出每种水果的数量,像这样:
import numpy as np
(unique, counts) = np.unique(fruits, return_counts=True)
{x:y for x,y in zip(unique, counts)}
结果:
{'banana': 3, 'apple': 1}