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}

下面是使用itertools的另一个简洁的替代方案。Groupby也适用于无序输入:

from itertools import groupby

items = [5, 1, 1, 2, 2, 1, 1, 2, 2, 3, 4, 3, 5]

results = {value: len(list(freq)) for value, freq in groupby(sorted(items))}

结果

format: {value: num_of_occurencies}

{1: 4, 2: 4, 3: 2, 4: 1, 5: 2}

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)

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))

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'])

#!usr/bin/python
def frq(words):
    freq = {}
    for w in words:
            if w in freq:
                    freq[w] = freq.get(w)+1
            else:
                    freq[w] =1
    return freq

fp = open("poem","r")
list = fp.read()
fp.close()
input = list.split()
print input
d = frq(input)
print "frequency of input\n: "
print d
fp1 = open("output.txt","w+")
for k,v in d.items():
fp1.write(str(k)+':'+str(v)+"\n")
fp1.close()