How to count the frequency of the elements in an unordered list?

For your first question, iterate the list and use a dictionary to keep track of an elements existsence.

For your second question, just use the set operator.

Count the number of appearances manually by iterating through the list and counting them up, using a collections.defaultdict to track what has been seen so far:

from collections import defaultdict

appearances = defaultdict(int)

for curr in a:
    appearances[curr] += 1

Counting the frequency of elements is probably best done with a dictionary:

b = {}
for item in a:
    b[item] = b.get(item, 0) + 1

To remove the duplicates, use a set:

a = list(set(a))

seta = set(a)
b = [a.count(el) for el in seta]
a = list(seta) #Only if you really want it.

In Python 2.7+, you could use collections.Counter to count items

>>> a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
>>>
>>> from collections import Counter
>>> c=Counter(a)
>>>
>>> c.values()
[4, 4, 2, 1, 2]
>>>
>>> c.keys()
[1, 2, 3, 4, 5]

In Python 2.7 (or newer), you can use collections.Counter:

>>> import collections
>>> a = [5, 1, 2, 2, 4, 3, 1, 2, 3, 1, 1, 5, 2]
>>> counter = collections.Counter(a)
>>> counter
Counter({1: 4, 2: 4, 5: 2, 3: 2, 4: 1})
>>> counter.values()
dict_values([2, 4, 4, 1, 2])
>>> counter.keys()
dict_keys([5, 1, 2, 4, 3])
>>> counter.most_common(3)
[(1, 4), (2, 4), (5, 2)]
>>> dict(counter)
{5: 2, 1: 4, 2: 4, 4: 1, 3: 2}
>>> # Get the counts in order matching the original specification,
>>> # by iterating over keys in sorted order
>>> [counter[x] for x in sorted(counter.keys())]
[4, 4, 2, 1, 2]

If you are using Python 2.6 or older, you can download an implementation here.

Python 2.7+ introduces Dictionary Comprehension. Building the dictionary from the list will get you the count as well as get rid of duplicates.

>>> a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
>>> d = {x:a.count(x) for x in a}
>>> d
{1: 4, 2: 4, 3: 2, 4: 1, 5: 2}
>>> a, b = d.keys(), d.values()
>>> a
[1, 2, 3, 4, 5]
>>> b
[4, 4, 2, 1, 2]

This answer is more explicit

a = [1,1,1,1,2,2,2,2,3,3,3,4,4]

d = {}
for item in a:
    if item in d:
        d[item] = d.get(item)+1
    else:
        d[item] = 1

for k,v in d.items():
    print(str(k)+':'+str(v))

# output
#1:4
#2:4
#3:3
#4:2

#remove dups
d = set(a)
print(d)
#{1, 2, 3, 4}

#!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 inputn: "
print d
fp1 = open("output.txt","w+")
for k,v in d.items():
fp1.write(str(k)+':'+str(v)+"n")
fp1.close()

Yet another solution with another algorithm without using collections:

def countFreq(A):
   n=len(A)
   count=[0]*n                     # Create a new list initialized with '0'
   for i in range(n):
      count[A[i]]+= 1              # increase occurrence for value A[i]
   return [x for x in count if x]  # return non-zero count

I would simply use scipy.stats.itemfreq in the following manner:

from scipy.stats import itemfreq

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

freq = itemfreq(a)

a = freq[:,0]
b = freq[:,1]

you may check the documentation here: http://docs.scipy.org/doc/scipy-0.16.0/reference/generated/scipy.stats.itemfreq.html

def frequencyDistribution(data):
    return {i: data.count(i) for i in data}   

print frequencyDistribution([1,2,3,4])

…

 {1: 1, 2: 1, 3: 1, 4: 1}   # originalNumber: count

str1='the cat sat on the hat hat'
list1=str1.split();
list2=str1.split();

count=0;
m=[];

for i in range(len(list1)):
    t=list1.pop(0);
    print t
    for j in range(len(list2)):
        if(t==list2[j]):
            count=count+1;
            print count
    m.append(count)
    print m
    count=0;
#print m

One more way is to use a dictionary and the list.count, below a naive way to do it.

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)

You can do this:

import numpy as np
a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
np.unique(a, return_counts=True)

Output:

(array([1, 2, 3, 4, 5]), array([4, 4, 2, 1, 2], dtype=int64))

The first array is values, and the second array is the number of elements with these values.

So If you want to get just array with the numbers you should use this:

np.unique(a, return_counts=True)[1]

num=[3,2,3,5,5,3,7,6,4,6,7,2]
print ('nelements are:t',num)
count_dict={}
for elements in num:
    count_dict[elements]=num.count(elements)
print ('nfrequency:t',count_dict)

You can use the in-built function provided in python

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])

The above code automatically removes duplicates in a list and also prints the frequency of each element in original list and the list without duplicates.

Two birds for one shot ! X D

This approach can be tried if you don’t want to use any library and keep it simple and short!

a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
marked = []
b = [(a.count(i), marked.append(i))[0] for i in a if i not in marked]
print(b)

o/p

[4, 4, 2, 1, 2]

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'])

from collections import OrderedDict
a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
def get_count(lists):
    dictionary = OrderedDict()
    for val in lists:
        dictionary.setdefault(val,[]).append(1)
    return [sum(val) for val in dictionary.values()]
print(get_count(a))
>>>[4, 4, 2, 1, 2]

To remove duplicates and Maintain order:

list(dict.fromkeys(get_count(a)))
>>>[4, 2, 1]

i’m using Counter to generate a freq. dict from text file words in 1 line of code

def _fileIndex(fh):
''' create a dict using Counter of a
flat list of words (re.findall(re.compile(r"[a-zA-Z]+"), lines)) in (lines in file->for lines in fh)
'''
return Counter(
    [wrd.lower() for wrdList in
     [words for words in
      [re.findall(re.compile(r'[a-zA-Z]+'), lines) for lines in fh]]
     for wrd in wrdList])

a=[1,2,3,4,5,1,2,3]
b=[0,0,0,0,0,0,0]
for i in range(0,len(a)):
    b[a[i]]+=1

I am quite late, but this will also work, and will help others:

a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
freq_list = []
a_l = list(set(a))

for x in a_l:
    freq_list.append(a.count(x))


print 'Freq',freq_list
print 'number',a_l

will produce this..

Freq  [4, 4, 2, 1, 2]
number[1, 2, 3, 4, 5]

For the record, a functional answer:

>>> L = [1,1,1,1,2,2,2,2,3,3,4,5,5]
>>> import functools
>>> >>> functools.reduce(lambda acc, e: [v+(i==e) for i, v in enumerate(acc,1)] if e<=len(acc) else acc+[0 for _ in range(e-len(acc)-1)]+[1], L, [])
[4, 4, 2, 1, 2]

It’s cleaner if you count zeroes too:

>>> functools.reduce(lambda acc, e: [v+(i==e) for i, v in enumerate(acc)] if e<len(acc) else acc+[0 for _ in range(e-len(acc))]+[1], L, [])
[0, 4, 4, 2, 1, 2]

An explanation:

• we start with an empty acc list;
• if the next element e of L is lower than the size of acc, we just update this element: v+(i==e) means v+1 if the index i of acc is the current element e, otherwise the previous value v;
• if the next element e of L is greater or equals to the size of acc, we have to expand acc to host the new 1.

The elements do not have to be sorted (itertools.groupby). You’ll get weird results if you have negative numbers.

Here’s another succint alternative using itertools.groupby which also works for unordered input:

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))}

results

format: {value: num_of_occurencies}

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

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

# 1. Get counts and store in another list
output = []
for i in set(a):
    output.append(a.count(i))
print(output)

# 2. Remove duplicates using set constructor
a = list(set(a))
print(a)

1. Set collection does not allow duplicates, passing a list to the set() constructor will give an iterable of totally unique objects. count() function returns an integer count when an object that is in a list is passed. With that the unique objects are counted and each count value is stored by appending to an empty list output
2. list() constructor is used to convert the set(a) into list and referred by the same variable a

Output

D:MLrecvenvScriptspython.exe D:/MLrec/listgroup.py
[4, 4, 2, 1, 2]
[1, 2, 3, 4, 5]

Simple solution using a dictionary.

def frequency(l):
     d = {}
     for i in l:
        if i in d.keys():
           d[i] += 1
        else:
           d[i] = 1

     for k, v in d.iteritems():
        if v ==max (d.values()):
           return k,d.keys()

print(frequency([10,10,10,10,20,20,20,20,40,40,50,50,30]))

Another approach of doing this, albeit by using a heavier but powerful library – NLTK.

import nltk

fdist = nltk.FreqDist(a)
fdist.values()
fdist.most_common()

Found another way of doing this, using sets.

#ar is the list of elements
#convert ar to set to get unique elements
sock_set = set(ar)

#create dictionary of frequency of socks
sock_dict = {}

for sock in sock_set:
    sock_dict[sock] = ar.count(sock)

To find the count of unique elements in a sorted array using dictionary:

def CountFrequency(my_list): 
    # Creating an empty dictionary  
    freq = {} 
    for item in my_list: 
        if (item in freq): 
            freq[item] += 1
        else: 
            freq[item] = 1
  
    for key, value in freq.items(): 
        print ("% d : % d"%(key, value))

# Driver function 
if __name__ == "__main__":  
    my_list = [1, 1, 1, 5, 5, 3, 1, 3, 3, 1, 4, 4, 4, 2, 2, 2, 2] 
  
    CountFrequency(my_list)

Source: GeeksforGeeks

For an unordered list you should use:

[a.count(el) for el in set(a)]

The output is

[4, 4, 2, 1, 2]

Suppose we have a list:

fruits = ['banana', 'banana', 'apple', 'banana']

We can find out how many of each fruit we have in the list like so:

import numpy as np    
(unique, counts) = np.unique(fruits, return_counts=True)
{x:y for x,y in zip(unique, counts)}

Result:

{'banana': 3, 'apple': 1}

a = [1,1,1,1,2,2,2,2,3,3,4,5,5]
counts = dict.fromkeys(a, 0)
for el in a: counts[el] += 1
print(counts)
# {1: 4, 2: 4, 3: 2, 4: 1, 5: 2}