How do I count the occurrences of a list item?

Question

Given a single item, how do I count occurrences of it in a list, in Python?

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_{A related but different problem is counting occurrences of each different element in a collection, getting a dictionary or list as a histogram result instead of a single integer. For that problem, see Using a dictionary to count the items in a list .}

Answer 1

If you only want one item's count, use the count<\/code> method:

>>> [1, 2, 3, 4, 1, 4, 1].count(1)
3

Answer 2

Use Counter<\/code><\/a> if you are using Python 2.7 or 3.x and you want the number of occurrences for each element:

>>> from collections import Counter
>>> z = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> Counter(z)
Counter({'blue': 3, 'red': 2, 'yellow': 1})

Answer 3

Counting the occurrences of one item in a list<\/strong>

>>> l = ["a","b","b"]
>>> l.count("a")
1
>>> l.count("b")
2

Answer 4

在字典中获取每个项目出现次数的另一种方法：

dict((i, a.count(i)) for i in a)

Answer 5

Given an item, how can I count its occurrences in a list in Python?

Here's an example list:

>>> l = list('aaaaabbbbcccdde')
>>> l
['a', 'a', 'a', 'a', 'a', 'b', 'b', 'b', 'b', 'c', 'c', 'c', 'd', 'd', 'e']

list.count

There's the list.count method

>>> l.count('b')
4

This works fine for any list. Tuples have this method as well:

>>> t = tuple('aabbbffffff')
>>> t
('a', 'a', 'b', 'b', 'b', 'f', 'f', 'f', 'f', 'f', 'f')
>>> t.count('f')
6

collections.Counter

And then there's collections.Counter. You can dump any iterable into a Counter, not just a list, and the Counter will retain a data structure of the counts of the elements.

Usage:

>>> from collections import Counter
>>> c = Counter(l)
>>> c['b']
4

Counters are based on Python dictionaries, their keys are the elements, so the keys need to be hashable. They are basically like sets that allow redundant elements into them.

Further usage of collections.Counter

You can add or subtract with iterables from your counter:

>>> c.update(list('bbb'))
>>> c['b']
7
>>> c.subtract(list('bbb'))
>>> c['b']
4

And you can do multi-set operations with the counter as well:

>>> c2 = Counter(list('aabbxyz'))
>>> c - c2                   # set difference
Counter({'a': 3, 'c': 3, 'b': 2, 'd': 2, 'e': 1})
>>> c + c2                   # addition of all elements
Counter({'a': 7, 'b': 6, 'c': 3, 'd': 2, 'e': 1, 'y': 1, 'x': 1, 'z': 1})
>>> c | c2                   # set union
Counter({'a': 5, 'b': 4, 'c': 3, 'd': 2, 'e': 1, 'y': 1, 'x': 1, 'z': 1})
>>> c & c2                   # set intersection
Counter({'a': 2, 'b': 2})

Why not pandas?

Another answer suggests:

Why not use pandas?

Pandas is a common library, but it's not in the standard library. Adding it as a requirement is non-trivial.

There are builtin solutions for this use-case in the list object itself as well as in the standard library.

If your project does not already require pandas, it would be foolish to make it a requirement just for this functionality.

Answer 6

list.count(x) returns the number of times x appears in a list

see: http://docs.python.org/tutorial/datastructures.html#more-on-lists

Answer 7

I've compared all suggested solutions (and a few new ones) with perfplot<\/a> (a small project of mine).

<\/h3>

For large enough arrays, it turns out that

<\/h3>
 
           

Answer 8

If you want to count all values at once<\/strong> you can do it very fast using numpy arrays and bincount<\/code> as follows

import numpy as np
a = np.array([1, 2, 3, 4, 1, 4, 1])
np.bincount(a)

Answer 9

If you can use pandas<\/code> , then value_counts<\/code> is there for rescue.

>>> import pandas as pd
>>> a = [1, 2, 3, 4, 1, 4, 1]
>>> pd.Series(a).value_counts()
1    3
4    2
3    1
2    1
dtype: int64

Answer 10

Why not using Pandas?

import pandas as pd

my_list = ['a', 'b', 'c', 'd', 'a', 'd', 'a']

# converting the list to a Series and counting the values
my_count = pd.Series(my_list).value_counts()
my_count

Answer 11

I had this problem today and rolled my own solution before I thought to check SO. This:

dict((i,a.count(i)) for i in a)

Answer 12

Count of all elements with itertools.groupby()<\/code><\/h2>

Antoher possiblity for getting the count of all elements in the list could be by means of itertools.groupby()<\/code> .

 This happens because the input list L<\/code> was not sorted. This can be a benefit sometimes if the groups should in fact be separate.
 But it is shown here to draw a parallel to the duplicate count example.
"

Answer 13

Below are the three solutions:

Fastest is using a for loop and storing it in a Dict.

import time
from collections import Counter


def countElement(a):
    g = {}
    for i in a:
        if i in g: 
            g[i] +=1
        else: 
            g[i] =1
    return g


z = [1,1,1,1,2,2,2,2,3,3,4,5,5,234,23,3,12,3,123,12,31,23,13,2,4,23,42,42,34,234,23,42,34,23,423,42,34,23,423,4,234,23,42,34,23,4,23,423,4,23,4]


#Solution 1 - Faster
st = time.monotonic()
for i in range(1000000):
    b = countElement(z)
et = time.monotonic()
print(b)
print('Simple for loop and storing it in dict - Duration: {}'.format(et - st))

#Solution 2 - Fast
st = time.monotonic()
for i in range(1000000):
    a = Counter(z)
et = time.monotonic()
print (a)
print('Using collections.Counter - Duration: {}'.format(et - st))

#Solution 3 - Slow
st = time.monotonic()
for i in range(1000000):
    g = dict([(i, z.count(i)) for i in set(z)])
et = time.monotonic()
print(g)
print('Using list comprehension - Duration: {}'.format(et - st))

Result

#Solution 1 - Faster

{1: 4, 2: 5, 3: 4, 4: 6, 5: 2, 234: 3, 23: 10, 12: 2, 123: 1, 31: 1, 13: 1, 42: 5, 34: 4, 423: 3}
Simple for loop and storing it in dict - Duration: 12.032000000000153

 #Solution 2 - Fast

Counter({23: 10, 4: 6, 2: 5, 42: 5, 1: 4, 3: 4, 34: 4, 234: 3, 423: 3, 5: 2, 12: 2, 123: 1, 31: 1, 13: 1})
Using collections.Counter - Duration: 15.889999999999418

 #Solution 3 - Slow

{1: 4, 2: 5, 3: 4, 4: 6, 5: 2, 34: 4, 423: 3, 234: 3, 42: 5, 12: 2, 13: 1, 23: 10, 123: 1, 31: 1}
Using list comprehension - Duration: 33.0

Answer 14

Although it is very old question, since i didn't find a one liner, i made one.

# original numbers in list
l = [1, 2, 2, 3, 3, 3, 4]

# empty dictionary to hold pair of number and its count
d = {}

# loop through all elements and store count
[ d.update( {i:d.get(i, 0)+1} ) for i in l ]

print(d)
# {1: 1, 2: 2, 3: 3, 4: 1}

Answer 15

# Python >= 2.6 (defaultdict) && < 2.7 (Counter, OrderedDict)
from collections import defaultdict
def count_unsorted_list_items(items):
    """
    :param items: iterable of hashable items to count
    :type items: iterable

    :returns: dict of counts like Py2.7 Counter
    :rtype: dict
    """
    counts = defaultdict(int)
    for item in items:
        counts[item] += 1
    return dict(counts)


# Python >= 2.2 (generators)
def count_sorted_list_items(items):
    """
    :param items: sorted iterable of items to count
    :type items: sorted iterable

    :returns: generator of (item, count) tuples
    :rtype: generator
    """
    if not items:
        return
    elif len(items) == 1:
        yield (items[0], 1)
        return
    prev_item = items[0]
    count = 1
    for item in items[1:]:
        if prev_item == item:
            count += 1
        else:
            yield (prev_item, count)
            count = 1
            prev_item = item
    yield (item, count)
    return


import unittest
class TestListCounters(unittest.TestCase):
    def test_count_unsorted_list_items(self):
        D = (
            ([], []),
            ([2], [(2,1)]),
            ([2,2], [(2,2)]),
            ([2,2,2,2,3,3,5,5], [(2,4), (3,2), (5,2)]),
            )
        for inp, exp_outp in D:
            counts = count_unsorted_list_items(inp) 
            print inp, exp_outp, counts
            self.assertEqual(counts, dict( exp_outp ))

        inp, exp_outp = UNSORTED_WIN = ([2,2,4,2], [(2,3), (4,1)])
        self.assertEqual(dict( exp_outp ), count_unsorted_list_items(inp) )


    def test_count_sorted_list_items(self):
        D = (
            ([], []),
            ([2], [(2,1)]),
            ([2,2], [(2,2)]),
            ([2,2,2,2,3,3,5,5], [(2,4), (3,2), (5,2)]),
            )
        for inp, exp_outp in D:
            counts = list( count_sorted_list_items(inp) )
            print inp, exp_outp, counts
            self.assertEqual(counts, exp_outp)

        inp, exp_outp = UNSORTED_FAIL = ([2,2,4,2], [(2,3), (4,1)])
        self.assertEqual(exp_outp, list( count_sorted_list_items(inp) ))
        # ... [(2,2), (4,1), (2,1)]

Answer 16

It was suggested to use numpy's bincount<\/a> , however it works only for 1d arrays with non-negative integers<\/em> . Also, the resulting array might be confusing (it contains the occurrences of the integers from min to max of the original list, and sets to 0 the missing integers).

It returns a tuple with an array of the unique values and an array of the occurrences of each unique value.

# a = [1, 1, 0, 2, 1, 0, 3, 3]
a_uniq, counts = np.unique(a, return_counts=True)  # array([0, 1, 2, 3]), array([2, 3, 1, 2]

Answer 17

To count the number of diverse elements having a common type:

li = ['A0','c5','A8','A2','A5','c2','A3','A9']

print sum(1 for el in li if el[0]=='A' and el[1] in '01234')

Answer 18

You can also use countOf<\/code><\/a> method of a built-in module operator<\/code><\/a> .

>>> import operator
>>> operator.countOf([1, 2, 3, 4, 1, 4, 1], 1)
3

Answer 19

I would use filter()<\/code> , take Lukasz's example:

>>> lst = [1, 2, 3, 4, 1, 4, 1]
>>> len(filter(lambda x: x==1, lst))
3

Answer 20

use %timeit to see which operation is more efficient. np.array counting operations should be faster.

 from collections import Counter
 mylist = [1,7,7,7,3,9,9,9,7,9,10,0] 
 types_counts=Counter(mylist)
 print(types_counts)

Answer 21

May not be the most efficient, requires an extra pass to remove duplicates.

arr = np.array(['a','a','b','b','b','c'])
print(set(map(lambda x  : (x , list(arr).count(x)) , arr)))

Answer 22

Given a list X

 import numpy as np
 X = [1, -1, 1, -1, 1]

Answer 23

sum([1 for elem in <yourlist> if elem==<your_value>])

这将返回 your_value 的出现次数

Answer 24

Alternatively, you can also implement the counter by yourself. This is the way I do:

item_list = ['me', 'me', 'you', 'you', 'you', 'they']

occ_dict = {}

for item in item_list:
    if item not in occ_dict:
        occ_dict[item] = 1
    else:
        occ_dict[item] +=1

print(occ_dict)

Answer 25

if you want a number of occurrences for the particular element:

>>> from collections import Counter
>>> z = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> single_occurrences = Counter(z)
>>> print(single_occurrences.get("blue"))
3
>>> print(single_occurrences.values())
dict_values([3, 2, 1])

Answer 26

l2=[1,"feto",["feto",1,["feto"]],['feto',[1,2,3,['feto']]]]
count=0
 def Test(l):   
        global count 
        if len(l)==0:
             return count
        count=l.count("feto")
        for i in l:
             if type(i) is list:
                count+=Test(i)
        return count   
    print(Test(l2))

Answer 27

mot = ["compte", "france", "zied"]
lst = ["compte", "france", "france", "france", "france"]
dict((x, lst.count(x)) for x in set(mot))

Answer 28

For this topic I know the below six ways by which you can count the number of occurrences of the element in the list:

1) Using count() method

count() is the in-built function by which python count occurrences in list. It is the easiest among all other methods used to count the occurrence. Count() methods take one argument, ie, the element for which the number of occurrences is to be counted.

For example:

sample_list = ["a", "ab", "a", "abc", "ab", "ab"]
print(sample_list.count("a"))
print(sample_list.count("ab"))

Output

 2 3

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2) Using a loop

Another simple approach to counting the occurrence is by using a loop with the counter variable. Here, the counter variable keeps increasing its value by one each time after traversing through the given element. At last, the value of the counter variable displays the number of occurrences of the element.

For example:

def countElement(sample_list, element):
    return sample_list.count(element)


sample_list = ["a", "ab", "a", "abc", "ab", "ab"]
element = "ab"
print('{} has occurred {} times'.format(element, countElement(sample_list, element)))

Output

 ab has occurred 3 times

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3) Using countof() method

Operator module from python library consists of countof() method which helps to return the number of occurrence of the element from the lists. This method takes two arguments, ie, the list in which the count needs to be performed and the element which needs to be found. Moreover, you have to import the operator module before beginning the program using the import keyword as shown below:

For example:

sample_list = ["a", "ab", "a", "abc", "ab", "ab"]

import operator as op

print(op.countOf(sample_list,"a"))

Output

 2

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4) Using counter() method

Python possesses an in-built module named collections, including multiple methods to ease your programming. One such method is a counter() method where elements are stored as a dictionary with keys and counts as values.

Therefore, the counter() method helps you return the total number of occurrences of a given element inside the given list by taking one parameter as the list in which the element is to be counted. Remember that you have to import the collections module to use the counter() method as shown in the below example:

For example:

sample_list = ["a", "ab", "a", "abc", "ab", "ab"]

from collections import Counter

print(Counter(sample_list))

c = Counter(sample_list) 
print(c["a"])

Output

 Counter({'ab': 3, 'a': 2, 'abc': 1}) 2

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5) Using pandas library

Pandas is the in-built python library, highly popular for data analysis and data manipulation. It is an open-source tool with a large range of features and is widely used in the domains like machine learning and artificial intelligence.

Pandas possess a wide range of default methods, one of which is the value_count() method. Along with the value_count() method, pandas use series, ie, a one-dimensional array with axis label.

To count the occurrence of elements using pandas, you have to convert the given list into the series and then use the value_count() method, which returns the object in descending order. By these, you can easily note that the first element is always the most frequently occurring element.

Check out the below example for a better understanding of the Pandas library

For example:

import pandas as pd

sample_list = ["a", "ab", "a", "abc", "ab", "ab"]
count = pd.Series(sample_list).value_counts()
print(count["a"])

Output

 2

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6) Using loops and dict in python

This is the most traditional method by which python count occurrences in the list that is by using the loop, conditional statement, and dictionaries. By this method, you have to create the empty dictionary and then iterate over the list. Later, check if the element present in the list is available in the dictionary or not. If yes, then increase its value by one; otherwise, introduce a new element in the dictionary and assign 1 to it. Repeat the same process until all the elements in the lists are visited.

Remember that this method is quite different from the previous method using the loop and the counter variable. The early mentioned method does not make use of dictionary data structure, whereas this one does. At last, print the count of occurrence of each element as shown in the below example:

For example:

sample_list = ["a", "ab", "a", "abc", "ab", "ab"]

def countOccurrence(a):
  k = {}
  for j in a:
    if j in k:
      k[j] +=1
    else:
      k[j] =1
  return k

print(countOccurrence(sample_list))

Output

 {'a': 2, 'ab': 3, 'abc': 1}

Answer 29

a  =[random.randint(0,100) for i in range(100)]
list(zip(set(a),[a.count(i) for i in set(a)]))

Answer 30

test = [409.1, 479.0, 340.0, 282.4, 406.0, 300.0, 374.0, 253.3, 195.1, 269.0, 329.3, 250.7, 250.7, 345.3, 379.3, 275.0, 215.2, 300.0]

for i in test:
    print('{} numbers {}'.format(i, test.count(i)))

Answer 31

import pandas as pd
test = [409.1, 479.0, 340.0, 282.4, 406.0, 300.0, 374.0, 253.3, 195.1, 269.0, 329.3, 250.7, 250.7, 345.3, 379.3, 275.0, 215.2, 300.0]

#turning the list into a temporary dataframe
test  = pd.DataFrame(test)

#using the very convenient value_counts() function
df_counts = test.value_counts()
df_counts

then you can use df_counts.index and df_counts.values to get the data.

Answer 32

x = ['Jess', 'Jack', 'Mary', 'Sophia', 'Karen',
     'Addison', 'Joseph','Jack', 'Jack', 'Eric', 'Ilona', 'Jason']
the_item = input('Enter the item that you wish to find : ')
how_many_times = 0 
for occurrence in x:
     if occurrence == the_item : 
          how_many_times += 1
print('The occurrence of', the_item, 'in', x,'is',how_many_times) 

Created a list of names wherein the name 'Jack' is repeated. In order to check its Occurrence, I ran a for loop in the list named x . Upon each iteration, if the loop variable attains the value same that of received from the user and stored in the variable the_item , the variable how_many_times gets incremented by 1. After attaining some value...We print how_many_times which stores the value of the occurance of the word 'jack'

Answer 33

def countfrequncyinarray(arr1):
    r=len(arr1)
    return {i:arr1.count(i) for i in range(1,r+1)}
arr1=[4,4,4,4]
a=countfrequncyinarray(arr1)
print(a)