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Python | Counter Objects | elements()

  • Difficulty Level : Medium
  • Last Updated : 08 Aug, 2021

Counter class is a special type of object data-set provided with the collections module in Python3. Collections module provides the user with specialized container datatypes, thus, providing an alternative to Python’s general-purpose built-ins like dictionaries, lists, and tuples. 

Counter is a sub-class that is used to count hashable objects. It implicitly creates a hash table of an iterable when invoked.

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elements() is one of the functions of Counter class, when invoked on the Counter object will return an itertool of all the known elements in the Counter object.



Parameters : Doesn’t take any parameters
Return type : Returns an itertool for all the elements with positive count in the Counter object
Errors and Exceptions : 
-> It will print garbage value when directly printed because it returns an itertool, not a specific data-container. 
-> If the count of an item is already initialized in Counter object, then it will ignore the ones with zero and negative values. 
 

Code #1: Working of elements() on a simple data container  

Python3




# import counter class from collections module
from collections import Counter
 
# Creation of a Counter Class object using
# string as an iterable data container
x = Counter("geeksforgeeks")
 
# printing the elements of counter object
for i in x.elements():
    print ( i, end = " ")

Output: 

g g e e e e k k s s f o r 

Code #2: Elements on a variety of Counter Objects with different data-containers  

Python3




# import counter class from collections module
from collections import Counter
 
# Creation of a Counter Class object using
# a string as an iterable data container
# Example - 1
a = Counter("geeksforgeeks")
 
# Elements of counter object
for i in a.elements():
    print ( i, end = " ")
print()
     
# Example - 2
b = Counter({'geeks' : 4, 'for' : 1,
            'gfg' : 2, 'python' : 3})
 
for i in b.elements():
    print ( i, end = " ")
print()
 
# Example - 3
c = Counter([1, 2, 21, 12, 2, 44, 5,
              13, 15, 5, 19, 21, 5])
 
for i in c.elements():
    print ( i, end = " ")
print()             
               
# Example - 4
d = Counter( a = 2, b = 3, c = 6, d = 1, e = 5)
 
for i in d.elements():
    print ( i, end = " ")

Output:

g g e e e e k k s s f o r 
geeks geeks geeks geeks for gfg gfg python python python 
1 2 2 21 21 12 44 5 5 5 13 15 19 
a a b b b c c c c c c d e e e e e 

Code #3: To demonstrate what elements() return when it is printed directly  

Python3




# import Counter from collections
from collections import Counter
 
# creating a raw data-set
x = Counter ("geeksforgeeks")
 
# will return a itertools chain object
# which is basically a pseudo iterable container whose
# elements can be used when called with a iterable tool
print(x.elements())

Output: 

itertools.chain object at 0x037209F0

Code #4: When the count of an item in Counter is initialized with negative values or zero.  

Python3




# import Counter from collections
from collections import Counter
 
# creating a raw data-set using keyword arguments
x = Counter (a = 2, x = 3, b = 3, z = 1, y = 5, c = 0, d = -3)
 
# printing out the elements
for i in x.elements():
    print( "% s : % s" % (i, x[i]), end ="\n")

Output: 

a : 2
a : 2
x : 3
x : 3
x : 3
b : 3
b : 3
b : 3
z : 1
y : 5
y : 5
y : 5
y : 5
y : 5

Note: We can infer from the output that items with values less than 1 are omitted by elements().

Applications: 
Counter object along with its functions are used collectively for processing huge amounts of data. We can see that Counter() creates a hash-map for the data container invoked with it which is very useful than by manual processing of elements. It is one of a very high processing and functioning tools and can even function with a wide range of data too.
 




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