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Python | Counter Objects | elements()
  • Last Updated : 21 Aug, 2018

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 which is used to count hashable objects. It implicitly creates a hash table of an iterable when invoked.

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




# 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




# 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:

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

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




# 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 intialised with negative values or zero.




# 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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