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.
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( "neveropen" ) # 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
We can also create Counter class object using a list as an iterable data container.
Python3
# import counter class from collections module from collections import Counter #Creating a Counter class object using list as an iterable data container a = [ 12 , 3 , 4 , 3 , 5 , 11 , 12 , 6 , 7 ] x = Counter(a) #directly printing whole x print (x) #We can also use .keys() and .values() methods to access Counter class object for i in x.keys(): print (i, ":" , x[i]) #We can also make a list of keys and values of x x_keys = list (x.keys()) x_values = list (x.values()) print (x_keys) print (x_values) |
Output:
Counter({12: 2, 3: 2, 4: 1, 5: 1, 11: 1, 6: 1, 7: 1}) 12 : 2 3 : 2 4 : 1 5 : 1 11 : 1 6 : 1 7 : 1 [12, 3, 4, 5, 11, 6, 7] [2, 2, 1, 1, 1, 1, 1]
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( "neveropen" ) # Elements of counter object for i in a.elements(): print ( i, end = " " ) print () # Example - 2 b = Counter({ 'Lazyroar' : 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 Lazyroar Lazyroar Lazyroar Lazyroar 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 ( "neveropen" ) # 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.