Counter: A High-Performance Container
Get introduced to the Counter data-type and its functionalities.
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Every language evolves by trying to cope up with the limitations hindering the way to efficiency. With every new stable version, some functionalities are deleted and added to ensure flexibility.
In this lesson, you will come across a container sequence that is still a part of Python 3: Counter (New in version ). Let’s cover it in detail.
Counter datatype
It is a built-in class for counting objects, that implements the concept of multiset that allows elements in a set to have multiple occurrences. Like other languages have bags or multisets, Python has a Counter (an unordered) container. It’s a dict subclass for counting hashable objects. Just like a dictionary, a collection of Counter type holds elements as keys, and the number of occurrences as the value to the keys.
Note: The counts are allowed to be any integer value, including zero or negative counts.
The Counter() constructor either accepts an iterable like a list or a mapping like a dictionary. Run the following program to see the underlying implementation.
from collections import Counterc1 = Counter('Python 3: An In-Depth Exploration') # Using iteratablec2 = Counter({'numbers':10, 'letters': 26}) # Using mapping# Finding number of occurancesprint(c1['o'])print(c2['numbers'])print(c2['alphabets'])
In the code above, you can see that we import Counter at the beginning. Now, look at line 3, we make a Counter type object c1 using an iterable (string). In the next line, we make another Counter object c2, using a dictionary (mapping).
In the second part of the program, we are finding the number of occurrences.
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At line 7, we are finding the count of ‘o’ in
c1using subscript operator[]as:c1['o']. -
At line 8, we are finding the count of ‘numbers’ in
c2. -
What if an element doesn’t exist? It won’t give an error and will return 0 instead. Line 9 verifies ...