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Counting multiple repeating objects in one go has been a massive problem in the programming landscape. Fortunately, python provides several techniques and tools people can take advantage of in order to address this issue. The counter Python provides from its collections offers a pythonic, efficient and clean solution. 

This subclass offers excellent counting features out of the box, something that programmers are always looking for. Understanding what Python counter is and using it effectively is a handy skill that Python developers must learn. 

How Python Counts Objects

There are plenty of situations where people have to count the amount of objects present in a data source for learning how regularly they occur. Simply said, you want to learn what their frequency is. For instance, you may want to determine how often a particular item shows up on a sequence of values or list. Counting items can be incredibly fast and straightforward, especially when lists are short. On the other hand, counting can become quite time consuming and complicated when there is a long list. 

People generally utilize a counter for counting objects effectively. For those who are wondering, a counter is an integer variable that has zero as its initial value. After counting, you have to increment the counter you are using for reflecting the amount of times a certain object shows up in the data source (input). 

Whenever you are counting the amount of times an object shows up, using a single counter would be ideal. However, counting numerous objects is entirely different as you have to form counter for each unique object you are counting. Using a Python dictionary would be a wise choice if you want to count multiple objects in one go. 

The keys in the dictionary will help you save any object you intend on counting. What’s more, the dictionary values can keep track of an object’s repetitions, ensuring the counting process becomes relatively straightforward. 

For instance, if you want to use a dictionary for counting objects that are in sequential form, it would be best to loop over the entire sequence and check whether the object in question is in the dictionary for initializing the key value pair. Once you do so, you can increment the count according to the situation. 

How the Python Counter Works

As mentioned before, the counter is essentially a subclass of the Python dictionary, particularly designed to count hashable objects present in the Python program. This dictionary keeps objects like counts and keys in the form of values. If you want to utilize the counter, you have to offer an iterable or sequence of various hashable objects, which will act as a critical argument towards the constructor of the class. 

The counter initially iterates with the help of input sequence, after which it counts the amount of times a certain object shows up. Now, let us discuss the common techniques programmers utilize for constructing counters:

Counter Construction

You can utilize multiple techniques to develop counter instances, but if your main objective is to count multiple objects simultaneously, it would be best to use an iterable or sequence for beginning the count.

Updating Object Counts

After getting a counter instance, use the .update() command for updating it with brand new counts and objects. Instead of replacing values, the implementation of .update() that counter provides makes sure that existing counts are together. It also develops new pairs of key count whenever it is necessary. 

Programmers can utilize the .update() command with both mappings and iterables as arguments. Remember, if you utilize an iterable, this method will counts the items, after which it makes updates to the counter.

Counter with String

Python considers everything an object, including string. You can easily create Python string by clising characters using double quote. It’s worth remembering that since Python doesn’t recognize character types, it treats the strings as one, which in the programming world is referred to as substring. 

The example mentioned below showcases a string that passed the Counter. Besides returning the dictionary format using the key and value pair, it also takes consideration of pace. 

 

from collections import Counter

my_str = “Welcome to learning programming!”

print(Counter(my_str))

Output:

Counter({‘o’: 3, ‘ ‘: 3, ‘u’: 3, ‘e’: 2, ‘l’: 2, ‘t’: 2, ‘r’: 2, ‘9’: 2, ‘W’: 1,

 ‘c’: 1, ‘m’: 1, ‘G’: 1, ‘T’: 1, ‘i’: 1, ‘a’: 1, ‘s’: 1, ‘!’: 1})

 

Counter with Dictionary

Dictionary contains elements in the form of key and value pair. You have to write these elements within curly brackets. The dictionary converts into hashtable objects after it goes towards the counter. Meanwhile, the elements turn into keys. Below is an example to make things clearer:

from collections import Counter

dict1 =  {‘x’: 4, ‘y’: 2, ‘z’: 2, ‘z’: 2}

print(Counter(dict1))

Output:

Counter({‘x’: 4, ‘y’: 2, ‘z’: 2})

 

Countering with Tuple

Tuple, at its core, is a group of objects split up with the help of commas present in round brackets. Counter offers the count for every element within the tuple. Tuple becomes a hashtable object after it goes to the counter, whereas the elements present in it end up becoming keys and the values represent the total number of elements.

Python Counter – What are the Key Takeaways

In this piece, we discussed what Python Counter is and its way of helping people count numerous objects present within an iterable. Here are the key takeaways of what we learned.

  • Counter utilizes dict object, lists, string and other iterables to count objects as long as they are hashable
  • You must utilize the most_common command if you want to find common elements within collection objects
  • Whenever making use of Counter Class, programmers can come across errors in case there is a unhashable element present within the container object (for example: list object). You can address this issue by taking a list element and converting it into Tuple prior to passing it to Counter Class