Overview
Dictionary comprehension may be a fast way to form a modern dictionary from an existing object like a list, tuple, or dictionary đđ. In this lesson, we'll jump more profound into dictionary comprehension, covering its syntax đđ, how to utilize it, and a few best practices to take after.
What is Dictionary Comprehension?
Dictionary comprehension may be a valuable and flexible feature of Python that can be utilized to form a new dictionary based on an existing iterable object. This iterable object can be a list, tuple, or another lexicon. The syntax for dictionary comprehension is brief and proficient, permitting you to write code more expressively and exquisitely, which can spare you a lot of time and exertion đ.
Using dictionary comprehension, you can quickly filter and change information from the first iterable object while developing the new dictionary đ. This could assist you in disengaging and organizing information in a way that's more important and useful. Additionally, dictionary comprehension permits you to perform complex operations on the data, such as sorting, gathering, and amassing đ, with fair a couple of lines of code đ».
In expansion, lexicon comprehension is open to more than straightforward key-value sets. You can use it to make settled word references, where each key value combined is a word reference. This will be a valuable strategy for organizing and organizing complex information progressively.
Generally, word reference comprehension is a virtual device for any Python engineer who needs to compose efficient, readable, and expressive code. It may be an effective highlight that can assist you in controlling and changing information in various ways, and it is well worth taking the time to memorize and ace.
Syntax
Dictionary comprehension has a simple and elegant syntax that consists of two parts:
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The for loop and the if statement are the two fundamental building blocks of dictionary comprehension. The for loop iterates over the iterable object, and the if statement filters the elements based on a condition.
Let's see some examples of dictionary comprehension in action.
Creating a new dictionary of squared values
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In this example, we're creating a new dictionary called squared_numbers that contains the squared values of the values in the numbers dictionary.
Filtering elements in a dictionary
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In this example, we're creating a new dictionary called even_numbers that contains only the key-value pairs from the numbers dictionary where the value is even.
Using a dictionary comprehension with strings
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In this example, we're creating a new dictionary called word_lengths that contains the length of each word in the word list.
Best Practices
Here are a few best hones to take after when utilizing dictionary comprehension in your code:
Conclusion
Dictionary comprehension efficiently creates a new dictionary from an existing iterable object, such as a list or another dictionary. The syntax for dictionary comprehension is simple and elegant, allowing you to filter and transform data while constructing the new dictionaryđ.
Key Takeaways
Quiz
Answer: a. A way to create a new dictionary from an existing iterable object
Answer: c. both a and b
Answer: c. Use curly braces to enclose the dictionary comprehension
Answer: b. numbers = {'one': 1, 'two': 2, 'three': 3} even_numbers = {key: value for key, value in numbers.items() if value % 2 == 0}
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