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Скачать или смотреть Extracting Values from Dictionaries Using Python

  • vlogize
  • 2025-08-10
  • 0
Extracting Values from Dictionaries Using Python
Extract dictionary data which match with other dictionarypythondictionary
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Описание к видео Extracting Values from Dictionaries Using Python

Learn how to extract matching dictionary values in Python effortlessly. This guide explains how to use recursion to match keys and retrieve values from an original dictionary based on a reference dictionary.
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This video is based on the question https://stackoverflow.com/q/65074027/ asked by the user 'PSEUDO' ( https://stackoverflow.com/u/9565432/ ) and on the answer https://stackoverflow.com/a/65074253/ provided by the user 'Aplet123' ( https://stackoverflow.com/u/5923139/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Extract dictionary data which match with other dictionary

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The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
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Extracting Values from Dictionaries Using Python: A Step-by-Step Guide

In the world of programming, handling data structures efficiently is crucial for effective coding. One common challenge you might encounter is needing to extract specific data from nested dictionaries based on a reference. This situation often arises when you have a primary dataset (original dictionary) and a secondary dataset (reference dictionary) that defines what you need. In this post, we'll explore how to extract matching keys and their corresponding values from an original dictionary using Python.

The Problem: Matching Keys in Dictionaries

Imagine you have two dictionaries: an original_dict containing a variety of data and a reference_dict that specifies the keys you want to extract.

Example Dictionaries

Here’s what our original and reference dictionaries look like:

[[See Video to Reveal this Text or Code Snippet]]

Desired Outcome

From these dictionaries, we want to create an extracted_dict that includes only the matching keys from the reference_dict, retaining the values from the original_dict. The expected result would be:

[[See Video to Reveal this Text or Code Snippet]]

The Solution: Using Recursion

To accomplish this, you can use a recursive function that traverses through the dictionaries, matching keys and extracting the required values. Below is a step-by-step breakdown of how the function works.

Step 1: Define the Merge Function

We will define a function merge(value_dict, key_dict) that takes two arguments:

value_dict: This is the original dictionary.

key_dict: This is the reference dictionary.

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Iterate Through the Reference Dictionary

Using a for loop, we will iterate through each key-value pair in the key_dict.

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Handle Nested Dictionaries

If the corresponding value in the original_dict is a dictionary, we need to call the merge function recursively to extract its content.

[[See Video to Reveal this Text or Code Snippet]]

Step 4: Return the Result

Finally, return the ret dictionary containing all the matched keys and values.

[[See Video to Reveal this Text or Code Snippet]]

Step 5: Putting It All Together

Now, you can call this function with your dictionaries:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

In a few simple steps, we have created a recursive function in Python to match keys between two dictionaries and extract the desired values. This solution can be particularly useful in data processing, making your code cleaner and more efficient.

Feel free to adapt and use this function for your specific data extraction needs!

By understanding this approach, you'll be better equipped to work with complex data structures in Python. Happy coding!

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