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Скачать или смотреть How to Merge Two Lists of Dictionaries by Key in Python

  • vlogize
  • 2025-10-07
  • 0
How to Merge Two Lists of Dictionaries by Key in Python
Python: match two list of dictionaries by key and merge matched dictspythonlistdictionarymergeintersection
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Описание к видео How to Merge Two Lists of Dictionaries by Key in Python

Learn how to merge two lists of dictionaries by matching keys in Python with ease. This guide provides effective methods to achieve this efficiently.
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This video is based on the question https://stackoverflow.com/q/64045604/ asked by the user 'An Se' ( https://stackoverflow.com/u/5860340/ ) and on the answer https://stackoverflow.com/a/64046531/ provided by the user 'N. Jonas Figge' ( https://stackoverflow.com/u/14326433/ ) 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: Python: match two list of dictionaries by key and merge matched dicts

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
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.

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Merging Two Lists of Dictionaries by Key in Python

In the world of data manipulation, handling lists of dictionaries is a common scenario in Python. But what happens when you need to merge data from two separate lists based on a common key? This task can be tricky, especially if you're striving for optimal code efficiency and readability. Today, we will unravel a straightforward solution for matching and merging two lists of dictionaries based on a shared key, specifically id.

The Problem

You might have two lists of dictionaries, similar to the following examples:

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

Your goal is to find the intersections of both lists based on the id key and create a new list of merged dictionaries that combine relevant data from both lists. The desired output would look like this:

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

The Solution

Method 1: Nested Loop Approach

One way to tackle this problem is through the use of nested loops. This method is straightforward, where you'll iterate through both lists to compare and merge the items. Here's how you can do it:

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

Explanation of the Code:

A new list, new_dictlist, is created to store the merged dictionaries.

The first loop goes through each item in the small list, denoted as d1.

The second nested loop compares each d1 dictionary with each dictionary d2 in the big list.

If the id values match, a new dictionary is created, merging relevant data from both dictionaries, and appended to new_dictlist.

Method 2: List Comprehension

For those who prefer a more concise and pythonic approach, you can achieve the same result using a list comprehension, which is both elegant and efficient:

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

Breakdown of the One-Liner:

This one-liner utilizes dictionary unpacking ({**x, **y}) to merge dictionaries directly within the list comprehension.

It iterates through every combination of dictionaries from the big and small lists.

The condition if x['id'] == y['id'] ensures that only those dictionaries with matching ids are merged.

Conclusion

In conclusion, both methods presented above effectively solve the problem of merging two lists of dictionaries based on a common key. The nested loop approach is clear and straightforward while the list comprehension offers a more compact solution. Depending on your coding style or project requirements, you can choose either option to implement this functionality in your Python code.

Now, you have the tools to handle dictionary merging like a pro! Give it a try with your datasets and streamline your data processing tasks.

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