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Скачать или смотреть Efficiently Matching Dictionary Keys with 3D Coordinate Lists in Python

  • vlogize
  • 2025-09-17
  • 0
Efficiently Matching Dictionary Keys with 3D Coordinate Lists in Python
Matching the keys of a dictionary with a reference list and getting the valuespythonlistdictionary
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Описание к видео Efficiently Matching Dictionary Keys with 3D Coordinate Lists in Python

Learn how to match keys of a dictionary with coordinates in a 3D list to extract values in Python with clear examples and step-by-step guidance.
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This video is based on the question https://stackoverflow.com/q/62970815/ asked by the user 'Carlos Eduardo Corpus' ( https://stackoverflow.com/u/12954626/ ) and on the answer https://stackoverflow.com/a/62970859/ provided by the user 'Andrej Kesely' ( https://stackoverflow.com/u/10035985/ ) 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: Matching the keys of a dictionary with a reference list and getting the values

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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.

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Efficiently Matching Dictionary Keys with 3D Coordinate Lists in Python

When working with data structures in Python, you may occasionally need to match keys from a dictionary with coordinates in a multidimensional list. This is a common problem encountered by many developers when handling structured data. In this post, we will explore a method to effectively match keys of a dictionary with a reference list of coordinates and retrieve the corresponding values. We’ll break down the solution step-by-step, ensuring you grasp the concept fully.

The Problem

Imagine you have a 3D list of coordinates that serves as a reference for your data. Alongside this, there is a dictionary whose keys correspond to these coordinates. Your goal is to match each coordinate in the list with its corresponding dictionary key and collect the associated values in a new 3D list.

Let’s consider the provided example of the 3D reference list and corresponding dictionary:

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

In this setup, you want to create a new list that mirrors the structure of reference, where each set of coordinates from reference will point to its corresponding values from mydict.

The Solution

To solve this problem, we can utilize a nested list comprehension to efficiently match the dictionary keys with the coordinates in the 3D list. Here’s how to do it, step-by-step:

Step 1: Convert Coordinates to Tuples

Python dictionaries use tuple keys, so we need to convert the coordinates in the 3D list format into tuples. However, this step can be eliminated as we directly fetch values from the dictionary in the final comprehension.

Step 2: Using List Comprehension for Matching Values

You can use list comprehension to iterate over each sublist and retrieve values from the dictionary based on the coordinates. Here’s the concise code that does exactly that:

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

Step 3: Print the Output

After running the above code, you can use pprint to visualize the new 3D list which contains the matched values:

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

This will result in the following output:

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

Step 4: Understanding the Output Structure

The result, out, preserves the structure of the original reference, but instead of coordinates, you get the corresponding values from the dictionary. This keeps your output clean and organized, exactly as desired.

Conclusion

In this post, we learned how to effectively match dictionary keys with a 3D list of coordinates in Python. By employing list comprehension, we could simplify the process of extracting the necessary values, resulting in a clear and structured output. Whether you're a beginner looking to improve your Python skills or need a reliable way to manage structured data, mastering techniques like these will greatly enhance your coding toolkit.

If you have any questions or need further assistance, feel free to drop a comment below. Happy coding!

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