Скачать или смотреть How to Split a NumPy Array by the First Column's Value

Discover simple methods to efficiently `split a NumPy array` based on the values in its first column.
---
This video is based on the question https://stackoverflow.com/q/63001861/ asked by the user 'TheBeautifulOrc' ( https://stackoverflow.com/u/10338680/ ) and on the answer https://stackoverflow.com/a/63002052/ provided by the user 'V. Ayrat' ( https://stackoverflow.com/u/8852551/ ) 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: Split numpy array by value of the first column

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.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Split a NumPy Array by the First Column's Value

Working with NumPy arrays is an everyday task for many Python developers. However, organizing and manipulating these arrays effectively can sometimes pose challenges, particularly when you wish to separate data based on specific criteria. One common requirement is to split a NumPy array based on the values in the first column. In this guide, we’ll explore how to efficiently achieve this task with two different solutions.

Understanding the Problem

Given a NumPy array:

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

We want to split this array into several sub-arrays, where each sub-array contains rows with the same first-column value. The expected output would be structured like this:

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

Solution 1: Using np.array_split for Sorted Data

If the values in the first column are already grouped together, the np.array_split function can be a quick way to achieve the desired split. Here’s how you can implement this:

Step-by-Step Guide

Import NumPy:
Start by importing the NumPy library.

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

Define the Array:
Create the NumPy array as shown below:

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

Split the Array:
Use np.flatnonzero with np.diff to identify the boundaries where the first column changes:

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

Output

This will yield the desired sub-arrays, each containing rows with the same value in the first column.

Solution 2: Sorting the Array First

If your array is not sorted, or if the values in the first column are scattered, you can sort the array first and then split it. Let’s see how it's done:

Step-by-Step Guide

Import NumPy:
Import the necessary library as before.

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

Define and Sort the Array:
Create your array, and use the sort method to sort by the first column:

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

Split the Sorted Array:
After sorting, apply the same logic to split the array:

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

Output

This will properly segregate the rows into respective sub-arrays based on the sorted first column values.

Conclusion

Splitting a NumPy array based on the values in the first column can be accomplished efficiently using either direct array splitting on sorted data or by sorting the data beforehand. Each of these methods is straightforward and can be integrated into larger data processing workflows. As you work with NumPy arrays, keep this approach in mind for cleaner and more organized data handling!