Unexpected results from np.argsort with structured arrays in NumPy 1.25
I'm deploying to production and I'm having a hard time understanding I'm deploying to production and I'm learning this framework and Hey everyone, I'm running into an issue that's driving me crazy... I'm trying to sort a structured NumPy array based on one of its fields, but I'm getting unexpected results... I have a structured array where each element has two fields: 'name' (string) and 'age' (integer). I want to sort this array by the 'age' field, but using `np.argsort()` seems to not work as I expected. Here's the code I've been using: ```python import numpy as np # Create a structured array arr = np.array([('Alice', 30), ('Bob', 25), ('Charlie', 35)], dtype=[('name', 'U10'), ('age', 'i4')]) # Attempt to sort by 'age' sorted_indices = np.argsort(arr['age']) sorted_arr = arr[sorted_indices] print(sorted_arr) ``` When I run this, I expect to get the array sorted by age: ``` [('Bob', 25), ('Alice', 30), ('Charlie', 35)] ``` but instead, I get: ``` [('Alice', 30), ('Bob', 25), ('Charlie', 35)] ``` I checked the dtype of the structured array and confirmed that 'age' is indeed an integer. I've also tried using `np.sort()` directly on `arr`, but the output doesn't change. I've looked through the documentation but need to find any mention of restrictions or edge cases for sorting structured arrays. Is there something I'm missing or doing incorrectly here? Any help would be appreciated! This is part of a larger web app I'm building. Any help would be greatly appreciated! For context: I'm using Python on Ubuntu. Any examples would be super helpful. This is happening in both development and production on Windows 10. Thanks in advance! This is happening in both development and production on Windows 10.