Unexpected results when using np.unique with return_counts=True on non-integer arrays
Hey everyone, I'm running into an issue that's driving me crazy. I need some guidance on I've been struggling with this for a few days now and could really use some help... I'm experimenting with I tried several approaches but none seem to work... I'm relatively new to this, so bear with me. I've searched everywhere and can't find a clear answer. I'm working with a NumPy array of strings and trying to count the unique occurrences of each string using `np.unique` with the `return_counts=True` option. However, the results don't seem to match my expectations. Here's the code snippet I'm using: ```python import numpy as np arr = np.array(['apple', 'banana', 'apple', 'orange', 'banana', 'kiwi']) unique, counts = np.unique(arr, return_counts=True) print(unique) print(counts) ``` When I run this, I get the following output: ``` ['apple' 'banana' 'kiwi' 'orange'] [2 2 1 1] ``` This is what I expected for `apple` and `banana`, but I was under the impression that the counts should be sorted according to the order of the unique elements. Instead, it appears that the output is sorted alphabetically. Is there a way to modify the output of `np.unique` to return the counts in the same order as the original array? Or should I be using a different approach to achieve this? I've also considered using a dictionary to manually count occurrences, but I wanted to explore the capabilities of NumPy first. Any guidance would be appreciated! Thanks in advance! I'm coming from a different tech stack and learning Python. Thanks for any help you can provide! This is happening in both development and production on Ubuntu 20.04. Thanks for any help you can provide! Thanks for any help you can provide! Any ideas how to fix this?