implementing np.where not behaving as expected when using complex conditions in NumPy 1.24
I'm working through a tutorial and I'm converting an old project and Quick question that's been bugging me - I've looked through the documentation and I'm still confused about I've looked through the documentation and I'm still confused about I'm trying to use `np.where` to filter values in a 2D NumPy array based on multiple conditions, but I'm getting unexpected results..... I have the following array: ```python import numpy as np data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) ``` I want to get the indices of elements that are greater than 2 and less than 8. My initial attempt looks like this: ```python condition = (data > 2) & (data < 8) indices = np.where(condition) ``` However, when I print `indices`, it returns a tuple of arrays, which is expected, but when I try to access the elements like this: ```python filtered_values = data[indices] ``` I expected to get an array of values `[3, 4, 5, 6, 7]`, but instead, I get `[3, 4, 5, 6]`, missing `7`. I suspect that the scenario might be with how I'm interpreting the condition, but I'm not sure why it's excluding `7`. I also tried using `np.flatnonzero(condition)` as an alternative, but I still get the same output. It seems like I might be misunderstanding how to use `np.where` with multiple conditions or how to properly filter the values. Can anyone help clarify what's going wrong here? Is there a better approach? I'm working on a web app that needs to handle this. Any pointers in the right direction? My development environment is Debian. I'm working on a application that needs to handle this. Any advice would be much appreciated. For reference, this is a production mobile app. Thanks for your help in advance!