How to Delete Sub-Arrays from Multidimensional Numpy Arrays using a Condition

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How to Delete Sub-Arrays from Multidimensional Numpy Arrays using a Condition

Working with multidimensional arrays in Numpy can sometimes be tricky, especially when it comes to filtering data based on specific criteria. If you find yourself in a situation where you want to delete certain sub-arrays from a Numpy array based on conditions, you're not alone. In this post, we'll explore a common problem and provide a clear solution so you can handle your Numpy arrays more effectively.

The Problem: Removing Specific Sub-Arrays

Let's imagine you’re working with a multidimensional Numpy array and there are certain values within the sub-arrays that you want to filter out. For instance, in the example below, you want to remove all sub-arrays containing the value 999:

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

Step-by-step Explanation

Identify the condition: First, you need to define what condition will determine which sub-arrays to delete. In our case, we want to check for the presence of the value 999.

Implementation

Here’s how you can do this with the provided example:

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

Result

The output will be as desired, keeping only the sub-arrays that do not contain the value 999:

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

Improving Efficiency

If you're looking for ways to improve efficiency for larger datasets, consider these tips:

In your original attempt with win_list_multi and win_list_hyper, you could use similar logic to filter out unwanted entries without a loop.

Conclusion