Array filtering in NumPy means selecting elements from an array based on conditions.

What is Numpy Filtering ?

NumPy filtering uses boolean arrays (True/False) to decide which elements to keep.

The boolean array must be the same size as the original array.


Filtering using Boolean Indexing :

Python 
import numpy as np arr = np.array([10, 20, 30, 40, 50]) filtered = arr[arr > 25] print(filtered) #output [30 40 50]


Filtering with Multiple Conditions :

Use logical operators:

  • & → AND

  • | → OR

  • ~ → NOT

Python 
import numpy as np arr = np.array([10, 20, 30, 40, 50]) filtered = arr[(arr > 20) & (arr < 50)] print(filtered) #output [30 40]


Filtering 2D Arrays :
Python 
import numpy as np arr = np.array([[10, 20, 30], [40, 50, 60]]) filtered = arr[arr > 25] print(filtered) #output [30 40 50 60]


Filtering using np.where( ) :

Returns indices instead of values

Python 
import numpy as np arr = np.array([10, 20, 30, 40, 50]) filtered = np.where(arr > 25) print(filtered) #output [2 3 4]