This tutorial will discuss about unique ways to remove elements from a numpy array based on a mask.
Suppose we have a numpy array of numbers,
# create sample numpy array arr = np.array([20, 25, 15, 30, 22, 18])
Now we want to remove elements from this array based on a boolean array or a mask.
Suppose this is our boolean array,
mask = [False, True, True, True, False, False]
The size of this boolean array or mask should be equal to the size of the original numpy array. This boolean array contains certain True values and certain False values. Now if we pass this boolean array into the subscript operator of the number array like this,
# Use boolean indexing to remove # elements from array arr = arr[mask]
It will select only those values from the array for which this boolean sequence had True value. Basically, it will delete those values from the number array for which this mask had False value.
This way we can remove certain elements from a NumPy array based on a mask.
Let’s see the complete example,
import numpy as np # create sample numpy array arr = np.array([20, 25, 15, 30, 22, 18]) print('Original Array: ') print(arr) # create boolean mask for removing elements mask = [False, True, True, True, False, False] # Use boolean indexing to remove # elements from array arr = arr[mask] print('Array after Removing elements:') print(arr)
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Original Array: [20 25 15 30 22 18] Array after Removing elements: [25 15 30]
We learned how to remove elements from a NumPy Array nased on a mask in Python.
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