Arrays - selecting

NumPy - The Basics

NumPyPython

Boolean indexing selects array elements that satisfy a condition.
The condition returns a boolean array (True / False) of the same shape.
Use logical operators to combine multiple conditions:
- & - logical AND
- | - logical OR
- ~ - logical NOT
Parentheses are required around each condition when combining with & or |.
The result is a 1D array of elements where the condition(s) is True.

How it works:

A condition is applied to the array → produces a boolean mask.
The boolean mask is used to select only the True elements.
You can combine multiple conditions with parentheses to create complex selection logic.

Examples:

import numpy as np

arr = np.array([1, 3, 5, 7, 9, 12, 17, 20])

# Single condition

print("arr < 7:", arr[arr < 7])

# → [1 3 5]

# Multiple conditions (AND)

print("arr > 4 AND arr <= 17:", arr[(arr > 4) & (arr <= 17)])

# → [5 7 9 12 17]

# Multiple conditions (OR)

print("arr <=2 OR arr > 18 OR arr == 9:", arr[((arr <= 2) | (arr > 18)) | (arr == 9)])

# → [1 9 20]