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NumPy II

Array Arithmetic

Learn how to perform element-wise arithmetic on NumPy arrays — adding, subtracting, multiplying, and more — without writing a single loop.

NumPy arrays support arithmetic directly — operations apply to every element at once, with no loop needed.

Adding a number to an array shifts every element by that amount:

import numpy as np
arr = np.array([1, 2, 3, 4])
result = arr + 10
print(result)

Python

Output

The same works for -, *, /, and **. The value on the right applies to every element.

import numpy as np
arr = np.array([2, 4, 6])
print(arr * 3)

Python

 [ 6 12 18]
 Output

 [2 4 6]
 Output

 [5 7 9]
 Output

Two arrays of the same shape can be combined element by element:

import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
print(a + b)
print(a * b)

Python

Output

import numpy as np
a = np.array([10, 20, 30])
b = np.array([1, 2, 3])
print(a - b)

Python

 [ 9 18 27]
 Output

 [10 20 30]
 Output

 [11 22 33]
 Output

The ** operator raises each element to a power:

import numpy as np
arr = np.array([1, 2, 3, 4])
print(arr ** 2)

Python

Output

import numpy as np
arr = np.array([2, 3, 4])
print(arr ** 2 + 1)

Python

 [4 9 16]
 Output

 [ 5 10 17]
 Output

 [3 4 5]
 Output

Division always returns floats, even when values divide evenly:

import numpy as np
arr = np.array([10, 20, 30])
print(arr / 10)

Python

Output

import numpy as np
arr = np.array([6, 9, 12])
print(arr / 3)

Python

 [2. 3. 4.]
 Output

 [2 3 4]
 Output

 [3. 6. 9.]
 Output

You can chain operations — NumPy follows standard order of evaluation just like Python.

import numpy as np
a = np.array([1, 2, 3])
b = np.array([1, 2, 3])
print(a * b + a)

Python

 [1 4 9]
 Output

 [ 2  6 12]
 Output

 [ 3  8 15]
 Output

import numpy as np
arr = np.array([4, 8, 16])
print(arr / 4 * 2)

Python

 [1. 2. 4.]
 Output

 [4 8 16]
 Output

 [2. 4. 8.]
 Output