NumPy Array Operations

Last Updated: 09 Nov 2025

NumPy performs them element-wise and super fast (no loops needed).

Hinglish Tip: “NumPy me loop likhne ki zarurat nahi, operations ek saath poore array par apply ho jaate hain — isse code fast aur clean hota hai.”

Basic Arithmetic Operations

These operations happen element-wise — NumPy matches each position in both arrays.

import numpy as np

a = np.array([10, 20, 30, 40])
b = np.array([1, 2, 3, 4])

print(a + b)   # Addition
print(a - b)   # Subtraction
print(a * b)   # Multiplication
print(a / b)   # Division
print(a % b)   # Modulus
print(a ** b)  # Power

Example 1 – scalar + array

arr = np.array([1, 2, 3])
print(arr + 10)          # [11 12 13]

Example 2 – 2-D + 1-D

a = np.array([[1, 2, 3],
              [4, 5, 6]])
b = np.array([10, 20, 30])

print(a + b)
# [[11 22 33]
#  [14 25 36]]

Above concept is called Broadcasting. We will learn more about it later.
Hinglish Tip: “Broadcasting ka matlab hai chhote array ko bada bana ke match kar dena — bina actual copy banaye!”

Built-in Universal Functions (ufuncs)

NumPy provides special mathematical functions called ufuncs that work on entire arrays.

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

print(np.add(a, 5))      # Add scalar to array
print(np.subtract(a, 2)) # Subtract scalar
print(np.multiply(a, 3)) # Multiply by scalar
print(np.divide(a, 2))   # Divide by scalar
print(np.mod(a, 2))      # Modulo

Comparison Operations

We can compare arrays directly — the result is a boolean array.

x = np.array([10, 20, 30])
y = np.array([20, 20, 10])

print(x == y)
print(x > y)
print(x <= y)

array_equal()

  • Two arrays 100% identical in shape AND every single number.
  • equal_nan=True treat NaN as equal
import numpy as np

a = np.array([1, 2, 3])
b = np.array([1, 2, 3])
c = np.array([1, 2, 4])
d = np.array([1, 2, 3, 4])

print(np.array_equal(a, b))   # True   ← perfect match
print(np.array_equal(a, c))   # False  ← one number different
print(np.array_equal(a, d))   # False  ← different length

Insertion and Appending

  • insert() method adds an element to an array at a specified index.
  • append() method adds an element to the end of an array.
arr = np.array([1, 2, 3])
print(arr)

arr.insert(1, 99)
print(arr)
# [1 99 2 3]

arr.append(100)
print(arr)
# [1 99 2 3 100]

Type Casting

  • astype() method changes the data type of an array.
  • dtype attribute returns the data type of an array.
  • dtype.name returns the name of the data type.
arr = np.array([1, 2, 3])
print(arr.dtype)

arr = arr.astype(np.float64)
print(arr.dtype)
← PreviousNext →