interview

home / developersection / interviews / explain the python arrays

Ask Question
ICSM

IT-Hardware & Networking

Ravi Vishwakarma is a dedicated Software Developer with a passion for crafting efficient and innovative solutions. With a keen eye for detail and years of experience, he excels in developing robust software systems that meet client needs. His expertise spans across multiple programming languages and technologies, making him a valuable asset in any software development project.

Message
Can you answer this question?
Answer

1 Answers

ICSM

ICSM

29-Sep-2025

Python Arrays – The Basics

In Python, when people say “arrays,” they might mean two different things:

  • Lists (built-in)
    • Most common “array-like” structure in Python.
    • Can store items of mixed types (e.g., integers, strings, objects).
numbers = [1, 2, 3, 4, 5]
mixed = [1, "hello", 3.14, True]
  • Array module (array library)
    • Provides a true array type (from the array module).
    • Stores elements of a single data type only (like C-style arrays).
    • More memory-efficient than lists for large collections of numbers.
import array

nums = array.array('i', [1, 2, 3, 4, 5])  # 'i' means signed integer
nums.append(6)
print(nums)
  • NumPy arrays (numpy.ndarray)
    • Most powerful, used in data science, machine learning, and scientific computing.
    • Supports multi-dimensional arrays (matrices, tensors).
    • Provides fast vectorized operations.
import numpy as np

arr = np.array([1, 2, 3, 4, 5])
print(arr * 2)  # vectorized operation

Quick Comparison

Feature List array module NumPy Array
Stores mixed types? Yes No (one type only) No (one type only)
Performance Slower Faster than list Fastest (C backend)
Dimensions 1D, nested 1D only Multi-dimensional
Use case General usage Memory efficiency Data science, math
  • So, if you’re coding everyday Python apps: use lists.
  • If you need efficiency with numbers: use array.
  • If you’re working with data or math-heavy stuff: use NumPy.
MindStick Training
MindStick Training

Liked By

We use cookies to ensure you have the best browsing experience on our website. By using our site, you acknowledge that you have read and understood our Cookie Policy & Privacy Policy