NumPy axis=0 and axis=1 Explained Simply

Confused about axis=0 and axis=1 in NumPy? This beginner-friendly tutorial explains the concept in the simplest way possible using real-world examples and 2D arrays.

You'll learn how NumPy performs operations across rows and columns, how sum() and mean() work with the axis parameter, and how to remember the difference between axis=0 and axis=1 forever.

📚 Topics Covered

✔ What is an axis in NumPy?
✔ Understanding Rows and Columns
✔ axis=0 Explained (Column Operations)
✔ axis=1 Explained (Row Operations)
✔ Using sum(axis=0) and sum(axis=1)
✔ Using mean(axis=0) and mean(axis=1)
✔ Real-Life Sales and Student Marks Examples
✔ Common Beginner Mistakes

💻 Example Code
import numpy as np

sales = np.array([
[100, 120, 90],
[80, 95, 110]
])

print(sales.sum(axis=0))
print(sales.sum(axis=1))
🎯 What You'll Learn
How NumPy treats rows and columns
When to use axis=0
When to use axis=1
How to calculate totals and averages per row or per column
The easiest memory trick for understanding axes
🚀 Perfect For
Python Beginners
NumPy Learners
Data Science Students
Machine Learning Beginners
University Students
Anyone struggling with NumPy axes
💡 Easy Memory Trick
axis=0 → Down the columns
axis=1 → Across the rows

After watching this video, you'll never be confused about NumPy axes again!

📌 NumPy Complete Playlist

This video is part of a complete NumPy tutorial series where you'll learn NumPy from beginner to advanced with practical examples and easy explanations.

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Видео NumPy axis=0 and axis=1 Explained Simply канала Quantum Logics