Numpy

🔢 NumPy Masterclass and Practice Sheet From Zero to Confident - A Beginner’s Guide to Numerical Computing in Python Who is this for? You know Python basics - lists, loops, functions - and you want to level up into data science. NumPy is your first real step. Everything in data science (Pandas, Scikit-learn, TensorFlow) is built on top of it. 📌 Table of Contents What is NumPy and Why Should You Care? Installing and Importing NumPy Creating Arrays Array Attributes Indexing and Slicing Array Operations - Math Made Easy Universal Functions (ufuncs) Aggregation Functions Reshaping and Transposing Stacking and Splitting Arrays Boolean Masking and Fancy Indexing Broadcasting Working with Random Numbers Linear Algebra with NumPy Sorting and Searching Copies vs Views Saving and Loading Arrays Practice Questions What We Covered + What’s Next 1. What is NumPy and Why Should You Care? Python lists are flexible and easy to use - but they are slow when it comes to heavy number crunching. If you have a million exam scores and want to find the average, a Python loop will take noticeably longer than it should. ...

NumPy Masterclass - From Basics to Advanced Prerequisites: Python basics, lists, loops, functions Install: pip install numpy Import convention: import numpy as np Table of Contents What is NumPy and Why Use It? Creating Arrays Array Properties Indexing and Slicing Modifying Arrays Reshaping and Stacking Math Operations and Broadcasting Universal Functions (ufuncs) Aggregations and Statistics Sorting and Searching Boolean Operations and Masking Random Number Generation Linear Algebra Working with Files Performance Tips and Best Practices 1. What is NumPy and Why Use It? NumPy (Numerical Python) is the foundation of the entire Python data science stack. Pandas, Matplotlib, Scikit-learn, and TensorFlow all build on top of it. ...