Introduction to NumPy

Intermediate Python

Learn how to create and change array shapes to suit your needs

Finally, discover numpy's many data types and how they contribute to speedy array operations

Create new arrays by pulling data based on conditional statements, and add and remove data along any dimension to suit your purpose

Along the way, you’ll learn the shape and dimension compatibility principles to prepare for super-fast array math

You’ll use flipping and transposing functionality to quickly transform our masterpiece

Next, you’ll pull the monet array apart, make changes, and reconstruct it using array stacking to see the results

Leverage numpy’s speedy vectorized operations to gather summary insights on sales data for american liquor stores, restaurants, and department stores

Vectorize python functions for use in your numpy code

Finally, use broadcasting logic to perform mathematical operations between arrays of different sizes