Tagged: Numpy

NumPy's linear algebra object allows you to work with matrices and perform a wide variety of matrix and vector operations.

Arithmetic operations in NumPy (addition, subtraction, multiplication, and division) are element-wise operations that are designed to work efficiently across large arrays.

It is important to differentiate between views and copies when working with NumPy Arrays to ensure you don't accidentally overwrite data in a parent array.

Sub arrays are created using NumPy slice notation which is a powerful data manipulation technique.

This guide serves as an introduction to NumPy and covers array creation, sorting, and concatenation.