NumPy Essential Training: 1 Foundations of NumPy

Learn about NumPy, the most useful Python library for data science and numerical computing.

Introduction

• Introduction
• What you should know

1. NumPy Overview and Introduction to Jupyter Notebook

• Why should you use NumPy?
• Python lists vs. NumPy arrays
• Jupyter Notebook basics

2. NumPy Array Types and Creating NumPy Arrays

• Array types and conversions between types
• Multidimensional arrays
• Creating arrays from lists and other Python structures
• Intrinsic NumPy array creation
• Creating arrays filled with constant values
• Finding the shape and size of an array

3. Manipulate NumPy Arrays

• Adding, removing, and sorting elements
• Copies and views
• Reshaping arrays
• Indexing and slicing
• Joining and splitting arrays

4. Functions and Operations

• Arithmetic operations and functions
• Broadcasting
• Aggregate functions
• How to get unique items and counts
• Transpose like operations
• Reversing an array

Conclusion

• Next steps