Learn about NumPy, the most useful Python library for data science and numerical computing.
Overview
Syllabus
Introduction
- Take advantage of the power of NumPy
- What you should know
- Why should you use NumPy?
- Python lists vs. NumPy arrays
- Jupyter Notebook basics
- 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
- Adding, removing, and sorting elements
- Copies and views
- Reshaping arrays
- Indexing and slicing
- Joining and splitting arrays
- Arithmetic operations and functions
- Broadcasting
- Aggregate functions
- How to get unique items and counts
- Transpose like operations
- Reversing an array
- Next steps
Taught by
Terezija Semenski
