Intro to NumPy: Mastering Data Manipulation with NumPy

ACI Learning

Justin Dennison

Cherokee Boose

Peter van Rysdam

€187.99

Video Jun 2024 4hrs 51mins 1st Edition

ACI Learning

Justin Dennison

Cherokee Boose

Peter van Rysdam

€187.99

Video Jun 2024 4hrs 51mins 1st Edition

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

View table of contents

Key benefits

Comprehensive coverage of NumPy basics and advanced operations
Practical exercises on data visualization and graphing
Hands-on project on time series analysis

Description

Embark on a foundational journey with NumPy, starting with an overview and setting up the scientific Python environment. This course refreshes Python basics using Jupyter notebooks, preparing you to explore NumPy arrays. Learn array creation, manipulation, and the various supported data types, building a strong foundation for complex operations. Progress through essential concepts like indexing, slicing, and the differences between copies and views of arrays. Discover the power of elementwise and broadcasting operations for efficient numerical computations. Engage in hands-on exercises in graphing and visualization to present your data effectively. Topics such as reduction, shape, and sort operations are covered in detail, equipping you to manipulate large datasets with ease. In the final section, delve into specialized topics like structured arrays and data type management, including casting and size considerations. The course culminates in a practical project on time series analysis, applying all the skills learned to real-world data. This project-based approach ensures you understand both the theoretical aspects and gain practical experience using NumPy for scientific computing and data analysis.

Who is this book for?

This course is designed for data scientists, engineers, and technical professionals with a basic understanding of Python. Prerequisites include familiarity with Python programming and an eagerness to learn about scientific computing and data manipulation.