Tackle the most sophisticated problems associated with scientific computing and data manipulation using SciPy
About This Book
- Covers a wide range of data science tasks using SciPy, NumPy, pandas, and matplotlib
- Effective recipes on advanced scientific computations, statistics, data wrangling, data visualization, and more
- A must-have book if you're looking to solve your data-related problems using SciPy, on-the-go
Who This Book Is For
Python developers, aspiring data scientists, and analysts who want to get started with scientific computing using Python will find this book an indispensable resource. If you want to learn how to manipulate and visualize your data using the SciPy Stack, this book will also help you. A basic understanding of Python programming is all you need to get started.
What You Will Learn
- Get a solid foundation in scientific computing using Python
- Master common tasks related to SciPy and associated libraries such as NumPy, pandas, and matplotlib
- Perform mathematical operations such as linear algebra and work with the statistical and probability functions in SciPy
- Master advanced computing such as Discrete Fourier Transform and K-means with the SciPy Stack
- Implement data wrangling tasks efficiently using pandas
- Visualize your data through various graphs and charts using matplotlib
In Detail
With the SciPy Stack, you get the power to effectively process, manipulate, and visualize your data using the popular Python language. Utilizing SciPy correctly can sometimes be a very tricky proposition. This book provides the right techniques so you can use SciPy to perform different data science tasks with ease.
This book includes hands-on recipes for using the different components of the SciPy Stack such as NumPy, SciPy, matplotlib, and pandas, among others. You will use these libraries to solve real-world problems in linear algebra, numerical analysis, data visualization, and much more. The recipes included in the book will ensure you get a practical understanding not only of how a particular feature in SciPy Stack works, but also of its application to real-world problems. The independent nature of the recipes also ensure that you can pick up any one and learn about a particular feature of SciPy without reading through the other recipes, thus making the book a very handy and useful guide.
Style and approach
This book consists of hands-on recipes where you'll deal with real-world problems.
You'll execute a series of tasks as you walk through scientific computing challenges using SciPy.
Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.
