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Showing 4 outstanding Python books published on

Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter

by Wes McKinney

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.
Published on : Sept. 20, 2022
Python version: TH
579 pages

Mathematical Logic through Python

by Gonczarowski Yannai A.

Using a unique pedagogical approach, this text introduces mathematical logic by guiding students in implementing the underlying logical concepts and mathematical proofs via Python programming. This approach, tailored to the unique intuitions and strengths of the ever-growing population of programming-savvy students, brings mathematical logic into the comfort zone of these students and provides clarity that can only be achieved by a deep hands-on understanding and the satisfaction of having created working code
Published on : Sept. 15, 2022
Python version: TH
284 pages

Bioinformatics with Python Cookbook: Use modern Python libraries and applications to solve real-world computational biology problems

by Tiago Antao

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python. This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets.
Published on : Sept. 27, 2022
Python version: TH
360 pages

Full Stack FastAPI, React, and MongoDB: Build Python web applications with the FARM stack

by Marko Aleksendric

The book quickly introduces each element of the stack and then helps you merge them to build a medium-sized web application. You'll set up a document store with MongoDB, build a simple API with FastAPI, and create an application with React. Security is crucial on the web, so you'll learn about authentication and authorization with JSON Web Tokens. You'll also understand how to optimize images, cache responses with Redis, and add additional features to your application as well as explore tips, tricks, and best practices to make your development experience a breeze. Before you know it, you'll be deploying the application to different platforms.
Published on : Sept. 23, 2022
Python version: TH
336 pages