Introdu O Linguagem Python
Download Introdu O Linguagem Python PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Introdu O Linguagem Python book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Introduction to Computation and Programming Using Python, revised and expanded edition
An introductory text that teaches students the art of computational problem solving, covering topics that range from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of “data science” for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in a massive open online course (or MOOC) offered by the pioneering MIT-Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.
Introdução à linguagem Python
Author: José Augusto N. G. Manzano
language: pt-BR
Publisher: Novatec Editora
Release Date: 2018-11-21
Este livro apresenta a linguagem Python 3 de forma básica e introdutória para leitores e estudantes de programação que não possuem conhecimentos prévios da linguagem. Neste texto encontra-se a apresentação de detalhes e informações sobre: características básicas da linguagem, tipos de dados built-in; variáveis; constantes internas; operadores aritméticos; expressões aritméticas; operações de entrada e saída; condições; decisões; operadores relacionais e lógicos; desvios condicionais; ações de divisibilidade; expressões condicionais; laços; sub-rotinas como funções e procedimentos; passagem de parâmetro; funções lambda; programação com módulos; tratamento de dados; estruturas de dados; orientação a objetos; manipulação de arquivos externos; constantes para localização geográfica; conversões entre bases numéricas; simulação para definição de constantes; uso do modo terminal ANSI; plataforma cruzada e aplicação com geometria de tartaruga (turtle graphics).
Python for Data Analysis
Author: Wes McKinney
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2017-09-25
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second 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, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples