This book uses the Python 3 language. Python for everybody is designed to introduce students to programming and software development through the lens of exploring data. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. Python for everybody Exploring Data in Python 3.
Python for Everybody: Exploring Data in Python 3 #ad - . The earlier python 2 version of this book is titled "Python for Informatics: Exploring Information". There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www. Py4e. Com.
Automate the Boring Stuff with Python: Practical Programming for Total BeginnersNo Starch Press #ad - Even if you’ve never written a line of code, you can make your computer do the grunt work. If you’ve ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. No starch Press. Once you’ve mastered the basics of programming, merge, and rename files and folders–search the web and download online content–update and format data in Excel spreadsheets of any size–Split, you’ll create Python programs that effortlessly perform useful and impressive feats of automation to:–Search for text in a file or across multiple files–Create, watermark, and encrypt PDFs–Send reminder emails and text notifications–Fill out online formsStep-by-step instructions walk you through each program, move, update, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.
Don’t spend your time doing work a well-trained monkey could do. Learn how in Automate the Boring Stuff with Python. Note: the programs in this book are written to run on Python 3. But what if you could have your computer do them for you?in Automate the Boring Stuff with Python, you’ll learn how to use Python to write programs that do in minutes what would take you hours to do by hand—no prior programming experience required.
Python for Informatics: Exploring InformationCreateSpace Independent Publishing Platform #ad - This book is designed to teach people to program even if they have no prior experience. An updated version of this book that covers Python 3 is available and is titled, "Python for Everybody: Exploring Data in Python 3". All the supporting materials for the book are available under open and remixable licenses at the www.
Py4inf. Com web site. You can think of python as your tool to solve problems that are far beyond the capability of a spreadsheet. No starch Press. There are free downloadable copies of this book in various electronic formats and a self-paced free online course where you can explore the course materials. This book covers Python 2.
Python for Informatics: Exploring Information #ad - It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh, and Linux computers. This book is designed to introduce students to programming and computational thinking through the lens of exploring data.
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPythonO'Reilly Media #ad - It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. 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. Python for data analysis wes mckinney.
. You’ll learn the latest versions of pandas, IPython, NumPy, 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. Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python.
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython #ad - Python for data analysis. Data files and related material are available on GitHub. Use the ipython shell and jupyter notebook for exploratory computinglearn basic and advanced features in NumPy Numerical PythonGet started with data analysis tools in the pandas libraryUse flexible tools to load, transform, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, clean, merge, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, dice, detailed examples No starch Press.
Introduction to Networking: How the Internet WorksCreateSpace Independent Publishing Platform #ad - Understanding how these technologies work is invaluable. Python for data analysis wes mckinney. Python for data analysis. This book was written for everyone - no technical knowledge is required! While this book is not specifically about the Network+ or CCNA certifications, it as a way to give students interested in these certifications a starting point.
No starch Press. This book demystifies the amazing architecture and protocols of computers as they communicate over the Internet. Networks and networked applications are embedded in our lives. While very complex, the Internet operates on a few relatively simple concepts that anyone can understand.
Head First Python: A Brain-Friendly GuideO'Reilly Media #ad - Python for data analysis wes mckinney. Want to learn the python language without slogging your way through how to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built in data structures and functions. Why waste your time struggling with new concepts? This multi sensory learning experience is designed for the way your brain really works.
Python for data analysis. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text heavy approach that puts you to sleep.
Head First Python: A Brain-Friendly Guide #ad - Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. No starch Press. If you’re intrigued by what you can do with context managers, and generators, comprehensions, decorators, it’s all here. O reilly Media.
Learning Python, 5th EditionO'Reilly Media #ad - You’ll also learn some advanced language features that recently have become more common in Python code. Explore python’s major built-in object types such as numbers, and other tools into larger components with modulesdive into classes: Python’s object-oriented programming tool for structuring codeWrite large programs with Python’s exception-handling model and development toolsLearn advanced Python tools, and learn Python’s general syntax modelUse functions to avoid code redundancy and package code for reuseOrganize statements, including decorators, functions, descriptors, metaclasses, and dictionariesCreate and process objects with Python statements, lists, and Unicode processing No starch Press.
Python for data analysis wes mckinney. Python for data analysis. Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. O'reilly Media. O reilly Media. Based on author mark lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python.
Learning Python, 5th Edition #ad - It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, and helpful illustrations, this easy-to-follow, exercises, self-paced tutorial gets you started with both Python 2.7 and 3.
R for Data Science: Import, Tidy, Transform, Visualize, and Model DataO'Reilly Media #ad - You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to:wrangle—transform your datasets into a form convenient for analysisProgram—learn powerful R tools for solving data problems with greater clarity and easeExplore—examine your data, and quickly test themModel—provide a low-dimensional summary that captures true "signals" in your datasetCommunicate—learn R Markdown for integrating prose, code, generate hypotheses, and results No starch Press.
Python for data analysis. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors hadley wickham and garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results.
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data #ad - O reilly Media. Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to r, fluent, a collection of R packages designed to work together to make data science fast, RStudio, and the tidyverse, and fun. Python for data analysis wes mckinney. O'reilly Media. O reilly Media.
Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to ProgrammingNo Starch Press #ad - O reilly Media. This book teaches beginners the basics of programming in Python with a focus on real projects. This is the second edition of the best selling Python book in the world. O reilly Media. O'reilly Media. No starch Press. Python crash course, 2nd edition teaches beginners the essentials of Python quickly so that they can build practical programs and develop powerful programming techniques.
Author eric matthes dispenses with the sort of tedious, Python fundamentals, unnecessary information that can get in the way of learning how to program, choosing instead to provide a foundation in general programming concepts, and problem solving. Second edition of the best selling Python book in the world.
Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming #ad - Python crash course, 2nd Edition is a straightforward introduction to the core of Python programming. A fast-paced, no-nonsense guide to programming in Python. Readers will learn how to create a simple video game, use data visualization techniques to make graphs and charts, and build and deploy an interactive web application.
. Three real world projects in the second part of the book allow readers to apply their knowledge in useful ways. Python for data analysis wes mckinney. Python for data analysis.
Information and Society The MIT Press Essential Knowledge SeriesThe MIT Press #ad - He explores what individuals and societies do with information; offers a basic summary of how collected documents are arranged and described; considers the nature of naming; explains the uses of metadata; and evaluates selection methods, recall, considering relevance, and precision. Using information in its everyday, michael buckland explores the influence of information on what we know, the role of communication and recorded information in our daily lives, nonspecialized sense, and the difficulty or ease of finding information.
Python for data analysis. He examines the physical manifestation of information as documents, the emergence of data sets, and how documents and data are discovered and used. The mit Press. He shows that all this involves human perception, social behavior, changing technologies, and issues of trust. Buckland argues that every society is an “information society”; a “non-information society” would be a contradiction in terms.
Python for data analysis wes mckinney. Buckland describes the rising flood of data, outlines the dramatic long-term growth of documents, and records, documents, and traces the rise of techniques to cope with them. A short, informal account of our ever-increasing dependence on a complex multiplicity of messages, records, documents, and data.
Information and Society The MIT Press Essential Knowledge Series #ad - We live in an information society, or so we are often told. But what does that mean? this volume in the mit press essential Knowledge series offers a concise, documents, informal account of the ways in which information and society are related and of our ever-increasing dependence on a complex multiplicity of messages, records, and data.
Data Science MIT Press Essential Knowledge seriesThe MIT Press #ad - O reilly Media. Python for data analysis wes mckinney. Finally, it considers the future impact of data science and offers principles for success in data science projects. This volume in the mit press essential knowledge series offers a concise introduction to the emerging field of data science, data infrastructure issues, explaining its evolution, current uses, and ethical challenges.
It has never been easier for organizations to gather, store, and process data. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. No starch Press. O'reilly Media. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems.
Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.
Data Science MIT Press Essential Knowledge series #ad - It is closely related to the fields of data mining and machine learning, but broader in scope. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Today data science determines the ads we see online, which emails are filtered into our spam folders, the books and movies that are recommended to us online, and even how much we pay for health insurance.