R and Python for Oceanographers

R and Python for Oceanographers
Author: Hakan Alyuruk
Publsiher: Elsevier
Total Pages: 186
Release: 2019-06-09
ISBN 10: 0128134925
ISBN 13: 9780128134924
Language: EN, FR, DE, ES & NL

R and Python for Oceanographers Book Review:

R and Python for Oceanographers: A Practical Guide with Applications describes the uses of scientific Python packages and R in oceanographic data analysis, including both script codes and graphic outputs. Each chapter begins with theoretical background that is followed by step-by-step examples of software applications, including scripts, graphics, tables and practical exercises for better understanding of the subject. Examples include frequently used data analysis approaches in physical and chemical oceanography, but also contain topics on data import/export and GIS mapping. The examples seen in book provide uses of the latest versions of Python and R libraries. Presents much needed oceanographic data analysis approaches to chemical and physical oceanography Includes examples with software applications (based on Python and R), including free software for the analysis of oceanographic data Provides guidance on how to get started, along with guidance on example code and output

Oceanographic Analysis with R

Oceanographic Analysis with R
Author: Dan E. Kelley
Publsiher: Springer
Total Pages: 290
Release: 2018-10-17
ISBN 10: 1493988441
ISBN 13: 9781493988440
Language: EN, FR, DE, ES & NL

Oceanographic Analysis with R Book Review:

This book presents the R software environment as a key tool for oceanographic computations and provides a rationale for using R over the more widely-used tools of the field such as MATLAB. Kelley provides a general introduction to R before introducing the ‘oce’ package. This package greatly simplifies oceanographic analysis by handling the details of discipline-specific file formats, calculations, and plots. Designed for real-world application and developed with open-source protocols, oce supports a broad range of practical work. Generic functions take care of general operations such as subsetting and plotting data, while specialized functions address more specific tasks such as tidal decomposition, hydrographic analysis, and ADCP coordinate transformation. In addition, the package makes it easy to document work, because its functions automatically update processing logs stored within its data objects. Kelley teaches key R functions using classic examples from the history of oceanography, specifically the work of Alfred Redfield, Gordon Riley, J. Tuzo Wilson, and Walter Munk. Acknowledging the pervasive popularity of MATLAB, the book provides advice to users who would like to switch to R. Including a suite of real-life applications and over 100 exercises and solutions, the treatment is ideal for oceanographers, technicians, and students who want to add R to their list of tools for oceanographic analysis.

Data Science Using Python and R

Data Science Using Python and R
Author: Chantal D. Larose,Daniel T. Larose
Publsiher: Wiley
Total Pages: 240
Release: 2019-04-09
ISBN 10: 1119526817
ISBN 13: 9781119526810
Language: EN, FR, DE, ES & NL

Data Science Using Python and R Book Review:

Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets.

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences
Author: Johnny Wei-Bing Lin
Publsiher: Lulu.com
Total Pages: 186
Release: 2012
ISBN 10: 130007616X
ISBN 13: 9781300076162
Language: EN, FR, DE, ES & NL

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences Book Review:

This book is a mini-course for researchers in the atmospheric and oceanic sciences. "We assume readers will already know the basics of programming... in some other language." - Back cover.

Oceanography and Coastal Informatics Breakthroughs in Research and Practice

Oceanography and Coastal Informatics  Breakthroughs in Research and Practice
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 469
Release: 2018-11-02
ISBN 10: 1522573097
ISBN 13: 9781522573098
Language: EN, FR, DE, ES & NL

Oceanography and Coastal Informatics Breakthroughs in Research and Practice Book Review:

To date, a vast amount of the world’s oceans remains uncharted. With water covering more than 70 percent of the Earth’s surface, maritime and oceanographic exploration and research is vital. Oceanography and Coastal Informatics: Breakthroughs in Research and Practice is a critical source of academic knowledge centered on technologies, methodologies, and practices related to the biological and physical aspects of the ocean and coastal environments. This publication is divided into four sections: climate change and environmental concerns; data analysis and management; fisheries management and ecology; and GIS, geospatial analysis, and localization. This publication is an ideal reference source for oceanographers, marine and maritime professionals, researchers, and scholars interested in current research on various aspects of oceanography and coastal informatics.

Oceanographic and Marine Cross Domain Data Management for Sustainable Development

Oceanographic and Marine Cross Domain Data Management for Sustainable Development
Author: Diviacco, Paolo,Leadbetter, Adam,Glaves, Helen
Publsiher: IGI Global
Total Pages: 425
Release: 2016-09-23
ISBN 10: 1522507019
ISBN 13: 9781522507017
Language: EN, FR, DE, ES & NL

Oceanographic and Marine Cross Domain Data Management for Sustainable Development Book Review:

As human activity makes a greater impact on the environment, sustainability becomes an increasingly imperative goal. With the assistance of current technological innovations, environmental systems can be better preserved. Oceanographic and Marine Cross-Domain Data Management for Sustainable Development is a pivotal resource for the latest research on the collection of environmental data for sustainability initiatives and the associate challenges with this data acquisition. Highlighting various technological, scientific, semantic, and semiotic perspectives, this book is ideally designed for researchers, technology developers, practitioners, students, and professionals in the field of environmental science and technology.

SAS for R Users

SAS for R Users
Author: Ajay Ohri
Publsiher: John Wiley & Sons
Total Pages: 208
Release: 2019-09-24
ISBN 10: 1119256410
ISBN 13: 9781119256410
Language: EN, FR, DE, ES & NL

SAS for R Users Book Review:

BRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER SAS and R are widely-used, very different software environments. Prized for its statistical and graphical tools, R is an open-source programming language that is popular with statisticians and data miners who develop statistical software and analyze data. SAS (Statistical Analysis System) is the leading corporate software in analytics thanks to its faster data handling and smaller learning curve. SAS for R Users enables entry-level data scientists to take advantage of the best aspects of both tools by providing a cross-functional framework for users who already know R but may need to work with SAS. Those with knowledge of both R and SAS are of far greater value to employers, particularly in corporate settings. Using a clear, step-by-step approach, this book presents an analytics workflow that mirrors that of the everyday data scientist. This up-to-date guide is compatible with the latest R packages as well as SAS University Edition. Useful for anyone seeking employment in data science, this book: Instructs both practitioners and students fluent in one language seeking to learn the other Provides command-by-command translations of R to SAS and SAS to R Offers examples and applications in both R and SAS Presents step-by-step guidance on workflows, color illustrations, sample code, chapter quizzes, and more Includes sections on advanced methods and applications Designed for professionals, researchers, and students, SAS for R Users is a valuable resource for those with some knowledge of coding and basic statistics who wish to enter the realm of data science and business analytics. AJAY OHRI is the founder of analytics startup Decisionstats.com. His research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces to cloud computing, investigating climate change, and knowledge flows. He currently advises startups in analytics off shoring, analytics services, and analytics. He is the author of Python for R Users: A Data Science Approach (Wiley), R for Business Analytics, and R for Cloud Computing.

Climate Mathematics

Climate Mathematics
Author: Samuel S. P. Shen,Richard C. J. Somerville
Publsiher: Cambridge University Press
Total Pages: 456
Release: 2019-09-30
ISBN 10: 1108476872
ISBN 13: 9781108476874
Language: EN, FR, DE, ES & NL

Climate Mathematics Book Review:

Presents the core mathematics, statistics, and programming skills needed for modern climate science courses, with online teaching materials.

Data Science and Analytics with Python R and SPSS Programming

Data Science and Analytics  with Python  R and SPSS Programming
Author: V.K. Jain
Publsiher: KHANNA PUBLISHING HOUSE
Total Pages: 276
Release: 2021
ISBN 10: 9386173670
ISBN 13: 9789386173676
Language: EN, FR, DE, ES & NL

Data Science and Analytics with Python R and SPSS Programming Book Review:

The Book has been written completely as per AICTE recommended syllabus on "Data Sciences". SALIENT FEATURES OF THE BOOK: Explains how data is collected, managed and stored for data science. With complete courseware for understand the key concepts in data science including their real-world applications and the toolkit used by data scientists. Implement data collection and management. Provided with state of the arts subjectwise. With all required tutorials on R, Python and Bokeh, Anaconda, IBM SPSS-21 and Matplotlib.

Evaluating Climate Change Impacts

Evaluating Climate Change Impacts
Author: Vyacheslav Lyubchich,Yulia Gel,K. Halimeda Kilbourne,Thomas James Miller,Nathaniel K. Newlands,A. Smith
Publsiher: CRC Press
Total Pages: 382
Release: 2020-10-07
ISBN 10: 1351190814
ISBN 13: 9781351190817
Language: EN, FR, DE, ES & NL

Evaluating Climate Change Impacts Book Review:

Evaluating Climate Change Impacts discusses assessing and quantifying climate change and its impacts from a multi-faceted perspective of ecosystem, social, and infrastructure resilience, given through a lens of statistics and data science. It provides a multi-disciplinary view on the implications of climate variability and shows how the new data science paradigm can help us to mitigate climate-induced risk and to enhance climate adaptation strategies. This book consists of chapters solicited from leading topical experts and presents their perspectives on climate change effects in two general areas: natural ecosystems and socio-economic impacts. The chapters unveil topics of atmospheric circulation, climate modeling, and long-term prediction; approach the problems of increasing frequency of extreme events, sea level rise, and forest fires, as well as economic losses, analysis of climate impacts for insurance, agriculture, fisheries, and electric and transport infrastructures. The readers will be exposed to the current research using a variety of methods from physical modeling, statistics, and machine learning, including the global circulation models (GCM) and ocean models, statistical generalized additive models (GAM) and generalized linear models (GLM), state space and graphical models, causality networks, Bayesian ensembles, a variety of index methods and statistical tests, and machine learning methods. The reader will learn about data from various sources, including GCM and ocean model outputs, satellite observations, and data collected by different agencies and research units. Many of the chapters provide references to open source software R and Python code that are available for implementing the methods.

Python for R Users

Python for R Users
Author: Ajay Ohri
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2017-11-13
ISBN 10: 1119126762
ISBN 13: 9781119126768
Language: EN, FR, DE, ES & NL

Python for R Users Book Review:

The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations—complete with sample code—of R to Python and Python to R. Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Statistical modeling, machine learning, and data mining—including supervised and unsupervised data mining methods—are treated in detail, as are time series forecasting, text mining, and natural language processing. • Features a quick-learning format with concise tutorials and actionable analytics • Provides command-by-command translations of R to Python and vice versa • Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages • Offers numerous comparative examples and applications in both programming languages • Designed for use for practitioners and students that know one language and want to learn the other • Supplies slides useful for teaching and learning either software on a companion website Python for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. Mr. Ohri's research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. His other books include R for Business Analytics and R for Cloud Computing.

Oceanography and Marine Biology

Oceanography and Marine Biology
Author: S. J. Hawkins,A. J. Evans,A.C. Dale,L. B. Firth,I. P. Smith
Publsiher: CRC Press
Total Pages: 510
Release: 2018-11-21
ISBN 10: 0429845758
ISBN 13: 9780429845758
Language: EN, FR, DE, ES & NL

Oceanography and Marine Biology Book Review:

Key features: Explores the implications of long-term climate change for biogeography and ecological processes in the Southern Ocean Updates knowledge of symbiotic polychaetes in light of the last 20 years of research Considers the adaptions and environments of Antarctic marine biodiversity Examines the false hope of cetacean conservation Reviews work in Mediterranean venting systems releasing carbon dioxide as a model for understanding ocean acidification Looks at the impacts and environmental risks of oil spills of marine invertebrates, algae and seagrass Oceanography and Marine Biology: An Annual Review remains one of the most cited sources in marine science and oceanography. The ever increasing interest in work in oceanography and marine biology and its relevance to global environmental issues, especially global climate change and its impacts, creates a demand for authoritative reviews summarizing the results of recent research. OMBAR has catered to this demand since its foundation more than 50 years ago. Following the favourable reception and complimentary reviews accorded to all the volumes, Volume 56 continues to regard the marine sciences—with all their various aspects—as a unity. Physical, chemical, and biological aspects of marine science are dealt with by experts actively engaged in these fields, and every chapter is peer-reviewed by other experts working actively in the specific areas of interest. The series is an essential reference text for researchers and students in all fields of marine science and related subjects, and it finds a place in libraries of universities, marine laboratories, research institutes and government departments. It is consistently among the highest ranking series in terms of impact factor in the marine biology category of the citation indices compiled by the Institute for Scientific Information/Web of Science. Two chapters are available to read Open Access on our Routledge website at https://www.routledge.com/9781138318625

Marketing Data Science

Marketing Data Science
Author: Thomas W. Miller
Publsiher: FT Press
Total Pages: 225
Release: 2015-05-02
ISBN 10: 0133887340
ISBN 13: 9780133887341
Language: EN, FR, DE, ES & NL

Marketing Data Science Book Review:

Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Ocean Circulation in Three Dimensions

Ocean Circulation in Three Dimensions
Author: Barry A. Klinger,Thomas W. N. Haine
Publsiher: Cambridge University Press
Total Pages: 494
Release: 2019-03-31
ISBN 10: 0521768438
ISBN 13: 9780521768436
Language: EN, FR, DE, ES & NL

Ocean Circulation in Three Dimensions Book Review:

An innovative survey of large-scale ocean circulation that links observations, conceptual models, numerical models, and theories.

Python For Everyone

Python For Everyone
Author: Cay S. Horstmann,Rance D. Necaise
Publsiher: Wiley Global Education
Total Pages: 761
Release: 2019-02-21
ISBN 10: 1119498619
ISBN 13: 9781119498612
Language: EN, FR, DE, ES & NL

Python For Everyone Book Review:

Python for Everyone, 3rd Edition is an introduction to programming designed to serve a wide range of student interests and abilities, focused on the essentials, and on effective learning. It is suitable for a first course in programming for computer scientists, engineers, and students in other disciplines. This text requires no prior programming experience and only a modest amount of high school algebra. Objects are used where appropriate in early chapters and students start designing and implementing their own classes in Chapter 9. New to this edition are examples and exercises that focus on various aspects of data science.

The Practice of Reproducible Research

The Practice of Reproducible Research
Author: Justin Kitzes
Publsiher: Univ of California Press
Total Pages: 368
Release: 2017-10-17
ISBN 10: 0520967771
ISBN 13: 9780520967779
Language: EN, FR, DE, ES & NL

The Practice of Reproducible Research Book Review:

The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research. Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.

Atmospheric and Oceanic Fluid Dynamics

Atmospheric and Oceanic Fluid Dynamics
Author: Geoffrey K. Vallis
Publsiher: Cambridge University Press
Total Pages: 135
Release: 2006-11-06
ISBN 10: 1139459961
ISBN 13: 9781139459969
Language: EN, FR, DE, ES & NL

Atmospheric and Oceanic Fluid Dynamics Book Review:

Fluid dynamics is fundamental to our understanding of the atmosphere and oceans. Although many of the same principles of fluid dynamics apply to both the atmosphere and oceans, textbooks tend to concentrate on the atmosphere, the ocean, or the theory of geophysical fluid dynamics (GFD). This textbook provides a comprehensive unified treatment of atmospheric and oceanic fluid dynamics. The book introduces the fundamentals of geophysical fluid dynamics, including rotation and stratification, vorticity and potential vorticity, and scaling and approximations. It discusses baroclinic and barotropic instabilities, wave-mean flow interactions and turbulence, and the general circulation of the atmosphere and ocean. Student problems and exercises are included at the end of each chapter. Atmospheric and Oceanic Fluid Dynamics: Fundamentals and Large-Scale Circulation will be an invaluable graduate textbook on advanced courses in GFD, meteorology, atmospheric science and oceanography, and an excellent review volume for researchers. Additional resources are available at www.cambridge.org/9780521849692.

Mining Imperfect Data

Mining Imperfect Data
Author: Ronald K. Pearson
Publsiher: SIAM
Total Pages: 581
Release: 2020-09-10
ISBN 10: 1611976278
ISBN 13: 9781611976274
Language: EN, FR, DE, ES & NL

Mining Imperfect Data Book Review:

It has been estimated that as much as 80% of the total effort in a typical data analysis project is taken up with data preparation, including reconciling and merging data from different sources, identifying and interpreting various data anomalies, and selecting and implementing appropriate treatment strategies for the anomalies that are found. This book focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them. As both data sources and free, open-source data analysis software environments proliferate, more people and organizations are motivated to extract useful insights and information from data of many different kinds (e.g., numerical, categorical, and text). The book emphasizes the range of open-source tools available for identifying and treating data anomalies, mostly in R but also with several examples in Python. Mining Imperfect Data: With Examples in R and Python, Second Edition presents a unified coverage of 10 different types of data anomalies (outliers, missing data, inliers, metadata errors, misalignment errors, thin levels in categorical variables, noninformative variables, duplicated records, coarsening of numerical data, and target leakage). It includes an in-depth treatment of time-series outliers and simple nonlinear digital filtering strategies for dealing with them, and it provides a detailed introduction to several useful mathematical characteristics of important data characterizations that do not appear to be widely known among practitioners, such as functional equations and key inequalities. While this book is primarily for data scientists, researchers in a variety of fields—namely statistics, machine learning, physics, engineering, medicine, social sciences, economics, and business—will also find it useful.

Statistical Quality Control

Statistical Quality Control
Author: Bhisham C. Gupta
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2021-07-23
ISBN 10: 1119671728
ISBN 13: 9781119671725
Language: EN, FR, DE, ES & NL

Statistical Quality Control Book Review:

STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.

Starting Out with Python

Starting Out with Python
Author: Tony Gaddis
Publsiher: Pearson
Total Pages: 744
Release: 2017-03-06
ISBN 10: 9780134444321
ISBN 13: 0134444329
Language: EN, FR, DE, ES & NL

Starting Out with Python Book Review:

For courses in Python programming. A clear and student-friendly introduction to the fundamentals of Python In Starting Out with Python�, 4th EditionTony Gaddis' accessible coverage introduces students to the basics of programming in a high level language. Python, an easy-to-learn and increasingly popular object-oriented language, allows readers to become comfortable with the fundamentals of programming without the troublesome syntax that can be challenging for novices. With the knowledge acquired using Python, students gain confidence in their skills and learn to recognize the logic behind developing high-quality programs. Starting Out with Python discusses control structures, functions, arrays, and pointers before objects and classes. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real-world examples, focused explanations, and an abundance of exercises appear in every chapter. Updates to the 4th Edition include revised, improved problems throughout, and new Turtle Graphics sections that provide flexibility as assignable, optional material. Also Available with MyLab Programming. MyLab(tm)Programming is an online learning system designed to engage students and improve results. MyLabProgramming consists of programming exercises correlated to the concepts and objectives in this book. Through practice exercises and immediate, personalized feedback, MyLab Programming improves the programming competence of beginning students who often struggle with the basic concepts of programming languages. Note: You are purchasing a standalone product; MyLab Programming does not come packaged with this content. Students, if interested in purchasing this title with MyLab Programming, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab Programming, search for: 0134543661 / 9780134543666 Starting Out with Python Plus MyLab Programming with Pearson eText -- Access Card Package, 4/e Package consists of: 0134444329 / 9780134444321 Starting Out with Python 0134484967 / 9780134484969 MyLab Programming with Pearson eText -- Access Code Card -- for Starting Out with Python Students can use the URL and phone number below to help answer their questions: http://247pearsoned.custhelp.com/app/home 800-677-6337