Introduction to Python Programming And Data Structure By Liang

Your research has generated gigabytes of data and now you need to analyse it. You hate using spreadsheets but it is all you know, so what else can you do? This book will transform how you work with large and complex data sets, teaching you powerful programming tools for slicing and dicing data to suit your needs. Written in a fun and accessible style, this step-by-step guide will inspire and inform non-programmers about the essential aspects of Unix and Perl. It shows how, with just a little programming knowledge, you can write programs that could save you hours, or even days. No prior experience is required and new concepts are introduced using numerous code examples that you can try out for yourself. Going beyond the basics, the authors touch upon many broader topics that will help those new to programming, including debugging and how to write in a good programming style.

Collecting, Managing, and Assessing Data Using Sample Surveys provides a thorough, step-by-step guide to the design and implementation of surveys. Beginning with a primer on basic statistics, the first half of the book takes readers on a comprehensive tour through the basics of survey design. Topics covered include the ethics of surveys, the design of survey procedures, the design of the survey instrument, how to write questions and how to draw representative samples. Having shown readers how to design surveys, the second half of the book discusses a number of issues surrounding their implementation, including repetitive surveys, the economics of surveys, web-based surveys, coding and data entry, data expansion and weighting, the issue of non-response, and the documenting and archiving of survey data. The book is an excellent introduction to the use of surveys for graduate students as well as a useful reference work for scholars and professionals.

This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accom

An approachable and stimulating introduction to Anglo-Saxon literature, this book provides indispensable guidance for students on this important and rewarding area of literary studies. The chapters are clearly organized by topic and significant attention is paid to key individual works, including Beowulf, The Seafarer and writings by Bede. All textual quotations are translated into Modern English, with the original language texts carefully explained. The Introduction synthesizes and develops dominant approaches to Anglo-Saxon literature today, integrating Old English and Latin traditions, and placing the literature in larger historical and theoretical contexts. The structure, style and layout are attractive and user-friendly, including illustrative figures and textboxes, and Magennis provides guidance on resources for studying Anglo-Saxon literature, informing the reader of opportunities for investigating the subject further. Overall, the book enables a thorough understanding and appre

Now available to an English-speaking audience, this book is a comprehensive grammar of classical Nahuatl, the literary language of the Aztecs. It offers students of Nahuatl a complete and clear treatment of the language's structure, grammar and vocabulary. It is divided into 35 chapters, beginning with basic syntax and progressing gradually to more complex structures. Each grammatical concept is illustrated clearly with examples, exercises and passages for translation. A key is provided to allow students to check their answers. By far the most approachable textbook of Nahuatl available, this book will be an excellent teaching tool both for classroom use and for readers pursuing independent study of the language. It will be an invaluable resource to anthropologists, ethnographers, historians, archaeologists and linguists alike.

Margaret Atwood offers an immensely influential voice in contemporary literature. Her novels have been translated into over 22 languages and are widely studied, taught and enjoyed. Her style is defined by her comic wit and willingness to experiment. Her work has ranged across several genres, from poetry to literary and cultural criticism, novels, short stories and art. This Introduction summarizes Atwood's canon, from her earliest poetry and her first novel, The Edible Woman, through The Handmaid's Tale to The Year of the Flood. Covering the full range of her work, it guides students through multiple readings of her oeuvre. It features chapters on her life and career, her literary, Canadian and feminist contexts, and how her work has been received and debated over the course of her career. With a guide to further reading and a clear, well organised structure, this book presents an engaging overview for students and readers.

Organised around problem solving, this book gently introduces the reader to computational simulation of biomedical transport processes, bridging fundamental theory with real-world applications. Using this book the reader will gain a complete foundation to the subject, starting with problem simplification, implementing it in software, through to interpreting the results, validation, and optimisation. Ten case studies, focusing on emerging areas such as thermal therapy and drug delivery, with easy to follow step-by-step instructions, provide ready-to-use templates for further applications. Solution process using the commonly used tool COMSOL Multiphysics is described in detail; useful biomedical property data and correlations are included; and background theory information is given at the end of the book for easy reference. A mixture of short and extended exercises make this book a complete course package for undergraduate and beginning graduate students in biomedical and biochemical eng

What is the nature of syntactic structure? Why do some languages have radically free word order ('nonconfigurationality')? Do parameters vary independently (the micro-view) or can they co-vary en masse (the macro-view)? Mirrors and Microparameters examines these questions by looking beyond the definitional criterion of nonconfigurationality - that arguments may be freely ordered, omitted, and split. Drawing on data from Kiowa, a member of the largely undescribed Kiowa-Tanoan language family, the book reveals that classically nonconfigurational languages can nonetheless exhibit robustly configurational effects. Reconciling the cooccurrence of such freedom with such rigidity has major implications for the Principles and Parameters program. This approach to nonconfigurational languages challenges widespread assumptions of linguistic theory and throws light on the syntactic structures, ordering principles, and nature of parametrization that comprise Universal Grammar.

This introductory text explores the theory of graph spectra: a topic with applications across a wide range of subjects, including computer science, quantum chemistry and electrical engineering. The spectra examined here are those of the adjacency matrix, the Seidel matrix, the Laplacian, the normalized Laplacian and the signless Laplacian of a finite simple graph. The underlying theme of the book is the relation between the eigenvalues and structure of a graph. Designed as an introductory text for graduate students, or anyone using the theory of graph spectra, this self-contained treatment assumes only a little knowledge of graph theory and linear algebra. The authors include many developments in the field which arise as a result of rapidly expanding interest in the area. Exercises, spectral data and proofs of required results are also provided. The end-of-chapter notes serve as a practical guide to the extensive bibliography of over 500 items.

A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.

Written by a team based at one of the world's leading centres for linguistic teaching and research, the second edition of this highly successful textbook offers a unified approach to language, viewed from a range of perspectives essential for students' understanding of the subject. Using clear explanations throughout, the book is divided into three main sections: sounds, words, and sentences. In each, the foundational concepts are introduced, along with their application to the fields of child language acquisition, psycholinguistics, language disorders, and sociolinguistics, giving the book a unique yet simple structure that helps students to engage with the subject more easily than other textbooks on the market. This edition includes a completely new section on sentence use, including an introduction and discussion of core areas of pragmatics and conversational analysis; coverage of sociolinguistic topics, introducing communities of practice; a wealth of new exercise material and upda

R is a programming language, and the name of a software system that implements the language. This book shows how to use the R software package for data analysis, statistical programming, and graphics.

This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.

Combinatory logic and lambda-calculus, originally devised in the 1920s, have since developed into linguistic tools, especially useful in programming languages. The authors' previous book served as the main reference for introductory courses on lambda-calculus for over 20 years: this version is thoroughly revised and offers an account of the subject with the same authoritative exposition. The grammar and basic properties of both combinatory logic and lambda-calculus are discussed, followed by an introduction to type-theory. Typed and untyped versions of the systems, and their differences, are covered. Lambda-calculus models, which lie behind much of the semantics of programming languages, are also explained in depth. The treatment is as non-technical as possible, with the main ideas emphasized and illustrated by examples. Many exercises are included, from routine to advanced, with solutions to most at the end of the book.

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers

This lively and innovative introduction to Shakespeare promotes active engagement with the plays, rather than recycling factual information. Covering a range of texts, it is divided into seven subject-based chapters: Character; Performance; Texts; Language; Structure; Sources and History, and it does not assume any prior knowledge. Instead, it develops ways of thinking and provides the reader with resources for independent research through the 'Where next?' sections at the end of each chapter. The book draws on scholarship without being overwhelmed by it, and unlike other introductory guides to Shakespeare it emphasizes that there is space for new and fresh thinking by students and readers, even on the most-studied and familiar plays.

C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for C# implementation of data structures and algorithms found in the .NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O notation to analyze the efficiency of an approach. Coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. This is the perfect resource for C# professionals and students alike.

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

JavaTech is a practical introduction to the Java programming language with an emphasis on the features that benefit technical computing. After presenting the basics of object-oriented programming in Java, it examines introductory topics such as graphical interfaces and thread processes. It goes on to review network programming and develops Web client-server examples for tasks such as monitoring remote devices. The focus then shifts to distributed computing with RMI. Finally, it examines how Java programs can access the local platform and interact with hardware. Topics include combining native code with Java, communication via serial lines, and programming embedded processors. An extensive web site supports the book with additional instructional materials. JavaTech demonstrates the ease with which Java can be used to create powerful network applications and distributed computing applications. It will be used as a textbook for programming courses, and by researchers who need to learn Jav

Many practical applications require the reconstruction of a multivariate function from discrete, unstructured data. This book gives a self-contained, complete introduction into this subject. It concentrates on truly meshless methods such as radial basis functions, moving least squares, and partitions of unity. The book starts with an overview on typical applications of scattered data approximation, coming from surface reconstruction, fluid-structure interaction, and the numerical solution of partial differential equations. It then leads the reader from basic properties to the current state of research, addressing all important issues, such as existence, uniqueness, approximation properties, numerical stability, and efficient implementation. Each chapter ends with a section giving information on the historical background and hints for further reading. Complete proofs are included, making this perfectly suited for graduate courses on multivariate approximation and it can be used to suppo

John Stuart Mill was the leading British philosopher of the nineteenth century and his famous essay Utilitarianism is the most influential statement of the philosophy of utilitarianism: that actions, laws, policies and institutions are to be evaluated by their utility or contribution to good or bad consequences. Henry West has written the most up-to-date and user-friendly introduction to utilitarianism available. The book serves as both a commentary to and interpretation of the text. It also defends Mill against his critics. An appendix reviews in detail the structure and arguments of Utilitarianism. This book is primarily intended as a textbook for students in philosophy assigned to read Utilitarianism but it should also prove helpful to students and professionals in other fields such as political science, history and economics.

An examples-driven treatment of introductory economic dynamics for students with a basic familiarity with spreadsheets. Shone approaches the subject with the belief that true understanding of a subject can only be achieved by students themselves setting out a problem and manipulating it experimentally. Although all economics students now have access to spreadsheets, they are often used for little more than graphing economic data. This book encourages students to go several stages further and set up and investigate simple dynamic models. The book presents the essentials of macro and micro economic dynamics, including: demand and supply dynamics, Keynesian dynamics, IS-LM, Inflation-unemployment, dynamics of the firm, rational expectations and saddle points, fiscal dynamics and the Maastricht Treaty and Chaos theory. The book contains 50 exercises. The support website contains an additional 100 questions for students and 100 for lecturers: www.cambridge.org/resources/economics.

Fundamentals of OOP and Data Structures in Java is a text for an introductory course on classical data structures. Part One of the book presents the basic principles of Object-Oriented Programming (OOP) and Graphical User Interface (GUI) programming with Java as the example language. Part Two introduces each of the major data structures with supporting, GUI-based laboratory programs designed to reinforce the basic concepts and principles of the text. These laboratories allow the reader to explore and experiment with the properties of each data structure. All source code for the laboratories is available on the web. By integrating the principles of OOP and GUI programming, this book takes the unique path of presenting the fundamental issues of data structures within the context of paradigms that are essential to today's professional software developer. The authors assume the reader has only an elementary understanding of Java and no experience with OOP.

This book, first published in 2000, is a concise introduction to ring theory, module theory and number theory, ideal for a first year graduate student, as well as an excellent reference for working mathematicians in other areas. Starting from definitions, the book introduces fundamental constructions of rings and modules, as direct sums or products, and by exact sequences. It then explores the structure of modules over various types of ring: noncommutative polynomial rings, Artinian rings (both semisimple and not), and Dedekind domains. It also shows how Dedekind domains arise in number theory, and explicitly calculates some rings of integers and their class groups. About 200 exercises complement the text and introduce further topics. This book provides the background material for the authors' companion volume Categories and Modules, soon to appear. Armed with these two texts, the reader will be ready for more advanced topics in K-theory, homological algebra and algebraic number theory

Concurrent Programming in ML focuses on the practical use of concurrency to implement naturally concurrent applications. In addition to a tutorial introduction to programming in Concurrent ML (CML), the book presents three extended examples using CML for practical systems programming: a parallel software build system, a simple concurrent window manager, and an implementation of distributed tuple spaces. CML, which is included as part of the SML of New Jersey (SML/NJ) distribution, combines the best features of concurrent programming and functional programming. This book also illustrates advanced SML programming techniques, and includes a chapter on the implementation of concurrency using features provided by the SML/NJ system. It will be of interest to programmers, students, and professional researchers working in computer language development.

The goal of this book is to provide a comprehensive and systematic introduction to the important and highly applicable method of data refinement and the simulation methods used for proving its correctness. The authors concentrate in the first part on the general principles needed to prove data refinement correct. They begin with an explanation of the fundamental notions, showing that data refinement proofs reduce to proving simulation. The book's second part contains a detailed survey of important methods in this field, which are carefully analysed, and shown to be either incomplete, with counterexamples to their application, or to be always applicable whenever data refinement holds. This is shown by proving, for the first time, that all these methods can be described and analysed in terms of two simple notions: forward and backward simulation. The book is self-contained, going from advanced undergraduate level and taking the reader to the state of the art in methods for proving simula

Fundamentals of Engineering Programming with C and Fortran, first published in 1998, is a beginner's guide to problem solving with computers which shows how to quickly prototype a program for a particular engineering application. The book's side by side coverage of C and Fortran, the predominant computer languages in engineering, is unique. It emphasizes the importance of developing programming skills in C while carefully presenting the importance of maintaining a good reading knowledge of Fortran. Beginning with a brief description of computer architecture, the book then covers the fundamentals of computer programming for problem solving. It devotes separate chapters to data types and operators, control flow, type conversion, arrays, and file operations. The final chapter contains case studies that illustrate particular elements of modeling and visualization. Also included are a number of appendices covering C and Fortran language summaries and other useful topics. This concise and ac

Biologists are notoriously reticent about using mathematics. This textbook is both an introduction to quantitative biology and a guide for the number-shy. Richard Burton fosters a sense of the fundamental importance and usefulness of mathematical principles in biology, with a fascinating range of examples. The book is geared towards the non-mathematician, and covers the basics as well as various more advanced topics from many diverse biological disciplines. Questions and calculations encourage active participation without holding up the reader. A key feature is the structure of the book. Rather than building it around biological disciplines, Dr Burton emphasises the common ways of reasoning used in areas as diverse as insect and population growth, seed mortality and sensory response (to mention a few that use logarithms). Written primarily for beginning undergraduates, this enlightening text will also be an essential aid for students throughout their undergraduate and graduate years.

The complex internal structure of the Sun can now be studied in detail through helioseismology and neutrino astronomy. The VI Canary Islands Winter School of Astrophysics was dedicated to examining these powerful new techniques. Based on this meeting, seven specially written chapters by world experts renowned for their teaching skills are presented in this 1996 volume. With a clear and pedagogical style we are shown how the internal composition (density, He abundance, etc.) and dynamical structure (rotation, sub-surface velocity fields, etc.) of the Sun can be deduced through helioseismology; and how the central temperature can be inferred from measurements of the flux of solar neutrinos. This volume provides an excellent introduction for graduate students and an up-to-date overview for researchers working on the Sun, neutrino astronomy and helio- and asteroseismology.

The rewards and dangers of speculating in the modern financial markets have come to the fore in recent times with the collapse of banks and bankruptcies of public corporations as a direct result of ill-judged investment. At the same time, individuals are paid huge sums to use their mathematical skills to make well-judged investment decisions. Here now is the first rigorous and accessible account of the mathematics behind the pricing, construction and hedging of derivative securities. Key concepts such as martingales, change of measure, and the Heath-Jarrow-Morton model are described with mathematical precision in a style tailored for market practitioners. Starting from discrete-time hedging on binary trees, continuous-time stock models (including Black-Scholes) are developed. Practicalities are stressed, including examples from stock, currency and interest rate markets, all accompanied by graphical illustrations with realistic data. A full glossary of probabilistic and financial terms

This book attempts to uncover the basic form and structure of the Babylonian Talmud, which is a centrally important text in Jewish studies. The contribution made by Dr Jacobs to the study of the Talmud consists in his presentation of the literary principles employed in its composition, and he here presents a clear survey indicating the manner in which earlier material was reworked in order to make each component, or sugya, into a carefully structured and self-consistent unit. Jacobs compares the editors' methods in this regard with the manner in which Shakespeare converted the variety of chronicles and source material available to him into a much more dramatic literary form, which - while preserving the kernel of the story - completely transformed its character and impact. Dr Jacobs' study constitutes an excellent introduction to the Babylonian Talmud and to the nature of rabbinic thinking.

A detailed introduction to the methods used by ecologists--classification and ordination--to clarify and interpret large, unwieldy masses of multivariate field data. Permits ecologists to understand,

This volume is a translated and edited collection of studies on the Shi ji (Records of the historian) by SimaQian, authored by the prestigious Japanese sinologist Miyazaki Ichisada. Providing a pathbreaking analysis of the structure and formation of the Shi ji, it serves not only as an excellent introduction to Sima Qian’s masterpiece but also offers historiographical and methodological insights that will stimulate further debate and research.In this volume, Miyazaki presents fascinating evidence of the influence of narrative fiction and drama in Sima Qian’s recreation of the entire length and breadth of Chinese history right up to his own time. By establishing a foundational model for writing comprehensive histories in China, Sima Qian’s work is essential for understanding the subsequent tradition of historical writing. This volume offers readers valuable insights into how Sima Qian constructed his seminal work.A monument of Japanese scholarship on the Shi ji, Prof. Miyazaki Ichisada’

An Introduction to Global Media for the Twenty-First Century provides a thorough introduction to the field of global media today. The book presents the key changes taking place as the global media landscape evolves, and the main theories of the field, that explain these developments.Tracing, first, the formative development of an international and global media landscape throughout the 20th century from the telegraph, television and film export, and transnational television to the Internet, the book then focuses on developments in the 21st century. This includes: the digitization of the global media and communications sector; the popularization of the Internet and digital infrastructure such as the smartphone and platforms; the emergence of global online media and services; the production and distribution of digital media content; and the exploitation of user data. Case studies illustrate key developments throughout the book.The book shows how the field is characterized by a continuity

This text provides deep and comprehensive coverage of the mathematical background for data science, including machine learning, optimal recovery, compressed sensing, optimization, and neural networks. In the past few decades, heuristic methods adopted by big tech companies have complemented existing scientific disciplines to form the new field of Data Science. This text embarks the readers on an engaging itinerary through the theory supporting the field. Altogether, twenty-seven lecture-length chapters with exercises provide all the details necessary for a solid understanding of key topics in data science. While the book covers standard material on machine learning and optimization, it also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressed sensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background will appreciate the appendice

Now in its fourth edition, this comprehensive introduction of fundamental panel data methodologies provides insights on what is most essential in panel literature. A capstone to the forty-year career of a pioneer of panel data analysis, this new edition's primary contribution will be the coverage of advancements in panel data analysis, a statistical method widely used to analyze two or higher-dimensional panel data. The topics discussed in early editions have been reorganized and streamlined to comprehensively introduce panel econometric methodologies useful for identifying causal relationships among variables, supported by interdisciplinary examples and case studies. This book, to be featured in Cambridge's Econometric Society Monographs series, has been the leader in the field since the first edition. It is essential reading for researchers, practitioners and graduate students interested in the analysis of microeconomic behavior.

Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional str