R and Python for Oceanographers

R and Python for Oceanographers
Author: Hakan Alyuruk,Murat Gunduz
Publsiher: Elsevier
Total Pages: 300
Release: 2019-06-15
ISBN 10: 9780128134917
ISBN 13: 0128134917
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

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.

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.

Chemical Oceanography

Chemical Oceanography
Author: Steven R. Emerson,Roberta C. Hamme
Publsiher: Cambridge University Press
Total Pages: 500
Release: 2022-03-31
ISBN 10: 1107179890
ISBN 13: 9781107179899
Language: EN, FR, DE, ES & NL

Chemical Oceanography Book Review:

A broad, clear introductory textbook on chemical oceanography for undergraduate and graduate students and a reference text for researchers.

Time Series Data Analysis in Oceanography

Time Series Data Analysis in Oceanography
Author: Chunyan Li
Publsiher: Cambridge University Press
Total Pages: 483
Release: 2022-05-05
ISBN 10: 1108474276
ISBN 13: 9781108474276
Language: EN, FR, DE, ES & NL

Time Series Data Analysis in Oceanography Book Review:

Textbook for students and researchers in oceanography and Earth science on theory and practice of time series analysis using MATLAB.

Python and R for the Modern Data Scientist

Python and R for the Modern Data Scientist
Author: Rick J. Scavetta,Boyan Angelov
Publsiher: "O'Reilly Media, Inc."
Total Pages: 198
Release: 2021-06-22
ISBN 10: 1492093378
ISBN 13: 9781492093374
Language: EN, FR, DE, ES & NL

Python and R for the Modern Data Scientist Book Review:

Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together

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

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.

Mastering Python Scientific Computing

Mastering Python Scientific Computing
Author: Hemant Kumar Mehta
Publsiher: Packt Publishing Ltd
Total Pages: 300
Release: 2015-09-23
ISBN 10: 1783288833
ISBN 13: 9781783288830
Language: EN, FR, DE, ES & NL

Mastering Python Scientific Computing Book Review:

A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered. Most of the Python APIs and tools used in scientific computing are discussed in detail The concepts are discussed with suitable example programs Who This Book Is For If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming. What You Will Learn Fundamentals and components of scientific computing Scientific computing data management Performing numerical computing using NumPy and SciPy Concepts and programming for symbolic computing using SymPy Using the plotting library matplotlib for data visualization Data analysis and visualization using Pandas, matplotlib, and IPython Performing parallel and high performance computing Real-life case studies and best practices of scientific computing In Detail In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing. At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python. The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs. Style and approach This book follows a hands-on approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.

Algorithms For Dummies

Algorithms For Dummies
Author: John Paul Mueller,Luca Massaron
Publsiher: John Wiley & Sons
Total Pages: 432
Release: 2017-04-24
ISBN 10: 1119330491
ISBN 13: 9781119330493
Language: EN, FR, DE, ES & NL

Algorithms For Dummies Book Review:

Discover how algorithms shape and impact our digital world All data, big or small, starts with algorithms. Algorithms are mathematical equations that determine what we see—based on our likes, dislikes, queries, views, interests, relationships, and more—online. They are, in a sense, the electronic gatekeepers to our digital, as well as our physical, world. This book demystifies the subject of algorithms so you can understand how important they are business and scientific decision making. Algorithms for Dummies is a clear and concise primer for everyday people who are interested in algorithms and how they impact our digital lives. Based on the fact that we already live in a world where algorithms are behind most of the technology we use, this book offers eye-opening information on the pervasiveness and importance of this mathematical science—how it plays out in our everyday digestion of news and entertainment, as well as in its influence on our social interactions and consumerism. Readers even learn how to program an algorithm using Python! Become well-versed in the major areas comprising algorithms Examine the incredible history behind algorithms Get familiar with real-world applications of problem-solving procedures Experience hands-on development of an algorithm from start to finish with Python If you have a nagging curiosity about why an ad for that hammock you checked out on Amazon is appearing on your Facebook page, you'll find Algorithm for Dummies to be an enlightening introduction to this integral realm of math, science, and business.

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.

Proceedings of the 10th Ph D Retreat of the HPI Research School on Service oriented Systems Engineering

Proceedings of the 10th Ph D  Retreat of the HPI Research School on Service oriented Systems Engineering
Author: Meinel, Christoph , Plattner, Hasso , Döllner, Jürgen , Weske, Mathias , Polze, Andreas , Hirschfeld, Robert , Naumann, Felix , Giese, Holger , Baudisch, Patrick , Friedrich, Tobias , Müller, Emmanuel
Publsiher: Universitätsverlag Potsdam
Total Pages: 255
Release: 2018-01-17
ISBN 10: 3869563907
ISBN 13: 9783869563909
Language: EN, FR, DE, ES & NL

Proceedings of the 10th Ph D Retreat of the HPI Research School on Service oriented Systems Engineering Book Review:

Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application. Commonly used technologies, such as J2EE and .NET, form de facto standards for the realization of complex distributed systems. Evolution of component systems has lead to web services and service-based architectures. This has been manifested in a multitude of industry standards and initiatives such as XML, WSDL UDDI, SOAP, etc. All these achievements lead to a new and promising paradigm in IT systems engineering which proposes to design complex software solutions as collaboration of contractually defined software services. Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.

Earth Observation Using Python

Earth Observation Using Python
Author: Rebekah B. Esmaili
Publsiher: John Wiley & Sons
Total Pages: 304
Release: 2021-08-04
ISBN 10: 1119606918
ISBN 13: 9781119606918
Language: EN, FR, DE, ES & NL

Earth Observation Using Python Book Review:

Learn basic Python programming to create functional and effective visualizations from earth observation satellite data sets Thousands of satellite datasets are freely available online, but scientists need the right tools to efficiently analyze data and share results. Python has easy-to-learn syntax and thousands of libraries to perform common Earth science programming tasks. Earth Observation Using Python: A Practical Programming Guide presents an example-driven collection of basic methods, applications, and visualizations to process satellite data sets for Earth science research. Gain Python fluency using real data and case studies Read and write common scientific data formats, like netCDF, HDF, and GRIB2 Create 3-dimensional maps of dust, fire, vegetation indices and more Learn to adjust satellite imagery resolution, apply quality control, and handle big files Develop useful workflows and learn to share code using version control Acquire skills using online interactive code available for all examples in the book The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more about this book from this Q&A with the Author

Deep Learning with Python

Deep Learning with Python
Author: Francois Chollet
Publsiher: Simon and Schuster
Total Pages: 384
Release: 2017-11-30
ISBN 10: 1638352046
ISBN 13: 9781638352044
Language: EN, FR, DE, ES & NL

Deep Learning with Python Book Review:

Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

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.

Examining the Roles of Teachers and Students in Mastering New Technologies

Examining the Roles of Teachers and Students in Mastering New Technologies
Author: Podovšovnik, Eva
Publsiher: IGI Global
Total Pages: 434
Release: 2020-02-21
ISBN 10: 1799821064
ISBN 13: 9781799821069
Language: EN, FR, DE, ES & NL

Examining the Roles of Teachers and Students in Mastering New Technologies Book Review:

The development of technologies, education, and economy play an important role in modern society. Digital literacy is important for personal development and for the economic growth of society. Technological learning provides students with specific knowledge and capabilities for using new technologies in their everyday lives and in their careers. Examining the Roles of Teachers and Students in Mastering New Technologies is a critical scholarly resource that examines computer literacy knowledge levels in students and the perception of computer use in the classroom from various teacher perspectives. Featuring a wide range of topics such as higher education, special education, and blended learning, this book is ideal for teachers, instructional designers, curriculum developers, academicians, policymakers, administrators, researchers, and students.

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.

Essentials of Paleomagnetism

Essentials of Paleomagnetism
Author: Lisa Tauxe
Publsiher: Univ of California Press
Total Pages: 489
Release: 2010-03-19
ISBN 10: 0520260317
ISBN 13: 9780520260313
Language: EN, FR, DE, ES & NL

Essentials of Paleomagnetism Book Review:

"This book by Lisa Tauxe and others is a marvelous tool for education and research in Paleomagnetism. Many students in the U.S. and around the world will welcome this publication, which was previously only available via the Internet. Professor Tauxe has performed a service for teaching and research that is utterly unique."—Neil D. Opdyke, University of Florida