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R and Python for Oceanographers

R and Python for Oceanographers
Author: Hakan Alyuruk
Publisher: Elsevier
Total Pages: 186
Release: 2019-06-09
Genre: Science
ISBN: 0128134925
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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
Publisher: Springer
Total Pages: 290
Release: 2018-10-17
Genre: Medical
ISBN: 1493988441
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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.

Python and R for the Modern Data Scientist

Python and R for the Modern Data Scientist
Author: Rick J. Scavetta
Publisher: "O'Reilly Media, Inc."
Total Pages: 198
Release: 2021-06-22
Genre: Computers
ISBN: 1492093351
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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
Publisher: John Wiley & Sons
Total Pages: 369
Release: 2017-11-13
Genre: Computers
ISBN: 1119126762
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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.

Chemical Oceanography

Chemical Oceanography
Author: Steven R. Emerson
Publisher: Cambridge University Press
Total Pages: 403
Release: 2022-04-07
Genre: Science
ISBN: 1107179890
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A broad, clear introductory textbook on chemical oceanography for undergraduate and graduate students and a reference text for researchers.

Chemical Oceanography

Chemical Oceanography
Author: Frank J. Millero
Publisher: CRC Press
Total Pages: 594
Release: 2016-04-19
Genre: Science
ISBN: 1482211823
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Over the past ten years, a number of new large-scale oceanographic programs have been initiated. These include the Climate Variability Program (CLIVAR) and the recent initiation of the Geochemical Trace Metal Program (GEOTRACES). These studies and future projects will produce a wealth of information on the biogeochemistry of the world's oceans. Aut

Python and R for the Modern Data Scientist

Python and R for the Modern Data Scientist
Author: Rick J. Scavetta
Publisher: O'Reilly Media
Total Pages: 175
Release: 2021-09-30
Genre:
ISBN: 9781492093404
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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. With this book, data scientists from the Python and R communities will learn how to speak the dialects of each language. By recognizing the strengths of working with both, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Boyan Angelov and Rick Scavetta 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. Not only will you learn how to use Python and R together in real-world settings, but you'll also broaden your knowledge and job opportunities by working 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 real-world case study that demonstrates ways to use these languages together

Oceanographic and Marine Cross-Domain Data Management for Sustainable Development

Oceanographic and Marine Cross-Domain Data Management for Sustainable Development
Author: Diviacco, Paolo
Publisher: IGI Global
Total Pages: 450
Release: 2016-09-23
Genre: Science
ISBN: 1522507019
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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.

Modern Observational Physical Oceanography

Modern Observational Physical Oceanography
Author: Carl Wunsch
Publisher: Princeton University Press
Total Pages: 511
Release: 2015-05-04
Genre: Science
ISBN: 0691158827
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The essential introduction to modern physical oceanography With the advent of computers, novel instruments, satellite technology, and increasingly powerful modeling tools, we know more about the ocean than ever before. Yet we also have a new generation of oceanographers who have become increasingly distanced from the object of their study. Ever fewer scientists collect the observational data on which they base their research. Instead, many download information without always fully understanding how far removed it is from the original data, with opportunity for great misinterpretation. This textbook introduces modern physical oceanography to beginning graduate students in marine sciences and experienced practitioners in allied fields. Real observations are strongly emphasized, as are their implications for understanding the behavior of the global ocean. Written by a leading physical oceanographer, Modern Observational Physical Oceanography explains what the observational revolution of the past twenty-five years has taught us about the real, changing fluid ocean. Unlike any other book, it provides a broad and accessible treatment of the subject, covering everything from modern methods of observation and data analysis to the fluid dynamics and modeling of ocean processes and variability. Fully illustrated in color throughout, the book describes the fundamental concepts that are needed before delving into more advanced topics, including internal-inertial waves, tides, balanced motions, and large-scale circulation physics. Provides an accessible introduction to modern physical oceanography Written by a leading physical oceanographer Emphasizes real observations of the fluid ocean Features hundreds of color illustrations An online illustration package is available to professors

Evaluating Climate Change Impacts

Evaluating Climate Change Impacts
Author: Vyacheslav Lyubchich
Publisher: CRC Press
Total Pages: 395
Release: 2020-10-06
Genre: Mathematics
ISBN: 1351190822
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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 reader 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.