R and Python for Oceanographers Book

R and Python for Oceanographers


  • Author : Hakan Alyuruk
  • Publisher : Elsevier
  • Release Date : 2019-06-09
  • Genre: Science
  • Pages : 186
  • ISBN 10 : 9780128134924
  • Total Read : 71
  • File Size : 10,8 Mb

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R and Python for Oceanographers Summary:

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 Book

R and Python for Oceanographers


  • Author : Hakan Alyuruk
  • Publisher : Elsevier
  • Release Date : 2019-06-15
  • Genre: Science
  • Pages : 300
  • ISBN 10 : 0128134917
  • Total Read : 61
  • File Size : 7,7 Mb

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R and Python for Oceanographers Summary:

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 Book

Oceanographic Analysis with R


  • Author : Dan E. Kelley
  • Publisher : Springer
  • Release Date : 2018-10-17
  • Genre: Medical
  • Pages : 290
  • ISBN 10 : 9781493988440
  • Total Read : 76
  • File Size : 15,5 Mb

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Oceanographic Analysis with R Summary:

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 Book

Oceanography and Coastal Informatics Breakthroughs in Research and Practice


  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release Date : 2018-11-02
  • Genre: Science
  • Pages : 469
  • ISBN 10 : 9781522573098
  • Total Read : 99
  • File Size : 12,5 Mb

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Oceanography and Coastal Informatics Breakthroughs in Research and Practice Summary:

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 Book

Chemical Oceanography


  • Author : Steven R. Emerson
  • Publisher : Cambridge University Press
  • Release Date : 2022-04-07
  • Genre: Science
  • Pages : 403
  • ISBN 10 : 9781107179899
  • Total Read : 97
  • File Size : 16,8 Mb

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Chemical Oceanography Summary:

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 Book

Time Series Data Analysis in Oceanography


  • Author : Chunyan Li
  • Publisher : Cambridge University Press
  • Release Date : 2022-05-05
  • Genre: Computers
  • Pages : 483
  • ISBN 10 : 9781108474276
  • Total Read : 84
  • File Size : 14,7 Mb

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Time Series Data Analysis in Oceanography Summary:

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

Climate Mathematics Book

Climate Mathematics


  • Author : Samuel S. P. Shen
  • Publisher : Cambridge University Press
  • Release Date : 2019-09-19
  • Genre: Science
  • Pages : 417
  • ISBN 10 : 9781108476874
  • Total Read : 65
  • File Size : 12,8 Mb

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Climate Mathematics Summary:

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

Python and R for the Modern Data Scientist Book

Python and R for the Modern Data Scientist


  • Author : Rick J. Scavetta
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2021-06-22
  • Genre: Computers
  • Pages : 199
  • ISBN 10 : 9781492093374
  • Total Read : 85
  • File Size : 6,6 Mb

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Python and R for the Modern Data Scientist Summary:

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