European Parliament Library

Environmental data analysis with MATLAB or Python, principles, applications, and prospects, William Menke

Summary
Environmental Data Analysis with MATLAB, Third Edition, is a new edition that expands fundamentally on the original with an expanded tutorial approach, more clear organization, new crib sheets, and problem sets providing a clear learning path for students and researchers working to analyze real data sets in the environmental sciences. The work teaches the basics of the underlying theory of data analysis and then reinforces that knowledge with carefully chosen, realistic scenarios, including case studies in each chapter. The new edition is expanded to include applications to Python, an open source software environment. Significant content in Environmental Data Analysis with MATLAB, Third Edition is devoted to teaching how the programs can be effectively used in an environmental data analysis setting. This new edition offers chapters that can both be used as self-contained resources or as a step-by-step guide for students, and is supplemented with data and scripts to demonstrate relevant use cases
Table Of Contents
Intro -- Environmental Data Analysis with MatLab: Principles, Applications, and Prospects -- Copyright -- Contents -- Preface -- Acknowledgment -- Advice on scripting for beginners -- Chapter 1: Data analysis with MATLAB or Python -- Part A: MATLAB -- 1A.1. Getting started -- 1A.2. Navigating folders -- 1A.3. Simple arithmetic and algebra -- 1A.4. Vectors and matrices -- 1A.5. Addition, subtraction and multiplication of column-vectors and matrices -- 1A.6. Element access -- 1A.7. Representing functions -- 1A.8. To loop or not to loop -- 1A.9. The matrix inverse -- 1A.10. Loading data from a file -- 1A.11. Plotting data -- 1A.12. Saving data to a file -- 1A.13. Some advice on writing scripts -- Think before you type -- Name variables consistently -- Save old scripts -- Cut and paste sparingly -- Start small -- Test your scripts -- Dont be too clever -- Comment your scripts -- Part B: Python -- 1B.1. Installation -- 1B.2. The first cell in the edapy_01 Jupyter Notebook -- 1B.3. A very simple Python script -- 1B.4. Navigating folders -- 1B.5. Simple arithmetic and algebra -- 1B.6. List-like data -- 1B.7. Creating column-vectors and matrices -- 1B.8. Addition, subtraction and multiplication of column-vectors and matrices -- 1B.9. Element access -- 1B.10. Representing functions -- 1B.11. To loop or not to loop -- 1B.12. The matrix inverse -- 1B.13. Loading data from a file -- 1B.14. Plotting data -- 1B.15. Saving data to a file -- 1B.16. Some advice on writing scripts -- Think before you type -- Name variables consistently -- Save old scripts -- Cut and paste sparingly -- Start small -- Test your scripts -- Dont be too clever -- Comment your scripts -- Problems -- Chapter 2: Systematic explorations of a new dataset -- 2.1. Case study: Black rock forest temperature data -- 2.2. More on graphics
Language
eng
Literary Form
non fiction
Copyright
Edition
Third edition.
Physical Description
1 online resource (466 pages)
Specific Material Designation
remote
Form Of Item
online
Isbn
9780323955775

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