Introduction To Python In Earth Science Data Analysis
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Introduction To Python In Earth Science Data Analysis
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Author : Maurizio Petrelli
language : en
Publisher: Springer Nature
Release Date : 2021-09-16
Introduction To Python In Earth Science Data Analysis written by Maurizio Petrelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-16 with Science categories.
This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.
Earth Observation Using Python
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Author : Rebekah B. Esmaili
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-24
Earth Observation Using Python written by Rebekah B. Esmaili and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-24 with Science categories.
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
Python Recipes For Earth Sciences
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Author : Martin H. Trauth
language : en
Publisher: Springer Nature
Release Date : 2022-09-28
Python Recipes For Earth Sciences written by Martin H. Trauth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-28 with Science categories.
Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.
Machine Learning For Earth Sciences
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Author : Maurizio Petrelli
language : en
Publisher: Springer Nature
Release Date : 2023-09-22
Machine Learning For Earth Sciences written by Maurizio Petrelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-22 with Science categories.
This textbook introduces the reader to Machine Learning (ML) applications in Earth Sciences. In detail, it starts by describing the basics of machine learning and its potentials in Earth Sciences to solve geological problems. It describes the main Python tools devoted to ML, the typival workflow of ML applications in Earth Sciences, and proceeds with reporting how ML algorithms work. The book provides many examples of ML application to Earth Sciences problems in many fields, such as the clustering and dimensionality reduction in petro-volcanological studies, the clustering of multi-spectral data, well-log data facies classification, and machine learning regression in petrology. Also, the book introduces the basics of parallel computing and how to scale ML models in the cloud. The book is devoted to Earth Scientists, at any level, from students to academics and professionals.
Data Analysis In The Earth Sciences Using Matlab
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Author : Gerard V. Middleton
language : en
Publisher:
Release Date : 2000
Data Analysis In The Earth Sciences Using Matlab written by Gerard V. Middleton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Earth sciences categories.
Exploring the application of MATLAB to the various earth sciences, this text presents an integrated, step-by-step introduction to data analysis and the use of MATLAB.
An Introduction To Python Programming For Scientists And Engineers
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Author : Johnny Wei-Bing Lin
language : en
Publisher: Cambridge University Press
Release Date : 2022-07-07
An Introduction To Python Programming For Scientists And Engineers written by Johnny Wei-Bing Lin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-07 with Computers categories.
Textbook that uses examples and Jupyter notebooks from across the sciences and engineering to teach Python programming.
Python For Data Analysis
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Author : Erick Thompson
language : en
Publisher:
Release Date : 2020-11-29
Python For Data Analysis written by Erick Thompson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-29 with Computers categories.
Do you want to master data using python? If yes, then keep reading! Data analysis plays a significant job in numerous parts of your regular day to day existence today. From the second you wake up, you cooperate with information at various levels. A great deal of significant choices are made dependent on information examination. None of the organizations would capacity and run effectively without individuals who realize how to utilize ace this incredible asset. Organizations use information to Understand Their Customer Needs and produce the Best Possible Product or Service. Python Programming Language is one of the best framework with regards to information examination, and in the event that you are considering starting your own business some time or another or as of now have one, this is certainly a device you should comprehend and utilize. Data Scientist is the most requested job of the 21st century and Python is the most popular programming language of the 21st century. The average salary of a Data Scientist is around 120 thousand dollars per year and the average salary of a Pythton Developer is around 100 thousand dollars. So it's pretty obvious that anyone have skills in both Data Science and Python will be in great demand in industry. You needn't bother with an exhausting and costly reading material. This book is the best one for every readers. This book covers: - Introduction to Python and data analysis - Python basics - Python history - Installing Python - Data analysis with Python - NumPy for numerical data processing - Data visualization with Python - Machine learning with Python And much more! Be it Data Processing, Data Analytics, Data Modeling, Data Visualization, Data Predictive, Machine Learning, or taking the photo of Blackhole: Python is everywhere and it is the most powerful programming language of 21st century. Beloved by the data scientists and new generation developers, Pyhton will eat the word! Ready to get started? Click "Buy Now"!
A Hands On Introduction To Using Python In The Atmospheric And Oceanic Sciences
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Author : Johnny Wei-Bing Lin
language : en
Publisher: Lulu.com
Release Date : 2012-08-18
A Hands On Introduction To Using Python In The Atmospheric And Oceanic Sciences written by Johnny Wei-Bing Lin and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-18 with Computers categories.
This book is a mini-course for researchers in the atmospheric and oceanic sciences. "We assume readers will already know the basics of programming... in some other language." - Back cover.
Introduction To Geological Data Analysis
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Author : ARH Swan
language : en
Publisher: Wiley-Blackwell
Release Date : 1995-03-29
Introduction To Geological Data Analysis written by ARH Swan and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-03-29 with Science categories.
Unlike most other sciences, geology does not have a strong tradition of numerical analysis. It is, however, increasingly common for primary geological information to be quantitative rather than descriptive, and analysis of numerical data is now a skill of immense value to any earth scientist. The authors of this book have set out to provide students at undergraduate and graduate level with a thorough grounding in the statistical techniques required in the earth sciences. All the modern statistical methods employed by geologists and geophysicists are covered, with clear worked examples using the type of data the reader is likely to encounter.
Python Programming For Data Analysis
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Author : José Unpingco
language : en
Publisher: Springer Nature
Release Date : 2021-05-04
Python Programming For Data Analysis written by José Unpingco and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-04 with Technology & Engineering categories.
This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns. After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly. The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples.