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Gerald R.
Statistics and Data Visualization in Climate Science with R and Python
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4739085Statistics and Data Visualization in Climate Science with R and Pythonhttps://www.gandhi.com.mx/statistics-and-data-visualization-in-climate-science-with-r-and-python-9781108905275/phttps://gandhi.vtexassets.com/arquivos/ids/4341847/image.jpg?v=63844667196403000010711306MXNCambridge University PressInStock/Ebooks/<p>A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and modern computing tools for the climate sciences and many others such as geography and environmental engineering. It is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. The examples and exercises in the book empower readers to work on real climate data from station observations, remote sensing and simulated results. For example, students can use R or Python code to read and plot the global warming data and the global precipitation data in netCDF, csv, txt, or JSON; and compute and interpret empirical orthogonal functions. The books computer code and real-world data allow readers to fully utilize the modern computing technology and updated datasets. Online supplementary resources include R code and Python code, data files, figure files, tutorials, slides and sample syllabi.</p>...4450028Statistics and Data Visualization in Climate Science with R and Python10711306https://www.gandhi.com.mx/statistics-and-data-visualization-in-climate-science-with-r-and-python-9781108905275/phttps://gandhi.vtexassets.com/arquivos/ids/4341847/image.jpg?v=638446671964030000InStockMXN99999DIEbook20239781108905275_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_<p>A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and modern computing tools for the climate sciences and many others such as geography and environmental engineering. It is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. The examples and exercises in the book empower readers to work on real climate data from station observations, remote sensing and simulated results. For example, students can use R or Python code to read and plot the global warming data and the global precipitation data in netCDF, csv, txt, or JSON; and compute and interpret empirical orthogonal functions. The books computer code and real-world data allow readers to fully utilize the modern computing technology and updated datasets. Online supplementary resources include R code and Python code, data files, figure files, tutorials, slides and sample syllabi.</p>...9781108905275_Cambridge University Presslibro_electonico_9781108905275_9781108905275Gerald R.InglésMéxicohttps://getbook.kobo.com/koboid-prod-public/cambridgeupress-epub-cc258ce8-e870-4172-947e-b833f7c474c7.epub2023-11-30T00:00:00+00:00Cambridge University Press