
Автор: Jerry D. Davis
Издательство: CRC Press
Серия: Data Science Series
Год: 2023
Страниц: 403
Язык: английский
Формат: pdf (true)
Размер: 75.7 MB
Introduction to Environmental Data Science focuses on data science methods in the R language applied to environmental research, with sections on exploratory data analysis in R including data abstraction, transformation, and visualization; spatial data analysis in vector and raster models; statistics and modelling ranging from exploratory to modelling, considering confirmatory statistics and extending to machine learning models; time series analysis, focusing especially on carbon and micrometeorological flux; and communication. Introduction to Environmental Data Science is an ideal textbook to teach undergraduate to graduate level students in environmental science, environmental studies, geography, earth science, and biology, but can also serve as a reference for environmental professionals working in consulting, NGOs, and government agencies at the local, state, federal, and international levels. In the Chapter 2 we’ll introduce the R language, using RStudio to explore its basic data types, structures, functions and programming methods in base R.