Ebook: Introduction to Python in Earth Science Data Analysis From Descriptive Statistics to Machine Learning

The book is organized into five parts plus three appendixes. The Part I, entitled
“Python for Geologists: A Kickoff,” focuses on the very basics of Python programming, from setting up an environment for scientific computing to solving your first
geology problems using Python. The Part II is entitled “Describing Geological Data”
and explains how to start visualizing (i.e., making plots) and generating descriptive
statistics, both univariate and bivariate. The Part III, entitled “Integrals and Differential Equations in Geology,” discusses integrals and differential equations while
highlighting various applications in geology. The Part IV deals with “Probability
Density Functions and Error Analysis” applied to the evaluation and modeling of
Earth Science data. Finally, the Part V, entitled “Robust Statistics and Machine Learning” analyzes data sets that depart from normality (statistically speaking) and the
application of machine learning techniques to data modeling in the Earth Sciences.