Titlebook: Introduction to Python in Earth Science Data Analysis; From Descriptive Sta Maurizio Petrelli Textbook 2021 The Editor(s) (if applicable) a

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Graphical Visualization of a Geological Data SetChapter 4 deals with the visualization of a geological data set using Python. It introduces the reader to the visualization of univariate data using histograms and cumulative distribution functions. Then, it begins showing how to prepare a publication-ready diagram. The chapter ends with a first attempt at visualizing multivariate data.

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Descriptive Statistics 1: Univariate AnalysisMastering descriptive statistics is mandatory for a geologist. Chapter 5 shows how to describe a geological data set using Python programming, starting with basic metrics such as the location, dispersion, and degree of symmetry of a univariate data set. It then shows how to perform descriptive statistics in pandas and introduces box plot diagrams.

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Error AnalysisChapter 10 is about errors and error propagation. It defines precision, accuracy, standard error, and confidence intervals. Then it demonstrates how to report uncertainties in binary diagrams. Finally, it shows two approaches to propagate the uncertainties: the linearized and Monte Carlo methods.

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Introduction to Robust StatisticsChapter 11 introduces robust statistics. It presents an approach to determine whether or not a sample follows a normal distribution. Chapter 11 continues defining robust approaches for the estimation of the location and the scale of a sample. It concludes by discussing the role of robust statistics in geochemistry.

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Machine LearningChapter 12 introduces the reader to the application of machine learning techniques in geology. It provides some basic concepts of machine learning and their implementation in Python, and guides the reader through a geological case study that utilizes machine learning.

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Python Essentials for a Geologistdescribes how to start working with Python scripts in the Spyder Integrated Development Environment (IDE). It also explains how to perform conditional statements and loops, and how to define a function and perform basic mathematical operations.

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Probability Density Functions and Their Use in Geologysity functions, and introduces meaningful probability density functions in geology. Examples are the normal and log-normal distributions. Chapter 9 ends by showing how to perform a probability density estimation.

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https://doi.org/10.1007/978-3-030-78055-5Modelling Geological Data; Earth Science Python Programming; Python Learning for Geologists; Machine Le