Call number:
9783030780555 (e-book)
Description / Table of Contents:
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.
Type of Medium:
12
Pages:
1 Online-Ressource (xv, 229 Seiten)
,
Illustrationen, Diagramme
ISBN:
9783030780555
,
978-3-030-78055-5
ISSN:
2510-1307
,
2510-1315
Series Statement:
Springer Textbooks in Earth Sciences, Geography and Environment
URL:
Ebook (access only within the AWI network)
DOI:
10.1007/978-3-030-78055-5
Language:
English
Note:
Contents
Part I Python for Geologists: A Kickoff
1 Setting Up Your Python Environment, Easily
1.1 The Python Programming Language
1.2 Programming Paradigms
1.3 A Local Python Environment for Scientific Computing
1.4 Remote Python Environments
1.5 Python Packages for Scientific Applications
1.6 Python Packages Specifically Developed for Geologists
2 Python Essentials for a Geologist
2.1 Start Working with IPython Console
2.2 Naming and Style Conventions
2.3 Working with Python Scripts
2.4 Conditional Statements, Indentation, Loops, and Functions
2.5 Importing External Libraries
2.6 Basic Operations and Mathematical Functions
3 Solving Geology Problems Using Python: An Introduction
3.1 My First Binary Diagram Using Python
3.2 Making Our First Models in Earth Science
3.3 Quick Intro to Spatial Data Representation
Part II Describing Geological Data
4 Graphical Visualization of a Geological Data Set
4.1 Statistical Description of a Data Set: Key Concepts
4.2 Visualizing Univariate Sample Distributions
4.3 Preparing Publication-Ready Binary Diagrams
4.4 Visualization of Multivariate Data: A First Attempt
5 Descriptive Statistics 1: Univariate Analysis
5.1 Basics of Descriptive Statistics
5.2 Location
5.3 Dispersion or Scale
5.4 Skewness
5.5 Descriptive Statistics in Pandas
5.6 Box Plots
6 Descriptive Statistics 2: Bivariate Analysis
6.1 Covariance and Correlation
6.2 Simple Linear Regression
6.3 Polynomial Regression
6.4 Nonlinear Regression
Part III Integrals and Differential Equations in Geology
7 Numerical Integration
7.1 Definite Integrals
7.2 Basic Properties of Integrals
7.3 Analytical and Numerical Solutions of Definite Integrals
7.4 Fundamental Theorem of Calculus and Analytical Solutions
7.5 Numerical Solutions of Definite Integrals
7.6 Computing the Volume of Geological Structures
7.7 Computing the Lithostatic Pressure
8 Differential Equations
8.1 Introduction
8.2 Ordinary Differential Equations
8.3 Numerical Solutions of First-Order Ordinary Differential Equations
8.4 Fick’s Law of Diffusion—A Widely Used Partial Differential Equation
Part IV Probability Density Functions and Error Analysis
9 Probability Density Functions and Their Use in Geology
9.1 Probability Distribution and Density Functions
9.2 The Normal Distribution
9.3 The Log-Normal Distribution
9.4 Other Useful PDFs for Geological Applications
9.5 Density Estimation
9.6 The Central Limit Theorem and Normal Distributed Means
10 Error Analysis
10.1 Dealing with Errors in Geological Measurements
10.2 Reporting Uncertainties in Binary Diagrams
10.3 Linearized Approach to Error Propagation
10.4 The Mote Carlo Approach to Error Propagation
Part V Robust Statistics and Machine Learning
11 Introduction to Robust Statistics
11.1 Classical and Robust Approaches to Statistics
11.2 Normality Tests
11.3 Robust Estimators for Location and Scale
11.4 Robust Statistics in Geochemistry
12 Machine Learning
12.1 Introduction to Machine Learning in Geology
12.2 Machine Learning in Python
12.3 A Case Study of Machine Learning in Geology
Appendix A: Python Packages and Resources for Geologists
Appendix B: Introduction to Object Oriented Programming
Appendix C: The Matplotlib Object Oriented API
Appendix D: Working with Pandas
Further Readings
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