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The book Python Recipes for Earth Sciences is designed to help undergraduate and postgraduate students, doctoral students, post-doctoral researchers, and professionals alike find quick solutions to common data analysis problems in the earth sciences. It provides a minimal amount of theoretical background and demonstrates the application of all described methods via examples. The book is based on the popular MATLAB Recipes for Earth Sciences book that I wrote many years ago, which is now available in its 5th edition (Springer 2021). The idea for this new book was to translate the text of the MATLAB book to another, increasingly popular programming language in the spirit of the classic Numerical Recipes book by W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery (Cambridge University Press 2007). The present book contains Python scripts that can be used to solve typical problems in the earth sciences via simple statistics, time series analysis, geostatistics, and image processing. It also demonstrates the application of selected advanced techniques of data analysis, such as nonlinear time series analysis, adaptive filtering, bootstrapping, and terrain analysis. The book’s supplementary electronic material (available online through Springer Link) includes recipes that contain all the example data and all the Python commands featured in the book. The Python codes can be easily modified for use with the reader’s own data and projects. The Python software, which has existed for more than 30 years, is used since it not only provides numerous ready-to-use algorithms for most methods of data analysis, but also allows the existing routines to be modified and expanded and additionally enables new software to be developed. However, most methods are introduced with very simple codes before any Pythonspecific functions are used. As a result, users of alternatives to Python will also find value in this book.