Coding for Chemists: Saving Time and Solving Problems with Python
Forthcoming
Coding for Chemists introduces coding in Python as a tool for solving real-world problems commonly encountered by experimental chemists. It will be of interest to anyone who wants to increase their research sophistication or streamline their workflows.
Summary
Johnson and Lear’s Coding for Chemists is targeted to experimental chemists who are curious how coding might improve their research. Assuming no prior knowledge of coding and quickly introducing concepts and workflows that will be applicable to nearly all practicing experimental chemists, this book is written to function as the framework for a 1-quarter or 1-semester course on programming at either the undergraduate or graduate level. It can also be used for individual study or to support the introduction of coding into chemical laboratory courses.
Using a narrative structure that frames coding concepts in terms of tasks common to chemical research, the reader will learn to plan experiments, automate the generation of publication-quality figures, fit experimental data to any desired model, and process data using advanced data anlysis techniques. The goal is to bring the reader from any prior knowledge regarding coding to the point that they are able to extend the capabilities of their research, while also saving a great deal of time. The book includes examples, detailed comments on code, and numerous problems. It is supported by online resources.