Python For Chemists
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Python for Chemists
Author: Kiyoto Aramis Tanemura
language: en
Publisher: American Chemical Society
Release Date: 2022-08-24
Programming in Python empowers chemists to apply their domain knowledge to scales unreachable by manual effort. Learning Python is easy, but contextualizing chemical problems in Python is not always obvious. Readers of this primer develop the skill to identify problems in their research for which code may automate operations and scale a large volume of data or calculation. In addition, the authors shorten the time from “learning” to “using” Python through meaningful problem sets in Chapter One.
Python for Chemists
Author: Christian Hill
language: en
Publisher: Cambridge University Press
Release Date: 2023-10-26
Accessible and self-contained guide to the programming language, Python, with a focus on applications in chemistry and chemical physics.
Python for Chemistry
Author: Dr. M. Kanagasabapathy
language: en
Publisher: BPB Publications
Release Date: 2023-03-20
A one-stop guide to teach chemists how to use Python for coding and iterations in a hands-on and practical manner KEY FEATURES ● Understand the core Python functions and algorithms for the computation of chemical parameters. ● Learn how to use Cheminformatics modules to process and analyze elemental data and molecular structures. ● Get familiar with the algorithms for numerical and symbolic computations. DESCRIPTION Python is a versatile and powerful computer language without a steep learning curve. It can be deployed to simulate various physicochemical parameters or to analyze complex molecular, bio-molecular, and crystalline structures. The objective of this book is to give a gentle introduction to Python programming with relevant algorithms, iterations, and basic simulations from a chemist’s perspective. This book outlines the fundamentals of Python coding through the built-in functions, libraries, and modules as well as with a few selected external packages for physical/materials/inorganic/analytical/organic/ nuclear chemistry in terms of numerical, symbolic, structural, and graphical data analysis using the default, Integrated Development and Learning Environment. You will also learn about the Structural Elucidation of organic molecules and inorganic complexes with specific Cheminformatics modules. In addition to this, the book covers chemical data analysis with Numpy and also includes topics such as SymPy and Matplotlib for Symbolic calculations and Plotting. By the end of the book, you will be able to use Python as a graphical tool or a calculator for numerical and symbolic computations in the interdisciplinary areas of chemistry. WHAT YOU WILL LEARN ● To fetch elemental, nuclear, atomic or molecular data with list or dictionary functions. ● Understanding the algorithms for the computation of Thermodynamic, Electrochemical, Kinetics, Molecular and Spectral parameters. ● Stoichiometrical calculation of the reactant and product coefficients from Matrices. ● Symbolic computations with reference to Physical Chemistry. ● With Matplotlib package, interpretation and plotting of the analyzed data in the desired graphical format. ● With various cheminformatics modules, correlate the structure of complex and bulkier molecules. WHO THIS BOOK IS FOR This book is for Chemists, Chemical Engineers, Material Scientists, Bio-chemists, Biotechnologists, and Physicists. Students of Chemistry, Chemical Engineering, Materials Chemistry, Biochemistry, Biotechnology, and Physics will find this book resourceful. TABLE OF CONTENTS 1. Understanding Python Functions for Chemistry 2. Computations in Chemistry with NumPy 3. Interpolation, Physico-chemical Constants, and Units with SciPy 4. SymPy for Symbolic Computations in Chemistry 5. Interactive Plotting of Physico-chemical Data with Matplotlib 6. Introduction to Cheminformatics with RDKit 7. ChemFormula for Atomic and Molecular Data 8. Chemlib for Physico-chemical Parameters 9. ChemPy for Computations in Chemistry 10. Mendeleev Package For Atomic and Ionic Data 11. Computations of Parameters of Electrolytes with PyEQL 12. STK Module for Molecular Structures