Christian Hill is a physicist and physical chemist with over twenty-five years' experience in scientific programming, data analysis and database design in atomic and molecular physics. Currently the Head of the Atomic and Molecular Data Unit at International Atomic Energy Agency, Vienna, he has previously held positions at the University of Cambridge, the University of Oxford, and University College London.

'This book is a very useful addition to the library of python books, and is squarely directed at chemists, covering all the main aspects of python that they will find useful, without getting bogged down in programming detail. The clear focus on chemistry examples from the start means that students will be able to quickly perform useful, Python-based tasks without having to invest time in learning abstract syntax. Python for chemists will be a valuable resource for chemists who wish to add an element of programming to their skills base.' John McGrady, University of Oxford

• 1. Introduction; 2. Basic Python usage; 3. Strings; 4. Lists and loops; 5. Comparisons and flow control; 6. Functions; 7. Data structures; 8. File input/output; 9. Basic numpy; 10. Graph plotting with Matplotlib; 11. The steady-state approximation; 12. Liquid-vapour equilibrium; 13. Jupyter notebook; 14. LaTeX; 15. Chemistry databases and file formats; 16. More NumPy and Matplotlib; 17. Thermodynamic cycles; 18. Vectors, matrices and linear algebra; 19. Linear least squares fitting I; 20. Linear least squares fitting II; 21. Numerical integration; 22. Optimization with scipy.optimize; 23. Vibrational spectroscopy; 24. The morse oscillator; 25. Solving ordinary differential equations; 26. The oregonator; 27. Root-finding with scipy.optimize; 28. Rotational spectroscopy; 29. Peak finding; 30. Fitting the vibrational spectrum of CO; 31. pandas; 32. Simulating a powder diffraction spectrum; 33. The Hückel approximation; 34. Nonlinear fitting and constrained optimization; 35. SymPy; 36. Molecular orbital theory for H2+; 37. Approximations of the helium atom electronic energy; 38. Computational chemistry with Psi4 and Python; 39. Atomic structure; 40. Solutions.

Christian Hill is a physicist and physical chemist with over twenty-five years' experience in scientific programming, data analysis and database design in atomic and molecular physics. Currently the Head of the Atomic and Molecular Data Unit at International Atomic Energy Agency, Vienna, he has previously held positions at the University of Cambridge, the University of Oxford, and University College London.

'This book is a very useful addition to the library of python books, and is squarely directed at chemists, covering all the main aspects of python that they will find useful, without getting bogged down in programming detail. The clear focus on chemistry examples from the start means that students will be able to quickly perform useful, Python-based tasks without having to invest time in learning abstract syntax. Python for chemists will be a valuable resource for chemists who wish to add an element of programming to their skills base.' John McGrady, University of Oxford

• 1. Introduction; 2. Basic Python usage; 3. Strings; 4. Lists and loops; 5. Comparisons and flow control; 6. Functions; 7. Data structures; 8. File input/output; 9. Basic numpy; 10. Graph plotting with Matplotlib; 11. The steady-state approximation; 12. Liquid-vapour equilibrium; 13. Jupyter notebook; 14. LaTeX; 15. Chemistry databases and file formats; 16. More NumPy and Matplotlib; 17. Thermodynamic cycles; 18. Vectors, matrices and linear algebra; 19. Linear least squares fitting I; 20. Linear least squares fitting II; 21. Numerical integration; 22. Optimization with scipy.optimize; 23. Vibrational spectroscopy; 24. The morse oscillator; 25. Solving ordinary differential equations; 26. The oregonator; 27. Root-finding with scipy.optimize; 28. Rotational spectroscopy; 29. Peak finding; 30. Fitting the vibrational spectrum of CO; 31. pandas; 32. Simulating a powder diffraction spectrum; 33. The Hückel approximation; 34. Nonlinear fitting and constrained optimization; 35. SymPy; 36. Molecular orbital theory for H2+; 37. Approximations of the helium atom electronic energy; 38. Computational chemistry with Psi4 and Python; 39. Atomic structure; 40. Solutions.