David J. Pine has taught physics and chemical engineering for over 40 years at four different institutions: Cornell University (as a graduate student), Haverford College, UCSB, and NYU, where he is a Professor of Physics, Mathematics, and Chemical & Biomolecular Engineering. He has taught a broad spectrum of courses, including numerical methods. He does research on optical materials and in experimental soft-matter physics, which is concerned with materials such as polymers, emulsions, and colloids.

1. Introduction

2. Launching Python

3. Integrated Development Environments

4. Strings, Lists, Arrays, and Dictionaries

5. Input and Output

6. Conditionals and Loops

7. Functions

8. Plotting

9. Numerical Routines: SciPy and NumPy

10. Python Classes: Encapsulation

11. Data Manipulation and Analysis: Pandas

12. Animation

13. Speeding up numerical calculations

Appendix A Maintaining your installation Python

Appendix B Glossary

Appendix C Python Resources

Index Index