We often use Jupyter Notebooks in several of my courses together with JupyterLab being the current user interface of choice. In my view this interactive development environment maps the workflow of developing ideas and software for data analysis best. I especially appreciate the mixture of code cells and formatted text cells, in which Markdown (a lightweight markup language) and MathJax (special markup language for pretty math printing).

This allows me to develop, describe and implement ideas to solve certain problems in a highly dynamic manner. Starting with an assumption on how a particular problem can be solved, I implement it (usually in Python) and test.

My favorite book on introduction to Python. Printed version published by O'Reilly, pdf officially downloadable from here: http://www.greenteapress.com/thinkpython/

• http://scipy-lectures.github.io/
  (Includes also an excellent Python language intro and ref.)

• http://docs.scipy.org/doc/numpy/reference/
• http://docs.scipy.org/doc/numpy/user/

• http://docs.scipy.org/doc/scipy/reference/

• http://docs.scipy.org/doc/

Hans Petter Langtangen has written two excellent books on Scientific Programming with Python. The one I use in my courses is A primer on Scientific Programming with Python, which is also available in the university library.

UPDATE: Hans Petter passed away on Oct. 10, 2016 at 54 because of cancer.
This makes me very sad. I would have loved to meet him once.

All his web pages at University Oslo have been removed.

• Dead link: Homepage of Hans Petter Langtangen
• Dead link: Comparison of his two books
• Resources for “A Primer on Scientific Programming with Python”

• Lecture Slides (home)

• Norwegian Introduction (pdf)
• Chapter 1: Computing with Formulas (pdf)
• Chapter 2: Lists and Loops (pdf)
• Chapter 3: Functions and Branching (pdf)
• Chapter 4: Input Data and Error Handling (pdf)
• Chapter 5: Array Computing and Curve Plotting (pdf)
• Chapter 6: Files, Strings, and Dictionaries (pdf)
• Chapter 7: Introduction to Classes (pdf)
• Chapter 8: Random Numbers and Simple Games (pdf)
• Chapter 9: Object-Oriented Programming (pdf)
• Summary of Python Functionality in INF1100 (pdf)
• Sequences and Difference Equations (Appendix A) (pdf)
• Programming of Differential Equations (Appendix E) (pdf)

• All chapters in one document (pdf)

Just install Anaconda3 Python distribution.

Simon Funke <simon at simula.no>, UiO (University of Oslo), Simula Research Lab

The great teaching material on “Higher Level Programming” can be found on https://uio-inf3331.github.io/

“The lecture was initially created by Hans Petter Langtangen and extended by Joakim Sundnes, Ola Skavhaug, Jonathan Feinberg, Karl-Erik Holter, Vidar Tonaas Fauske, Benjamin Ragan-Kelley and Simon Funke. It is being taught on a yearly basis at University of Oslo under the name INF3331/INF4331.” (Cited from the Github repo)