Python and Jupyter notebooks

This is a rapid introduction to the basics of Python and the use of Jupyter notebooks.

Good online cheat-sheets:

• Python Crash Course

• datacamp cheat-sheets

• Python debugging flowchart

What you should know from Python and Jupyter notebooks: part 01:

1. Know how to switch between Code and Markdown cells and how to run them (shift-Return or Run button)

2. Basics of Python evaluation and printing

   • string concatenation

   • exponentiation with **

   • use of fstrings

3. Importing numpy and basic functions (sqrt, exp, sin, \(\ldots\))

   • numpy arrays using arange(min, max, step)

4. Getting help via Google (or alternative): StackOverflow and manuals

5. Defining functions in Python

   • def my_function(x): \(\longleftarrow\) semicolon and then indented lines

   • position vs. keyword argument and defaults

   • shift + tab + tab to reveal definitions

6. Plotting with Matplotlib

   • Standard sequence for plot: data \(\longrightarrow\) make figure \(\longrightarrow\) add subplots \(\longrightarrow\) make plot

   • dressing up and saving a plot

   • names for the figure and axis objects are our choice

7. Numpy linear algebra

   • defining a matrix and finding its shape or particular elements

   • matrix (or vector) operations: multiplying them with @, transpose, trace, inverse, eigensolution