wrote roughly down the outline (:

outline-old.md

@@ -10,22 +10,83 @@
 
 ### Session PM2 Python Intro
 
-- TODO
+#### Python Intro
+
+- done by rgieseke
+- introduction to the python notebook
+- basic language features (print, int, variables, type, ...)
+- basic operators: math, string, comparison, boolean
+- len, round
+- import numpy as np
+- tab complettion
+- example functions np
+- using a method
+- lists, indexing, slicing
+  - **not included**: list comprehensions
+- tuples
+- traceback error (short explanation for understanding)
+- dictionaries
+- numpy arrays and basic operations
+- for loops, enumerate, zip
+- matplotlib.pyplot.plt
+- if elif else
+
+#### Numpy Intro
+
+- np.loadtxt the example and short analysis of the loaded data
+- slcing in multiple dimensions
+-  apply all the numpy operations (e.g. mean)
+- demonstrate axis keyword
 
 ## DAY 2 AM
 
 ### Session AM1 Python Basics I
 
-- TODO
+#### functions and modules
+- functions
+  - positional arguments
+  - keyword a.
+  - functions as arguments (write your own `map` function)
+  - **not included**: \*, \*args, \*\*kwargs, mandatory keyword arguments
+- formatted strings, i.e. `f"Hello {variable}"`
+- write a function in a module and load it in the notebook, including `help`
+- readable functions ... i.e. use long, meaningful variable names (and take advantage of autocompletion)
+
+#### speeding up code with numba
+
+- demonstrate simple loop example
+  - *comment*: the second `idx` definition in `process_numpy` could be replaced by `idx = ~idx` and that should be (marginally and probably irrelevantly) faster (:
+- use `nb.vectorize` to create an np ufunc
 
 ### Session AM2: Python Basics II
 
-- TODO
+#### Defensive Programming
+
+- assertions 
+- simple example for test-driven development
+- Debuggung ... long monologue and emphasize the important points, not going to repeat all of that here ... [I put some work into the presentation here, so they can take it home](https://github.com/swc-bb/2017-05-15-python-novice-lessons/blob/master/lesson-notebooks/lesson-tim/defensive%20programming.ipynb)
+
+#### command line programs
+
+- that was fun
+- explain the shebang and how to make a script executable
+- using sys.argv and showing how useless it is
+- go to argparse and show how awesome it is
+  - ad different kinds of arguments, let them play around if possible
+- read from stdin
+- show the argcomplete magic
+
 
 ## DAY 2 PM
 
 ### Session PM1: Python Final Project
 
-- TODO
+- load stuff in pandas and plot it
+-  use `describe`, `loc`, `T`, various ways of pandas indexing
+- the actual project:
+  - easily get nice results so everybody is happy
+  - give the loading of the data file for free as this could set people back
+  - but then have some backup questions so even the quick people have enough to do
+  - finally do a challenge that actually involves some reading of the docs and thinking
 
 ### Session PM2: Wrap up