Additional references to python toolkits and expand matplotlib notes

_episodes/01-syntax.md

@@ -24,7 +24,7 @@ keypoints:
   - `yield`
 - sets - `{1,2,3}`
 - function argument passing: `*`, `**`, `/`
-  - packing/unpacking
+  - packing/unpacking and the catchall pattern `first, *, last = mylist`
 - multi-dimension slicing (numpy/pandas)
 - `dot` - i.e. `this.that`
 - `_`, `__` - single, double underscore (meaning)
@@ -69,7 +69,7 @@ title: The Title of the Section
   - an estimate of time required for teaching & exercises
   - main questions answered in the section
   - learning objectives
-  - key points to summarise what's covered in the section
+  - key points to summarise what's covered in the section (these end are added at the end of the lession section)
 - as an example, below is the front matter for this page
 
 ~~~
@@ -180,6 +180,8 @@ Similarly, exercises written like this
 > {: .language-python}
 >
 > > ## Solution
+> >
+> > This text will only be visible if the solution is expanded
 > > ~~~
 > > Hopper Grace
 > > ~~~
@@ -203,6 +205,8 @@ will be rendered like this (note the expandable box containing the solution):
 > {: .language-python}
 >
 > > ## Solution
+> >
+> > This text will only be visible if the solution is expanded
 > > ~~~
 > > Hopper Grace
 > > ~~~

_episodes/02-data.md

@@ -31,8 +31,8 @@ keypoints:
 - Pandas
   - when an array just isn't enough
   - DataFrames - re-use material from [Software Carpentry][swc-python-gapminder]?
-    - ideally with a more relevant example dataset...
-    - include an aside about I/O - reading/writing files (pandas, numpy, `open()`, (?) bytes vs strings, (?) encoding)
+    - ideally with a more relevant example dataset... [maybe a COVID one](https://data.europa.eu/euodp/en/data/dataset/covid-19-coronavirus-data/resource/260bbbde-2316-40eb-aec3-7cd7bfc2f590)
+    - include an aside about I/O - reading/writing files (pandas (the `.to_*()` methods and highlight some: `csv`, `json`, `feather`, `hdf`), numpy, `open()`, (?) bytes vs strings, (?) encoding)
   - Finish with example of `df.plot()` to set the scene for plotting section
 
 {% include links.md %}

_episodes/03-plotting.md

@@ -18,6 +18,21 @@ keypoints:
 
 - Renato currently scheduled to lead this session
 - Matplotlib
-- plotnine?
+  - The multiple matplotlib interfaces: `pyplot` vs `OO API` vs obsolete `pylab`. See [this](https://matplotlib.org/api/index.html#usage-patterns)
+  - Concepts:
+    - [Artists & containers](https://matplotlib.org/tutorials/intermediate/artists.html#artist-tutorial)
+        - Figure
+        - Axes
+        - Axis & Ticks
+        - ...
+    - Sub-plots
+    - Labels
+    - Annotations
+    - Saving formats
+    - Jupyter integration(?)
+    - 3D plotting (?)
+    - Interactive plots (?)
+- plotting from pandas
+- altair? & plotnine?
 
 {% include links.md %}

_episodes/04-argparse.md

@@ -25,5 +25,9 @@ keypoints:
   - options
   - capturing multiple items in a single argument
   - usage statements
+  - help text
+- [`docopt`](http://docopt.org/) (?)
+- [`click`](https://click.palletsprojects.com/en/7.x/) (?)
+- [comparison of argparse, docopt and click](https://realpython.com/comparing-python-command-line-parsing-libraries-argparse-docopt-click/)
 
 {% include links.md %}

_episodes/05-style.md

@@ -21,12 +21,16 @@ keypoints:
 
 - Toby currently scheduled to lead this session
 - can base a lot of this on https://merely-useful.github.io/py-rse/py-rse-style.html
+- something on project structure and file organization (?)
+  - specially relevant if planning to make a python package
+  - code organisation & jargon (packages, modules, files, classes, functions)
+    - a word about avoiding circular imports (?)
 - PEP8
-- `black`
+  - `pycodestyle`/`pylint` - only warn, doesn't modify code - [see also this comparison](https://books.agiliq.com/projects/essential-python-tools/en/latest/linters.html)
+  - `black` - modifies code - note still [**beta**](https://github.com/psf/black#note-this-is-a-beta-product)
 - documentation
   - docstrings
   - `sphinx`?
-- code organisation
 - include tips for good Jupyter hygiene
   - name the notebook before you do anything else!
   - be careful with cell order