_episodes/02-data.md

@@ -35,4 +35,40 @@ keypoints:
     - 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
 
+> ## Working with Filtered Data
+>
+> 1. On what date were the most cases reported in Germany so far?
+> 2. What was the mean number of cases reported per day in Germany in April 2020?
+> 3. Is this higher or lower than the mean for March 2020?
+> 4. On how many days in March was the number of cases in Germany higher than the mean for April?
+> 
+> > ## Solution
+> > ~~~
+> > # 1
+> > mask_germany = covid_cases['countryterritoryCode'] == 'DEU'
+> > id_max = covid_cases[mask_germany]['cases'].idxmax()
+> > print(covid_cases.iloc[id_max]['dateRep'])
+> >
+> > # 2
+> > mask_april = (covid_cases['year'] == 2020) & (covid_cases['month'] == 4)
+> > mean_april = covid_cases[mask_germany & mask_april]['cases'].mean()
+> > print(mean_april)
+> >
+> > # 3
+> > mask_march = (covid_cases['year'] == 2020) & (covid_cases['month'] == 3)
+> > mean_march = covid_cases[mask_germany & mask_march]['cases'].mean()
+> > print(mean_march)
+> > print("Mean cases per day was {} in April than in March 2020.".
+> >       format(["lower", "higher"][mean_april > mean_march]))
+> >
+> > # 4
+> > mask_higher_mean_april = (covid_cases['cases'] > mean_april)
+> > selection = covid_cases[mask_germany & mask_march & mask_higher_mean_april]
+> > nbr_days = len(selection)   # Assume clean data
+> > print(nbr_days)
+> > ~~~
+> > {: .language-python }
+> {: .solution }
+{: .challenge }
+
 {% include links.md %}

_episodes/04-argparse.md

@@ -30,4 +30,59 @@ keypoints:
 - [`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/)
 
+> ## Options & Arguments
+> The code block below shows the start of a program
+> that takes three input files and returns either
+> the product, the sum, or the mean, of the values
+> given somewhere within them.
+> (The details of how the files are processed and
+> the returned values calculated are not shown.)
+>
+> Fill in the blanks in the code (indicated with `___`),
+> so that the program can take an option,
+> `--output=output.csv`, to specify an output file,
+> or write to STDOUT otherwise.
+> (Note: `sys.stdout` is an object representing the STDOUT stream.)
+>
+> ~~~
+> from sys import argv, stdout
+> from numpy import prod # use math.prod here if you're running Python 3.8
+> from statistics import mean
+>
+> input_files = argv[-3:]
+>
+> modes = {'--sum': sum,
+>          '--product': prod,
+>          '--mean': mean}
+> output_file = ___
+>
+> for option in argv[___:-3]:
+>   if option in modes:
+>     output_function=modes[option]
+>   elif ___:
+>     output_file = option.split___
+> ~~~
+> {: .language-python}
+>
+> Once you've done this, try to change the code
+> so that the program can take an arbitrary number of input files.
+>
+> Look at the code again.
+> Do you think this is a good way to construct an interface for a program like this?
+> What potential problems can you identify with this approach?
+> Pair up and discuss with a partner.
+{: .challenge}
+
+> ## Carry the Zero
+>
+> What does `sys.argv[0]` return when you run it in a script?
+> What about in a Jupyter Notebook?
+> In what circumstances might this be useful?
+> Is the full path included in the returned value?
+> If not, take a look at [the documentation for `os`][os-file-dir]
+> and [`pathlib`][pathlib],
+> other modules in the standard library,
+> to find another function that could get this for you.
+{: .challenge}
+
 {% include links.md %}

_episodes/05-style.md

@@ -36,4 +36,81 @@ keypoints:
   - be careful with cell order
   - clear output before saving
 
+> ## Fashions change. Style is forever.
+> Look at the following three code blocks. (Based on [this script][matplotlib-hinton] from the Matplotlib Example Gallery).
+>
+> **Block A**
+> ~~~
+> def hinton(matrix, max_weight=None, ax=None):
+>   """Draw Hinton diagram for visualizing a weight matrix."""
+>   ax = ax if ax is not None else plt.gca()
+>
+>   if not max_weight:
+>     max_weight = 2 ** np.ceil(np.log(np.abs(matrix).max()) / np.log(2))
+>
+>   ax.patch.set_facecolor('gray')
+>   ax.set_aspect('equal', 'box')
+>   ax.xaxis.set_major_locator(plt.NullLocator())
+>   ax.yaxis.set_major_locator(plt.NullLocator())
+>
+>   for (x,y), w in np.ndenumerate(matrix):
+>     color = 'white' if w > 0 else 'black'
+>     size = np.sqrt(np.abs(w) / max_weight)
+>     rect = plt.Rectangle([x - size/2, y - size/2], size, size,
+>                          facecolor=color, edgecolor=color)
+>     ax.add_patch(rect)
+> ~~~
+> {: .language-python }
+>
+> **Block B**
+> ~~~
+> def hinton(matrix, max_weight=None, ax=None):
+>     """Draw Hinton diagram for visualizing a weight matrix."""
+>     ax = ax if ax is not None else plt.gca()
+>
+>     if not max_weight:
+>         max_weight = 2 ** np.ceil(np.log(np.abs(matrix).max()) / np.log(2))
+>
+>     ax.patch.set_facecolor('gray')
+>     ax.set_aspect('equal', 'box')
+>     ax.xaxis.set_major_locator(plt.NullLocator())
+>     ax.yaxis.set_major_locator(plt.NullLocator())
+>
+>     for (x, y), w in np.ndenumerate(matrix):
+>         color = 'white' if w > 0 else 'black'
+>         size = np.sqrt(np.abs(w) / max_weight)
+>         rect = plt.Rectangle([x - size / 2, y - size / 2], size, size,
+>                          facecolor=color, edgecolor=color)
+>         ax.add_patch(rect)
+> ~~~
+> {: .language-python }
+>
+> **Block C**
+> ~~~
+> def hinton (matrix,max_weight=None,ax=None) :
+>   """Draw Hinton diagram for visualizing a weight matrix."""
+>   ax=ax if ax is not None else p.gca()
+>
+>   if not max_weight:
+>       max_weight=2**np.ceil(np.log(np.abs(matrix).max())/np.log(2))
+>
+>   ax.patch.set_facecolor('gray')
+>   ax.set_aspect('equal','box')
+>   ax.xaxis.set_major_locator(plt.NullLocator())
+>   ax.yaxis.set_major_locator(plt.NullLocator())
+>
+>   for (x,y),w in np.ndenumerate(matrix):
+>     color = 'white' if w>0 else 'black'
+>     size = np.sqrt(np.abs(w)/max_weight)
+>     rect = plt.Rectangle([x-size/2,y-size/2],size,size,facecolor=color,edgecolor=color)
+>     ax.add_patch(rect)
+> ~~~
+> {: .language-python}
+>
+> - Which block conforms to the standards described in PEP8?
+> - Is it also the block you find easiest to read?
+> - In each block, mark the lines/places where you consider the style to be _problematic_ (that is, where the [lack of] style actively makes the code difficult to read/inaccessible in some other way).
+> - Pair up and compare your notes with a partner's. Did you both identify the same problems?
+{: .challenge }
+
 {% include links.md %}

_includes/links.md

@@ -33,11 +33,14 @@
 [lesson-reference]: {{ relative_root_path }}{% link reference.md %}
 [lesson-setup]: {{ relative_root_path }}{% link setup.md %}
 [markdown-cheatsheet]: https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet
+[matplotlib-hinton]: https://matplotlib.org/examples/specialty_plots/hinton_demo.html
 [mit-license]: https://opensource.org/licenses/mit-license.html
 [morea]: https://morea-framework.github.io/
 [numfocus]: https://numfocus.org/
+[os-file-dir]: https://docs.python.org/3.8/library/os.html#os-file-dir
 [osi]: https://opensource.org
 [pandoc]: https://pandoc.org/
+[pathlib]: https://docs.python.org/3/library/pathlib.html
 [paper-now]: https://github.com/PeerJ/paper-now
 [python-gapminder]: https://swcarpentry.github.io/python-novice-gapminder/
 [pyyaml]: https://pypi.python.org/pypi/PyYAML

data/CovidLockdowns.csv

+Countries and territories,Start date,End date
+Albania,2020-03-13,2020-06-01
+Algeria,2020-03-23,2020-05-14
+Argentina,2020-03-19,2020-06-28
+Armenia,2020-03-24,2020-05-04
+Australia,2020-03-23,
+Austria,2020-03-16,2020-04-13
+Azerbaijan,2020-03-31,2020-04-20
+Bangladesh,2020-03-26,2020-05-16
+Barbados,2020-03-28,2020-05-03
+Belgium,2020-03-18,2020-05-04 
+Bermuda,2020-04-04,2020-05-02
+Bolivia,2020-03-22,2020-04-15
+Botswana,2020-04-02,2020-04-30
+Brazil,2020-03-17,2020-05-10
+Colombia,2020-03-25,2020-06-30
+Republic of the Congo,2020-03-31,2020-04-20
+Costa Rica,2020-03-23,
+Croatia,2020-03-18,2020-04-19
+Czech Republic,2020-03-16,2020-04-12
+Ecuador,2020-03-16,2020-03-31
+El Salvador,2020-03-12,2020-04-02
+Eritrea,2020-04-02,2020-04-23
+Fiji,2020-03-20,2020-04-17
+Finland,2020-03-27,2020-04-16
+France,2020-03-17,2020-05-11
+Georgia,2020-03-31,2020-04-21
+Germany,2020-03-23,2020-04-20 to 2020-05-10
+Ghana,2020-03-30,2020-04-12
+Greece,2020-03-23,2020-05-04
+Guernsey,2020-03-25,
+Honduras,2020-03-20,2020-05-17
+Hungary,2020-03-28,2020-04-10
+India,2020-03-25,2020-06-30
+Iran,2020-03-14,2020-04-20
+Iraq,2020-03-22,2020-04-11
+Ireland,2020-03-12,2020-05-18
+Israel,2020-04-02,
+Italy,2020-03-09,2020-05-18
+Jamaica,2020-04-15,2020-04-22
+Jordan,2020-03-18,2020-04-30
+Kosovo,2020-03-14,2020-05-04 
+Kuwait,2020-03-14,2020-03-29
+Lebanon,2020-03-15,2020-03-28
+Liberia,2020-03-23,2020-04-11
+Libya,2020-03-22,
+Lithuania,2020-03-16,2020-06-18
+Madagascar,2020-03-23,2020-04-20
+Malaysia,2020-03-18,2020-06-09
+Mexico,2020-03-23,2020-06-01
+Mongolia,2020-03-10,2020-03-16
+Montenegro,2020-03-24,
+Morocco,2020-03-19,2020-06-10
+Namibia,2020-03-27,2020-05-04
+Nepal,2020-03-24,2020-06-14
+New Zealand,2020-03-26,2020-05-14
+Nigeria,2020-03-30,2020-04-12
+Northern Cyprus,2020-03-30,
+Oman,2020-04-10,
+Pakistan,2020-03-24,2020-05-09
+Panama,2020-03-25,
+Papua New Guinea,2020-03-24,2020-04-07
+Paraguay,2020-03-20,2020-05-03
+Peru,2020-03-16,2020-06-30
+Philippines,2020-03-15,2020-05-31
+Poland,2020-03-13,2020-04-11
+Portugal,2020-03-19,2020-04-02
+Qatar,2020-03-11,
+Romania,2020-03-25,2020-05-12
+Russia,2020-03-28,2020-05-12
+Rwanda,2020-03-21,2020-04-19
+Samoa,2020-03-26,2020-04-08
+San Marino,2020-03-14,2020-05-05
+Saudi Arabia,2020-03-09,
+Serbia,2020-03-15,2020-04-21 to 2020-05-04
+Singapore,2020-04-07,2020-06-01
+South Africa,2020-03-26,2020-04-30
+Spain,2020-03-14,2020-05-09
+Sri Lanka,2020-03-18,2020-05-26
+Thailand,2020-03-25,2020-05-31
+Trinidad and Tobago,2020-03-17,2020-03-31
+Tunisia,2020-03-22,2020-04-19
+Turkey,2020-04-23,2020-04-27
+Ukraine,2020-03-17,2020-04-24
+United Arab Emirates,2020-03-26,2020-04-17
+United Kingdom,2020-03-23,
+United States,2020-03-19,
+Venezuela,2020-03-17,2020-05-13
+Vietnam,2020-04-01,2020-04-22
+Zimbabwe,2020-03-30,2020-05-02