Worked example of working with climate data (wrap-up to novice Python lesson)

[gvwilson]

This PR contains a capstone lesson for the novice Python material that shows how to use requests, cStringIO, csv, and the World Bank's Climate Data API to download data from the web and do some simple analysis with it.

[lexnederbragt]

That should probably be

for ( (left_year, left_value), (right_year, right_value) ) in zip(left_country, right_country):

[lexnederbragt]

I like the example. It shows combining importing modules, fetching data, parsing data, writing functions and unit tests.

Why not add some plotting? For example, the temperatures over time for the two countries? Makes for a more appealing example, imho...

[PBarmby]

Looks good, comments below all minor things.

Possible typos:
"First 100 characters of data is" -> "first 100 characters of data are"
"Python stops executed" -> "Python stops executing"

I wonder if there are more intuitive names than "reader" and "wrapper":
wrapper = csv.reader(reader)
may be a bit too terse for people?

instead of
if record[0] != 'year':
you could also test the datatype of records (but maybe you don't want to go there)

Re: left and right in section 5/6: I haven't seen it done with this syntax before (I would probably just use x1 and x2, or something) but maybe that's just me. Is there any dnager of left/right here being confused with other things, like the left-most characters in a string, etc?

Minor wording changes which I think help clarify:
"it can switch back & forth" --> "it can switch back & forth between these two approaches"
"how we could do this using a couple of standard Python libraries" --> "how we could parse the data using a couple of standard Python libraries"

"Escape sequences" box: important info but I think it disrupts the flow a bit.