Linear Frequency
MAT 259, 2013
Giovanni

Introduction
Question:
I would like to visualize the “presence” of the oldest 15 European Union member countries in the Library in 2011 (and compare it with the PIL (GDP) , population, squaremeters...)

Some statistics:

EU15 (1995)

English: EU 27: Further European Union enlargement
Current members
Candidate and acceding (Croatia) countries
Potential candidate countries
Membership possible

http://it.wikipedia.org/wiki/Stati_membri_dell%27Unione_europea (ita)
http://en.wikipedia.org/wiki/Member_state_of_the_European_Union (eng)

Currently the EU is composed by 27 members, but because of the small numbers of the last joining countries, I used the first 15 members (chronologically) the correspond at the EU situation in 1995.


Background
and Sketches


Query
SELECT year(cout) as 'Year', SUM(CASE WHEN title like "% belgium %" THEN 1 ELSE 0 END) as Belgium, SUM(CASE WHEN title like "% france %" THEN 1 ELSE 0 END) as France, SUM(CASE WHEN title like "% germany %" THEN 1 ELSE 0 END) as Germany, SUM(CASE WHEN title like "% italy %" THEN 1 ELSE 0 END) as Italy, SUM(CASE WHEN title like "% netherlands %" or title like "% holland %" THEN 1 ELSE 0 END) as Netherlands, SUM(CASE WHEN title like "% denmark %" THEN 1 ELSE 0 END) as Denmark, SUM(CASE WHEN title like "% ireland %" THEN 1 ELSE 0 END) as Ireland, SUM(CASE WHEN title like "% united kingdom %" or title like "% england %" or title like "% scotland %" or title like "% wales %" or title like "% nothern ireland %" THEN 1 ELSE 0 END) as UK, SUM(CASE WHEN title like "% greece %" THEN 1 ELSE 0 END) as Greece, SUM(CASE WHEN title like "% portugal %" THEN 1 ELSE 0 END) as Portugal, SUM(CASE WHEN title like "% spain %" THEN 1 ELSE 0 END) as Spain, SUM(CASE WHEN title like "% austria %" THEN 1 ELSE 0 END) as Austria, SUM(CASE WHEN title like "% finland %" THEN 1 ELSE 0 END) as Finland, SUM(CASE WHEN title like "% sweden %" THEN 1 ELSE 0 END) as Sweden FROM inraw where year(cout) = '2011' GROUP BY year(cout);
Query results


Results and Analysis


Code
I used Processing.

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Source Code