I decided to visualize the results of the last federal
election (Bundestagswahl 2013) with a focus on the bad guys which will here be
defined by their vote for the NPD. The website www.bundeswahlleiter.de offers
detailed data related to the bygone election. For the visualization we need
geodata which contains the information of geometry and attributes. Thus, we can
use the provided Shapefile data of the 299 election districts. This data can be
connected to our attribute data, which is the table of the election results that is
in CSV-format. Both datasets are downloadable on the mentioned website.
After data cleaning with Excel or OpenOffice, the CSV table can
be imported in QGIS and then joined to the election districts by using the Join
function and connecting the data through the election district ID. A quick
check whether the intuition about the heterogeneous distribution of the party’s
follwers can now be made by visualizing the results with the graduated
symbology option in QGIS.
As we can see, the data seems to reflect the thesis of an
allocation of bad guys in the eastern part of Germany.
We could now stop our work and finish with a clear and
simple output that supports our thesis. Nevertheless, this kind of visualization
is quite boring and will not necessarily catch our audience’s attention.
Therefore, I decided to create a cartogram. Cartograms distort
the geometry of each feature according to an attribute value. There are several
beautiful cartograms that for example show the size of each country
according to its population/wealth/beer consume and so on.
By using the awesome GIS programme ScapeToad 1.1 (www.scapetoad.choros.ch) we can
easily use the number of electorates and the number of votes for the NPD to
create two cartograms. The cartogram that is based on the electorate shows the
size of each election district according to the number of eligible voters, the other
one should show the size in relation to the actual votes for the NPD.
ScapeToad offers also to generate a distorted grid for every
cartogram and the option to export our outcomes in Shapefile format. Thus, we
can now finish our map by working on the styling and using the new Print
Composer. I decided to colour the election circles with high population to
highlight major cities so we can examine the differences in distortion between
cities and the countryside.
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Click to enlarge |
Our result shows each election circle’s importance for
the nationwide outcome and in comparison the importance of each circle
according to the NPD votes. The right map shows the blown up eastern part of
the country quite well. Moreover, I find it interesting to study the major cities. For
example, Munich, Hamburg, Freiburg and Cologne seem to have less problems with
the bad guys than Dresden and Leipzig but also Berlin.
Download map in high quality
Download map in high quality
2 comments:
Hola! Me gusta mucho su sitio. La representación cartográfica que ha tenido éxito. También su tema "donde los chicos malos votan" es interesante, pero la pregunta sigue siendo: ¿por qué esta observó heterogeneidad se produce? GIS no sólo debe representar resultados, sino también para permitir suposiciones acerca de la distribución de los fenómenos en el espacio.
Thank you for your feedback. There are different explanations that are discussed controversially according the hetergoneus distribution of extreme right-winged votes. The major factors seem to be the history of the German Democratic Republic (GDR) between 1949 and 1990 and a much higher unemployment in the east. I did not include explanations for this allocation because it is not really my expertise. The focus was more put on the workflow to visualize rather than finding an explanation.
If you are interested in further details, I can recommend this article: An East German Problem? Racist Violence in Germany
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