bundestag {flexclust} | R Documentation |
Results of the elections 2002 and 2005 for the German Bundestag, the first chamber of the German parliament.
data(btw2002) data(btw2005) bundestag(year, second=TRUE, percent=TRUE, nazero=TRUE, state=FALSE)
year |
numeric or character, year of the election. |
second |
logical, return second or first votes? |
percent |
logical, return percentages or absolute numbers? |
nazero |
logical, convert NA s to 0? |
state |
logical, if TRUE then only column state
from the corresponding data frame is returned, and all other
arguments are ignored. |
btw2002
and btw2005
are data frames with 299 rows
(corresponding to constituencies) and 17 columns. All columns except
state
are numeric.
Missing values indicate that a party did not candidate in the corresponding constituency.
btw2002
and btw2005
are the original data sets.
bundestag()
is a helper function which extracts first
or second votes, calculates percentages (number of votes for a party divided by
number of valid votes), replaces missing values by zero, and converts
the result from a data frame to a matrix. By default
it returns the percentage of second votes for each party, which
determines the number of seats each party gets in parliament.
Half of the Members of the German Bundestag are elected directly from Germany's 299 constituencies, the other half on the parties' land lists. Accordingly, each voter has two votes in the elections to the German Bundestag. The first vote, allowing voters to elect their local representatives to the Bundestag, decides which candidates are sent to Parliament from the constituencies.
The second vote is cast for a party list. And it is this second vote that determines the relative strengths of the parties represented in the Bundestag. At least 598 Members of the German Bundestag are elected in this way. In addition to this, there are certain circumstances in which some candidates win what are known as ``overhang mandates'' when the seats are being distributed.
Homepage of the Bundestag: http://www.bundestag.de
p02 <- bundestag(2002) pairs(p02) p05 <- bundestag(2005) pairs(p05) state <- bundestag(2002, state=TRUE) table(state) pairs(p05, col=2-(state=="Bayern"))