| ei_SCO_2007 | R Documentation |
This tibble contains 73 data sets corresponding to the 2007 Scottish National Assembly election. Each data set includes party and candidate vote results by voting unit as well as their associate cross-distributions (for votes and percentages) at the district (constituency) level.
data(ei_SCO_2007)
A tibble containing 73 observations and 6 variables:
Number_of_districtNumber assigned to the district/constituency by the New Zealand Electoral Commission.
DistrictName of the district/constituency.
Votes_to_partiesA tibble for each constituency/district with the party votes recorded in each voting unit of the district.
Votes_to_candidatesA tibble for each constituency/district with the candidate votes recorded in each voting unit of the district.
District_cross_votesA tibble for each constituency/district with the parties-candidates cross-distribution of votes in the entire constituency/district.
District_cross_percentagesA tibble for each constituency/district, with the parties to candidates voter transition probabilities (in percentages) in the entire constituency/district.
Description of the Votes_to_parties, Votes_to_candidates, District_cross_votes and District_cross_percentages variables in more detail, where N(i), R(i) and C(i) denote, respectively, the number of voting units, party voting options and candidate voting options in district i:
Votes_to_parties: A list of 73 tibbles/data.frames, with each data.frame containing N(i) observations and 2+R(i) variables. The two first variables, Polling and Address inform, respectively, about the code in the district assigned to the voting unit and the voting unit address. The rest of the columns correspond to the votes gained by the different party voting options competing in the district. The orders of the voting units in Votes_to_parties and Votes_to_candidates coincide.
Votes_to_candidates: A list of 73 tibbles/data.frames, with each data.frame containing N(i) observations and 2+C(i) variables. The two first variables, Polling and Address inform, respectively, about the code in the district assigned to the voting unit and the voting unit address. The rest of the columns correspond to the votes gained by the different candidate voting options competing in the district. The orders of the voting units in Votes_to_candidates and Votes_to_parties coincide.
District_cross_votes: A list of 73 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
District_cross_percentages: A list of 73 tibbles/data.frames, with each data.frame containing R(i) rows and 1+C(i) columns (variables). The first variable, which is labelled after the name of the district, contains the names of the parties in the same order than in corresponding Votes_to_parties tibble, the rest of the variables (columns), ordered as in the corresponding Votes_to_candidates tibble, are labelled as the candidate voting options.
Jose M. Pavia, pavia@uv.es
Own elaboration from raw data downloading from the Scotland Electoral Office website in 2011 by Carolina Plescia. These data are not longer available in that site.
ei.Datasets: Real datasets for assessing ecological inference algorithms, Social Science Computer Review, forthcoming.
ei_NZ_2002 ei_NZ_2005 ei_NZ_2008
ei_NZ_2011 ei_NZ_2014 ei_NZ_2017
ei_NZ_2020
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