| Title: | New Zealand Election Data |
|---|---|
| Description: | Convenient access to New Zealand election results by voting place. Voting places have been matched to Regional Council, Territorial Authority, and Area Unit, to facilitate matching with additional data. Opinion polls since 2002 and some convenience analytical function are also supplied. |
| Authors: | Peter Ellis [aut, cre] |
| Maintainer: | Peter Ellis <[email protected]> |
| License: | GPL-3 |
| Version: | 0.4.0 |
| Built: | 2024-11-14 04:44:50 UTC |
| Source: | https://github.com/cran/nzelect |
Convenient access to New Zealand election results by voting place. Voting places have been matched to Regional Council, Territorial Authority, and Area Unit, to facilitate matching with additional data. Opinion polls since 2002 and some convenience analytical function are also supplied.
Maintainer: Peter Ellis [email protected]
Allocates seats in Parliament after an election using the Sainte-Lague allocation formula
allocate_seats(votes, parties = names(votes), nseats = 120, threshold = 0.05, electorate = rep(0, length(votes)))allocate_seats(votes, parties = names(votes), nseats = 120, threshold = 0.05, electorate = rep(0, length(votes)))
votes |
vector of vote proportions or counts. |
parties |
vector of names of parties. |
nseats |
number of seats to allocate. Note that in mixed systems such as New Zealand's
where |
threshold |
minimum proportion of votes needed to be allocated a seat. |
electorate |
a numeric vector of same length as parties, for use in mixed-member
proportional systems such as New Zealand's. If the ith |
A list with two elements: a data frame seats_df and a vector
seats_v, each of which provides information on the number of seats
allocated to each party.
The data frame has four columns: proportionally_allocated,
electorate_seats, final and party. In New Zealand, the number of
"list MPs" for each party is final - electorate_seats.
The vector is the same as final in the data frame, with names equal to party.
Peter Ellis
http://www.elections.org.nz/voting-system/mmp-voting-system/sainte-lague-allocation-formula
See also Wikipedia on the Webster/Sainte-Lague method.
# From Wikipedia; should return 3, 2, 2: allocate_seats(c(53000, 24000, 23000), nseats = 7, threshold = 0) # From 2014 New Zealand election votes <- c(National = 1131501, Labour = 604535, Green = 257359, NZFirst = 208300, Cons = 95598, IntMana = 34094, Maori = 31849, Act = 16689, United = 5286, Other = 20411) electorate = c(41, 27, 0, 0, 0, 0, 1, 1, 1, 0) # Actual result: allocate_seats(votes, electorate = electorate) # Result if there were no 5% minimum threshold: allocate_seats(votes, electorate = electorate, threshold = 0)$seats_v# From Wikipedia; should return 3, 2, 2: allocate_seats(c(53000, 24000, 23000), nseats = 7, threshold = 0) # From 2014 New Zealand election votes <- c(National = 1131501, Labour = 604535, Green = 257359, NZFirst = 208300, Cons = 95598, IntMana = 34094, Maori = 31849, Act = 16689, United = 5286, Other = 20411) electorate = c(41, 27, 0, 0, 0, 0, 1, 1, 1, 0) # Actual result: allocate_seats(votes, electorate = electorate) # Result if there were no 5% minimum threshold: allocate_seats(votes, electorate = electorate, threshold = 0)$seats_v
New Zealand 2014 general election results by voting place
GE2014GE2014
A data frame with 136,195 rows and 7 variables.
ApproxLocation. Approximate location of voting place
VotingPlace. Exact location of voting place
Party. Party voted for (party vote) or party of candidate voted for
(candidate vote)
Votes. Number of votes
Electorate. Electorate in which voters were enrolled. Note that this
is not necessarily the physical location of the VotingPlace, so VotingPlace
and Electorate have a many to many relationship
VotingType. Party (proportional representation) or Candidate (first past
the vote). In New Zealand each voter has to vote for both an individual
candidate to represent their electorate, and a party vote for the overall makeup
of Parliament.
Candidate. If VotingType == "Candidate", the name of the candidate;
otherwise NA
GE2014 is deprecated; please use nzge instead - it has results back to 2002 and is the one we
will update in future.
http://www.electionresults.govt.nz/electionresults_2014/e9/html/statistics.html
# the following matches the results published at # http://www.electionresults.govt.nz/electionresults_2014/e9/html/e9_part1.html library(tidyr) library(dplyr) GE2014 %>% mutate(VotingType = paste0(VotingType, "Vote")) %>% group_by(Party, VotingType) %>% summarise(Votes = sum(Votes)) %>% spread(VotingType, Votes) %>% select(Party, PartyVote, CandidateVote) %>% ungroup() %>% arrange(desc(PartyVote))# the following matches the results published at # http://www.electionresults.govt.nz/electionresults_2014/e9/html/e9_part1.html library(tidyr) library(dplyr) GE2014 %>% mutate(VotingType = paste0(VotingType, "Vote")) %>% group_by(Party, VotingType) %>% summarise(Votes = sum(Votes)) %>% spread(VotingType, Votes) %>% select(Party, PartyVote, CandidateVote) %>% ungroup() %>% arrange(desc(PartyVote))
Voting places for the New Zealand 2014 general election
Locations2014Locations2014
A data frame with 2,568 rows and 9 variables.
ElectorateNumber
ElectorateName. Name of electorate in which the voting place is
physically located.
VotingPlaceID.
NZTM2000Northing
NZTM2000Easting
WGS84Latitude
WGS84Longitude
VotingPlace. Address of the VotingPlace. Cross-references to
GE2014$VotingPlace.
TA2014_NAM. Name of the Territorial Authority in which the voting
place is physically located.
REGC2014_n. Name of the Regional Council in which the voting place is physically located.
AU2014. Number of the Area Unit in which the voting place is physically located.
MB2014. Number of the Mesh Block in which the voting place is physically located.
Locations2014 is deprecated; please use voting_places instead - it has locations back to
2008 and is the one we will update in future.
http://www.electionresults.govt.nz/electionresults_2014/e9/html/statistics.html for the voting place locations. http://www.stats.govt.nz/browse_for_stats/Maps_and_geography/Geographic-areas/digital-boundary-files.aspx for the 2014 shapefiles for Regional Council, Territorial Authority, and Area Unit. See https://github.com/ellisp/nzelect/tree/master/prep for the code linking the two.
New Zealand general election results by voting place for 2002, 2005, 2008, 2011 and 2014
nzgenzge
A data frame with 728,602 rows and 9 variables.
approx_location. Approximate location of voting place
vorting_place. Description of exact location of voting place
party. Party voted for (party vote) or party of candidate voted for
(candidate vote)
votes. Number of votes
electorate. Electorate in which voters were enrolled. Note that this
is not necessarily the physical location of the voting_place, so voting_place
and electorate have a many to many relationship
voting_type. Party (proportional representation) or Candidate (first past
the vote). In New Zealand each voter has to vote for both an individual
candidate to represent their electorate, and a party vote for the overall makeup
of Parliament.
candidate. If voting_type == "Candidate", the name of the candidate;
otherwise NA
election_year. Year of the election.
electorate_number. Number of the electorate.
http://www.electionresults.govt.nz/electionresults_2014/e9/html/statistics.html
# the following matches the results published at # http://www.electionresults.govt.nz/electionresults_2014/e9/html/e9_part1.html library(tidyr) library(dplyr) nzge %>% mutate(voting_type = paste0(voting_type, " vote")) %>% group_by(party, voting_type, election_year) %>% summarise(votes = sum(votes)) %>% spread(voting_type, votes) %>% ungroup() %>% arrange(election_year, desc(`Party vote`))# the following matches the results published at # http://www.electionresults.govt.nz/electionresults_2014/e9/html/e9_part1.html library(tidyr) library(dplyr) nzge %>% mutate(voting_type = paste0(voting_type, " vote")) %>% group_by(party, voting_type, election_year) %>% summarise(votes = sum(votes)) %>% spread(voting_type, votes) %>% ungroup() %>% arrange(election_year, desc(`Party vote`))
Metadata associated with New Zealand political parties in the early 21st century
parties_dfparties_df
A data frame of colours, shades, short and long names
https://en.wikipedia.org/wiki/Wikipedia:Index_of_New_Zealand_political_party_meta_attributes
Colours associated with New Zealand political parties in the early 21st century
parties_vparties_v
A named vector of colours
https://en.wikipedia.org/wiki/Wikipedia:Index_of_New_Zealand_political_party_meta_attributes
# Example use of parties_v in a colour scale for ggplot2 if(require(ggplot2) & require(scales) & require(dplyr) & require(forcats)){ polls %>% filter(MidDate > as.Date("2014-11-20") & !is.na(VotingIntention)) %>% filter(Party %in% c("National", "Labour", "Green", "NZ First")) %>% mutate(Party = fct_reorder(Party, VotingIntention, .desc = TRUE), Party = fct_drop(Party)) %>% ggplot(aes(x = MidDate, y = VotingIntention, colour = Party, linetype = Pollster)) + geom_line(alpha = 0.5) + geom_point(aes(shape = Pollster)) + geom_smooth(aes(group = Party), se = FALSE, colour = "grey15", span = .4) + scale_colour_manual(values = parties_v) + scale_y_continuous("Voting intention", label = percent) + scale_x_date("") + facet_wrap(~Party, scales = "free_y") }# Example use of parties_v in a colour scale for ggplot2 if(require(ggplot2) & require(scales) & require(dplyr) & require(forcats)){ polls %>% filter(MidDate > as.Date("2014-11-20") & !is.na(VotingIntention)) %>% filter(Party %in% c("National", "Labour", "Green", "NZ First")) %>% mutate(Party = fct_reorder(Party, VotingIntention, .desc = TRUE), Party = fct_drop(Party)) %>% ggplot(aes(x = MidDate, y = VotingIntention, colour = Party, linetype = Pollster)) + geom_line(alpha = 0.5) + geom_point(aes(shape = Pollster)) + geom_smooth(aes(group = Party), se = FALSE, colour = "grey15", span = .4) + scale_colour_manual(values = parties_v) + scale_y_continuous("Voting intention", label = percent) + scale_x_date("") + facet_wrap(~Party, scales = "free_y") }
Opinion polling of voting intention for New Zealand general elections
pollspolls
A data frame of 7 columns
Intended party vote. Note the original source says 'Refusals are generally excluded from the party vote percentages, while question wording and the treatment of "don't know" responses and those not intending to vote may vary between survey organisations.'
EndData and StartDate refer to the data collection period. These
dates were entered by hand, use with caution and check against the WikipediaDates
column which is the version from the original source.
Where the date in Wikipedia is given only as "released on X", the start and end dates have been deemed to be two days before release.
The data for the 2005 election are particularly unreliable and in some cases it is not clear whether some parties have been omitted. For example, the Digipoll from 22 March to 30 March 2005 has figures only for National and Labour (47.5 and 34.5).
https://en.wikipedia.org/wiki/Opinion_polling_for_the_New_Zealand_general_election,_2005 https://en.wikipedia.org/wiki/Opinion_polling_for_the_New_Zealand_general_election,_2008 https://en.wikipedia.org/wiki/Opinion_polling_for_the_New_Zealand_general_election,_2011 https://en.wikipedia.org/wiki/Opinion_polling_for_the_New_Zealand_general_election,_2014 https://en.wikipedia.org/wiki/Opinion_polling_for_the_New_Zealand_general_election,_2017
if(require(ggplot2) & require(scales) & require(dplyr) & require(forcats)){ election_dates <- polls %>% filter(Pollster == "Election result") %>% select(MidDate) %>% distinct() polls %>% filter(Party %in% c("National", "Labour", "Green", "NZ First")) %>% mutate(Party = fct_reorder(Party, VotingIntention, .desc = TRUE), Pollster = fct_relevel(Pollster, "Election result")) %>% ggplot(aes(x = MidDate, y = VotingIntention, linetype = Pollster)) + geom_line(alpha = 0.5) + geom_point(aes(colour = Client), size = 0.7) + geom_smooth(aes(group = Party), se = FALSE, colour = "grey15", span = .20) + scale_y_continuous("Voting intention", label = percent) + scale_x_date("") + facet_wrap(~Party, scales = "free_y") + geom_vline(xintercept = as.numeric(election_dates$MidDate), colour = "grey80") }if(require(ggplot2) & require(scales) & require(dplyr) & require(forcats)){ election_dates <- polls %>% filter(Pollster == "Election result") %>% select(MidDate) %>% distinct() polls %>% filter(Party %in% c("National", "Labour", "Green", "NZ First")) %>% mutate(Party = fct_reorder(Party, VotingIntention, .desc = TRUE), Pollster = fct_relevel(Pollster, "Election result")) %>% ggplot(aes(x = MidDate, y = VotingIntention, linetype = Pollster)) + geom_line(alpha = 0.5) + geom_point(aes(colour = Client), size = 0.7) + geom_smooth(aes(group = Party), se = FALSE, colour = "grey15", span = .20) + scale_y_continuous("Voting intention", label = percent) + scale_x_date("") + facet_wrap(~Party, scales = "free_y") + geom_vline(xintercept = as.numeric(election_dates$MidDate), colour = "grey80") }
Voting places for the New Zealand general elections in 2008, 2011 and 2014
voting_placesvoting_places
A data frame with 7,909 rows and 15 variables.
electorate_number
electorate. Name of electorate in which the voting place is
physically located.
voting_place_id.
voting_place_suburb
northing Coordinates, on one of two incompatible systems - either NZTM2000 or NZMG -
see the coordinate_system variable for which.
easting as per northing
longitude Use with caution.
latitude Use with caution.
voting_place. Address of the VotingPlace. Cross-references to
nzge$voting_place.
election_year. Year in which this was a voting place for the election.
coordinate_system. Either NZMG (New Zealand Map Grid) or NZTM2000 (New Zealand Transverse
Mercator Projection)
TA2014_NAM. Name of the Territorial Authority in which the voting
place is physically located. Use with caution.
REGC2014_n. Name of the Regional Council in which the voting place is physically located. Use with caution.
AU2014. Number of the Area Unit in which the voting place is physically located. Use with caution.
MB2014. Number of the Mesh Block in which the voting place is physically located. Use with caution.
There are problems with the locations of many voting places which will be resolved in future versions.
http://www.electionresults.govt.nz/electionresults_2014/e9/html/statistics.html (and similar for earlier years) for the voting place locations. http://www.stats.govt.nz/browse_for_stats/Maps_and_geography/Geographic-areas/digital-boundary-files.aspx for the 2014 shapefiles for Regional Council, Territorial Authority, and Area Unit. See https://github.com/ellisp/nzelect/tree/master/prep for the code linking the two.
Create a vector of weights to use in calculating a weighted average
weight_polls(polldates, n = rep(1, length(polldates)), method = c("pundit", "curia"), refdate = Sys.Date(), electiondate = as.Date("2017-09-23"))weight_polls(polldates, n = rep(1, length(polldates)), method = c("pundit", "curia"), refdate = Sys.Date(), electiondate = as.Date("2017-09-23"))
polldates |
a vector of dates of polls. |
n |
a vector of sample sizes of polls. |
method |
which weighting method to use; either that used in 2017 by Curia or Pundit (two New Zealand poll aggregators). |
refdate |
date against which to compare polling dates (both methods give more weight to more recent polls). |
electiondate |
date of the next election (the Curia weighting method gives more weight to polls close to the election). |
This function is experimental and so far it has not been possible to match published results. Use with caution.
This function is to facilitate reproduction of existing poll aggregation methods.
Both methods provide weights proportional to the sample sizes.
The Pundit Poll of Polls states its method is an adaptation of that used by fivethirtyeight. It gives polls a half life of 30 days, so a poll that is 120 days old gets 0.125 the weight of one conducted today.
The Curia method gives weight of 1 to all polls that are seven or less days old; 0 to polls older than 38 days; and a linear interpolation for inbetween. Note that this method gives zero weight to many older surveys that would get a weight in the pundit method.
Caution - as at March 2017, this function had failed to exactly replicate results on the webpages of Curia and Pundit.
a vector of weights, adding up to one, for use in calculating a weighted average of opinion polls
http://www.curia.co.nz/methodology/ http://www.pundit.co.nz/content/poll-of-polls
polldates <- tail(unique(polls$MidDate), 20) weight_polls(polldates, method = "curia", refdate = as.Date("2017-09-22")) weight_polls(polldates, method = "pundit", refdate = as.Date("2017-09-22"))polldates <- tail(unique(polls$MidDate), 20) weight_polls(polldates, method = "curia", refdate = as.Date("2017-09-22")) weight_polls(polldates, method = "pundit", refdate = as.Date("2017-09-22"))