data-raw/riding_data_processing.R
In mccormackandrew/mapcan: Tools for Plotting Canadian Choropleth Maps and Choropleth Alternatives
library(tidyverse)
library(devtools)
# Creating a Dataset of Canadian federal election results by riding ---------------------------
## Canadian election results by riding for the 1997, 200, 2004, 2006, 2008, 2011, and 2015 elections.
## These data were obtained from the Elections Canada
## website: http://www.elections.ca/content.aspx?section=ele&dir=pas&document=index&lang=e.
# 1997 and 2000 election results --------------------------------------------------------------------------------------------
## Elections Canada provides 1997 and 2000 elections results by riding in tab-delimited format. The file is called `edsum.txt`
## though I rename is `1997_2000_election_results.txt`
## http://www.elections.ca/content.aspx?section=res&document=edsumexe&dir=rep/off/37p&lang=e.
election1997_2000 <- read.delim("data-raw/election_results/1997_2000_election_results.txt", stringsAsFactors = F)
election1997_2000 <- election1997_2000 %>%
mutate(election_year = case_when(event_english_name == "Thirty-sixth General Election 1997" ~ 1997,
event_english_name == "Thirty-seventh general election 2000" ~ 2000)) %>%
dplyr::select(-event_english_name, -event_french_name)
election1997_2000 <- election1997_2000 %>%
mutate(candidate = paste0(election1997_2000$elected_last_name, ", ",
election1997_2000$elected_first_name, " ",
election1997_2000$elected_middle_name)) %>%
mutate(candidate = trimws(candidate),
riding_code = ed_code) %>%
mutate(population = population_cnt,
voter_turnout = voter_participation_percentage,
party = elected_party_english_name,
province = province_name_english,
riding_name_english = ed_english_name,
riding_name_french = ed_french_name) %>%
dplyr::select(province, riding_name_english, riding_name_french, riding_code,
population, voter_turnout, candidate, election_year, party)
# 2004 to 2015 election results ----------------------------------------------------------------------------
### 2004
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2004_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/38gedata&document=summary&lang=e
### 2006
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2006_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/39gedata&document=summary&lang=e
### 2008
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2008_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/40gedata&document=summary&lang=e
### 2011
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2011_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/41gedata&document=summary&lang=e
### 2015
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2015_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/42gedata&document=summary&lang=e
## Because of some minor inconsistencies in naming and variables,
## it takes a some wrangling to make these files consistent enough to be merged together.
## Get all the file names with attached path
election_file_names <- paste0("data-raw/election_results/",
list.files(path = "data-raw/election_results/", pattern = "*.csv"))
## Read in all the files to a list
election_files <- lapply(election_file_names, function(x) read.csv(x, fileEncoding="latin1", stringsAsFactors = F))
## Create a vector to give unique election_year column to each dataframe in the list
election_years <- c(2004, 2006, 2008, 2011, 2015)
## Assign unique election_year column to each dataframe in the list
for(i in 1:length(election_files)) {
election_files[[i]]$election_year <- election_years[i]
}
## Naming is inconsistent, but variables all mean the same thing
## 2004 and 2006 do not have election district number, just names
names(election_files[[1]]) <- c("province", "riding", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
# Create empty "riding_code" variable to enable merging with 08/11/15 data frames (which do have riding_code)
election_files[[1]]$riding_code <- rep(NA, nrow(election_files[[1]]))
names(election_files[[2]]) <- c("province", "riding", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
# Create empty "riding_code" variable to enable merging with 08/11/15 data frames (which do have riding_code)
election_files[[2]]$riding_code <- rep(NA, nrow(election_files[[2]]))
names(election_files[[3]]) <- c("province", "riding", "riding_code", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
names(election_files[[4]]) <- c("province", "riding", "riding_code", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
names(election_files[[5]]) <- c("province", "riding", "riding_code", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
## Select and order variables of interest
for(i in 1:length(election_files)) {
election_files[[i]] <- election_files[[i]] %>%
dplyr::select(province, riding, riding_code, population, voter_turnout, candidate, election_year)
}
## Merge the dataframes together!
elections_2004_2015 <- do.call("rbind", election_files)
elections_2004_2015$party <- rep(NA, nrow(elections_2004_2015))
## Create a party variable
for(i in 1:nrow(elections_2004_2015)) {
if (grepl("Liberal", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Liberal"
} else if (grepl("Conservative", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Conservative"
} else if (grepl("N.D.P.|NDP|New Democratic Party", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "NDP"
} else if (grepl("Bloc Québécois|Bloc Québécois", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Bloc"
} else if (grepl("Green", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Green"
} else if (grepl("Independent|No Affiliation", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Independent"
} else {
elections_2004_2015$party[i] <- elections_2004_2015$party[i]
}
}
elections_2004_2015$candidate <- gsub("Conservative/conservateur|Conservative/Conservateur|Liberal/Libéral|N.D.P./N.P.D.|
|Bloc Québécois/Bloc Québécois|No Affiliation/Aucune appartenance|Independent/Indépendant|
|NDP-New Democratic Party/NPD-Nouveau Parti démocratique|NDP-New Democratic Party/NPD-Nouveau Parti démocratique|
|Green Party/Parti Vert|Liberal/Libéral|Bloc Québécois/Bloc Québécois", "", elections_2004_2015$candidate)
elections_2004_2015$candidate <- trimws(elections_2004_2015$candidate)
elections_2004_2015 <- elections_2004_2015 %>%
separate(riding, c("riding_name_english", "riding_name_french"), sep = "/")
for(i in 1:nrow(elections_2004_2015)) {
if (is.na(elections_2004_2015$riding_name_french[i])) {
elections_2004_2015$riding_name_french[i] <- elections_2004_2015$riding_name_english[i]
} else {
elections_2004_2015$riding_name_french[i] <- elections_2004_2015$riding_name_english[i]
}
}
elections_2004_2015$province[elections_2004_2015$province ==
"Newfoundland and Labrador/Terre-Neuve-et-Labrador"] <- "Newfoundland and Labrador"
elections_2004_2015$province[elections_2004_2015$province ==
"Prince Edward Island/Île-du-Prince-Édouard"] <- "Prince Edward Island"
elections_2004_2015$province[elections_2004_2015$province %in%
c("Nova Scotia/Nouvelle-Écosse",
"Nova Scotia/Nouvelle-Ã\u0089cosse")] <- "Nova Scotia"
elections_2004_2015$province[elections_2004_2015$province ==
"New Brunswick/Nouveau-Brunswick"] <- "New Brunswick"
elections_2004_2015$province[elections_2004_2015$province ==
"British Columbia/Colombie-Britannique"] <- "British Columbia"
elections_2004_2015$province[elections_2004_2015$province ==
"Northwest Territories/Territoires du Nord-Ouest"] <- "Northwest Territories"
elections_2004_2015$province[elections_2004_2015$province ==
"Prince Edward Island/Ã\u008ele-du-Prince-Ã\u0089douard"] <- "Prince Edward Island"
elections_2004_2015$province[elections_2004_2015$province %in%
c("Quebec/Québec", "Quebec/Québec")] <- "Quebec"
# Merging all the elections together -----------------------------------
federal_election_results <- rbind(election1997_2000, elections_2004_2015)
# Add additional province identifiers -----------------------------------
federal_election_results$province[federal_election_results$province == "Newfoundland"] <- "Newfoundland and Labrador"
federal_election_results$province[federal_election_results$province == "Yukon Territory"] <- "Yukon"
federal_election_results$pr_alpha <- dplyr::recode(federal_election_results$province,
`Newfoundland and Labrador` = "NL",
`Prince Edward Island` = "PE",
`Nova Scotia` = "NS",
`New Brunswick` = "NB",
`Quebec` = "QC",
`Ontario` = "ON",
`Manitoba` = "MB",
`Saskatchewan` = "SK",
`Alberta` = "AB",
`British Columbia` = "BC",
`Yukon` = "YK",
`Northwest Territories` = "NT",
`Nunavut` = "NU")
federal_election_results$pr_french <- dplyr::recode(federal_election_results$pr_alpha,
`NL` = "Terre-Neuve-et-Labrador",
`PE` = "Île-du-Prince-Édouard",
`NS` = "Nouvelle-Écosse",
`NB` = "Nouveau-Brunswick",
`QC` = "Québec",
`ON` = "Ontario",
`MB` = "Manitoba",
`SK` = "Saskatchewan",
`AB` = "Alberta",
`BC` = "Colombie-Britannique",
`YK` = "Yukon",
`NT` = "Territoires du Nord-Ouest",
`NU` = "Nunavut")
federal_election_results$pr_sgc_code <- dplyr::recode(federal_election_results$pr_alpha,
`NL` = 10L,
`PE` = 11L,
`NS` = 12L,
`NB` = 13L,
`QC` = 24L,
`ON` = 35L,
`MB` = 46L,
`SK` = 47L,
`AB` = 48L,
`BC` = 59L,
`YK` = 60L,
`NT` = 61L,
`NU` = 62L)
federal_election_results <- federal_election_results %>%
mutate(pr_english = province) %>%
dplyr::select(-province)
# Make riding_code consistent (i.e. just numbers)
federal_election_results$riding_code <- gsub("ED", "", federal_election_results$riding_code) %>%
gsub("-", "", .)
federal_election_results$riding_code <- as.numeric(federal_election_results$riding_code)
federal_election_results <- federal_election_results %>%
mutate_if(is.character, stringi::stri_enc_toascii)
use_data(federal_election_results, overwrite = T)
mccormackandrew/mapcan documentation built on June 2, 2019, 6:57 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library(tidyverse)
library(devtools)
# Creating a Dataset of Canadian federal election results by riding ---------------------------
## Canadian election results by riding for the 1997, 200, 2004, 2006, 2008, 2011, and 2015 elections.
## These data were obtained from the Elections Canada
## website: http://www.elections.ca/content.aspx?section=ele&dir=pas&document=index&lang=e.
# 1997 and 2000 election results --------------------------------------------------------------------------------------------
## Elections Canada provides 1997 and 2000 elections results by riding in tab-delimited format. The file is called `edsum.txt`
## though I rename is `1997_2000_election_results.txt`
## http://www.elections.ca/content.aspx?section=res&document=edsumexe&dir=rep/off/37p&lang=e.
election1997_2000 <- read.delim("data-raw/election_results/1997_2000_election_results.txt", stringsAsFactors = F)
election1997_2000 <- election1997_2000 %>%
mutate(election_year = case_when(event_english_name == "Thirty-sixth General Election 1997" ~ 1997,
event_english_name == "Thirty-seventh general election 2000" ~ 2000)) %>%
dplyr::select(-event_english_name, -event_french_name)
election1997_2000 <- election1997_2000 %>%
mutate(candidate = paste0(election1997_2000$elected_last_name, ", ",
election1997_2000$elected_first_name, " ",
election1997_2000$elected_middle_name)) %>%
mutate(candidate = trimws(candidate),
riding_code = ed_code) %>%
mutate(population = population_cnt,
voter_turnout = voter_participation_percentage,
party = elected_party_english_name,
province = province_name_english,
riding_name_english = ed_english_name,
riding_name_french = ed_french_name) %>%
dplyr::select(province, riding_name_english, riding_name_french, riding_code,
population, voter_turnout, candidate, election_year, party)
# 2004 to 2015 election results ----------------------------------------------------------------------------
### 2004
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2004_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/38gedata&document=summary&lang=e
### 2006
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2006_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/39gedata&document=summary&lang=e
### 2008
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2008_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/40gedata&document=summary&lang=e
### 2011
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2011_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/41gedata&document=summary&lang=e
### 2015
# File downloaded: "Table 11: Voting results, by electoral district", renamed to `2015_election_results.csv`.
# Source: http://www.elections.ca/content.aspx?section=res&dir=rep/off/42gedata&document=summary&lang=e
## Because of some minor inconsistencies in naming and variables,
## it takes a some wrangling to make these files consistent enough to be merged together.
## Get all the file names with attached path
election_file_names <- paste0("data-raw/election_results/",
list.files(path = "data-raw/election_results/", pattern = "*.csv"))
## Read in all the files to a list
election_files <- lapply(election_file_names, function(x) read.csv(x, fileEncoding="latin1", stringsAsFactors = F))
## Create a vector to give unique election_year column to each dataframe in the list
election_years <- c(2004, 2006, 2008, 2011, 2015)
## Assign unique election_year column to each dataframe in the list
for(i in 1:length(election_files)) {
election_files[[i]]$election_year <- election_years[i]
}
## Naming is inconsistent, but variables all mean the same thing
## 2004 and 2006 do not have election district number, just names
names(election_files[[1]]) <- c("province", "riding", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
# Create empty "riding_code" variable to enable merging with 08/11/15 data frames (which do have riding_code)
election_files[[1]]$riding_code <- rep(NA, nrow(election_files[[1]]))
names(election_files[[2]]) <- c("province", "riding", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
# Create empty "riding_code" variable to enable merging with 08/11/15 data frames (which do have riding_code)
election_files[[2]]$riding_code <- rep(NA, nrow(election_files[[2]]))
names(election_files[[3]]) <- c("province", "riding", "riding_code", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
names(election_files[[4]]) <- c("province", "riding", "riding_code", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
names(election_files[[5]]) <- c("province", "riding", "riding_code", "population", "electors",
"total_polls", "valid_ballots", "valid_ballots_pct", "rejected_ballots",
"rejected_ballots_pct", "total_ballots", "voter_turnout", "candidate", "election_year")
## Select and order variables of interest
for(i in 1:length(election_files)) {
election_files[[i]] <- election_files[[i]] %>%
dplyr::select(province, riding, riding_code, population, voter_turnout, candidate, election_year)
}
## Merge the dataframes together!
elections_2004_2015 <- do.call("rbind", election_files)
elections_2004_2015$party <- rep(NA, nrow(elections_2004_2015))
## Create a party variable
for(i in 1:nrow(elections_2004_2015)) {
if (grepl("Liberal", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Liberal"
} else if (grepl("Conservative", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Conservative"
} else if (grepl("N.D.P.|NDP|New Democratic Party", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "NDP"
} else if (grepl("Bloc Québécois|Bloc Québécois", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Bloc"
} else if (grepl("Green", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Green"
} else if (grepl("Independent|No Affiliation", elections_2004_2015$candidate[i]) == T) {
elections_2004_2015$party[i] <- "Independent"
} else {
elections_2004_2015$party[i] <- elections_2004_2015$party[i]
}
}
elections_2004_2015$candidate <- gsub("Conservative/conservateur|Conservative/Conservateur|Liberal/Libéral|N.D.P./N.P.D.|
|Bloc Québécois/Bloc Québécois|No Affiliation/Aucune appartenance|Independent/Indépendant|
|NDP-New Democratic Party/NPD-Nouveau Parti démocratique|NDP-New Democratic Party/NPD-Nouveau Parti démocratique|
|Green Party/Parti Vert|Liberal/Libéral|Bloc Québécois/Bloc Québécois", "", elections_2004_2015$candidate)
elections_2004_2015$candidate <- trimws(elections_2004_2015$candidate)
elections_2004_2015 <- elections_2004_2015 %>%
separate(riding, c("riding_name_english", "riding_name_french"), sep = "/")
for(i in 1:nrow(elections_2004_2015)) {
if (is.na(elections_2004_2015$riding_name_french[i])) {
elections_2004_2015$riding_name_french[i] <- elections_2004_2015$riding_name_english[i]
} else {
elections_2004_2015$riding_name_french[i] <- elections_2004_2015$riding_name_english[i]
}
}
elections_2004_2015$province[elections_2004_2015$province ==
"Newfoundland and Labrador/Terre-Neuve-et-Labrador"] <- "Newfoundland and Labrador"
elections_2004_2015$province[elections_2004_2015$province ==
"Prince Edward Island/Île-du-Prince-Édouard"] <- "Prince Edward Island"
elections_2004_2015$province[elections_2004_2015$province %in%
c("Nova Scotia/Nouvelle-Écosse",
"Nova Scotia/Nouvelle-Ã\u0089cosse")] <- "Nova Scotia"
elections_2004_2015$province[elections_2004_2015$province ==
"New Brunswick/Nouveau-Brunswick"] <- "New Brunswick"
elections_2004_2015$province[elections_2004_2015$province ==
"British Columbia/Colombie-Britannique"] <- "British Columbia"
elections_2004_2015$province[elections_2004_2015$province ==
"Northwest Territories/Territoires du Nord-Ouest"] <- "Northwest Territories"
elections_2004_2015$province[elections_2004_2015$province ==
"Prince Edward Island/Ã\u008ele-du-Prince-Ã\u0089douard"] <- "Prince Edward Island"
elections_2004_2015$province[elections_2004_2015$province %in%
c("Quebec/Québec", "Quebec/Québec")] <- "Quebec"
# Merging all the elections together -----------------------------------
federal_election_results <- rbind(election1997_2000, elections_2004_2015)
# Add additional province identifiers -----------------------------------
federal_election_results$province[federal_election_results$province == "Newfoundland"] <- "Newfoundland and Labrador"
federal_election_results$province[federal_election_results$province == "Yukon Territory"] <- "Yukon"
federal_election_results$pr_alpha <- dplyr::recode(federal_election_results$province,
`Newfoundland and Labrador` = "NL",
`Prince Edward Island` = "PE",
`Nova Scotia` = "NS",
`New Brunswick` = "NB",
`Quebec` = "QC",
`Ontario` = "ON",
`Manitoba` = "MB",
`Saskatchewan` = "SK",
`Alberta` = "AB",
`British Columbia` = "BC",
`Yukon` = "YK",
`Northwest Territories` = "NT",
`Nunavut` = "NU")
federal_election_results$pr_french <- dplyr::recode(federal_election_results$pr_alpha,
`NL` = "Terre-Neuve-et-Labrador",
`PE` = "Île-du-Prince-Édouard",
`NS` = "Nouvelle-Écosse",
`NB` = "Nouveau-Brunswick",
`QC` = "Québec",
`ON` = "Ontario",
`MB` = "Manitoba",
`SK` = "Saskatchewan",
`AB` = "Alberta",
`BC` = "Colombie-Britannique",
`YK` = "Yukon",
`NT` = "Territoires du Nord-Ouest",
`NU` = "Nunavut")
federal_election_results$pr_sgc_code <- dplyr::recode(federal_election_results$pr_alpha,
`NL` = 10L,
`PE` = 11L,
`NS` = 12L,
`NB` = 13L,
`QC` = 24L,
`ON` = 35L,
`MB` = 46L,
`SK` = 47L,
`AB` = 48L,
`BC` = 59L,
`YK` = 60L,
`NT` = 61L,
`NU` = 62L)
federal_election_results <- federal_election_results %>%
mutate(pr_english = province) %>%
dplyr::select(-province)
# Make riding_code consistent (i.e. just numbers)
federal_election_results$riding_code <- gsub("ED", "", federal_election_results$riding_code) %>%
gsub("-", "", .)
federal_election_results$riding_code <- as.numeric(federal_election_results$riding_code)
federal_election_results <- federal_election_results %>%
mutate_if(is.character, stringi::stri_enc_toascii)
use_data(federal_election_results, overwrite = T)
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