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Saskatchewan Election Results

Graphs of the 2020 & 2024 Saskatchewan Provincial Election Results

Introduction

The 2020 Saskatchewan provincial election was won by the Saskatchewan Party who won 48 (+2) of the 61 seats. Second place went to the NDP who won 13 seats. Surpringly, third place went to the newly formed Buffalo Party who beat out the Green Party despite only running candidates in 17 ridings and even came in second in 4 rural ridings, beating out the NDP. Hilariously, the Liberal Party only ran 3 candidates and only received a total of 355 votes throughout the province.

All images are from Wikipedia

Election Results

2024

2020

2016

2011

2007

2003

1999

1995

1991

Animation

library(magick)
# all images are in a folder called `maps`
fnames <- list.files("maps")
mp <- image_read(paste("maps", fnames, sep = "/")) %>% image_scale("x800")
image_write(image_animate(mp, fps = 1), "Saskatchewan_Provincial_Elections.gif")

Data

Elections SK

# devtools::install_github("derekmichaelwright/agData")
library(agData)
library(readxl)

Prepare Data

# Prep data
myCaption <- "www.dblogr.com/ or derekmichaelwright.github.io/dblogr/ | Data: Elections SK"
#
myPs2020 <- c("SP", "NDP", "BP", "GP", "PC", "LIB", "IND")
myCs2020 <- c("darkgreen", "darkorange", "burlywood4", "green", 
              "darkblue", "darkred", "darkgrey")
#
d2020 <- read_xlsx("data_saskatchewan_elections.xlsx","2020") %>% 
  select(Constituency, 2:8) %>%
  gather(Party, Votes, 2:8) %>%
  mutate(Party = factor(Party, levels = myPs2020))
#
myPs2024 <- c("SP", "NDP", "SUP", "GP", "PC", "BP", "SPP", "IND")
myCs2024 <- c("darkgreen", "darkorange", "steelblue", "green", 
              "darkblue", "burlywood4", "darkred", "darkgrey")
d2024 <- read_xlsx("data_saskatchewan_elections.xlsx","2024") %>% 
  select(Constituency, 2:9) %>%
  gather(Party, Votes, 2:9) %>%
  mutate(Party = factor(Party, levels = myPs2024))

2020

Total Votes

# Prep data
xx <- d2020 %>% 
  group_by(Party) %>%
  summarise(Votes = sum(Votes, na.rm = T)) %>%
  ungroup() %>%
  mutate(Percent = round(100 * Votes / sum(Votes), 1))
# Plot
mp <- ggplot(xx, aes(x = Party, y = Percent, fill = Party)) +
  geom_col(color = "black", alpha = 0.7) +
  geom_label(aes(label = paste(Percent, "%\n", Votes)), 
             vjust = -0.15, alpha = 0.7) +
  scale_fill_manual(values = myCs2020) +
  scale_y_continuous(breaks = seq(0,60,by=10), limits = c(0,72)) +
  theme_agData(legend.position = "none") + 
  labs(title = "2020 Saskatchewan Election", x = NULL,
       y = "Thousand Votes", caption = myCaption)
ggsave("saskatchewan_2020_election_01.png", mp, width = 6, height = 4)

Votes vs Seats

# Seats data
xs <- d2020 %>% 
  group_by(Constituency) %>%
  top_n(1)
xs <- as.data.frame(table(xs$Party)) %>% 
  rename(Party=1, Value=2) %>%
  filter(Value > 0) %>%
  arrange(desc(Party)) %>%
  mutate(Percent = 100 * Value / sum(Value, na.rm = T),
         LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  mutate(Measurement = "Seats")
# Votes data
xv <- d2020 %>% 
  mutate(Party = ifelse(Party %in% c("SP","NDP"), as.character(Party), "Other"),
         Party = factor(Party, levels = c("SP","NDP","Other"))) %>%
  group_by(Party) %>%
  summarise(Value = sum(Votes, na.rm = T)) %>%
  ungroup() %>%
  arrange(desc(Party)) %>%
  mutate(Percent = 100 * Value / sum(Value, na.rm = T),
         LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  mutate(Measurement = "Votes")
#
xx <- bind_rows(xv, xs) %>%
  mutate(Measurement = factor(Measurement, levels = c("Votes", "Seats")))
# Plot Bars
mp <- ggplot(xx, aes(x = Party, y = Percent, fill = Party)) +
  geom_col(color = "black", alpha = 0.7) +
  geom_label(aes(label = Value), fill = "white", vjust = -0.15) +
  facet_wrap(Measurement ~ .) +
  scale_fill_manual(values = c(myCs2020[1:2],"grey")) +
  scale_y_continuous(breaks = seq(0,80,by=10), limits = c(0,84)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_02.png", mp, width = 6, height = 4)
# Plot Pie
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.3) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = Value)) +
  facet_wrap(Measurement ~ .) +
  scale_fill_manual(values = c(myCs2020[1:2],"grey")) +
  theme_agData_pie(legend.position = "bottom") +
  labs(title = "2020 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_03.png", mp, width = 6, height = 4)

All Ridings

PDF

pdf("saskatchewan_2020_election_districts.pdf", width = 8, height = 4)
districts <- unique(d2020$Constituency)
#i<-"THE BATTLEFORDS"
for(i in districts) {
  xi <- d2020 %>% filter(Constituency == i) %>%
    mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
    arrange(desc(Party)) %>%
    mutate(LabelPos = cumsum(Percent) - (Percent / 2),
           #LabelPos = ifelse(Votes == 0, NA, LabelPos)
           )
  # Bar Chart
  mp1 <- ggplot(xi, aes(x = Party, y = Percent, fill = Party)) +
    geom_col(color = "black", alpha = 0.7) +
    geom_label(aes(label = Votes), vjust = -0.15, 
               color = "white", alpha = 0.7) + 
    facet_wrap(Constituency ~ .) +
    scale_fill_manual(values = myCs2020, drop = F) +
    scale_x_discrete(drop = F) +
    ylim(c(0,88)) +
    theme_agData(legend.position = "none") +
    labs(title = "2020 Saskatchewan Election", 
         x = NULL, caption = "")
  # Plot Pie
  mp2 <- ggplot(xi, aes(x = "", y = Percent)) +
    geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.3) +
    coord_polar("y", start = 0) +
    geom_label(aes(y = LabelPos, label = round(Percent)), nudge_x = 0.3) +
    facet_wrap(Constituency ~ .) +
    scale_fill_manual(values = myCs2020, breaks = myPs2020) +
    theme_agData_pie(legend.position = "none") +
    labs(title = "", x = NULL, caption = myCaption)
  #
  mp <- ggarrange(mp1, mp2, ncol = 2, align = "h")
  print(mp)
}
dev.off()
## png 
##   2

Facetted

# Prep data
xx <- d2020 %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  arrange(desc(Party)) %>%
  mutate(LabelPos = cumsum(Percent) - (Percent / 2))
xw <- xx %>% top_n(1, Percent)
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 6, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 8) +
  scale_fill_manual(values = myCs2020) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_04.png", mp, width = 24, height = 18)
# Plot Pie
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.4) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = paste(round(Percent),"%")), 
             size = 5, nudge_x = 0.15) +
  facet_wrap(Constituency ~ ., ncol = 13) +
  scale_fill_manual(values = myCs2020) +
  theme_agData_pie(legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 1)) +
  labs(title = "2020 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_05.png", mp, width = 36, height = 16)

Rural Ridings

# Prep data
xx <- d2020 %>%
  filter(!grepl("REGINA|SASKATOON|PRINCE ALBERT|MOOSE JAW|BATTLEFORDS|
                SWIFT CURRENT|YORKTON|CUMBERLAND|ATHABASCA", Constituency)) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  arrange(desc(Party)) %>%
  mutate(LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  arrange(desc(Percent)) %>% 
  mutate(Constituency = factor(Constituency, levels = unique(.$Constituency)))
xw <- xx %>% top_n(1, Percent)
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 4, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 7) +
  scale_fill_manual(values = myCs2020) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election - Rural Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_06.png", mp, width = 18, height = 8)
# Plot Pie
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.2) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = paste(round(Percent),"%")), 
             size = 4, nudge_x = 0.1) +
  facet_wrap(Constituency ~ ., ncol = 9) +
  scale_fill_manual(values = myCs2020) +
  theme_agData_pie(legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 1)) +
  labs(title = "2020 Saskatchewan Election - Rural Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_07.png", mp, width = 20, height = 8)

Urban Ridings

# Prep data
xx <- d2020 %>%
  filter(grepl("REGINA|SASKATOON|PRINCE ALBERT|MOOSE JAW|BATTLEFORDS|
                SWIFT CURRENT|YORKTON|CUMBERLAND|ATHABASCA", Constituency)) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  arrange(desc(Party)) %>%
  mutate(LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  arrange(Party, desc(Percent)) %>% 
  mutate(Constituency = factor(Constituency, levels = unique(.$Constituency)))
xw <- xx %>% top_n(1, Percent)
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 6, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 7) +
  scale_fill_manual(values = myCs2020) +
  ylim(c(0,80)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election - Urban + Northern Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_08.png", mp, width = 20, height = 10)
# Plot Pie
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.4) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = paste(round(Percent),"%")), 
             size = 4, nudge_x = 0.1) +
  facet_wrap(Constituency ~ ., ncol = 7) +
  scale_fill_manual(values = myCs2020) +
  theme_agData_pie(legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 1)) +
  labs(title = "2020 Saskatchewan Election - Urban + Northern Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_09.png", mp, width = 26, height = 20)

Buffalo Party

All Ridings

# Prep data
myCs <- d2020 %>% filter(Party == "BP", Votes > 0) %>% 
  arrange(desc(Votes)) %>% pull(Constituency)
xx <- d2020 %>%
  filter(Constituency %in% myCs) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T),
         Constituency = factor(Constituency, levels = myCs))
xw <- xx %>% filter(Party == "BP") 
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 4, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 6) +
  scale_fill_manual(values = myCs2020) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election - Buffalo Party", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_10.png", mp, width = 16, height = 6)

Buffalo Wins

# Prep data
myCs <- c("ESTEVAN", "CYPRESS HILLS", "CANNINGTON", "KINDERSLEY")
xx <- d2020 %>%
  filter(Constituency %in% myCs) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T),
         Constituency = factor(Constituency, levels = myCs))
xw <- xx %>% filter(Party == "BP") 
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 4, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 2) +
  scale_fill_manual(values = myCs2020) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election - Buffalo Party", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_11.png", mp, width = 6, height = 6)

Less than …

# Prep data
xp <- d2020 %>% group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  filter(Party %in% c("SP", "NDP"))
myMeasures <- c("< 10% of votes", "< 20% of votes",
                "< 30% of votes", "< 40% of votes",
                "> 50% of votes", "> 60% of votes",
                "> 70% of votes", "> 80% of votes")
x1 <- xp %>% filter(Percent < 10) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[1])
x2 <- xp %>% filter(Percent < 20) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[2])
x3 <- xp %>% filter(Percent < 30) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[3])
x4 <- xp %>% filter(Percent < 40) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[4])
x5 <- xp %>% filter(Percent > 50) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[5])
x6 <- xp %>% filter(Percent > 60) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[6])
x7 <- xp %>% filter(Percent > 70) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[7])
x8 <- xp %>% filter(Percent > 80) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[8])
xx <- bind_rows(x1, x2, x3, x4, x5, x6, x7, x8) 
# Plot
mp <- ggplot(xx, aes(x = Party, y = n)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_label(aes(label = n), vjust = -0.1) +
  facet_wrap(. ~ Measurement, ncol = 4) +
  scale_fill_manual(values = myCs2020) +
  ylim(c(0,46)) +
  theme_agData(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election", 
       subtitle = "Total number of districts = 61",
       y = "Number of Districts with ...", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_12.png", mp, width = 6, height = 5)

2024

Total Votes

# Prep data
xx <- d2024 %>% 
  group_by(Party) %>%
  summarise(Votes = sum(Votes, na.rm = T)) %>%
  ungroup() %>%
  mutate(Percent = round(100 * Votes / sum(Votes), 1))
# Plot
mp <- ggplot(xx, aes(x = Party, y = Percent, fill = Party)) +
  geom_col(color = "black", alpha = 0.7) +
  geom_label(aes(label = paste(Percent, "%\n", Votes)), 
             vjust = -0.15, alpha = 0.7) +
  scale_fill_manual(values = myCs2024) +
  scale_y_continuous(breaks = seq(0,60,by=10), limits = c(0,72)) +
  theme_agData(legend.position = "none") + 
  labs(title = "2024 Saskatchewan Election", x = NULL,
       y = "Thousand Votes", caption = myCaption)
ggsave("saskatchewan_2024_election_01.png", mp, width = 6, height = 4)

Votes vs Seats

# Seats data
xs <- d2024 %>% 
  group_by(Constituency) %>%
  top_n(1)
xs <- as.data.frame(table(xs$Party)) %>% 
  rename(Party=1, Value=2) %>%
  filter(Value > 0) %>%
  arrange(desc(Party)) %>%
  mutate(Percent = 100 * Value / sum(Value, na.rm = T),
         LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  mutate(Measurement = "Seats")
# Votes data
xv <- d2024 %>% 
  mutate(Party = ifelse(Party %in% c("SP","NDP"), as.character(Party), "Other"),
         Party = factor(Party, levels = c("SP","NDP","Other"))) %>%
  group_by(Party) %>%
  summarise(Value = sum(Votes, na.rm = T)) %>%
  ungroup() %>%
  arrange(desc(Party)) %>%
  mutate(Percent = 100 * Value / sum(Value),
         LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  mutate(Measurement = "Votes")
#
xx <- bind_rows(xv, xs) %>%
  mutate(Measurement = factor(Measurement, levels = c("Votes", "Seats")))
# Plot Bars
mp <- ggplot(xx, aes(x = Party, y = Percent, fill = Party)) +
  geom_col(color = "black", alpha = 0.7) +
  geom_label(aes(label = Value), fill = "white", vjust = -0.15) +
  facet_wrap(Measurement ~ .) +
  scale_fill_manual(values = c(myCs2024[1:2],"grey")) +
  scale_y_continuous(breaks = seq(0,80,by=10), limits = c(0,84)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_02.png", mp, width = 6, height = 4)
# Plot Pie
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.3) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = Value)) +
  facet_wrap(Measurement ~ .) +
  scale_fill_manual(values = c(myCs2024[1:2],"grey")) +
  theme_agData_pie(legend.position = "bottom") +
  labs(title = "2024 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_03.png", mp, width = 6, height = 4)

All Ridings

PDF

pdf("saskatchewan_2024_election_districts.pdf", width = 8, height = 4)
districts <- unique(d2024$Constituency)
#i<-"THE BATTLEFORDS"
for(i in districts) {
  xi <- d2024 %>% filter(Constituency == i) %>%
    mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
    arrange(desc(Party)) %>%
    mutate(LabelPos = cumsum(Percent) - (Percent / 2),
           #LabelPos = ifelse(Votes == 0, NA, LabelPos)
           )
  # Bar Chart
  mp1 <- ggplot(xi, aes(x = Party, y = Percent, fill = Party)) +
    geom_col(color = "black", alpha = 0.7) +
    geom_label(aes(label = Votes), vjust = -0.15, 
               color = "white", alpha = 0.7) + 
    facet_wrap(Constituency ~ .) +
    scale_fill_manual(values = myCs2024, drop = F) +
    scale_x_discrete(drop = F) +
    ylim(c(0,88)) +
    theme_agData(legend.position = "none") +
    labs(title = "2024 Saskatchewan Election", 
         x = NULL, caption = "")
  # Plot Pie
  mp2 <- ggplot(xi, aes(x = "", y = Percent)) +
    geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.3) +
    coord_polar("y", start = 0) +
    geom_label(aes(y = LabelPos, label = round(Percent)), nudge_x = 0.3) +
    facet_wrap(Constituency ~ .) +
    scale_fill_manual(values = myCs2024, breaks = myPs2024) +
    theme_agData_pie(legend.position = "none") +
    labs(title = "", x = NULL, caption = myCaption)
  #
  mp <- ggarrange(mp1, mp2, ncol = 2, align = "h")
  print(mp)
}
dev.off()
## png 
##   2

Facetted

# Prep data
xx <- d2024 %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  arrange(desc(Party)) %>%
  mutate(LabelPos = cumsum(Percent) - (Percent / 2))
xw <- xx %>% top_n(1, Percent)
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 6, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 8) +
  scale_fill_manual(values = myCs2024) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_04.png", mp, width = 24, height = 18)
# Plot Pie
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.4) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = paste(round(Percent),"%")), 
             size = 5, nudge_x = 0.15) +
  facet_wrap(Constituency ~ ., ncol = 13) +
  scale_fill_manual(values = myCs2024) +
  theme_agData_pie(legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 1)) +
  labs(title = "2024 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_05.png", mp, width = 36, height = 16)

Rural Ridings

# Prep data
xx <- d2024 %>%
  filter(!grepl("Regina|Saskatoon|Prince Albert|Moose Jaw|Battlefords|
                Swift Current|Yorkton|Cumberland|Athabasca", Constituency)) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  arrange(desc(Party)) %>%
  mutate(LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  arrange(desc(Percent)) %>% 
  mutate(Constituency = factor(Constituency, levels = unique(.$Constituency)))
xw <- xx %>% top_n(1, Percent)
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 4, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 7) +
  scale_fill_manual(values = myCs2024) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election - Rural Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_06.png", mp, width = 18, height = 8)
# Plot Pie
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.2) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = paste(round(Percent),"%")), 
             size = 4, nudge_x = 0.1) +
  facet_wrap(Constituency ~ ., ncol = 9) +
  scale_fill_manual(values = myCs2024) +
  theme_agData_pie(legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 1)) +
  labs(title = "2024 Saskatchewan Election - Rural Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_07.png", mp, width = 20, height = 8)

Urban Ridings

# Prep data
xx <- d2024 %>%
  filter(grepl("Regina|Saskatoon|Prince Albert|Moose Jaw|Battlefords|
                Swift Current|Yorkton|Cumberland|Athabasca", Constituency)) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  arrange(desc(Party)) %>%
  mutate(LabelPos = cumsum(Percent) - (Percent / 2)) %>%
  arrange(Party, desc(Percent)) %>% 
  mutate(Constituency = factor(Constituency, levels = unique(.$Constituency)))
xw <- xx %>% top_n(1, Percent)
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 6, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 7) +
  scale_fill_manual(values = myCs2024) +
  ylim(c(0,80)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election - Urban + Northern Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_08.png", mp, width = 20, height = 10)
# Plot Pie
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
mp <- ggplot(xx, aes(x = "", y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7, lwd = 0.4) +
  coord_polar("y", start = 0) +
  geom_label(aes(y = LabelPos, label = paste(round(Percent),"%")), 
             size = 4, nudge_x = 0.1) +
  facet_wrap(Constituency ~ ., ncol = 7) +
  scale_fill_manual(values = myCs2024) +
  theme_agData_pie(legend.position = "bottom") +
  guides(fill = guide_legend(nrow = 1)) +
  labs(title = "2024 Saskatchewan Election - + Northern Urban Ridings", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_09.png", mp, width = 26, height = 20)

BP & SUP

All Ridings

# Prep data
myCs <- d2024 %>% filter(Party %in% c("BP","SUP"), Votes > 0) %>% 
  arrange(desc(Votes)) %>% pull(Constituency) %>% unique()
xx <- d2024 %>%
  filter(Constituency %in% myCs) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T),
         Constituency = factor(Constituency, levels = myCs))
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  facet_wrap(Constituency ~ ., ncol = 6) +
  scale_fill_manual(values = myCs2024) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election - BP + SUP", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_10.png", mp, width = 16, height = 12)

Buffalo Wins

# Prep data
myCs <- c("Estevan-Big Muddy", "Cypress Hills", 
          "Cannington", "Kindersley-Biggar")
xx <- d2024 %>%
  filter(Constituency %in% myCs) %>%
  group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T),
         Constituency = factor(Constituency, levels = myCs))
xw <- xx %>% filter(Party == "BP") 
# Plot Bar
mp <- ggplot(xx, aes(x = Party, y = Percent)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_text(aes(label = round(Percent,1)), size = 4, vjust = -0.2) +
  geom_label(data = xw, x = 4, y = 70, color = "white", size = 7.5,
             aes(label = paste(round(Percent,1),"%"), fill = Party)) +
  facet_wrap(Constituency ~ ., ncol = 2) +
  scale_fill_manual(values = myCs2024) +
  ylim(c(0,89)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election - Buffalo Party", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_11.png", mp, width = 6, height = 6)

Less than …

# Prep data
xp <- d2024 %>% group_by(Constituency) %>%
  mutate(Percent = 100 * Votes / sum(Votes, na.rm = T)) %>%
  filter(Party %in% c("SP", "NDP"))
myMeasures <- c("< 10% of votes", "< 20% of votes",
                "< 30% of votes", "< 40% of votes",
                "> 50% of votes", "> 60% of votes",
                "> 70% of votes", "> 80% of votes")
x1 <- xp %>% filter(Percent < 10) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[1])
x2 <- xp %>% filter(Percent < 20) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[2])
x3 <- xp %>% filter(Percent < 30) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[3])
x4 <- xp %>% filter(Percent < 40) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[4])
x5 <- xp %>% filter(Percent > 50) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[5])
x6 <- xp %>% filter(Percent > 60) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[6])
x7 <- xp %>% filter(Percent > 70) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[7])
x8 <- xp %>% filter(Percent > 80) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[8])
xx <- bind_rows(x1, x2, x3, x4, x5, x6, x7, x8) %>%
  mutate(Measurement = factor(Measurement, levels = myMeasures))
# Plot
mp <- ggplot(xx, aes(x = Party, y = n)) +
  geom_col(aes(fill = Party), color = "black", alpha = 0.7) +
  geom_label(aes(label = n), vjust = -0.1) +
  facet_wrap(. ~ Measurement, ncol = 4, drop = F) +
  scale_fill_manual(values = myCs2024) +
  ylim(c(0,46)) +
  theme_agData(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election", 
       subtitle = "Total number of districts = 61",
       y = "Number of Districts with ...", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_12.png", mp, width = 6, height = 5)

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© Derek Michael Wright