dblogr/

Saskatchewan Election Results

Graphs of the 2020 & 2024 Saskatchewan Provincial Election Results

Election Results

All images are from Wikipedia

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")

Prepare Data

# devtools::install_github("derekmichaelwright/agData")
library(agData)
library(readxl)
# Prep data
myCaption <- "derekmichaelwright.github.io/dblogr/blog/saskatchewan_elections | 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))

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_col(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

Bars

# 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_col(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_02.png", mp, width = 6, height = 4)

Pies

# 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 Pies
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

Facetted Bars

# 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 Bars
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_col(legend.position = "none") +
  labs(title = "2024 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2024_election_04.png", mp, width = 24, height = 18)

Facetted Pies

# 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)
xx <- xx %>% mutate(LabelPos = ifelse(Party %in% c("SP","NDP"), LabelPos, NA))
# Plot Pies
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)

PDF

pdf("saskatchewan_2024_election_districts.pdf", width = 8, height = 4)
districts <- unique(d2024$Constituency)
#
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))
  # Plot Bars
  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_col(legend.position = "none") +
    labs(title = "2024 Saskatchewan Election", 
         x = NULL, caption = "")
  # Plot Pies
  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

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_col(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_col(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_col(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_col(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("< 20% of votes", "< 30% of votes", 
                "< 40% of votes", "< 50% of votes",
                "> 50% of votes", "> 60% of votes",
                "> 70% of votes", "> 80% of votes")
x1 <- xp %>% filter(Percent < 20) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[1])
x2 <- xp %>% filter(Percent < 30) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[2])
x3 <- xp %>% filter(Percent < 40) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[3])
x4 <- xp %>% filter(Percent < 50) %>% 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_col(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)

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_col(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

Bars

# 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_col(legend.position = "none") +
  labs(title = "2020 Saskatchewan Election", 
       x = NULL, caption = myCaption)
ggsave("saskatchewan_2020_election_02.png", mp, width = 6, height = 4)

Pies

# 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 Pies
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

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_col(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)

PDF

pdf("saskatchewan_2020_election_districts.pdf", width = 8, height = 4)
districts <- unique(d2020$Constituency)
#
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))
  # 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()

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_col(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_col(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_col(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_col(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("< 20% of votes", "< 30% of votes", 
                "< 40% of votes", "< 50% of votes",
                "> 50% of votes", "> 60% of votes",
                "> 70% of votes", "> 80% of votes")
x1 <- xp %>% filter(Percent < 20) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[1])
x2 <- xp %>% filter(Percent < 30) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[2])
x3 <- xp %>% filter(Percent < 40) %>% group_by(Party) %>% count() %>%
  mutate(Measurement = myMeasures[3])
x4 <- xp %>% filter(Percent < 50) %>% 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_col(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)

dblogr/


© Derek Michael Wright