Data

Source are from Sejong silok, summary table from Professor Oh, Kisoo.

region class class.2 vote counts
SL High Bureaus Yes 21
SL High Bureaus No 194
SL 3rd.current Bureaus Yes 259
SL 3rd.current Bureaus No 393
SL 3rd.former Bureaus Yes 443
SL 3rd.former Bureaus No 117
YH Commons Commons Yes 1123
YH Commons Commons No 71
GG Chief Bureaus Yes 29
GG Chief Bureaus No 5
GG Commons Commons Yes 17076
GG Commons Commons No 236
PA High Bureaus No 1
PA Chief Bureaus Yes 6
PA Chief Bureaus No 35
PA Commons Commons Yes 1326
PA Commons Commons No 28474
HH Chief Bureaus Yes 17
HH Chief Bureaus No 17
HH Commons Commons Yes 4454
HH Commons Commons No 15601
CC High Bureaus No 2
CC Chief Bureaus Yes 35
CC Chief Bureaus No 26
CC Commons Commons Yes 6982
CC Commons Commons No 14013
KW Chief Bureaus Yes 5
KW Chief Bureaus No 10
KW Commons Commons Yes 939
KW Commons Commons No 6888
HG High Bureaus No 1
HG Chief Bureaus Yes 3
HG Chief Bureaus No 14
HG Commons Commons Yes 75
HG Commons Commons No 7387
GS Chief Bureaus Yes 55
GS Chief Bureaus No 16
GS Commons Commons Yes 36262
GS Commons Commons No 377
JL High Bureaus No 2
JL Chief Bureaus Yes 42
JL Chief Bureaus No 12
JL Commons Commons Yes 29505
JL Commons Commons No 257

Total Pros and Cons

# pander(format(tbl.vote, big.mark = ","))
kable(t(as.matrix(format(tbl.vote, big.mark = ","))), caption = "Total Pros and Cons", align = 'c')
Total Pros and Cons
Yes No
98,657 74,149 
kable(t(as.table(format(tbl.vote, big.mark = ","))), caption = "Total Pros and Cons", align = 'c')
Total Pros and Cons
Yes No
98,657 74,149 
kable(t(as.table(format(prop.table(tbl.vote)*100, digits = 3, nsmall = 1))), caption = "Total Pros and Cons(%)", align = 'c')
Total Pros and Cons(%)
Yes No
57.1 42.9

Pie Charts

R-Base Plot

par(family = "NanumGothic")
gray.2 <- gray.colors(12)[c(12, 7)]
rainbow.2 <- rainbow(2)[2:1]
pie(tbl.vote, col = rainbow.2)
title(main = "Total Pros and Cons")
text(x = 0, y = c(0.4, -0.4), labels = format(tbl.vote, big.mark = ","))

# dev.copy(png, "../pics/sejong_total_pie.png", width = 480, height = 480)
# dev.off()

ggplot2

source("./theme_Nanum_kr.R")
# str(theme.kr)
# par(family = "NanumGothic")
vote.df <- as.data.frame(tbl.vote)
# y.coord <- cumsum(vote.df$Freq)/2 + c(0, cumsum(head(vote.df$Freq, -1))/2)
y.coord <- cumsum(vote.df$Freq)/2
pie.label <- paste(levels(vote.df$vote), format(vote.df$Freq, big.mark = ","), sep = "\n") 
str(vote.df)
## 'data.frame':    2 obs. of  2 variables:
##  $ vote: Factor w/ 2 levels "Yes","No": 1 2
##  $ Freq: int  98657 74149
p1 <- ggplot(vote.df, aes(x = "", y = Freq, fill = vote)) 
p2 <- p1 + 
  geom_bar(width = 1, stat = "identity")
p2

p2.2 <- p1 + 
  geom_bar(width = 1, stat = "identity", position = "dodge")
p2.2

p3.2 <- p2.2 + 
  theme_bw()
p3.2

p4.2 <- p3.2
p4.2 

p5.2 <- p4.2 + 
  scale_x_discrete(name = "Pros and Cons") +
  scale_y_continuous(name = "Total", breaks = vote.df$Freq, labels = format(vote.df$Freq, big.mark = ","))
p5.2

p6.2 <- p5.2 +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1], labels = vote.df$vote)
p6.2

p7.2 <- p6.2 +
  theme(legend.position = c(0.8, 0.85))
p7.2

# ggsave("../pics/sejong_geom_bar_total_ggplot.png", p7.2, dpi = 72)
p3 <- p2 + 
  theme_bw()
p3

p4 <- p3
p4 

p5 <- p4 + 
  scale_x_discrete(name = "Pros and Cons") +
  scale_y_continuous(name = "Total", breaks = cumsum(vote.df$Freq), labels = format(cumsum(vote.df$Freq), big.mark = ","))
p5

p6 <- p5 +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1], labels = vote.df$vote)
p6

# ggsave("../pics/sejong_geom_bar_total_ggplot_stack.png", p6, dpi = 72)
p7 <- p6 +
  theme(legend.position = c(0.5, 0.25))
p7

pie.total.1 <- p2 + 
  coord_polar(theta = "y", start = 3*pi/2, direction = -1)
pie.total.1

pie.total.2 <- pie.total.1 + 
  scale_y_continuous(name = "", breaks = NULL) +
  scale_x_discrete(name = "") 
pie.total.2

pie.total.3 <- pie.total.2 +
  scale_fill_manual(name = "", values = rainbow(2)[2:1])
pie.total.3

pie.total.4 <- pie.total.3 +
  theme_void(base_family = "NanumGothic")
pie.total.4

pie.total.5 <- pie.total.4 +
  guides(fill = "none")
pie.total.5

pie.total.6 <- pie.total.5 +
#  geom_text(aes(y = y.coord), label = pie.label, family = "NanumGothic")
  geom_text(aes(y = y.coord), label = pie.label, family = "NanumGothic", position = position_stack())
pie.total.6

pie.total.7 <- pie.total.6 +
  ggtitle("Total Pros and Cons") +
  theme(plot.margin = unit(c(1, 1, 1.5, 1), "lines"))
pie.total.7

# ggsave("../pics/sejong_total_pie_ggplot.png", pie.total.7, dpi = 72)

pie.gg()

pie.gg <- function(df, ggtitle = "", font.family = ""){
  n <- length(names(df))
  y.coord <- cumsum(df$Freq)
  pie.label <- paste(levels(df$vote), format(df$Freq, big.mark = ","), sep = "\n") 
  p1 <- ggplot(df, aes(x = "", y = Freq, fill = vote)) 
  p2 <- p1 + 
    geom_bar(width = 1, stat = "identity")
  pie.1 <- p2 + 
    coord_polar(theta = "y", start = 3*pi/2, direction = -1)
  pie.2 <- pie.1 + 
    scale_y_continuous(name = "", breaks = NULL) +
    scale_x_discrete(name = "") 
  pie.3 <- pie.2 +
    scale_fill_manual(name = "", values = rainbow(n)[n:1])
  pie.4 <- pie.3 +
    theme_void(base_family = font.family)
  pie.5 <- pie.4 +
    guides(fill = "none")
  pie.6 <- pie.5 +
    geom_text(aes(y = y.coord/n), label = pie.label, family = font.family, position = position_stack())
  pie.7 <- pie.6 +
    ggtitle(ggtitle) + 
    theme(plot.margin = unit(c(1, 1, 1.5, 1), "lines"))
  return(pie.7)
}
dump("pie.gg", file = "./pie.gg.R")
pie.gg(vote.df, ggtitle = "Total Pros and Cons", font.family = "NanumGothic")

Class and Region : Pros and Cons

Classwise Pros and Cons

kable(format(vote.class, big.mark = ","), align = "r", caption = "Classwise Pros and Cons")
Classwise Pros and Cons
High 3rd.current 3rd.former Chief Commons
Yes 21 259 443 192 97,742
No 200 393 117 135 73,304 
kable(format(prop.table(vote.class, margin = 2)*100, digits = 3, nsmall = 1), align = "r", caption = "Classwise Pros and Cons(%)")
Classwise Pros and Cons(%)
High 3rd.current 3rd.former Chief Commons
Yes 9.5 39.7 79.1 58.7 57.1
No 90.5 60.3 20.9 41.3 42.9

Commons Regionwise Analysis

Commons 수효가 상대적으로 많아서

kable(format(vote.class.2, big.mark = ","), align = rep("r", 2), caption = "Commons")
Commons
Bureaus Commons
Yes 915 97,742
No 845 73,304

소계를 교차표 주변에 계산

kable(format(vote.class.2.am, big.mark = ","), caption = "Bureaus and Commons(소계)", align = rep("r", 3))
Bureaus and Commons(소계)
Bureaus Commons 계
Yes 915 97,742 98,657
No 845 73,304 74,149
계 1,760 171,046 172,806

백분율을 계산하여 주변에 Total.

kable(format(prop.table(vote.class.2, margin = 2)*100, digits = 3, nsmall = 1), caption = "Bureaus and Commons(%)", align = rep("r", 3))
Bureaus and Commons(%)
Bureaus Commons
Yes 52.0 57.1
No 48.0 42.9

Pie Charts

R-Base Plot

par(family = "NanumGothic")
par(mfrow = c(1, 2))
pie(vote.class.2[, 1], labels = c("Yes", "No"), col = rainbow.2)
title(main = "Bureaus' Pros and Cons")
text(x = 0, y = c(0.4, -0.4), labels = vote.class.2[, 1])
pie(vote.class.2[, 2], labels = c("Yes", "No"), col = rainbow.2)
title(main = "Commons Pros and Cons")
text(x = 0, y = c(0.4, -0.4), labels = format(vote.class.2[, 2], big.mark = ","))

# dev.copy(png, "../pics/sejong_bureaus_commons_pie.png", width = 960, height = 480)
# dev.off()
par(mfrow = c(1, 1))

ggplot2

vote.class.2.df <- as.data.frame(vote.class.2)
v.names.class.en <- c("Pros.Cons", "Class", "Total")
kable(format(vote.class.2.df, big.mark = ","), align = c('c', 'c', 'r'), col.names = v.names.class.en, caption = "Bureaus and Commons")
Bureaus and Commons
Pros.Cons Class Total
Yes Bureaus 915
No Bureaus 845
Yes Commons 97,742
No Commons 73,304 
vote.bureaus.df <- subset(vote.class.2.df, vote.class.2.df$class.2 == "Bureaus", select = c("vote", "Freq"))
kable(format(vote.bureaus.df, big.mark = ","), align = 'r', col.names = v.names.class.en[-2], caption = "Bureaus' Pros and Cons")
Bureaus’ Pros and Cons
Pros.Cons Total
Yes 915
No 845 
vote.commons.df <- subset(vote.class.2.df, vote.class.2.df$class.2 == "Commons", select = c("vote", "Freq"))
kable(format(vote.commons.df, big.mark = ","), align = 'r', row.names = FALSE, col.names = v.names.class.en[-2], caption = "Commons' Pros and Cons")
Commons’ Pros and Cons
Pros.Cons Total
Yes 97,742
No 73,304 
pie.bureaus <- pie.gg(vote.bureaus.df, ggtitle = "Bureaus' Pros and Cons", font.family = "NanumGothic")
pie.commons <- pie.gg(vote.commons.df, ggtitle = "Commons' Pros and Cons", font.family = "NanumGothic")
pies.grid <- grid.arrange(pie.bureaus, pie.commons, ncol = 2, top = "")

pies.grid
## TableGrob (2 x 2) "arrange": 3 grobs
##   z     cells    name                grob
## 1 1 (2-2,1-1) arrange      gtable[layout]
## 2 2 (2-2,2-2) arrange      gtable[layout]
## 3 3 (1-1,1-2) arrange text[GRID.text.974]
# ggsave("../pics/sejong_bureaus_commons_pie_ggplot.png", pies.grid, width = 8, height = 4, dpi = 72)

Regionwise Pros and Cons

Bureaus and Commons

kable(vote.region.bureaus, caption = "Bureaus'들 Regionwise Pros and Cons")
Bureaus’들 Regionwise Pros and Cons
SL GG PA HH CC KW HG GS JL
Yes 723 29 6 17 35 5 3 55 42
No 704 5 36 17 28 10 15 16 14 
kable(format(prop.table(vote.region.bureaus, margin = 2)*100, digits = 3, nsmall = 1), align = rep("r", 9), caption = "Bureaus'들 Regionwise Pros and Cons(%)")
Bureaus’들 Regionwise Pros and Cons(%)
SL GG PA HH CC KW HG GS JL
Yes 50.7 85.3 14.3 50.0 55.6 33.3 16.7 77.5 75.0
No 49.3 14.7 85.7 50.0 44.4 66.7 83.3 22.5 25.0 
kable(format(vote.region.commons, big.mark = ","), align = rep("r", 9), caption = "Commons들 Regionwise Pros and Cons")
Commons들 Regionwise Pros and Cons
YH GG PA HH CC KW HG GS JL
Yes 1,123 17,076 1,326 4,454 6,982 939 75 36,262 29,505
No 71 236 28,474 15,601 14,013 6,888 7,387 377 257 
kable(format(prop.table(vote.region.commons, margin = 2)*100, digits = 1, nsmall = 1), align = rep("r", 9), caption = "Commons들 Regionwise Pros and Cons(%)")
Commons들 Regionwise Pros and Cons(%)
YH GG PA HH CC KW HG GS JL
Yes 94.1 98.6 4.4 22.2 33.3 12.0 1.0 99.0 99.1
No 5.9 1.4 95.6 77.8 66.7 88.0 99.0 1.0 0.9

Seoul Pros and Cons

kable(vote.seoul.class, caption = "Seoul Pros and Cons")
Seoul Pros and Cons
High 3rd.current 3rd.former
Yes 21 259 443
No 194 393 117 
kable(format(prop.table(vote.seoul.class, margin = 2)*100, digits = 1, nsmall = 1), align = rep("r", 3), caption = "Seoul Pros and Cons(%)")
Seoul Pros and Cons(%)
High 3rd.current 3rd.former
Yes 9.8 39.7 79.1
No 90.2 60.3 20.9

Barplots

R-Base Plot

Seoul Classwise Pros and Cons을 barplot으로 그려봄. text() 좌표는 locator()로 찾아냄.

par(family = "NanumGothic")
barplot(vote.seoul.class, col = rainbow.2)
title(main = "Seoul Pros and Cons")
text(x = c(0.7, 1.9, 1.9, 3.1, 3.1), y = c(120, 450, 135, 500, 220), labels = c("194","393", "259", "117", "443"))
legend("topleft", inset = 0.05, fill = rainbow.2, legend = c("Yes", "No"))

# dev.copy(png, "../pics/sejong_seoul_barplot.png", width = 480, height = 360)
# dev.off()

ggplot

Stack
vote.seoul.df <- as.data.frame(vote.seoul.class)
x.stack <- vote.seoul.df[, 2]
# y.stack <- unlist(tapply(vote.seoul.df$Freq, vote.seoul.df$class, function(x){cumsum(x) + c(0, cumsum(head(x, -1)))}))
y.stack <- unlist(tapply(vote.seoul.df$Freq, vote.seoul.df$class, cumsum))
b1.seoul <- ggplot(vote.seoul.df, aes(x = x.stack, y = Freq, fill = vote)) +
  geom_bar(stat = "identity", position = "stack")
b1.seoul

b2.seoul <- b1.seoul +
  theme_bw(base_family = "NanumGothic") +
  theme.kr +
  scale_x_discrete(name = "Class") +
  scale_y_continuous(name = "Total", breaks = vote.seoul.df$Freq, labels = vote.seoul.df$Freq) +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1])
b2.seoul  

b3.seoul <- b2.seoul +
# geom_text(aes(y = y.stack/2), label = vote.seoul.df$Freq)
  geom_text(aes(y = y.stack/2), label = vote.seoul.df$Freq, position = position_stack())
b3.seoul

# ggsave("../pics/sejong_seoul_barplot_stack_ggplot.png", b3.seoul, width = 6, height = 4.5, dpi = 72)

Dodge

b1.seoul.dodge <- ggplot(vote.seoul.df, aes(x = x.stack, y = Freq, fill = vote)) +
  geom_bar(stat = "identity", position = "dodge")
b1.seoul.dodge

b2.seoul.dodge <- b1.seoul.dodge +
  theme_bw(base_family = "NanumGothic") +
  theme.kr +
  scale_x_discrete(name = "Class") +
  scale_y_continuous(name = "Total", breaks = vote.seoul.df$Freq, labels = vote.seoul.df$Freq) +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1])
b2.seoul.dodge  

b3.seoul.dodge <- b2.seoul.dodge +
  geom_text(aes(y = vote.seoul.df$Freq/2), label = vote.seoul.df$Freq, position = position_dodge(width = 0.9)) +
  ggtitle("Seoul Pros and Cons")
b3.seoul.dodge

# ggsave("../pics/sejong_seoul_barplot_dodge_ggplot.png", b3.seoul.dodge, width = 6, height = 4.5, dpi = 72)

Fill

y.fill <- unlist(tapply(vote.seoul.df$Freq, x.stack, function(x){cumsum(x)/sum(x)}))
b1.seoul.fill <- ggplot(vote.seoul.df, aes(x = x.stack, y = Freq, fill = vote)) +
  geom_bar(stat = "identity", position = "fill")
b1.seoul.fill

b2.seoul.fill <- b1.seoul.fill +
  theme_bw(base_family = "NanumGothic") +
  theme.kr +
  scale_x_discrete(name = "Class") +
  scale_y_continuous(name = "Total", breaks = vote.seoul.df$Freq, labels = vote.seoul.df$Freq) +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1])
b2.seoul.fill  

b3.seoul.fill <- b2.seoul.fill +
  geom_text(aes(y = y.fill/2), label = vote.seoul.df$Freq, position = position_stack()) +
  ggtitle("Seoul Pros and Cons")
b3.seoul.fill

# ggsave("../pics/sejong_seoul_barplot_fill_ggplot.png", b3.seoul.fill, width = 6, height = 4.5, dpi = 72)

barplot.gg

barplot.gg.stack <- function(df, base_family = "", ggtitle = "", xlab = ""){
x <- df[, 2]
y <- unlist(tapply(df$Freq, x, cumsum))
b1 <- ggplot(df, aes(x = x, y = Freq, fill = vote)) +
  geom_bar(stat = "identity", position = "stack")
b2 <- b1 +
  theme_bw(base_family = base_family) +
#  theme.kr +
  scale_x_discrete(name = xlab) +
  scale_y_continuous(name = "Total", breaks = NULL) +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1], guide = guide_legend(reverse = TRUE))
b3 <- b2 +
  geom_text(aes(y = y/2), label = format(df$Freq, big.mark = ","), position = position_stack()) +
  ggtitle(ggtitle)
return(b3)
}
barplot.gg.dodge <- function(df, base_family = "", ggtitle = "", xlab = ""){
x <- df[, 2]
y <- unlist(tapply(df$Freq, x, cumsum))
b1 <- ggplot(df, aes(x = x, y = Freq, fill = vote)) +
  geom_bar(stat = "identity", position = "dodge")
b2 <- b1 +
  theme_bw(base_family = base_family) +
#  theme.kr +
  scale_x_discrete(name = xlab) +
  scale_y_continuous(name = "Total", breaks = NULL) +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1])
b3 <- b2 +
  geom_text(aes(y = df$Freq/2), label = format(df$Freq, big.mark = ","), position = position_dodge(width = 0.9)) +
  ggtitle(ggtitle)
return(b3)
}
barplot.gg.fill <- function(df, base_family = "", ggtitle = "", xlab = ""){
x <- df[, 2]
y <- unlist(tapply(df$Freq, x, function(x){cumsum(x)/sum(x)}))
b1 <- ggplot(df, aes(x = x, y = Freq, fill = vote)) +
  geom_bar(stat = "identity", position = "fill")
b2 <- b1 +
  theme_bw(base_family = base_family) +
#  theme.kr +
  scale_x_discrete(name = xlab) +
  scale_y_continuous(name = "Total", breaks = NULL) +
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1], guide = guide_legend(reverse = TRUE))
b3 <- b2 +
  geom_text(aes(y = y/2), label = format(df$Freq, big.mark = ","), position = position_stack()) +
  ggtitle(ggtitle)
return(b3)
}
barplot.gg <- function(x, position, base_family = "", ggtitle = "", xlab = ""){
  switch(position,
         stack = barplot.gg.stack(x, base_family = base_family, ggtitle = ggtitle, xlab = xlab),
         dodge = barplot.gg.dodge(x, base_family = base_family, ggtitle = ggtitle, xlab = xlab),
         fill = barplot.gg.fill(x, base_family = base_family, ggtitle = ggtitle, xlab = xlab))
}
(bar_seoul_stack <- barplot.gg(vote.seoul.df, position = "stack", base_family = "NanumGothic", ggtitle = "Seoul Pros and Cons", xlab = "Class"))

# ggsave("../pics/sejong_seoul_barplot_stack_ggplotv2.png", bar_seoul_stack, width = 6, height = 4.5, dpi = 72)
(bar_seoul_dodge <- barplot.gg(vote.seoul.df, position = "dodge", base_family = "NanumGothic", ggtitle = "Seoul Pros and Cons", xlab = "Class"))

# ggsave("../pics/sejong_seoul_barplot_dodge_ggplotv2.png", bar_seoul_dodge, width = 6, height = 4.5, dpi = 72)
(bar_seoul_fill <- barplot.gg(vote.seoul.df, position = "fill", base_family = "NanumGothic", ggtitle = "Seoul Pros and Cons", xlab = "Class"))

# ggsave("../pics/sejong_seoul_barplot_fill_ggplotv2.png", bar_seoul_fill, width = 6, height = 4.5, dpi = 72)
dump(c("barplot.gg","barplot.gg.stack", "barplot.gg.dodge", "barplot.gg.fill"), file = "./barplot.gg.R")

mosaic plot

R-Base Plot

par(family = "NanumGothic")
mosaicplot(t(vote.seoul.class), col = rainbow.2, main = "Seoul Pros and Cons", xlab = "Class" , ylab = "Pros and Cons")

# dev.copy(png, "../pics/sejong_seoul_mosaic.png", width = 480, height = 360)
# dev.off()

ggplot

vote.seoul.class.df <- as.data.frame(vote.seoul.class)
vote.seoul.class.sum <- tapply(vote.seoul.class.df$Freq, vote.seoul.class.df[, 2], sum)
vote.seoul.class.p.m <- prop.table(vote.seoul.class.sum)
vote.seoul.class.p <- prop.table(vote.seoul.class)
vote.seoul.class.p.2 <- prop.table(vote.seoul.class, margin = 2)
vote.seoul.class.p.df <- as.data.frame(vote.seoul.class.p)
vote.seoul.class.p.df$width <- vote.seoul.class.p.m[match(vote.seoul.class.p.df$class, names(vote.seoul.class.p.m))]
vote.seoul.class.p.df$height <- as.data.frame(vote.seoul.class.p.2)$Freq
vote.seoul.class.p.df$label.height <- unlist(tapply(vote.seoul.class.p.df$height, vote.seoul.class.p.df$class, cumsum))
x.center <- (cumsum(vote.seoul.class.p.m) + c(0, head(cumsum(vote.seoul.class.p.m), -1)))/2
vote.seoul.class.p.df$center <- x.center[match(vote.seoul.class.p.df$class, names(x.center))]
m1 <- ggplot(vote.seoul.class.p.df, aes(x = center, y = height)) + 
  geom_bar(aes(width = width, fill = vote), stat = "identity", col = "white", size = 2) 
m1

m2 <- m1 + 
  theme_bw(base_family = "NanumGothic")
m2

m3 <- m2 + 
  geom_text(aes(x = center, y = 1.05), label = vote.seoul.class.p.df$class, family = "NanumGothic")
m3

m4 <- m3 + 
  geom_text(aes(x = center, y = label.height/2), label = format(vote.seoul.class.df$Freq, big.mark = ","), position = position_stack())
m4

x.breaks <- c(0, ifelse(cumsum(vote.seoul.class.p.m) < 0.1, 0.0, cumsum(vote.seoul.class.p.m)))
x.label <- format(x.breaks, digits = 2, nsmall = 2)
m5 <- m4 + 
  scale_x_continuous(name = "Class", breaks = x.breaks, label = x.label) + 
  scale_y_continuous(name = "Pros and Cons") + 
  scale_fill_manual(name = "Pros and Cons", values = rainbow(2)[2:1], guide = guide_legend(reverse = TRUE)) +
  ggtitle("Seoul Pros and Cons")
m5

source("./mosaic.gg_en.R")
mosaic_gg
## function (tbl, base_family = "", ggtitle = "", xlab = "") 
## {
##     tbl.df <- as.data.frame(tbl)
##     tbl.sum <- tapply(tbl.df$Freq, tbl.df[, 2], sum)
##     tbl.p.m <- prop.table(tbl.sum)
##     tbl.p <- prop.table(tbl)
##     tbl.p.2 <- prop.table(tbl, margin = 2)
##     tbl.p.df <- as.data.frame(tbl.p)
##     tbl.p.df$width <- tbl.p.m[match(tbl.p.df[, 2], names(tbl.p.m))]
##     tbl.p.df$height <- as.data.frame(tbl.p.2)$Freq
##     tbl.p.df$label.height <- unlist(tapply(tbl.p.df$height, tbl.p.df[, 
##         2], cumsum))
##     x.center <- (cumsum(tbl.p.m) + c(0, head(cumsum(tbl.p.m), 
##         -1)))/2
##     tbl.p.df$center <- x.center[match(tbl.p.df[, 2], names(x.center))]
##     m1 <- ggplot(tbl.p.df, aes(x = center, y = height)) + geom_bar(aes(width = width, 
##         fill = vote), stat = "identity", col = "white", size = 1)
##     m1
##     m2 <- m1 + theme_bw(base_family = base_family)
##     m2
##     m3 <- m2 + geom_text(aes(x = center, y = 1.05), label = tbl.p.df[, 
##         2], family = base_family)
##     m3
##     m4 <- m3 + geom_text(aes(x = center, y = label.height/2), 
##         label = format(tbl.df$Freq, big.mark = ","), position = position_stack())
##     m4
##     x.breaks <- c(0, ifelse(cumsum(tbl.p.m) < 0.1, 0, cumsum(tbl.p.m)))
##     x.label <- format(x.breaks, digits = 2, nsmall = 2)
##     m5 <- m4 + scale_x_continuous(name = xlab, breaks = x.breaks, 
##         label = x.label) + scale_y_continuous(name = "Pros or Cons") + 
##         scale_fill_manual(name = "Pros or Cons", values = rainbow(2)[2:1], 
##             guide = guide_legend(reverse = TRUE)) + ggtitle(ggtitle) + 
##         theme(plot.margin = unit(c(1, 2, 1, 1), "lines"))
##     m5
##     return(m5)
## }
m5.seoul <- mosaic_gg(vote.seoul.class, base_family = "NanumGothic", ggtitle = "Seoul Pros and Cons", xlab = "Class")
m5.seoul

# ggsave("../pics/sejong_seoul_mosaic_ggplot.png", m5.seoul, width = 6, height = 4.5, dpi = 72)

Bureaus’ Regionwise Pros and Cons (Except for Seoul)

kable(vote.region.bureaus[, -1], caption = "Bureaus' Regionwise Pros and Cons (Except for Seoul)")
Bureaus’ Regionwise Pros and Cons (Except for Seoul)
GG PA HH CC KW HG GS JL
Yes 29 6 17 35 5 3 55 42
No 5 36 17 28 10 15 16 14 
kable(format(prop.table(vote.region.bureaus[, -1], margin = 2)*100, digits = 1, nsmall = 1), align = "r", caption = "Bureaus' Regionwise Pros and Cons (Except for Seoul)")
Bureaus’ Regionwise Pros and Cons (Except for Seoul)
GG PA HH CC KW HG GS JL
Yes 85.3 14.3 50.0 55.6 33.3 16.7 77.5 75.0
No 14.7 85.7 50.0 44.4 66.7 83.3 22.5 25.0

Barplots

R-Base Plot

par(family = "NanumGothic")
barplot(vote.region.bureaus[, -1], beside = FALSE, col = rainbow.2)
title(main = "Bureaus' Regionwise Pros and Cons (Except for Seoul)")
legend("topleft", inset = 0.05, fill = rainbow.2, legend = c("Yes", "No"))

# dev.copy(png, "../pics/sejong_bureaus.png", width = 720, height = 360)
# dev.off()

ggplot

vote.region.bureaus.df <- as.data.frame(vote.region.bureaus[, -1])
barplot.gg(vote.region.bureaus.df, position = "stack", base_family = "NanumGothic", ggtitle = "Bureaus' Regionwise Pros and Cons (Except for Seoul)", xlab = "Region")

# ggsave("../pics/sejong_bureaus_barplot_stack_ggplot.png", width = 9, height = 4.5, dpi = 72)

mosaic plot

R-Base Plot

par(family = "NanumGothic")
mosaicplot(t(vote.region.bureaus[, -1]), col = rainbow.2, main = "", xlab = "Region", ylab = "Pros and Cons")
title(main = "Bureaus' Regionwise Pros and Cons")

# dev.copy(png, "../pics/sejong_bureaus_mosaic.png", width = 720, height = 360)
# dev.off()

ggplot

# source("./mosaic.gg.R")
m5.bureaus <- mosaic_gg(vote.region.bureaus[, -1], base_family = "NanumGothic", ggtitle = "Bureaus' Regionwise Pros and Cons", xlab = "Regionwise Proprtion of Bureaus")
m5.bureaus

# ggsave("../pics/sejong_bureaus_mosaic_ggplot.png", m5.bureaus, width = 9, height = 4.5, dpi = 72)

Regionwise Commons’ Pros and Cons

Barplots

R-Base Plot

par(family = "NanumGothic")
barplot(vote.region.commons, beside = FALSE, col = rainbow.2, axes = FALSE)
axis(2, at = seq(0, 30000, by = 5000), labels = c("0", "", "10", "", "20", "", "30"), las = 1)
title(main = "Commons' Regionwise Pros and Cons")
legend("topleft", inset = 0.05, fill = rainbow.2, legend = c("Yes", "No"))

# dev.copy(png, "../pics/sejong_commons_barplot.png", width = 720, height = 360)
# dev.off()

ggplot

vote.region.commons.df <- as.data.frame(vote.region.commons)
barplot.gg(vote.region.commons.df, position = "stack", base_family = "NanumGothic", ggtitle = "Commons' Pros and Cons", xlab = "Region")

# ggsave("../pics/sejong_commons_barplot_stack_ggplot.png", width = 9, height = 4.5, dpi = 72)

mosaic plot

R-Base Plot

par(family = "NanumGothic")
mosaicplot(t(vote.region.commons), col = rainbow.2, main = "Commons; Regionwise Pros and Cons", xlab = "Region", ylab = "Pros and Cons")

# dev.copy(png, "../pics/sejong_commons_mosaic.png", width = 720, height = 360)
# dev.off()

ggplot

# source("./mosaic.gg.R")
m5.commons <- mosaic_gg(vote.region.commons, base_family = "NanumGothic", ggtitle = "Commons Pros and Cons", xlab = "Regionwise Commons Proportion")
m5.commons

# ggsave("../pics/sejong_commons_mosaic_ggplot.png", m5.commons, width = 12, height = 4.5, dpi = 72)

Chungcheong

Bureaus’들 Pros and Cons과 Commons Pros and Cons이 다른 곳.

kable(format(vote.chung.class, big.mark = ","), caption = "Chungcheong Case", align = "r")
Chungcheong Case
High Chief Commons
Yes 0 35 6,982
No 2 26 14,013 
kable(format(prop.table(vote.chung.class, margin = 2)*100, digits = 3, nsmall = 1), caption = "Chungcheong Case", align = "r")
Chungcheong Case
High Chief Commons
Yes 0.0 57.4 33.3
No 100.0 42.6 66.7

Barplots

R-Base Plot

par(mar = c(5.1, 4.1, 4.1, 8.1), xpd = TRUE, family = "NanumGothic")
barplot(prop.table(vote.chung.class, margin = 2), col = rainbow.2, ylim = c(0,  1.1), axes = FALSE)
axis(side = 2, at = c(0, 0.5, 1.0), labels = c("0", "50%", "100%"), las = 1)
title(main = "Chungcheong Classwise Pros and Cons 비율")
legend("right", inset = -0.3, fill = rainbow.2, legend = c("Yes", "No"))
text(x = c(0.6, 1.85, 1.85, 3.1, 3.1), y = c(0.5, 0.3, 0.8, 0.15, 0.65), labels = format(c(2, 35, 26, 6982, 14013), big.mark = ","))

# dev.copy(png, "../pics/sejong_chungcheong_barplot.png", width = 480, height = 360)
# dev.off()

ggplot

vote.chung.class.df <- as.data.frame(vote.chung.class)
barplot.gg(vote.chung.class.df, position = "fill", base_family = "NanumGothic", ggtitle = "Chungcheong Pros and Cons", xlab = "Class")

# ggsave("../pics/sejong_chungcheong_barplot_fill_ggplot.png", width = 6, height = 4.5, dpi = 72)

mosaic plot

수효 차이가 너무 커서 비교하기 어려움. ‘대신 등’ 제외하고 작업

par(family = "NanumGothic")
mosaicplot(t(vote.chung.class[, -1]), col = rainbow.2, main = "", xlab = "Class", ylab = "Pros and Cons")
title(main = "Chungcheong Pros and Cons")

# dev.copy(png, "../pics/sejong_chungcheong_mosaic.png", width = 480, height = 360)
# dev.off()

ggplot

# source("./mosaic.gg.R")
m5.chungcheong <- mosaic_gg(vote.chung.class[, -1], base_family = "NanumGothic", ggtitle = "Chungcheong Pros and Cons", xlab = "Class")
m5.chungcheong

# ggsave("../pics/sejong_chungcheong_mosaic_ggplot.png", m5.chungcheong, width = 12, height = 4.5, dpi = 72)

자료 정리

save.image(file = "./sejong_ggplot.RData")