6  Proporsi dan Komposisi

Teknik visualisasi ini digunakan untuk menunjukkan bagaimana suatu bagian berkontribusi terhadap keseluruhan.

6.1 Pie Charts

Diagram lingkaran yang digunakan untuk menunjukkan distribusi persentase suatu kategori.

6.1.1 Pie

Code 
df <- data.frame(value = c(15, 25, 32, 28),
                 group = paste0("G", 1:4))

# Get the positions
df2 <- df %>% 
  mutate(csum = rev(cumsum(rev(value))), 
         pos = value/2 + lead(csum, 1),
         pos = if_else(is.na(pos), value/2, pos))

ggplot(df, aes(x = "" , y = value, fill = fct_inorder(group))) +
  geom_col(width = 1, color = 1) +
  coord_polar(theta = "y") +
  scale_fill_brewer(palette = "Pastel1") +
  geom_label_repel(data = df2,
                   aes(y = pos, label = paste0(value, "%")),
                   size = 4.5, nudge_x = 1, show.legend = FALSE) +
  guides(fill = guide_legend(title = "Group")) +
  theme_void()

Code 
# Get the positions
df2 <- df %>% 
  mutate(csum = rev(cumsum(rev(value))), 
         pos = value/2 + lead(csum, 1),
         pos = if_else(is.na(pos), value/2, pos))

ggplot(df, aes(x = "", y = value, fill = fct_inorder(group))) +
  geom_col(width = 1, color = 1) +
  geom_text(aes(label = value),
            position = position_stack(vjust = 0.5)) +
  coord_polar(theta = "y") +
  guides(fill = guide_legend(title = "Group")) +
  scale_y_continuous(breaks = df2$pos, labels = df$group) +
  theme(axis.ticks = element_blank(),
        axis.title = element_blank(),
        axis.text = element_text(size = 15), 
        legend.position = "none", # Removes the legend
        panel.background = element_rect(fill = "white"))

6.1.2 Donut

Code 
df <- data.frame(value = c(10, 30, 32, 28),
                 group = paste0("G", 1:4))

# Increase the value to make the hole bigger
# Decrease the value to make the hole smaller
hsize <- 4

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col() +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5))

Code 
# Hole size
hsize <- 3.5

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col() +
  geom_text(aes(label = value),
            position = position_stack(vjust = 0.5)) +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5))

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col() +
  geom_label(aes(label = value),
             position = position_stack(vjust = 0.5),
             show.legend = FALSE) +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5))

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col(color = "black") +
  geom_label(aes(label = value),
             position = position_stack(vjust = 0.5),
             show.legend = FALSE) +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5))

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col(color = "black") +
  coord_polar(theta = "y") +
  scale_fill_manual(values = c("#FFF7FB", "#D0D1E6",
                               "#74A9CF", "#0570B0")) +
  xlim(c(0.2, hsize + 0.5))

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col(color = "black") +
  geom_text(aes(label = value),
             position = position_stack(vjust = 0.5)) +
  coord_polar(theta = "y") +
  scale_fill_brewer(palette = "GnBu") +
  xlim(c(0.2, hsize + 0.5)) +
  theme(panel.background = element_rect(fill = "white"),
        panel.grid = element_blank(),
        axis.title = element_blank(),
        axis.ticks = element_blank(),
        axis.text = element_blank())

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col(color = "black") +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5)) +
  scale_fill_discrete(labels = c("A", "B", "C", "D"))

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col(color = "black") +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5)) +
  guides(fill = guide_legend(title = "Title"))

Code 
# Hole size
hsize <- 3

df <- df %>% 
  mutate(x = hsize)

ggplot(df, aes(x = hsize, y = value, fill = group)) +
  geom_col(color = "black") +
  coord_polar(theta = "y") +
  xlim(c(0.2, hsize + 0.5)) +
  theme(legend.position = "none")

6.2 Treemap

Menampilkan hierarki data dalam bentuk persegi panjang bersarang.

Code 
group <- paste("Group", 1:9)
subgroup <- c("A", "C", "B", "A", "A",
              "C", "C", "B", "B")
value <- c(7, 25, 50, 5, 16,
           18, 30, 12, 41)

df <- data.frame(group, subgroup, value)
Code 
ggplot(df, aes(area = value, fill = group)) +
  geom_treemap()

Code 
ggplot(df, aes(area = value, fill = value)) +
  geom_treemap()

Code 
ggplot(df, aes(area = value, fill = group, label = value)) +
  geom_treemap() +
  geom_treemap_text()

Code 
ggplot(df, aes(area = value, fill = group, label = value)) +
  geom_treemap() +
  geom_treemap_text(colour = "white",
                    place = "centre",
                    size = 15)

Code 
ggplot(df, aes(area = value, fill = group,
               label = paste(group, value, sep = "\n"))) +
  geom_treemap() +
  geom_treemap_text(colour = "white",
                    place = "centre",
                    size = 15) +
  theme(legend.position = "none")

Code 
ggplot(df, aes(area = value, fill = value, label = group)) +
  geom_treemap() +
  geom_treemap_text(colour = "white",
                    place = "centre",
                    size = 15)

Code 
ggplot(df, aes(area = value, fill = value, label = group)) +
  geom_treemap() +
  geom_treemap_text(colour = "white",
                    place = "centre",
                    size = 15,
                    grow = TRUE)

Code 
ggplot(df, aes(area = value, fill = value,
               label = group, subgroup = subgroup)) +
  geom_treemap() +
  geom_treemap_subgroup_border(colour = "white", size = 5) +
  geom_treemap_subgroup_text(place = "centre", grow = TRUE,
                             alpha = 0.25, colour = "black",
                             fontface = "italic") +
  geom_treemap_text(colour = "white", place = "centre",
                    size = 15, grow = TRUE)

Code 
ggplot(df, aes(area = value, fill = value, label = group)) +
  geom_treemap() +
  geom_treemap_text(colour = c(rep("white", 2),
                               1, rep("white", 6)),
                    place = "centre", size = 15) +
  scale_fill_viridis_c()

Code 
ggplot(df, aes(area = value, fill = group, label = value)) +
  geom_treemap() +
  geom_treemap_text(colour = "white",
                    place = "centre",
                    size = 15) +
  scale_fill_brewer(palette = "Blues")

6.3 Sunburst Diagram

Mirip dengan treemap, tetapi berbentuk melingkar untuk menunjukkan hierarki.

Code 
# Create data
data <- list(
  label = c("A", "B", "C", "D"),
  parent = c("", "A", "A", "B"),
  value = c(10, 20, 30, 40)
)
data<-data.frame(data)
# Create sunburst chart
fig <- plot_ly(data, ids = ~label, labels = ~label, 
               parents = ~parent, values = ~value,
               type = 'sunburst')
fig
Code 
# Sample hierarchical data (Organization Structure)
data <- list(
  id = c("CEO", "HR", "HR-Manager", "HR-TeamLead", "HR-Staff", "Finance", 
         "Finance-Manager", "Finance-Accountant", "Finance-Analyst", "IT", 
         "IT-Manager",
         "IT-Developer", "IT-QA"),
  parent = c("", "CEO", "HR", "HR", "HR", "CEO", "Finance", "Finance", 
             "Finance", "CEO", 
             "IT", "IT", "IT"),
  value = c(1, 1, 3, 10, 1, 1, 1, 4, 2, 1, 1, 6, 3)
)
data<-data.frame(data)
# Create sunburst chart for organization structure
organization_sunburst <- plot_ly(data, ids = ~id, labels = ~id, parents = ~parent, 
                                 values = ~value, type = "sunburst")

# Display the chart
organization_sunburst
Code 
# Sample hierarchical data (File System Usage)
data <- list(
  id = c("Root", "usr", "usr-bin", "usr-lib", "usr-local", "home", "home-user1", 
         "home-user2", "home-user3", "var", "var-log", "var-tmp", "var-cache"),
  parent = c("", "Root", "usr", "usr", "usr", "Root", "home", "home", "home", "Root",
             "var", "var", "var"),
  value = c(100, 50, 30, 20, 10, 50, 20, 15, 15, 30, 25, 15, 10)
)
data<-data.frame(data)
# Create sunburst chart for file system usage
file_system_sunburst <- plot_ly(data, ids = ~id, labels = ~id, parents = ~parent, 
                                values = ~value, type = "sunburst")

# Display the chart
file_system_sunburst

6.4 Nightingale Chart

Variasi dari pie chart yang digunakan untuk menampilkan data dalam bentuk radial.

Code 
# Simulasi data mirip dengan Nightingale dataset
set.seed(123)
nightingale_sim <- data.frame(
  Month = rep(month.abb, 2),  # 12 bulan, 2 periode
  Year = rep(c(1854, 1855), each = 12),
  Disease = sample(50:150, 24, replace = TRUE),  # Kematian karena penyakit
  Wounds = sample(10:50, 24, replace = TRUE),    # Kematian karena luka
  Other = sample(5:30, 24, replace = TRUE)       # Kematian lainnya
)

# Ubah data ke long format
nightingale_long <- nightingale_sim %>%
  pivot_longer(cols = c(Disease, Wounds, Other), names_to = "Cause", values_to = "Rate") %>%
  mutate(
    Month = factor(Month, levels = month.abb),  # Urutan bulan
    Period = ifelse(Year == 1854, "April 1854 to March 1855", "April 1855 to March 1856")
  )

# Plot Nightingale Chart (Coxcomb Chart)
ggplot(nightingale_long, aes(Month, Rate, fill = Cause)) + 
  geom_col(width = 1, position = "identity") + 
  coord_polar() + 
  facet_wrap(~Period) +
  scale_fill_manual(values = c("skyblue3", "grey30", "firebrick")) +
  scale_y_sqrt() +
  theme_void() +
  theme(
    axis.text.x = element_text(size = 9),
    strip.text = element_text(size = 11),
    legend.position = "bottom",
    plot.background = element_rect(fill = alpha("cornsilk", 0.5)),
    plot.margin = unit(c(10, 10, 10, 10), "pt"),
    plot.title = element_text(vjust = 5)
  ) +
  ggtitle("Simulated Nightingale Chart: Causes of Mortality in the Army")

6.5 Voronoi Diagram

Membagi ruang menjadi wilayah berdasarkan kedekatan titik-titik data.

Code 
# Data
set.seed(1)
x <- sample(1:400, size = 100)
y <- sample(1:400, size = 100)
dist <- sqrt((x - 200) ^ 2 + (y - 200) ^ 2)

df <- data.frame(x, y, dist = dist)
Code 
ggplot(df, aes(x, y)) +
  stat_voronoi(geom = "path") 
Warning: `fortify(<SpatialPolygonsDataFrame>)` was deprecated in ggplot2 3.4.4.
ℹ Please migrate to sf.

Code 
ggplot(df, aes(x, y)) +
  stat_voronoi(geom = "path") +
  geom_point()

Code 
ggplot(df, aes(x, y)) +
  stat_voronoi(geom = "path",
               color = 4,      # Color of the lines
               lwd = 0.7,      # Width of the lines
               linetype = 1) + # Type of the lines
  geom_point()

Code 
ggplot(df, aes(x, y, fill = dist)) +
  geom_voronoi() +
  geom_point()

Code 
ggplot(df, aes(x, y, fill = dist)) +
  geom_voronoi() +
  stat_voronoi(geom = "path") +
  geom_point()

Code 
ggplot(df, aes(x, y, fill = dist)) +
  geom_voronoi(alpha = 0.75) +
  stat_voronoi(geom = "path") +
  geom_point()

Code 
ggplot(df, aes(x, y, fill = dist)) +
  geom_voronoi() +
  stat_voronoi(geom = "path") +
  geom_point() +
  scale_fill_gradient(low = "#F9F9F9",
                      high = "#312271")

Code 
ggplot(df, aes(x, y, fill = dist)) +
  geom_voronoi() +
  stat_voronoi(geom = "path") +
  geom_point() +
  theme(legend.position = "none")

6.5.1 Bounding box

Code 
# Circle
s <- seq(0, 2 * pi, length.out = 3000)
circle <- data.frame(x = 120 * (1 + cos(s)),
                     y = 120 * (1 + sin(s)),
                     group = rep(1, 3000))

ggplot(df, aes(x, y, fill = dist)) +
  geom_voronoi(outline = circle,
               color = 1, linewidth = 0.1) +
  scale_fill_gradient(low = "#B9DDF1",
                      high = "#2A5783",
                      guide = FALSE) +
  theme_void() +
  coord_fixed()
Warning: The `guide` argument in `scale_*()` cannot be `FALSE`. This was deprecated in
ggplot2 3.3.4.
ℹ Please use "none" instead.