Create Bar Chart with Descending Order of Proportion by Using geom_col()

Daily Graph Series

Rudis’s Solution

Bob Rudis used geom_segment() for creating this beautiful plot:

You can see his R codes here.

My Solution

Instead of using geom_segment() we can use geom_col() for creating the above plot as follows:

# Create data set: 

library(tidyverse)

read.table(text = 'store,closing,total
"Radio Shack",550,1500
"Payless",400,2600
"Rue21",400,1100
"The Limited",250,250
"bebe",180,180
"Wet Seal",170,170
"Crocs",160,560
"JCPenny",138,1000
"American Apparel",110,110
"Kmart",109,735
"hhgregg",88,220
"Sears",41,695', sep = ",", header = TRUE, stringsAsFactors = FALSE) %>% 
  as_tibble() %>% 
  mutate(remaining = total - closing,
         gone = round((closing/total) * 100)/100,
         stay = 1-gone,
         rem_lab = ifelse(remaining == 0, "", scales::comma(remaining))) %>% 
  arrange(desc(stay)) %>% 
  mutate(store = factor(store, levels = store)) -> closing_df


# Prepare data for ploting: 

closing_df %>% 
  select(store, remaining, closing) %>% 
  gather(type, n, -store) %>% 
  full_join(closing_df %>% select(store, stay), by = c("store")) %>% 
  arrange(-stay, store) %>% 
  mutate(store = factor(store, levels = store %>% unique())) -> df_ForPloting


# Make a draft: 

library(hrbrthemes)
my_font <- "Roboto Condensed"

df_ForPloting %>% 
  ggplot(aes(store, -n, fill = type)) + 
  geom_col(position = "fill", width = 0.7) +
  coord_flip() + 
  scale_y_percent() +
  labs(x = NULL, y = NULL, 
       title = "Selected 2017 Store closings (estimated)",
       subtitle = "Smaller specialty chains such as Bebe and American Apparel are closing their stores,\nwhile lareger chains such as J.C. Penny and Sears are scaling back their footprint.") +
  theme_ipsum_rc(grid = "X") +
  theme(legend.position = c(0.875, 1.025)) +
  theme(legend.direction = "horizontal") -> g

# Final plot: 

g + 
  geom_text(data = df_ForPloting %>% filter(type == "closing"), aes(store, -0.98, label = n), color = "white", family = my_font) + 
  geom_text(data = df_ForPloting %>% filter(type == "remaining", n > 0), aes(store, -0.02, label = n), color = "white", family = my_font) + 
  scale_fill_ipsum(name = NULL, labels = c("Closing", "Remaining")) +
  scale_y_continuous(labels = paste0(seq(0, 100, 25), "%"), expand = c(0.002, 0))