Share of Vietnam government spending on health care, 2014

Daily Graph Series

Economist-Style Plot using R

R Codes for Data Cleaning and Visualization

Above Economist-Style Plot can be created by using R as follows:

#==========================================
#  Collect data from WHO and pre-process
#==========================================

# devtools::install_github("expersso/WHO")

library(WHO)
library(tidyverse)

# Government and total expenditure data: 

expenditure_gov <- get_data("WHS7_108")
expenditure_total <- get_data("WHS7_105")

expenditure_gov %>% 
  filter(year == 2014, !is.na(country)) %>% 
  select(gov_exp = value, country) -> df_gov

expenditure_total %>% 
  filter(year == 2014, !is.na(country)) %>% 
  select(total_exp = value, country) -> df_total

nations <- intersect(df_gov$country, df_total$country)

full_join(df_total %>% filter(country %in% nations), 
          df_gov %>% filter(country %in% nations), by = "country") %>% 
  select(country, everything()) %>% 
  mutate(private_exp = total_exp - gov_exp) %>% 
  mutate(gov_rate = gov_exp / total_exp) %>% 
  arrange(gov_rate) %>% 
  mutate(rank = 1:nrow(.)) -> dfPlot

# Rename: 
dfPlot %>% 
  mutate(country = case_when(country == "Brunei Darussalam" ~ "Brunei", 
                             country == "Republic of Korea" ~ "South Korea", 
                             country == "United Kingdom of Great Britain and Northern Ireland" ~ "United Kingdom", 
                             country == "United States of America" ~ "United States", 
                             country == "Russian Federation" ~ "Russia", 
                             country == "Viet Nam" ~ "Vietnam", 
                             TRUE ~ country)) -> dfPlot

# Some countries selected: 

northernCon <- c("Denmark", "Finland", "Norway", "Sweden")
specialCon <- c("Qatar", "Brunei", "Cuba")
aseanCon <- c("Singapore", "Thailand", "Malaysia", "Vietnam")
others <- c("India", "China", "United States", "United Kingdom", "France", 
           "Germany", "Canada", "Japan", "South Korea")

dfPlot %>% 
  filter(country %in% c(northernCon, specialCon, aseanCon, others)) %>% 
  arrange(gov_rate) -> df

my_levels <- df %>% pull(country)

df %>% 
  mutate(country = factor(country, levels = my_levels)) %>%
  select(country, private_exp, gov_exp) %>% 
  gather(type, value, -country) -> df1

# Colors and font selected: http://pattern-library.economist.com/color.html
# https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/economist_pal/

my_colors <- c("#014d64", "#01a2d9")
my_font <- "Ubuntu Condensed"
colorLevels <- c("private_exp", "gov_exp")

#==================================
#  Solution 1 (but i do not like)
#==================================

df1 %>% 
  mutate(type = factor(type, levels = colorLevels)) -> df1

df1 %>% 
  ggplot(aes(x = country, y = value, fill = type)) + 
  geom_col(position = "fill") + 
  coord_flip() + 
  scale_fill_manual(values = my_colors) + 
  theme_minimal(base_family = my_font)

#================
#   Solution 2
#================

library(ggrepel)

df %>% 
  mutate(gov_rate = 100*gov_rate, total_rate = 100) %>% 
  mutate(country = factor(country, levels = country)) %>% 
  mutate(label = round(gov_rate, 1) %>% as.character()) %>% 
  mutate(label = case_when(!str_detect(label, "\\.") ~ paste0(label, ".0"), TRUE ~ label)) %>% 
  mutate(label = paste0(label, "%")) %>% 
  mutate(label_money = round(total_exp, 0) %>% scales::dollar()) -> dfSolution2

# Version 1: 

ggplot() + 
  coord_flip() + 
  theme_minimal(base_family = my_font, base_size = 14) + 
  geom_col(data = dfSolution2, aes(x = country, y = total_rate, fill = "Government"), width = 0.9) + 
  geom_col(data = dfSolution2, aes(x = country, y = gov_rate, fill = "Private"), width = 0.9) +
  scale_y_continuous(limits = c(0, 120)) + 
  geom_text(data = dfSolution2, aes(x = country, y = 5, label = label), color = "white", family = my_font, size = 4.5) + 
  scale_fill_manual(values = my_colors) + 
  geom_label_repel(data = dfSolution2, aes(x = country, y = 103, label = label_money), hjust = 0, 
                   family = my_font, size = 4.3, direction = "x", nudge_y = 1, label.r = 0, box.padding = 0) + 
  theme(legend.position = "top") 

# Version 2: 

midd <- (102 + 110) / 2

dfSolution2 %>% 
  mutate(color_label_y = case_when(country == "Vietnam" ~ "#e5001c", TRUE ~ "grey20")) %>% 
  mutate(bold_y = case_when(country == "Vietnam" ~ "bold", TRUE ~ "plain")) -> dfSolution2


ggplot() + 
  coord_flip() + 
  theme_minimal(base_family = my_font, base_size = 14) + 
  geom_col(data = dfSolution2, aes(x = country, y = total_rate, fill = "Private"), width = 0.9) + 
  geom_col(data = dfSolution2, aes(x = country, y = gov_rate, fill = "Government"), width = 0.9) +
  scale_y_continuous(limits = c(0, 110), expand = c(0, 0)) + 
  scale_x_discrete(expand = c(0.08, 0)) + 
  geom_text(data = dfSolution2, aes(x = country, y = 4, label = label), color = "white", family = my_font, size = 4.5) + 
  scale_fill_manual(values = my_colors) + 
  theme(legend.direction = "horizontal") + 
  theme(legend.position = c(0.5, 0.98)) + 
  theme(legend.title = element_blank()) + 
  theme(axis.title = element_blank()) + 
  theme(axis.text.x = element_blank()) + 
  theme(panel.grid = element_blank()) + 
  geom_rect(aes(xmin = 0.5, xmax = Inf, ymin = 102, ymax = 110), fill = "#efefe3") + 
  geom_text(data = dfSolution2 %>% filter(country == "Cuba"), aes(x = country, y = 106, label = "Total"), 
            vjust = -1.9, family = my_font, fontface = "bold", size = 4.5) + 
  geom_text(data = dfSolution2, aes(x = country, y = midd, label = scales::comma(round(total_exp, 0))), 
            family = my_font, size = 4.5, color = "grey30") + 
  theme(plot.margin = unit(rep(0.5, 4), "cm")) + 
  labs(x = NULL, y = NULL, 
       title = "Share of Vietnam government spending on health care, 2014", 
       subtitle = "Heath expenditure per capita in Vietnam was reported at $390 (PPP)\nand share of government spending on health care was 54.1%.", 
       caption = "Source: World Health Organization (WHO)") + 
  theme(plot.title = element_text(size = 23, colour = "grey20"), 
        plot.subtitle = element_text(color = "grey30", size = 15), 
        plot.caption = element_text(color = "grey30", face = "italic", size = 11)) + 
  theme(axis.text.y = element_text(color = dfSolution2$color_label_y, size = 12, face = dfSolution2$bold_y)) 

library(grid)
grid.rect(x = 0.015, y = 0.94, hjust = 1, vjust = 0, gp = gpar(fill = "#e5001c", lwd = 0))  
grid.rect(x = 1, y = 1 - 0.005, hjust = 1, vjust = 0,  gp = gpar(fill = "#e5001c", lwd = 0))