Gender Pay Gap by Britain Banks

Daily Graph Series

Gender Pay Gap by Bank

#==========================================================
#  References: https://www.bbc.com/news/business-43668187
#==========================================================

# Load some packages: 
library(tidyverse)

# Simulate a data frame: 
my_bonus <- data_frame(Bank = c("Barclays Bank", "Aberdeen Assets Managers", "HSBC", "Lloyds Bank"), 
                       women = c(27, 32, 39, 39), 
                       men = c(rep(100, 4)))
# Prepare data: 
my_bonus %>%   
  mutate(label = paste0(women, "p")) %>% 
  arrange(-women) %>% 
  mutate(Bank = factor(Bank, levels = Bank)) -> my_bonus


menColor <- "#7c4ea4"
womenColor <- "#7c4ea4"
my_font <- "Ubuntu Condensed"

dftext <- my_bonus %>% filter(Bank == my_bonus$Bank[4])

#===============
#  Solution 1
#===============

ggplot() + 
  coord_flip() + 
  geom_col(data = my_bonus, aes(x = Bank, y = men), fill = "#7c4ea4", alpha = 0.3, width = 0.8) + 
  geom_col(data = my_bonus, aes(x = Bank, y = women), fill = "#7c4ea4", width = 0.8) + 
  geom_text(data = my_bonus, aes(x = Bank, y = women, label = label), hjust = 1.3, color = "white", size = 6, family = my_font) + 
  labs(title = "Finance firms have the largest bonus gaps", 
       subtitle = "Women's bonuses as a proportition of men's among\nfinance firms with 5,000+ employees.") + 
  theme(panel.background = element_blank()) + 
  theme(panel.grid.major.x = element_line(colour = "gray90")) + 
  theme(axis.title.x = element_blank()) + 
  theme(axis.title.y = element_blank()) + 
  theme(axis.ticks.x = element_blank()) + 
  theme(axis.ticks.y = element_blank()) + 
  theme(text = element_text(family = my_font)) + 
  theme(axis.text.y = element_text(size = 16, family = my_font)) + 
  theme(axis.text.x = element_text(size = 16, family = my_font)) + 
  theme(plot.title = element_text(size = 28, hjust = 0)) + 
  theme(plot.subtitle = element_text(size = 18, color = "gray40")) + 
  theme(plot.margin = unit(rep(1.1, 4), "cm")) + 
  geom_hline(yintercept = c(0, 100), size = 0.8, color = "grey30") + 
  scale_y_continuous(labels = c("0p", "25p", "50p", "75p", "£1")) + 
  geom_text(data = dftext, aes(x = Bank, y = 65, label = "Women get a 27p bonus for\nevery £1 bonus paid to men"), 
            family = my_font, color = "gray20", size = 5) + 
  annotate("curve", 
           curvature = 0,
           x = 4, 
           xend = 4,
           y = 48, 
           yend = 28,
           arrow = arrow(angle = 20, length = unit(0.25, "cm")), size = 0.5)