Analyzing inequality in access to opportunities

# load libraries
library(aopdata)
library(sf)
#> Warning: package 'sf' was built under R version 4.0.4
library(ggplot2)
library(data.table)
library(units)
#> Warning: package 'units' was built under R version 4.0.4

df <- read_access(city='Curitiba',
                   mode='public_transport',
                   peak = T,
                   year=2019,
                   showProgress = F)

ggplot() +
  geom_boxplot(data=subset(df, !is.na(R003)),
               aes(x = factor(R003), y=CMAET30, color=factor(R003))) +
  scale_color_brewer(palette = 'RdBu') +
  labs(title='Distribution of the proportion of jobs accessible', color="Income\ndecile",
       subtitle='by public transport in less than 30 min. by income decile',
       x='Income decile', y="Accessibility") +
  scale_x_discrete(labels=c("D1 Poorest", paste0('D', 2:9), "D10 Wealthiest")) +
  scale_y_continuous(labels = scales::percent) +
  theme_minimal()

avg_access_10p_wealthiest <- df[ R003==10, weighted.mean(x=CMATT60, w=P001)]
avg_access_40p_poorest <- df[ R003<=4, weighted.mean(x=CMATT60, w=P001)]
palma_ratio <- avg_access_10p_wealthiest / avg_access_40p_poorest                

print( paste0('In less than 60 min. by public transport, the 10% wealthiest population could access on average ', round(palma_ratio,2), ' times more job opportunites than the 40% poorest people') )
#> [1] "In less than 60 min. by public transport, the 10% wealthiest population could access on average 2.65 times more job opportunites than the 40% poorest people"