This documentation accompanies the TrendCT story: Minorities were disproportionately charged for drug possession in urban Connecticut.

The analysis was based on arrests data from the Connecticut Judicial Branch.

## [1] "...All names matched. That's a rare thing."

Since 1999 there have been 54530 arrests for 21-279(d).

What’s the racial breakdown for thoses arrests?

race_year_d <- data.frame(table(just_d$Year,just_d$Def_Race))
colnames(race_year_d) <- c("Year", "Race", "Arrests")
ggplot(race_year_d, aes(Year, Arrests, group=Race, colour=Race)) +
  geom_path(alpha=0.5) +
  ggtitle("Race of those arrested for Possession since 1999") +
  theme_minimal()

# And by percent
ggplot(race_year_d, aes(Year, Arrests, group=Race, fill=Race)) + geom_area(position="fill")