cigs <- read.csv("")
cigs1 <- subset(cigs, state == 13)
ggplot(cigs1, aes(x = year, y = sales)) + geom_point(aes(color = ndi, size = 1)) +
    ggtitle("Sales of Cigarettes by Year in North Carolina") +
    scale_x_continuous(breaks = seq(63, 92, 2)) +
    scale_color_continuous(name = "Disposable Income")

As the title says, this scatter plot shows the change over time of cigarette sales, measured in packs, in North Carolina. Each data point represents the total sales in North Carolina for one year, and the measurement time goes from 1963 to 1992. The changing color shows the change in per capita disposable income over that same time period, with lighter colors corresponding to increasing income.

What interested me in this dataset was the immediately apparent change in people’s consumption habits over time. There’s an undeniable decrease in spending on cigarettes, even as disposable income increases. I like this dataset because it shows that educating the public about potential health risks can pay off in the long term.