7.6: Creating a More Complex Plot

In this section we will recreate Figure 6.2 from Chapter @ref{data-visualization}. Here is the code to generate the figure; we will go through each of its sections below.

oringDf <- read.table("data/orings.csv", sep = ",",
                      header = TRUE)

oringDf %>%
  ggplot(aes(x = Temperature, y = DamageIndex)) +
  geom_point() +
  geom_smooth(method = "loess",
              se = FALSE, span = 1) + 
  ylim(0, 12) +
  geom_vline(xintercept = 27.5, size =8, 
             alpha = 0.3, color = "red") +
  labs(
    y = "Damage Index",
    x = "Temperature at time of launch"
  ) +
  scale_x_continuous(breaks = seq.int(25, 85, 5)) +
  annotate(
    "text",
    angle=90,
    x = 27.5,
    y = 6,
    label = "Forecasted temperature on Jan 28",
    size = 5
  )