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Statistics LibreTexts

7.6: Creating a More Complex Plot

  • Page ID
    8744
  • 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
      )

    file44.png