Annotating plots

1. Using the mpg data, create a scatterplot of highway and city fuel efficiencies. Create a title, subtitle, caption, and axes labels.

library(tidyverse)

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mpg |> 
  ggplot(aes(x = cty, y = hwy)) +
  geom_point() +
  labs(title = "Fuel efficiency", subtitle = "Highway vs. city miles per gallon", caption = "Source: mpg data", x = "City miles per gallon", y = "Highway miles per gallon")

2. Repeat #1 adding a linear regression line. Use cor() to calculate the correlation coefficient for the correlation. Add it to the plot somewhere labeled and rounded to two decimals.

mpg_corr <- cor(mpg$hwy, mpg$cty)
mpg |> 
  ggplot(aes(x = cty, y = hwy)) +
  geom_smooth(method = "lm") +
  geom_point() +
  labs(title = "Fuel efficiency", subtitle = "Highway vs. city miles per gallon", caption = "Source: mpg data", x = "City miles per gallon", y = "Highway miles per gallon") +
  annotate(geom = "text", label = paste0("r = ", round(mpg_corr, 2)), x = 15, y = 40)

`geom_smooth()` using formula = 'y ~ x'

3. Repeat #1. Find the manufacturer and model of the data point with the highest city fuel efficiency. Label this point by drawing a line from the point to the text label and include the manufacturer and model (broken across two lines).

mpg |> 
  ggplot(aes(x = cty, y = hwy)) +
  geom_point() +
  labs(title = "Fuel efficiency", subtitle = "Highway vs. city miles per gallon", caption = "Source: mpg data", x = "City miles per gallon", y = "Highway miles per gallon") +
  annotate(geom = "text", label = "Volkswagon\nBeetle", x = 33, y = 40) +
  annotate(geom = "segment", x = 33, xend = 34.8, y = 41, yend = 43.5)

4. Repeat #1 drawing grey horizontal and vertical lines at 20 mpg for both axes underneath the data points. Add a lightpink rectangle under the points filling the upper right quandrant (>20 for both axes).

mpg |> 
  ggplot(aes(x = cty, y = hwy)) +
  geom_hline(yintercept = 20, color = "grey60") +
  geom_vline(xintercept = 20, color = "grey60") +
  annotate(geom = "rect", xmin = 20, xmax = 50, ymin = 20, ymax = 50, fill = "lightpink", alpha = 0.25) +
  geom_point() +
  labs(title = "Fuel efficiency", subtitle = "Highway vs. city miles per gallon", caption = "Source: mpg data", x = "City miles per gallon", y = "Highway miles per gallon") +
  coord_cartesian(xlim = c(9, 35), ylim = c(10, 45))

5. Create boxplots of fuel efficiency by class but order the class levels by mean highway fuel efficiency. At y = 10, add the sample size for each box (e.g., N=5, N=47, etc.).

mpg |> 
  ggplot(aes(x = fct_reorder(class, hwy), y = hwy)) +
  geom_boxplot() +
  geom_text(stat = "count", aes(label = paste0("N=", after_stat(count))), y = 10) +
  ylim(10, 44)