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This homework is due on April 26, 2021 at 11:00pm. Please submit as a pdf file on Canvas.

Problem 1: (2 pts)

Use the color picker app from the colorspace package (colorspace::choose_color()) to create a qualitative color scale containing four colors. One of the four colors should be #5626B4, so you need to find three additional colors that go with this one.

# replace "#FFFFFF" with your own colors
colors <- c("#5626B4", "#FFFFFF", "#FFFFFF", "#FFFFFF")

swatchplot(colors)

Problem 2: (4 pts) Take the following scatter plot of the penguins dataset and make three modifications:

  1. Use the colors you chose in Problem 1.
  2. Improve the visual appearance by choosing a theme and cleaning up axis labels.
  3. Remove the need for a legend by direct-labeling the points.
ggplot(penguins, aes(bill_length_mm, body_mass_g, color = species)) +
  geom_point(size = 2, na.rm = TRUE)

Problem 3: (4 pts) The following scatter plot shows per-capita income versus number of inhabitants in all Texas counties in 2010. Use geom_text_repel() to label a subset of the counties by name. You can choose the counties to subset as you wish. Also, choose a theme and clean up the axis labeling, and make any other improvements to the plot design you consider appropriate.

Hint: If youโ€™re not sure how to select a subset of counties to label, check out the examples on the ggrepel website for some inspiration: https://ggrepel.slowkow.com/articles/examples.html#examples-1

tx_census <- read_csv("https://wilkelab.org/SDS375/datasets/US_census.csv") %>%
  filter(state == "Texas") %>%
  select(county = name, pop2010, per_capita_income)

tx_census %>%
  ggplot(aes(pop2010, per_capita_income)) +
  geom_point(size = 1.5) +
  scale_x_log10()