Tidyverse and Data Visualization Answer Key

Exercises

1. Change the animals data frame to a tibble called animals_tb. Save the row names to a column called animal_names before turning it into a tibble.

# Create animals_tb
animals_tb <- animals %>%
        rownames_to_column(var = "animal_names") %>%
        as_tibble()

2. Use ggplot2 to plot the animal names (x-axis) versus the speed of the animal (y-axis) in animals_tb using a scatterplot. Customize the plot to display as shown below.

# Create scatterplot of animals_tb data
ggplot(animals_tb) +
        geom_point(aes(x = animal_names, y = speed), color = "purple") +
        theme_bw() +
        ggtitle("Speed Comparisons Between Animals") + 
        ylab("Speed (km/h)") +
        xlab("Animal") +
        theme(plot.title=element_text(hjust=0.5))

3. We decide that our plot would look better with the animal names ordered from slowest to fastest. Using the animals_tb tibble, reorder the animals on the x-axis to start with the slowest animal on the left-hand side of the plot to the fastest animal on the right-hand side of the plot by completing the following steps:

   a. Use the arrange() function to order the rows by speed from slowest to fastest. Then use the pull() function to extract the animal_names column as a vector of character values. Save the new variable as names_ordered_by_speed.

# Create vector with the names of animals ordered by their speed
names_ordered_by_speed <- animals_tb %>% arrange(speed) %>%
  pull(animal_names)

b. Turn the animal_names column of animals_tb into a factor and specify the levels as names_ordered_by_speed from slowest to fastest (output in part a). Note: this step is crucial, because ggplot2 uses factor as plotting order, instead of the order we observe in data frame.

# Convert animal_names column into a factor with the levels determined by the order of names_ordered_by_speed vector
animals_tb$animal_names <- factor(animals_tb$animal_names, 
                                  levels = names_ordered_by_speed)

c. Re-plot the scatterplot with the animal names in order from slowest to fastest.

# Create plot with releveled animal_names
ggplot(animals_tb) +
        geom_point(aes(x = animal_names, y = speed), color = "purple") +
        theme_bw() +
        ggtitle("Speed Comparisons Between Animals") + 
        ylab("Speed (km/h)") +
        xlab("Animal") +
        theme(plot.title=element_text(hjust=0.5))

Note

If you are interested in exploring other ways to reorder a variable in ggplot2, refer to this post.

4. Save the plot as a PDF called animals_by_speed_scatterplot.pdf to the results folder.

# Save plot as a PDF
ggplot(animals_tb) +
        geom_point(aes(x = animal_names, y = speed), color = "purple") +
        theme_bw() +
        ggtitle("Speed Comparisons Between Animals") + 
        ylab("Speed (km/h)") +
        xlab("Animal") +
        theme(plot.title=element_text(hjust=0.5))
ggsave("results/animals_by_speed_scatterplot.pdf")

5. Use the functions from the dplyr package to perform the following tasks:

a. Extract the rows of animals_tb tibble with color of gray or tan, order the rows based from slowest to fastest speed, and save to a variable called animals_gray_tan.

# Subset animals_tb by animals that are gray or tan then arrange them by their speed in ascending order
animals_gray_tan <- animals_tb %>% 
        filter(color == "Gray" | color == "Tan") %>%
        arrange(speed)

# Print out animals_gray_tan
animals_gray_tan

# A tibble: 3 × 3
  animal_names speed color
  <fct>        <dbl> <chr>
1 Elephant        40 Gray 
2 Lion            80 Tan  
3 Cheetah        120 Tan  

b. Save animals_gray_tan as a comma-separated value file called animals_tb_ordered.csv to the results folder.

write.csv(animals_gray_tan,
          file = "results/animals_tb_ordered.csv",
          quote = FALSE)