Day 4 Activities

Exercises

library(tidyverse)
animals <- read.csv("../../data/animals.csv", row.names=1)

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.

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

# A tibble: 6 × 3
  animal_names speed color
  <chr>        <dbl> <chr>
1 Elephant      40   Gray 
2 Cheetah      120   Tan  
3 Tortoise       0.1 Green
4 Hare          48   Grey 
5 Lion          80   Tan  
6 PolarBear     30   White

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.

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.

names_ordered_by_speed <- animals_tb %>% arrange(speed) %>% pull(animal_names)
names_ordered_by_speed

[1] "Tortoise"  "PolarBear" "Elephant"  "Hare"      "Lion"      "Cheetah"  

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.

animals_tb$animal_names <- factor(animals_tb$animal_names, 
                                  levels = names_ordered_by_speed)
animals_tb$animal_names

[1] Elephant  Cheetah   Tortoise  Hare      Lion      PolarBear
Levels: Tortoise PolarBear Elephant Hare Lion Cheetah

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

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.

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("../../figures/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.

animals_gray_tan <- animals_tb %>% 
        filter(color == "Gray" | color == "Tan") %>%
        arrange(speed)
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)