HDS 3.1-3.2

library(tidyverse)
library(palmerpenguins)

Begin by loading the tidyverse and palmerpenguins packages in the code chunk above and adding your name as the author.

Visualizing the penguins Data

Categorical Variables

Let’s start by making a bar chart of the species variable. Modify this code by filling in the ______ to do so:

ggplot(data = penguins, mapping = aes(x = species)) +
  geom_bar() +
  labs(
    x = "Penguin Species",
    y = "Number of Penguins",
    title = "Distribution of Penguin Species near Palmer Station, Antarctica"
  )

Make a bar chart showing the number of penguins on each island by using the code above as a template:

ggplot(data = penguins, mapping = aes(x = island)) +
  geom_bar() +
  labs(
    x = "Penguin Species",
    y = "Number of Penguins",
    title = "Distribution of Penguin by island near Palmer Station, Antarctica"
  )

Quantitative Variables

Now let’s make a histogram of the bill_length_mm variable. Modify this code by filling in the ______ to do so:

ggplot(data = penguins, mapping = aes(x = bill_length_mm)) +
  geom_histogram() +
  labs(
    x = "Bill Length mm",
    y = "Penguins",
    title = "Distribution of Penguins near Palmer Station, Antarctica by Bill Length in mm"
  )

Make a histogram of flipper_length_mm and set the binwidth to 4. Use the code above as a template:

ggplot(data = penguins, mapping = aes(x = flipper_length_mm)) +
  geom_histogram(binwidth = 4) +
  labs(
    x = "Flipper Length mm",
    y = "Penguins",
    title = "Distribution of Penguins near Palmer Station, Antarctica by Flipper Length in mm"
  )

Now make a density plot (instead of a histogram) of flipper_length_mm by using the geom_density() function:

ggplot(data = penguins, mapping = aes(x = flipper_length_mm)) +
  geom_density() +
  labs(
    x = "Flipper Length",
    y = "Penguins",
    title = "Distribution of Penguins near Palmer Station, Antarctica by Flipper Length in mm"
  )

Suppose we would like to look at how flipper_length_mm differs across species. Modify this code by filling in the ______ to do so:

ggplot(data = penguins, mapping = aes(x = flipper_length_mm)) +
  geom_histogram() +
  facet_wrap( ~ species) +
  labs(
    x = "Flipper Length in mm",
    y = "Number of Penguins",
    title = "Penguins' flipper length sorted by Species"
  )

Do different species have distinctly different flipper lengths?

Yes, the length of flippers for each penguin appears to be different by species. The Adelies species appears to be around 190 mm on average, the Chinstrap appears to be a little less than 200 mm on average, and the Gentoo is mostly between 210 and 220 mm.