HDS 3.1-3.2

Author

Andrew Weiser

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 Species 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",
    y = "Number of Penguins",
    title = "Number of Penguins With Each Bill Length"
  )

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",
    y = "Number of Penguins",
    title = "Number of Penguins With Each Flipper Length"
  )

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(binwidth = 4) +
  labs(
    x = "Flipper Length",
    y = "Number of Penguins",
    title = "Number of Penguins With Each Flipper Length"
  )

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",
    y = "Number of Penguins",
    title = "Flipper Length by Species"
  )

Do different species have distinctly different flipper lengths?

No because they all have similar overlap but some skew smaller or larger.