library(tidyverse)
library(palmerpenguins)HDS 3.1-3.2
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 = "Island",
y = "Number of Penguins",
title = "Distribution of Number of Penguins on Each Island"
)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 = "Number of Penguins",
title = "Distribution of 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(bin_width = 4) +
labs(
x = "Flipper Length mm",
y = "Number of Penguins",
title = "Distribution of Flipper Length"
)Warning in geom_histogram(bin_width = 4): Ignoring unknown parameters:
`bin_width`
`stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Warning: Removed 2 rows containing non-finite outside the scale range
(`stat_bin()`).
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(bin_width = 4) +
labs(
x = "Flipper Length mm",
y = "Number of Penguins",
title = "Distribution of Flipper Length"
)Warning in geom_density(bin_width = 4): Ignoring unknown parameters:
`bin_width`
Warning: Removed 2 rows containing non-finite outside the scale range
(`stat_density()`).
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 = "Penguin Species",
y = "Flipper Length mm",
title = "Different Penguin Species and Their Flipper Lengths"
)Do different species have distinctly different flipper lengths?
Yes.