First look at Palmer Penguins

Data visualization and transformation
Data Science with R

Introduction

How do bill sizes of penguins vary across species? And what happens if we don’t take species into consideration?

Packages

We will use the tidyverse packages for data wrangling and visualization and the palmerpenguins package for the data.

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.0     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(palmerpenguins)

Data

The dataset we will visualize is called penguins. Let’s glimpse() at it.

# add code here

Penguin bills

1. Create a scatterplot of bill_depth vs. bill_lengths of penguins. Overlay a line of best fit. Describe the relationship between the two variables.

# add code here

Add interpretation here.

2. Create a scatterplot of bill_depth vs. bill_lengths of penguins, colored by species. Overlay a line of best fit. Describe the relationship between the two variables for each of the species.

# add code here

Add interpretation here.

3. Reflect on the seemingly contradictory findings from the two visualizations you’ve created. Which one do you believe more, and why?