Setup & Q&A

• Open RStudio
• Open your fundRmentals R Project (click the blue cube in the top right corner of RStudio)
• Open a new Rmd file for today
• Install the palmerpenguins package by running the code below in the console:

install.packages("palmerpenguins")Copy Code

• In a new code chunk, load tidyverse & palmerpenguins using the library() command
• In another code chunk, create peng_data by copying the below code:

peng_data <- palmerpenguins::penguinsCopy Code

Overview

• ggplot2

• Scatterplot

• Means plot

• Next steps

ggplot2

• ggplot2 is a really useful package (part of tidyverse) for data visualisation

• We use the ggplot2::ggplot() function to create plots

• Plots are built in layers from 3 key components: data, coordinate system, & geometric elements (geoms)

• Plots created with ggplot2 are super customisable, you can make pretty much anything you can imagine

• Because it's pretty much unlimited, there is a huge amount of resources online & there is no need to memorise everything, we can easily look it up!

• Today we're going to try creating a few plots with the palmerpenguins data!

ggplot2::ggplot()

• Built layer by layer +

• Variables are mapped onto elements of the plot as 'aesthetics'

  • We use aes() to include variable(s) as an aesthetic

• Geoms are 'visual marks' that represent data points e.g.

  • geom_bar() – creates a layer of bars

  • geom_point() – creates a layer of data points

  • geom_histogram() – creates a layer with a histogram

  • geom_text() – creates layer with text on

& many more options...

Plot Building Process

1. Create base layer by specifying the data & the variables to map onto the plot

2. Add geom layer (to display our data points)

3. Add/edit visual properties (scale, colours, shapes etc.)

4. Add semantic properties (e.g. title, labels)

5. Add a theme to make our plot pretty

Scatterplots

peng_scatter <- ggplot2::ggplot(peng_data, aes(x = bill_length_mm, y = bill_depth_mm))
peng_scatter +
  geom_point() +
  labs(title = "Scatterplot of Bill Length & Bill Depth", x = "Bill Length (mm)", y = "Bill Depth (mm)") + 
  theme_bw()Copy Code

peng_scatter <- ggplot2::ggplot(peng_data, aes(x = bill_length_mm, y = bill_depth_mm))
peng_scatter +
  geom_point(colour = "dark blue", size = 3, shape = 20, alpha = .5) +
  geom_smooth(method = "lm", se = FALSE, colour = "orange") +
  labs(title = "Scatterplot of Bill Length & Bill Depth", x = "Bill Length (mm)", y = "Bill Depth (mm)") + 
  theme_bw()Copy Code

Means Plots

peng_means <- ggplot2::ggplot(peng_data, aes(x = species, y = flipper_length_mm))
peng_means +
  stat_summary(fun = "mean", geom = "point", size = 4, colour = "orange") +  
  labs(title = "Mean Flipper Length per Penguin Species", x = "Species", y = "Flipper Length (mm)") + 
  theme_minimal()Copy Code

Adding CIs

peng_means <- ggplot2::ggplot(peng_data, aes(x = species, y = flipper_length_mm))
peng_means +
  stat_summary(fun.data = "mean_cl_normal", geom = "pointrange", colour = "orange") +  
  labs(title = "Mean Flipper Length per Penguin Species", x = "Species", y = "Flipper Length (mm)") + 
  theme_minimal()Copy Code

Changing the Coordinate System

peng_means <- ggplot2::ggplot(peng_data, aes(x = species, y = flipper_length_mm))
peng_means +
  stat_summary(fun.data = "mean_cl_normal", geom = "pointrange", colour = "orange") +  
  labs(title = "Mean Flipper Length per Penguin Species", x = "Species", y = "Flipper Length (mm)") + 
  coord_cartesian(ylim = c(0, 250)) +
scale_y_continuous(breaks = seq(0, 250, 50)) +
  theme_minimal()Copy Code

Top Tips

• Run & inspect every change you make
• Be aware that creating plots with ggplot is often a long process
• A really common error is forgetting the + for each layer
• Set code chunk options to echo = FALSE (plot is displayed but the code isn't):

Next Steps

Save the RMarkdown document from today Ctrl + S or Command + S

For next week you should complete the discovr_09 tutorial on comparing means by pasting the below code into the Console in RStudio, pressing Enter

learnr::run_tutorial("discovr_09", package = "discovr")Copy Code