Rows: 365
Columns: 8
$ date <date> 2015-01-01, 2015-01-02, 2015-01-03, 2015-01-04, 2015-01-…
$ births <dbl> 8068, 10850, 8328, 7065, 11892, 12425, 12141, 12094, 1186…
$ wday <ord> Thu, Fri, Sat, Sun, Mon, Tue, Wed, Thu, Fri, Sat, Sun, Mo…
$ year <dbl> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 201…
$ month <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ day_of_year <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ day_of_month <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ day_of_week <dbl> 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, …
More ggplot2
Grayson White
Math 241
Week 2 | Spring 2026
Recap Data: Births2015
- Let’s think more about the scales.
- Let’s add more context!
Scales
- Maybe we want to change the default settings of a scale.
- Maybe we want a different scale than the default.
Context: Labels
- Prefer citing the data at the bottom?
Context: Labels
Prefer citing the data at the bottom?
For slide space, I will neglect my labeling in the for the rest of the slides.
Now we want to add even more context to help the reader understand whether or not birth rates on national holidays behave like weekends.
Context: Adding Holidays
Context: Adding Holidays
- Problems?
Context: Adding Holidays
Context: Adding Holidays
Context: Adding Holidays
Context: Adding Holidays
ggplot(data = Births2015,
mapping = aes(x = date, y = births,
color = wday)) +
geom_point(size = 6, color = "black",
data = holidays) +
geom_point(size = 5, color = "grey90",
data = holidays) +
geom_point() +
annotate("text", x = as_date("2015-09-01"),
y = 7500, label = "Holidays",
color="black", size=5)
Context: Adding Holidays
ggplot(data = Births2015,
mapping = aes(x = date, y = births,
color = wday)) +
geom_point(size = 6, color = "black",
data = holidays) +
geom_point(size = 5, color = "grey90",
data = holidays) +
geom_point() +
annotate("segment", colour = "black",
x = as_date("2015-09-01"),
xend = holidays$date,
y = 6800, yend = holidays$births,
size = 1, alpha = 0.2, arrow = arrow())+
annotate("text", x = as_date("2015-09-01"),
y = 7500, label = "Holidays",
color="black", size=5)
Context: Adding Holidays
Context: Adding Holidays
# devtools::install_github("dill/emoGG")
library(emoGG)
ggplot(data = Births2015,
mapping = aes(x = date, y = births,
color = wday)) +
geom_point() +
geom_text(mapping = aes(label = label),
data = label_data,
color = "black", vjust = "top",
hjust = "left") +
geom_emoji(data = holidays,
mapping = aes(emoji = emoji,
x = date,
y = births))
Context
And there are lots more ways to annotate your graph (shaded regions, other context…).
A few notes:
- Don’t over do it!
- Like with selecting a
geomor amappingor ascale, try several out first.
Handling Over-plotting
Let’s return to the US Forest Inventory and Analysis Program Idaho data
Handling Over-plotting
Handling Over-plotting
Handling Over-plotting
Handling Transformations
- Transform variables directly.
Handling Transformations
- Transform scale.
ColorBrewer
Color Options: Saturation
Color Options: Saturation
ColorBrewer YlGn palette
Viridis Palette
Viridis Palette
Viridis Palette
Color Options: Hue
Color Options: Hue
ColorBrewer Hue
Themes
ggplot(data = Births2015,
mapping = aes(x = date, y = births,
color = wday)) +
geom_point() +
theme(axis.title.x =
element_text(color = "#C1D82F", size = 20),
axis.title.y =
element_text(color = "#00857D", size = 25),
axis.text.x =
element_text(color = "#C1D82F", size = 12),
axis.text.y =
element_text(color = "#FF7401", size = 18)) 
Built-in Themes
Built-in Themes
Built-in Themes
- Useful for maps and pie charts!
Additional Themes Package: ggthemes
Additional Themes Package
Saving/exporting your figures
Reproducible Workflow
One where if you shared your data and work with someone else, they could reproduce your results.
Not the same as replication: Where someone collects new data following your same design to see if they get the same results.
Quartodocuments allow us to include ourRcode, output, and narrative in the same place.- Load the raw data.
- Be transparent about all the analysis steps.
- Even if you don’t showcase the
Rcode in the output file, it is contained in theqmdfile.
Creating reproducible examples with reprex
Why do I need to learn to create reproducible technical examples?
- So that you can ask and answer questions in our class Slack Workspace or Stack Overflow or other
Rhelp sites!
Minimal Code
Include the necessary libraries.
Test run the code in a restarted R session to make sure it is runnable!
Make sure your code is copy-and-paste-able!
Now we have our reproducible example:
How can I reorder the bars in the ggplot to go from the most frequent to the least frequent category?
How can we easily share it?
- Using the
reprex()function in thereprexpackage.