Faceting

• filter artist, get characteristics
• try different combinations of characteristics–which ones seem most related?
• diagnose error (unquoted ggplot)
• diagnose error (verb without _)
• plot with aesthetics
• plot text instead
• labs?

Faceting

You’ve learned to use color in your scatterplots.

Now you’ll learn another way to explore your data. plotnine lets you divide your plot into subplots to get one smaller graph for each level of a variable.

This is called faceting, and it’s another powerful way to communicate relationships within your data.

Faceting

asia_top200 = (
  music_top200
  >> filter(_.continent == "Asia")
)
asia_top200

	country	position	track_name	artist	streams	duration	continent
4600	Hong Kong	1	WANNABE	ITZY	112648	191.242	Asia
4601	Hong Kong	2	Intentions (feat. Quavo)	Justin Bieber	104467	212.867	Asia
4602	Hong Kong	3	Señorita	Shawn Mendes	84196	190.960	Asia
...	...	...	...	...	...	...	...
12197	Viet Nam	198	Đưa Nhau Đi Trốn (Chill Version)	Đen	20750	241.959	Asia
12198	Viet Nam	199	Hôm Nay Tôi Buồn	Phùng Khánh Linh	20580	275.000	Asia
12199	Viet Nam	200	Kick It	NCT 127	20495	233.013	Asia

2600 rows × 7 columns

For this example, we’ll use Spotify top 200 track data for countries in Asia.

Faceting

(asia_top200
  >> ggplot(aes("position", "streams", color = "country"))
   + geom_point()
)

This plot shows the number of streams for each top 200 track in Asian countries.

There are so many countries that the plot hits two issues:

1. it has to use many different colors.
2. many points are on top of each other.

A facetted plot could help here, by giving each country its own small panel.

Faceting

(asia_top200
  >> ggplot(aes("position", "streams", color = "country"))
   + geom_point()
   + facet_wrap('~country')
)

You facet a plot by adding another option, with a +, to the end of your code, after geom_point.

You add facet underscore wrap, then “tilde country” within the parentheses.

In R, the tilde symbol typically means “by”, meaning that we’re splitting the plot by country, and you can usually find it on the upper left of your keyboard. This tells ggplot2 to divide the data into subplots based on the country variable.

Let’s practice!

Scroll down to get started with practice!