Say It Ain’t So: using Weezer album cover colours in R

[This article was first published on Rstats – quantixed, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I’m a long-term fan of Weezer. Such was the brilliance of their first two albums that I have stuck with them through thick and thin. And dear me, there has been some very thin music. Nonetheless I own every album – thirteen of them. Among them are six albums entitled “Weezer”.

These records are colloquially referred to by the colour of the album. In chronological order: blue, green, red, white, teal and black. It struck me that these colours have a dataviz quality to them. They could be used for making colour palettes in R.

What are the colours?

Title Year rgb hex hsl RYM
blue 1994 rgb(24,155,204) #189BCC hsl(196,79,45) 3.91
green 2001 rgb(190,204,65) #BECC41 hsl(66,58,53) 3.02
red 2008 rgb(234,33,58) #EA213A hsl(353,83,52) 2.51
white 2016 rgb(243,243,243) #F3F3F3 hsl(0,0,95) 3.46
teal 2018 rgb(43,188,187) #2BBCBB hsl(180,63,45) 2.18
black 2019 rgb(13,13,13) #0D0D0D hsl(0,0,5) 2.18

Blue, green, red and teal are all plain colour. White and black albums are a gradient and the exact colour depends on where you sample.

Let’s use them in R!

We can specify the colours in hex format as a character vector and use them direct in ggplot, as shown below. Here I am plotting each “Weezer” album’s rating on rateyourmusic.


# weezer colours taken from weezer albums
weezer_album_colours <- c("#189BCC",
# ratings of weezer albums from taken on 2020-05-09
df <- data.frame(year=c("1994", "2001", "2008", "2016", "2018", "2019"),
# make a plot using these colours
p1 <- ggplot(df, aes(x = year, y = rym, fill = year)) +
  scale_fill_manual(values = weezer_album_colours) +
  geom_bar(stat="identity", colour = "black") +
  labs(title = "Ratings for Weezer's Weezer albums",
       subtitle = "Data from",
       x = "weezer", y = "Rating") +
  theme(text = element_text(family = "Futura-Medium"),
ggsave("ratings.png",p1,dpi = 300)

I used the extrafonts package to load in Futura Medium which is probably the basis for the Weezer band logo.

That was fun, but specifying the hex code for each album colour is a bit cumbersome.

How can we use these colours in a custom palette?

We can make a custom palette of named colours so that we can easily access the colours to make plots.

# now make a named character vector of weezer colours
weezer_colours <- c(
  `blue`  = "#189BCC",
  `green` = "#BECC41",
  `red` = "#EA213A",
  `white` = "#F3F3F3",
  `teal`  = "#2BBCBB",
  `black` = "#0D0D0D")

# a function to get hex codes of weezer colours
weezer_cols <- function(...) {
  cols <- c(...)
  if (is.null(cols))
    return (weezer_colours)

# all colours can be listed with
# or colours can be returned by character name(s)
weezer_cols("red", "blue")

# weezer colours can be used in a plot like this
p2 <- ggplot(mtcars, aes(x = hp, y = mpg)) +
  geom_point(color = weezer_cols("teal"),size = 3) +
  theme(text = element_text(family = "Futura-Medium"))
ggsave("teal_example.png", p2, dpi = 300)
An example plot using “teal” specified by the Teal Album colour

The example above shows how to use the album cover colours directly in a plot. How about generating a LUT/colour palette? We can specify a gradient of colours and get R to interpolate colours along the gradient to use for colourscales and other methods.

# now let's make some palettes
weezer_palettes <- list(
  `main`  = weezer_cols("blue", "red", "green"),
  `cool`  = weezer_cols("white", "teal"),
  `hot`   = weezer_cols("black", "red"),
  `mixed` = weezer_cols("blue", "green", "red", "white", "teal", "black"),
  `mono`  = weezer_cols("white", "black")

# function to interpolate palette. Default is main. Option to reverse
weezer_pal <- function(palette = "main", reverse = FALSE, ...) {
  pal <- weezer_palettes[[palette]]
  if (reverse) pal <- rev(pal)
  colorRampPalette(pal, ...)
# function to colour graph bjects
scale_colour_weezer <- function(palette = "main", discrete = TRUE, reverse = FALSE, ...) {
  pal <- weezer_pal(palette = palette, reverse = reverse)
  if (discrete) {
    discrete_scale("colour", paste0("weezer_", palette), palette = pal, ...)
  } else {
    scale_color_gradientn(colours = pal(256), ...)
# function for filling graph objects
scale_fill_weezer <- function(palette = "main", discrete = TRUE, reverse = FALSE, ...) {
  pal <- weezer_pal(palette = palette, reverse = reverse)
  if (discrete) {
    discrete_scale("fill", paste0("weezer_", palette), palette = pal, ...)
  } else {
    scale_fill_gradientn(colours = pal(256), ...)

These functions allow us to specify gradients between the different album cover colours. Here are some examples:

# examples of a plot using scale_colour_weezer
p2 <- ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  geom_point(size = 3) +
  scale_colour_weezer() +
  theme(text = element_text(family = "Futura-Medium"))
ggsave("colour_scale_example.png",p2,dpi = 300)
An example using the first three Weezer album colours (our default)
p3 <- ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Sepal.Length)) +
  geom_point(size = 3) +
  scale_colour_weezer(discrete = FALSE, palette = "hot") +
  theme(text = element_text(family = "Futura-Medium"))
ggsave("colour_scale_example2.png", p3, dpi = 300)
Example using “hot”, a gradient from the Black album to the Red album.
p4 <- ggplot(mpg, aes(manufacturer, fill = manufacturer)) +
  geom_bar() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  scale_fill_weezer(palette = "mixed", guide = "none") +
  theme(text = element_text(family = "Futura-Medium"))
ggsave("colour_scale_example3.png", p4, dpi = 300)
An example using mtcars. The colours follow a gradient through all “Weezer” album colours.

Most of the code above was adapted from this really useful post.

The post title is taken from “Say It Ain’t So” by Weezer taken from their debut LP “Weezer” also known as The Blue Album.

To leave a comment for the author, please follow the link and comment on their blog: Rstats – quantixed. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)