Skip to content

Latest commit

 

History

History
346 lines (264 loc) · 11 KB

README.md

File metadata and controls

346 lines (264 loc) · 11 KB
Raw

usydColours

Jazmin Ozsvar 04/06/2020

The University of Sydney colour palettes

The usydColours package is intended to provide a set of colour palettes for use with ggplot2 and plot graphs. The palettes have been derived from The University of Sydney Branding Document V2.0, and include the primary branding palette as well as some novelty palettes that capture the spirit and landmarks of the University.

For more information on University branding, refer to the following links:
* https://intranet.sydney.edu.au/services/marketing-communications/our-brand.html
* https://intranet.sydney.edu.au/content/dam/intranet/documents/services/marketing-communications/brand-documents/LR_Brand_Guidelines_V2.1_General.pdf

The functionality of usydColours is based on the wonderful wesanderson package (https://github.com/karthik/wesanderson).

Installation

library(devtools)

install_github("Sydney-Informatics-Hub/usydColours")

Usage

Below is a list of the currently available palettes.

##  [1] "primary"               "modern_diverging"      "extended"             
##  [4] "secondary"             "pastel"                "complementary_ReGr"   
##  [7] "complementary_ReBl"    "bright"                "muted"                
## [10] "trafficlight"          "heatmap"               "flametree"            
## [13] "jacaranda"             "harbour"               "sandstone"            
## [16] "ochre"                 "greyscale"             "BlGrYe"               
## [19] "BlOr"                  "diverging_blue_red"    "diverging_blue_orange"

Qualitative palettes

# Primary
util_visualise_pal(usyd_palettes[["primary"]])

# Extended
util_visualise_pal(usyd_palettes[["extended"]])

# Secondary
util_visualise_pal(usyd_palettes[["secondary"]])

# Pastel
util_visualise_pal(usyd_palettes[["pastel"]])

# Bright
util_visualise_pal(usyd_palettes[["bright"]])

Sequential palettes

# Flame tree
util_visualise_pal(usyd_palettes[["flametree"]])

# Jacaranda
util_visualise_pal(usyd_palettes[["jacaranda"]])

# Sandstone
util_visualise_pal(usyd_palettes[["sandstone"]])

# Harbour
util_visualise_pal(usyd_palettes[["harbour"]])

# Ochre
util_visualise_pal(usyd_palettes[["ochre"]])

# Greyscale
util_visualise_pal(usyd_palettes[["greyscale"]])

Diverging palettes

# Modern (red/green)
util_visualise_pal(usyd_palettes[["modern_diverging"]])

# Complementary (red/green)
util_visualise_pal(usyd_palettes[["complementary_ReGr"]])

# Complementary (red/blue)
util_visualise_pal(usyd_palettes[["complementary_ReBl"]])

# Muted
util_visualise_pal(usyd_palettes[["muted"]])

# Traffic light
util_visualise_pal(usyd_palettes[["trafficlight"]])

# Diverging (blue/red)
util_visualise_pal(usyd_palettes[["diverging_blue_red"]])

# Diverging (blue/orange)
util_visualise_pal(usyd_palettes[["diverging_blue_orange"]])

Use with ggplot2

Below are some examples of usydColours in action.

Categorical data

# Bar graph with the primary palette
diamonds %>%
  filter(price < 1000) %>%
  ggplot(aes(price, fill = cut)) +
    geom_histogram(colour = "black", position = "dodge", binwidth = 250) +
    theme_bw() +
    scale_fill_manual(values = usyd_palette("primary"))

# Density graph with the muted palette
iris %>%
  ggplot(aes(x = Sepal.Length, fill = Species)) + 
    geom_density() +
    theme_bw() +
    facet_wrap(. ~ Species) +
    scale_fill_manual(values = usyd_palette("muted")) 

# Scatter plot using the jacaranda palette
diamonds %>%
  filter(row_number() %% 5 == 1) %>%
  filter(carat < 3) %>%
  filter(clarity %in% c("SI2", "SI1", "VS2", "VVS2")) %>%
  ggplot(aes(carat, price, colour = clarity)) +
    geom_jitter(alpha = 0.7) +
    theme_bw() +
    scale_colour_manual(values = usyd_palette("jacaranda"))

Continuous data

Use usyd_palette to interpolate colours between the discrete colours of the available palettes for continuous data. Remember to supply values for n and set type = "continuous".

Tip: you can also use usyd_palette to generate more colours of your favourite palette for categorical plots too!

# Heatmap
mpg %>%
  count(class, drv) %>%
  complete(class, drv, fill = list(n = 0L)) %>%
  ggplot(aes(x = class, y = drv)) +
  geom_tile(mapping = aes(fill = n)) +
  theme_bw() +
  scale_fill_gradientn(colours = usyd_palette("flametree", 100, type = "continuous"))

library(maps)
library(mapproj)

# Chloropleth
# This example is from: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html
unemp <- read.csv("http://datasets.flowingdata.com/unemployment09.csv",
                  header = FALSE, stringsAsFactors = FALSE)
names(unemp) <- c("id", "state_fips", "county_fips", "name", "year",
                  "?", "?", "?", "rate")
unemp$county <- tolower(gsub(" County, [A-Z]{2}", "", unemp$name))
unemp$county <- gsub("^(.*) parish, ..$","\\1", unemp$county)
unemp$state <- gsub("^.*([A-Z]{2}).*$", "\\1", unemp$name)

county_df <- map_data("county", projection = "albers", parameters = c(39, 45))
names(county_df) <- c("long", "lat", "group", "order", "state_name", "county")
county_df$state <- state.abb[match(county_df$state_name, tolower(state.name))]
county_df$state_name <- NULL

state_df <- map_data("state", projection = "albers", parameters = c(39, 45))

choropleth <- merge(county_df, unemp, by = c("state", "county"))
choropleth <- choropleth[order(choropleth$order), ]


ggplot(choropleth, aes(long, lat, group = group)) +
  geom_polygon(aes(fill = rate), colour = alpha("white", 1 / 2), size = 0.2) +
  geom_polygon(data = state_df, colour = "white", fill = NA) +
  coord_fixed() +
  theme_void() +
  ggtitle("US unemployment rate by county") +
  theme(axis.line = element_blank(), axis.text = element_blank(),
        axis.ticks = element_blank(), axis.title = element_blank()) +
  scale_fill_gradientn(colours = usyd_palette("muted", 100, type = "continuous"))

Defining custom palettes

Want to make your own palette? No problem! You can also define your own palette by selecting colours of your choice with usyd_pal_gen.

Below is the full list of colour names contained in usydColours.

After you’ve decided on what colours you want, use usyd_pal_gen as shown below to make a custom palette.

# Define a new palette
my_palette <- usyd_pal_gen(
  "UpdatedOchre", 
  "LightOchre", 
  "NeutralGrey", 
  "Eucalypt", 
  "DarkEucalypt") 

# Use the new palette
diamonds %>%
  filter(price < 1000) %>%
  ggplot(aes(price, fill = cut)) +
  geom_histogram(colour = "black", position = "dodge", binwidth = 250) +
  theme_bw() +
  scale_fill_manual(values = my_palette)

RGB values and hex codes of colours

You can also refer to this table for RGB values and hex codes if you’d like to apply them in Photoshop or any other code.

colourName R G B hex
AccentBlue 1 72 164 #0148A4
AccentGrey 241 241 241 #F1F1F1
AccentYellow 255 184 0 #FFB800
MasterbrandBlack 10 10 10 #0A0A0A
MasterbrandCharcoal 66 66 66 #424242
MasterbrandOchre 230 70 38 #E64626
MasterbrandWhite 255 255 255 #FFFFFF
SecondaryBeige 253 202 144 #FDCA90
SecondaryBlue 78 152 211 #4E98D3
SecondaryDarkGreen 0 126 59 #007E3B
SecondaryDarkSeafoam 0 164 133 #00A485
SecondaryIvory 248 239 221 #F8EFDD
SecondaryLemon 251 243 141 #FBF38D
SecondaryLightBlue 145 189 229 #91BDE5
SecondaryLightGreen 189 220 150 #BDDC96
SecondaryLightPink 248 185 204 #F8B9CC
SecondaryLightSeafoam 104 198 182 #68C6B6
SecondaryLilac 184 150 198 #B896C6
SecondaryMaroon 122 32 0 #7A2000
SecondaryOrange 249 161 52 #F9A134
SecondaryPeach 247 156 114 #F79C72
SecondaryPink 214 81 157 #D6519D
SecondaryPurple 127 63 152 #7F3F98
DarkEucalypt 37 88 77 #25584D
Eucalypt 113 164 153 #71A499
NeutralGrey 224 224 224 #E0E0E0
LightOchre 255 173 140 #FFAD8C
UpdatedOchre 231 71 38 #E74726