{"id":2097,"date":"2018-01-01T16:37:39","date_gmt":"2018-01-01T16:37:39","guid":{"rendered":"http:\/\/pcool.dyndns.org:8080\/statsbook\/?page_id=2097"},"modified":"2025-06-22T08:45:13","modified_gmt":"2025-06-22T07:45:13","slug":"importing-fonts-setting-themes-and-defining-colours","status":"publish","type":"page","link":"https:\/\/pcool.dyndns.org\/index.php\/importing-fonts-setting-themes-and-defining-colours\/","title":{"rendered":"Fonts, Themes and Colours"},"content":{"rendered":"\n

The ggplot2 library1<\/a><\/sup> is very versatile and allows the creation of high quality plots. In this section, it is shown how to import a custom font (ie Google), setting a theme for all subsequent plots and define custom colours \/ palettes.<\/p>\n\n\n\n

Importing a custom font<\/strong><\/p>\n\n\n\n

Google<\/a> has a large collection of fonts that is available for download. For example the Roboto fonts (standard, condensed, slab and monospaced) can be downloaded<\/a>. Once downloaded, extract the zip file and save it to the fonts directory on you hard drive (Mac OSX: ~\/Library\/Fonts\/). In Windows, right click on the ttf file (true type font) and select install.<\/p>\n\n\n\n

The ~ (tilde) represents your home directory<\/em><\/p>\n\n\n\n

Once the font is installed on your system, R will need to know about it and import it to its database. This can be done with the extrafont package<\/a>2<\/a><\/sup> available from the CRAN website. To install the package and load it:<\/p>\n\n\n\n

install.packages(\"extrafont\")<\/em><\/span>\nlibrary(extrafont)<\/em><\/span>\nRegistering fonts with R<\/em><\/span><\/code><\/pre>\n\n\n\n
To import all available fonts into R’s font database:<\/p>\n\n\n\n
font_import()<\/em><\/span><\/code><\/pre>\n\n\n\n
but this may take a while……<\/p>\n\n\n\n
To import a single font, specify the path to the font library (ie Mac OSX):<\/p>\n\n\n\n
font_import(paths = \"~\/Library\/Fonts\", pattern = \"Roboto\")<\/span><\/em><\/code><\/pre>\n\n\n\n
To show the available \/ installed fonts:<\/p>\n\n\n\n
fonttable()<\/em><\/span><\/code><\/pre>\n\n\n\n
Setting a custom theme<\/strong><\/p>\n\n\n\n
The ggplot2 library allows customisation of themes to create plots with similar layout. To define a custom theme (paul_theme):<\/p>\n\n\n\n
library(ggplot2)<\/em><\/span>\npaul_theme <- function(base_size = 14, base_family = \"Roboto\"){<\/span><\/em>\n  theme_minimal(base_size = base_size, base_family = base_family) +<\/span><\/em>\n  theme(<\/span><\/em>\n    axis.text = element_text(size=8),<\/span><\/em>\n    axis.text.x = element_text(angle = 0, vjust = 0.5, hjust = 0.5),<\/span><\/em>\n    axis.title = element_text(size =8),<\/span><\/em>\n    panel.grid.major = element_line(color = \"gray\"),<\/span><\/em>\n    panel.grid.minor = element_blank(),<\/span><\/em>\n    panel.background = element_rect(fill = \"#ffffff\"),<\/span><\/em>\n    strip.background = element_rect(fill = \"black\", color = \"black\", <\/span><\/em>\n      linewidth = 0.5),<\/span><\/em>\n    strip.text = element_text(face = \"bold\", size = 8, color = <\/span><\/em>\n      \"white\"),<\/span><\/em>\n    legend.position = \"bottom\",<\/span><\/em>\n    legend.justification = \"center\",<\/span><\/em>\n    legend.background = element_blank(),<\/span><\/em>\n    panel.border = element_rect(color = \"grey5\", fill = NA, linewidth <\/span><\/em>\n      = 0.5)<\/span><\/em>\n  )<\/span><\/em>\n}<\/span><\/em>\ntheme_set(paul_theme())<\/em><\/span><\/code><\/pre>\n\n\n\n
Defining colours<\/strong><\/p>\n\n\n\n
Once a plot has been created, it is straight forward to change a palette, by using the scale_color_brewer() function:<\/p>\n\n\n\n
library(ggplot2)<\/em><\/span>\n data(mpg)<\/em><\/span>\n mpg<\/em><\/span>\n# A tibble: 234 \u00d7 11\n   manufacturer model      displ  year   cyl trans      drv     cty   hwy fl    class  \n   <chr>        <chr>      <dbl> <int> <int> <chr>      <chr> <int> <int> <chr> <chr>  \n 1 audi         a4           1.8  1999     4 auto(l5)   f        18    29 p     compact\n 2 audi         a4           1.8  1999     4 manual(m5) f        21    29 p     compact\n 3 audi         a4           2    2008     4 manual(m6) f        20    31 p     compact\n 4 audi         a4           2    2008     4 auto(av)   f        21    30 p     compact\n 5 audi         a4           2.8  1999     6 auto(l5)   f        16    26 p     compact\n 6 audi         a4           2.8  1999     6 manual(m5) f        18    26 p     compact\n 7 audi         a4           3.1  2008     6 auto(av)   f        18    27 p     compact\n 8 audi         a4 quattro   1.8  1999     4 manual(m5) 4        18    26 p     compact\n 9 audi         a4 quattro   1.8  1999     4 auto(l5)   4        16    25 p     compact\n10 audi         a4 quattro   2    2008     4 manual(m6) 4        20    28 p     compact\n# \u2139 224 more rows\n# \u2139 Use `print(n = ...)` to see more rows<\/mark><\/code><\/pre>\n\n\n\n
ggplot(mpg, aes(x = hwy, y = cty, colour = class)) + <\/em><\/span>\ngeom_point() + <\/em><\/span>\ntheme_bw() + <\/em><\/span>\nscale_color_brewer(palette = \"Set2\") + <\/em><\/span>\nggtitle(\"Set 2\")<\/em><\/span><\/code><\/pre>\n\n\n\n
\"\"<\/p>\n\n\n\n
ggplot(mpg, aes(x = hwy, y = cty, colour = class)) + <\/em><\/span>\ngeom_point() + <\/em><\/span>\ntheme_bw() + <\/em><\/span>\nscale_color_brewer(palette = \"Spectral\") + <\/em><\/span>\nggtitle(\"Spectral Set\")<\/em><\/span><\/code><\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
ggplot(mpg, aes(x = hwy, y = cty, colour = class)) + <\/em><\/span>\ngeom_point() + <\/em><\/span>\ntheme_bw() + <\/em><\/span>\nscale_color_brewer(palette = \"Blues\") + <\/em><\/span>\nggtitle(\"Blues\")<\/em><\/span><\/code><\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
It is also possible to define your own palette using the choose_palette() function in the colorspace package 3<\/a><\/sup>. To create a palette and give it a name (paul_palette):<\/p>\n\n\n\n
library(colorspace)<\/em><\/span>\npaul_palette <- choose_palette()<\/em><\/span><\/code><\/pre>\n\n\n\n
The graphical user interface will allow the creation of a custom palette based on the type of data and a default colour scheme. The number of colours to be available in the palette can also be selected:<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
Once finished, select OK and the palette will be available as paul_palette. If 4 colours of the palette are required, use:<\/p>\n\n\n\n
paul_palette(4)<\/span>\n[1] \"#823960\" \"#BD9AAA\" \"#91AA91\" \"#1C5F1D\"<\/span><\/code><\/pre>\n\n\n\n
You can also save a palette as an R file, by using the menu bar in colour picker. This will save a palette file to the working directory (ie pauls.R).<\/p>\n\n\n\n
To load the palette, use source:<\/p>\n\n\n\n
pauls <- source(\"pauls.R\")<\/span><\/code><\/pre>\n\n\n\n
This is a function and to recreate the palette as paul_palette:<\/p>\n\n\n\n
pauls_palette <- pauls$value<\/em><\/span>\npauls_palette(4)<\/em><\/span>\n[1] \"#0FCFC0\" \"#D5EAE7\" \"#F3E1EB\" \"#F79CD4\"<\/em><\/span><\/code><\/pre>\n\n\n\n
To show the palette create a vector of 10:<\/p>\n\n\n\n
vector <- c(1:10)<\/em><\/span>\nvector<\/em><\/span>\n [1] 1 2 3 4 5 6 7 8 9 10<\/em><\/span><\/code><\/pre>\n\n\n\n
Create a breaks vector:<\/p>\n\n\n\n
breaks <- c(0, vector)<\/em><\/span>\nbreaks<\/em><\/span>\n [1] 0 1 2 3 4 5 6 7 8 9 10<\/em><\/span><\/code><\/pre>\n\n\n\n
A histogram of 5 colours:<\/p>\n\n\n\n
hist(vector, breaks = breaks, col = pauls_palette(5))<\/em><\/span><\/code><\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
A histogram of 10 colours:<\/p>\n\n\n\n
hist(vector, breaks = breaks, col = pauls_palette(10))<\/span><\/em><\/code><\/pre>\n\n\n\n
\"\"<\/figure>\n","protected":false},"excerpt":{"rendered":"
The ggplot2 library is very versatile and allows the creation of high quality plots. In this section, it is shown how to import a custom font (ie Google), setting a theme for all subsequent plots and define custom colours \/ palettes. Importing a custom font Google has a large collection of fonts that is available […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"footnotes":""},"class_list":["post-2097","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages\/2097","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/comments?post=2097"}],"version-history":[{"count":8,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages\/2097\/revisions"}],"predecessor-version":[{"id":4262,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages\/2097\/revisions\/4262"}],"wp:attachment":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/media?parent=2097"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}