The package provides several wrappers and tools to use with ggplot2 to make graphics that follow the GLA City Intelligence Data Design Guidelines.
# To install from github use the devtools function: # This will install all required dependencies devtools::install_github("Greater-London-Authority/gglaplot")
library(ggplot2) library(gglaplot) library(dplyr) library(scales) library(lubridate) pal <- gla_pal(gla_theme = "default", palette_type = "highlight", n = c(1, 1)) theme_set(theme_gla(gla_theme = "default")) plot <- ggplot(data = LDNUK, mapping = aes(x = Year, y = GPG, group = location, colour = location)) + ggla_line(aes(size = location)) + scale_size_manual(values = c(4 * mm_to_pt, 2 * mm_to_pt)) + scale_colour_manual(values = pal) + ggla_highlight(filter_type = "end") + ggla_axisat0() + scale_y_continuous(expand = c(0, 0), limits = c(0, 32.5), labels = dollar_format(prefix = "", suffix = "%")) + scale_x_date(date_breaks = "1 year", date_labels = "'%y", expand = expand_scale(mult = c(0.05, 0.01))) + labs(title = "Gender Pay Gap - Total (Median)", subtitle = "Gender Pay Gap - Total (Median) - London VS UK", caption = "Note: 2017 data is provisional\nChart: GLA City Intelligence Source: London Datastore") plot
Plots can be incorporated in Rmarkdown/Notebooks or exported to be included in documents/slideshows etc
ggsave(plot = plot, path = "example_plot.svg")
.svg
is the best format to export plots, and the size and dpi of the output can be adjusted within ggsave()
.
For help with gglaplot itself, see the vignettes which are available on the gglaplot github pages.
The BBC has a similar package for their house style which has some comprehensive help pages here.