Inspired by other branding R packages such as
washi provides color palettes and themes consistent with Washington Soil Health Initiative (WaSHI) branding. This package is to be used only by direct collaborators within WaSHI, though you are welcome to adapt the package to suit your own organization’s branding.
Learn what functions are available and how to use them on the function reference webpage.
For help within RStudio, place your cursor within the function name then press
<F1> to open the help page or
<F2> to open the function source code.
washi from CRAN with:
Or, you can install the development version of
washi from our r-universe with:
install.packages('washi', repos = c( 'https://wa-department-of-agriculture.r-universe.dev', 'https://cloud.r-project.org') )
Then load the package with:
washi uses Poppins and Lato fonts through the
systemfonts packages. You can install these fonts on your computer with:
# install.packages("ragg") # install.packages("systemfonts") washi_install_fonts() #> ℹ To install the fonts on Windows: #> • Select all .ttf files in the newly opened directory. #> • Right-click + Install. #> • Restart RStudio.
To make these fonts available in RStudio, set the Graphics backend to use
AGG in the RStudio options dialog box.
To make these fonts available when knitting to
Quarto, use the following chunk setting:
knitr::opts_chunk$set(dev = "ragg_png")
To list the names of all available palettes, call
names(washi_pal). To view a palette, use the
This palette is primarily to access individual brand colors for fonts, table headers, graphic backgrounds, etc. These colors, when used together in plots, are not accessible to those who may have color blindness.
Individual colors can be accessed with
Available in green, blue, red, and gold.
washi_pal_view("green_gradient", n = 4, reverse = TRUE)
washi provides an example dataset, which was subset and anonymized from the WaSHI State of the Soils Assessment. This dataset comes in a long, tidy form with one measurement per row; and in a wide form with one sample per row. Its purpose is to provide an example soils dataset to use in plots and tables.
ggplot2 scale and theme functions that apply WaSHI colors, fonts, and styling.
library(ggplot2) # 1. Prepare data example_data_long |> subset(measurement %in% c("totalC_%", "poxC_mg.kg") & !texture == "Loamy Sand") |> # 2. Pipe to ggplot() ggplot(aes(x = value, fill = texture, color = texture)) + labs( title = "Distribution of POXC (mg/kg) and Total C (%)", subtitle = "Example with geom_density() and facet_wrap()." ) + geom_density(alpha = 0.4) + facet_wrap(. ~ measurement, scales = "free") + # 3. Add washi_theme() with argument to change legend position washi_theme(legend_position = "bottom") + # 4. Add washi_scale() washi_scale() + # 5. Tweak for your specific plot xlab(NULL) + guides(col = guide_legend(nrow = 2, byrow = TRUE))
# Single geom_point plot example_data_wide |> subset(crop %in% c("Apple", "Cherry", "Potato")) |> ggplot(aes(x = pH, y = Mn_mg.kg, color = crop)) + labs( title = "Scatter plot of pH and Mn (mg/kg)", subtitle = "Example with geom_point().", caption = "This is a caption." ) + geom_point(size = 2.5) + washi_theme() + washi_scale()
example_data_wide |> ggplot(aes(x = forcats::fct_rev(forcats::fct_infreq(crop)))) + geom_bar(fill = washi_pal[["standard"]][["blue"]]) + geom_text( aes( y = after_stat(count), label = after_stat(count) ), stat = "count", hjust = 2.5, color = "white" ) + # Flip coordinates to accomodate long crop names coord_flip() + labs( title = "Number of samples in each crop", subtitle = "Example plot with geom_bar() without gridlines.", y = NULL, x = NULL ) + # Turn gridlines off washi_theme(gridline_y = FALSE, gridline_x = FALSE) + # Remove x-axis theme(axis.text.x = element_blank())