if (!require('devtools')) install.packages('devtools')
library(ggplot2)
library(tidyverse)
devtools::install_github("connorrothschild/tpltheme")
library(tpltheme)This package creates a standardized formats for plots to be used in
reports created by the Texas Policy Lab. It primarily relies on
set_tpl_theme, which allows the user to specify whether the plot theme
should align with a standard plot (style = "print"), or one specially
created for plotting geographical data (style = "Texas").
The user is able to specify whether they want to use Lato or Adobe Caslon Pro in their figures.
To ensure that these fonts are installed and registered, use
tpl_font_test(). If fonts are not properly installed, install both
fonts online and then run tpl_font_install().
tpl_font_test()#> [1] "Adobe Caslon Pro is not imported and registered. Install the font online and import and register using font_install(). If that presents problems, try using sysfonts::font_add('Adobe Caslon Pro', regular = 'Adobe Caslon Pro.ttf') with your downloaded font name taking the place of 'Adobe Caslon Pro.ttf.'"
tpl_font_install()#> Importing fonts may take a few minutes, depending on the number of fonts and the speed of the system.
#> Continue? [y/n]
#> [1] "Adobe Caslon Pro is not imported and registered. Install the font online and import and register using font_install(). If that presents problems, try using sysfonts::font_add('Adobe Caslon Pro', regular = 'Adobe Caslon Pro.ttf') with your downloaded font name taking the place of 'Adobe Caslon Pro.ttf.'"
Load library(tpltheme) after library(ggplot2) and/or
library(tidyverse).
Here are some examples of sample TPL plots with different specifications
for style and font.
set_tpl_theme(style = "print", font = "adobe")
ggplot(iris, aes(x=Species, y=Sepal.Width, fill=Species)) +
geom_bar(stat="summary", fun.y="mean", show.legend = FALSE) +
scale_y_continuous(expand = expand_scale(mult = c(0, 0.001))) +
labs(x="Species", y="Mean Sepal Width (cm)", fill="Species", title="Iris Dataset")
set_tpl_theme(style = "print", font = "lato")
ggplot(iris, aes(x=jitter(Sepal.Width), y=jitter(Sepal.Length), col=Species, size = Petal.Length)) +
geom_point() +
labs(x="Sepal Width (cm)", y="Sepal Length (cm)", col="Species", size = "Petal Length", title="Iris Dataset")
By specifying style = "Texas" within set_tpl_theme, the user may
also create Texas-specific plots.
tx_vac <- readr::read_csv("https://raw.githubusercontent.com/connorrothschild/tpltheme/master/data/tx_vac_example.csv")
set_tpl_theme(style = "Texas", font = "adobe")
ggplot(data = tx_vac, mapping = aes(x = long, y = lat, group = group, fill = avgvac*100)) +
coord_fixed(1.3) +
scale_fill_continuous(limits = c(78.3,100)) +
geom_polygon(color = "black") +
labs(title = "Texas Vaccination Rate by County",
subtitle = "Among Kindergarteners",
fill = "Percent\nVaccinated",
caption = "Source: Texas DSHS")
And it also works for categorical variables:
set_tpl_theme(style = "Texas", font = "lato")
tx_vac %>%
dplyr::mutate(cat = factor(dplyr::case_when(avgvac*100 > 99 ~ "Great",
avgvac*100 > 90 ~ "Average",
avgvac*100 < 90 ~ "Bad"))) %>%
ggplot(mapping = aes(x = long, y = lat, group = group, fill = cat)) +
coord_fixed(1.3) +
geom_polygon(color = "black") +
labs(title = "Texas Vaccination Rate by County",
subtitle = "Among Kindergarteners",
fill = "Vaccination Rating",
caption = "Source: Texas DSHS")
If the number of colors exceeds the number of colors in the TPL palette
(9), the function tpl_color_pal() will drop the TPL color palette and
return the greatest number of unique colors possible within the
RColorBrewer’s “Paired” palette (for more information on the use of
RColorBrewer palettes, see this
chapter).
tx_vac %>%
ggplot(mapping = aes(x = long, y = lat, group = group, fill = subregion)) +
coord_fixed(1.3) +
geom_polygon(color = "black", show.legend = FALSE) +
labs(title = "Texas Counties")
# default to print afterwards
set_tpl_theme(style = "print")The user also has the option to include the TPL logo in single plots. This may be preferred for those reports being made especially public, or to serve as a pseudo-watermark in proprietary plots.
The user can specify the position of the logo as well as its scale.
The scale argument refers to the size of the logo object, with the
specified number corresponding to a multiplication with the normal logo
size. In other words, scale = 2 will double the size of the logo.
The logo defaults to 1/7th of the size of the plot.
plot <- ggplot(iris, aes(x=Species, y=Sepal.Width, fill=Species)) +
geom_bar(stat="summary", fun.y="mean", show.legend = FALSE) +
scale_y_continuous(expand = expand_scale(mult = c(0, 0.001))) +
labs(x="Species", y="Mean Sepal Width (cm)", fill="Species", title="Iris Dataset")
add_tpl_logo(plot, position = "top right", scale = 1.5)
There may be some instances when an all-out logo is not warranted or
preferred. If that is the case and the user would still like to
watermark their figures, they can use the function add_tpl_logo_text()
to add text to an existing plot object:
plot <- ggplot(iris, aes(x=jitter(Sepal.Width), y=jitter(Sepal.Length), col=Species, size = Petal.Length)) +
geom_point() +
labs(x="Sepal Width (cm)", y="Sepal Length (cm)", col="Species", size = "Petal Length", title="Iris Dataset")
add_tpl_logo_text(plot)
The user may also need to specify align, which moves the plot
horizontally across the bottom of the page.
plot <- ggplot(iris, aes(x=Species, y=Sepal.Width, fill=Species)) +
geom_boxplot(show.legend = FALSE) +
labs(x="Species", y="Sepal Width (cm)", fill="Species", title="Iris Dataset", subtitle ="When specifying align = 1")
add_tpl_logo_text(plot, align = 1) 
In the event that the user wishes to drop an axis, they may do so with
drop_axis(). The function may drop any combination of axes depending
on the user’s input (drop = "x", drop = "y", drop = "both", drop = "neither").
Unlike add_tpl_logo(), drop_axis() should be added to an existing
plot object:
ggplot(iris, aes(x=jitter(Sepal.Width), y=jitter(Sepal.Length), col=Species, size = Petal.Length)) +
geom_point() +
labs(x="Sepal Width (cm)", y="Sepal Length (cm)", col="Species", size = "Petal Length", title="Iris Dataset") +
drop_axis(axis = "y")
The function view_palette plots base color palettes included in
tpltheme. All TPL color palettes are led by the notation
palette_tpl_* and therefore can be easily autocompleted within
RStudio.
p1 <- view_palette(palette = palette_tpl_main) + ggtitle("Categorical")
p2 <- view_palette(palette = palette_tpl_diverging) + ggtitle("Diverging")
p3 <- view_palette(palette = palette_tpl_sequential) + ggtitle("Sequential")
gridExtra::grid.arrange(p1, p2, p3, nrow = 1)
These palettes were created using http://colorbrewer2.org and http://coloors.co and are colorblind friendly.
The user may specify the color palette in the scale_fill_* or
scale_color_* functions in a ggplot call. Specifically, the user can
specify the palette (categorical, diverging, sequential) and whether
the palette should be reversed.
set_tpl_theme(style = "print", font = "lato")
normal <- ggplot(diamonds) +
geom_bar(aes(x = cut, fill = clarity)) +
labs(title = "TPL Color Palette",
subtitle = "On sample data",
x = "Cut",
y = "Count",
fill = "Clarity") +
scale_y_continuous(expand = expand_scale(mult = c(0, 0.001))) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
reversed <- normal +
labs(subtitle = "(reversed)") +
scale_fill_discrete(reverse = TRUE)
gridExtra::grid.arrange(normal, reversed, nrow = 1)
normal <- diamonds %>%
group_by(clarity) %>%
summarise(price = mean(price)) %>%
mutate(clarity = forcats::fct_reorder(clarity, price)) %>%
ggplot() +
geom_col(aes(x = clarity, y = price, fill = clarity), show.legend = FALSE) +
labs(title = "TPL Color Palette",
subtitle = "in action",
x = "Clarity",
y = "Price",
fill = element_blank()) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
coord_flip() +
scale_fill_discrete() +
scale_y_continuous(expand = expand_scale(mult = c(0, 0.001))) +
drop_axis(axis = "x")
reversed <- normal +
labs(subtitle = "(reversed)") +
scale_fill_discrete(reverse = TRUE)
gridExtra::grid.arrange(normal, reversed)
data <- gapminder::gapminder %>%
dplyr::filter(gapminder::gapminder$country %in% c("France", "Germany", "Ireland", "Italy", "Japan", "Norway", "Mexico", "United States")) %>%
dplyr::mutate(year = as.Date(paste(year, "-01-01", sep = "", format='%Y-%b-%d')))
ggplot(data = data, aes(x = year, y = gdpPercap, fill = country)) +
geom_area(alpha = 0.8) +
scale_x_date(expand = c(0,0)) +
scale_y_continuous(expand = c(0, 0), labels = scales::dollar) +
labs(title = "GDP Per Capita Over Time",
subtitle = "Using the TPL Color Palette",
x = element_blank(),
y = "GDP Per Capita",
fill = "Country") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
By calling undo_tpl_theme, you are able to remove TPL-specific theme
settings and restores to ggplot defaults.
undo_tpl_theme()#> [1] "All TPL defaults were removed and the tpltheme package has been effectively detached from the current environment. To restore TPL defaults, use set_tpl_theme()."
ggplot(iris, aes(x=jitter(Sepal.Width), y=jitter(Sepal.Length), col=Species, size = Petal.Length)) +
geom_point() +
labs(x="Sepal Width (cm)", y="Sepal Length (cm)", col="Species", size = "Petal Length", title="Iris Dataset")
To restore the TPL theme, simply call set_tpl_theme():
set_tpl_theme()
last_plot()
read_word: Reads word into Rmarkdown, such that word documents can be edited and read into the main Rmarkdown file for creating reports.read_word_table: Reads a table from word into Rmarkdown, such that tables in word can be edited and then imported into Rmarkdown.