library(tidyverse)
library(ggplot2)
#devtools::install_github("connorrothschild/bbdata")
library(bbdata)
library(gapminder)
bbd_font_install(device = 'win', force = TRUE)
data <- gapminder %>%
dplyr::filter(gapminder$country %in% c("Italy", "Japan", "Norway", "Mexico", "United States")) %>%
dplyr::mutate(year = as.Date(paste(year, "-01-01", sep = "", format='%Y-%b-%d')))
set_bbd_theme()
ggplot(data = data, aes(x = year, y = gdpPercap/1000, fill = country)) +
geom_area() +
scale_x_date(expand = c(0,0)) +
bbd_fix_bars() +
labs(title = "GDP Per Capita Over Time",
subtitle = "Using the BBD Color Palette",
x = "Year",
y = "GDP Per Capita\n(thousands of $)",
fill = "Country",
caption = "Source: Gapminder")
ggtext
:#devtools::install_github("clauswilke/ggtext")
library(ggtext)
data <- gapminder %>%
filter(year == 2007) %>%
mutate(rank = rank(gdpPercap)) %>%
filter(rank > 132)
ggplot(data, aes(x = reorder(country, gdpPercap),
y = gdpPercap,
fill = ifelse(country == "Norway", "1", "0"))) +
geom_col(show.legend = FALSE) +
scale_y_continuous(expand = c(0, 0), labels = scales::dollar) +
coord_flip() +
labs(y = "GDP per capita",
x = element_blank(),
title = "The Wealthiest Countries",
subtitle = "<span style='color:#00315B'>**Norway**</span> leads in GDP per capita",
caption = "Source: Gapminder") +
theme(plot.subtitle = element_markdown(lineheight = 1.1))
set_bbd_theme(style = "Texas")
tx_vac <- readr::read_csv("https://raw.githubusercontent.com/connorrothschild/tpltheme/master/data/tx_vac_example.csv")
plot <- ggplot(data = tx_vac, aes(x = tx_vac$long,
y = tx_vac$lat,
group = tx_vac$group,
fill = tx_vac$avgvac * 100)) +
coord_fixed(1.3) +
geom_polygon(color = "black") +
labs(title = "Texas Vaccination Rate by County",
subtitle = "Among Kindergarteners",
fill = "Percent\nVaccinated")
add_bbd_logo(plot, scale = 1.5, position = "bottom right")
set_bbd_theme(style = "print")
tx_vac_low <- tx_vac %>%
group_by(subregion) %>%
summarise(avgvac = mean(avgvac)) %>%
mutate(rank = rank(avgvac)) %>%
filter(rank < 10) %>%
arrange(desc(avgvac)) %>%
mutate(subregion = str_to_title(subregion))
plot <- ggplot(data = tx_vac_low, aes(x = reorder(subregion, avgvac),
y = avgvac,
fill = ifelse(subregion == "Terry", "1", "0"))) +
geom_col(show.legend = FALSE) +
labs(title = "Texas Vaccination Rate by County",
subtitle = "Among Kindergarteners") +
coord_flip() +
geom_text(aes(label = ifelse(subregion == "Terry", paste0(100*round(tx_vac_low$avgvac, 2), "%"), '')), hjust = -.25) +
scale_y_continuous(expand = c(0, 0), limits = c(0,1), labels = scales::percent) +
labs(y = "Percent Vaccinated",
x = element_blank(),
title = "The Least Vaccinated Counties",
subtitle = "<span style='color:#00315B'>**Terry County**</span> has the lowest Kindergarten vaccination rate in Texas",
caption = "Source: Texas Department of State Health Services") +
theme(plot.subtitle = element_markdown(lineheight = 1.1),
legend.position = "none")
add_bbd_logo(plot, scale = 1.5)
p1 <- view_palette(palette = palette_bbd_main) + ggtitle("Categorical")
p2 <- view_palette(palette = palette_bbd_diverging) + ggtitle("Diverging")
p3 <- view_palette(palette = palette_bbd_sequential) + ggtitle("Sequential")
gridExtra::grid.arrange(p1, p2, p3, nrow = 1)
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