Maya Workflow Kit
The whole Maya workflow in Blender, in one install. Free and open source, Blender 4.5 – 5.2.
翻譯準備中
Additional themes, scales, and geoms for ggplot2
翻譯準備中
外掛GitHub @jrnold自行安裝營運者未確認
試用過了嗎? 點一下就好,不需要登入。
尚未收集儲存庫資訊。
尚未偵測到更新。GitHub 發布版本後會顯示在這裡。
製作者的介紹僅有上面的一句話。 更多詳情請閱讀儲存庫 README。 儲存庫 README ↗
正在載入完整 README。
檢視完整 README ↗ggthemes adds themes, scales and geoms to ggplot2 that reproduce the look of well-known publications and software, and of the graphics advocated by Edward Tufte and Stephen Few:
Install the released version from CRAN:
install.packages("ggthemes")
Or the development version from GitHub:
# install.packages("pak")
pak::pak("jrnold/ggthemes")
Every theme is shown below with its matching color scale, where it has one. Each figure links to the theme’s reference page.
Data and base plots used in the examples
library(ggplot2)
library(ggthemes)
mtcars2 <- within(mtcars, {
vs <- factor(vs, labels = c("V-shaped", "Straight"))
am <- factor(am, labels = c("Automatic", "Manual"))
cyl <- factor(cyl)
gear <- factor(gear)
})
p1 <- ggplot(mtcars2) +
geom_point(aes(x = wt, y = mpg, colour = gear)) +
labs(
title = "Fuel economy falls with weight",
x = "Weight (1000 lbs)",
y = "Fuel economy (mpg)",
colour = "Gears"
)
# `theme_map()` intentionally removes axes, so use geographic data rather than
# a scatterplot. `theme_solid()` is likewise intended to leave only geoms.
us_states <- map_data("state")
p_map <- ggplot(us_states, aes(long, lat, group = group)) +
geom_polygon(aes(fill = region), colour = "white", linewidth = 0.15) +
coord_map("albers", lat0 = 39, lat1 = 45) +
guides(fill = "none")
p_solid <- ggplot(mtcars2) +
geom_point(aes(x = wt, y = mpg, colour = gear), size = 3) +
guides(colour = "none")
p1 + theme_base() +
scale_colour_colourblind()
p1 + theme_calc() +
scale_colour_calc()
p1 + theme_clean() +
scale_colour_tableau()
p1 + theme_economist() +
scale_colour_economist()
p1 + theme_excel() +
scale_colour_excel()
p1 + theme_excel_new() +
scale_colour_excel_new()
p1 + theme_few() +
scale_colour_few()
p1 + theme_fivethirtyeight() +
scale_colour_fivethirtyeight()
p1 + theme_foundation() +
scale_colour_colourblind()
p1 + theme_gdocs() +
scale_colour_gdocs()
p1 + theme_hc() +
scale_colour_hc()
p1 + theme_igray()
p_map +
theme_map()
p1 + theme_numbers() +
scale_colour_numbers()
p1 + theme_pander() +
scale_colour_pander()
p1 + theme_par() +
scale_colour_colourblind()
p1 + theme_selenized() +
scale_colour_selenized()
p1 + theme_solarized() +
scale_colour_solarized()
p1 + theme_solarized_2() +
scale_colour_solarized()
p_solid +
theme_solid(fill = "#202124") +
scale_colour_tableau()
p1 + theme_stata() +
scale_colour_stata()
p1 + theme_tufte() +
scale_colour_few()
p1 + theme_wsj(base_size = 8) +
scale_colour_wsj()
A sample of the color palettes is shown below. The palette gallery shows every palette in the package.
geom_rangeframe() draws Tufte’s range frame, axis lines that span only
the range of the data. geom_tufteboxplot() draws his minimal box plot.
ggplot(mtcars, aes(wt, mpg)) +
geom_point() +
geom_rangeframe() +
coord_cartesian(clip = "off") +
labs(x = "Weight (1000 lbs)", y = "Miles per gallon") +
theme_tufte()
ggplot(mtcars, aes(factor(cyl), mpg)) +
geom_tufteboxplot() +
labs(x = "Cylinders", y = "Miles per gallon") +
theme_tufte()