ggplot with the pipe
This package wraps most ggplot2 functions so they work with the pipe %>% with minimal overhead (if noticeable).
You can install ggpipe from github with:
# install.packages("devtools") devtools::install_github("zeehio/ggpipe")# as ggpipe wraps ggplot2 functions, do not use library(ggplot2) in your scripts library(ggpipe) ggplot(mtcars) %>% geom_point(aes(x = mpg, y = disp)) 
This package provides an additional unggplot() function to get back the data from the plot, so multiple plots could be generated on a single pipe:
iris_sepal_png <- "README-iris_sepal.png" iris_petal_png <- "README-iris_petal.png" iris %>% ggplot() %>% geom_point(aes(x = Sepal.Length, y = Sepal.Width, color = Species)) %>% ggsave(iris_sepal_png, height = 3, width = 5, dpi = 72) %>% unggplot() %>% ggplot() %>% geom_point(aes(x = Petal.Length, y = Petal.Width, color = Species)) %>% ggsave(iris_petal_png, height = 3, width = 5, dpi = 72) %>% unggplot() %>% head() #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.2 setosa #> 2 4.9 3.0 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa #> 4 4.6 3.1 1.5 0.2 setosa #> 5 5.0 3.6 1.4 0.2 setosa #> 6 5.4 3.9 1.7 0.4 setosaPlot the two figures:
knitr::include_graphics(iris_sepal_png)
knitr::include_graphics(iris_petal_png)