In terminological/ggrrr: Addressing Annoyances and Irritations

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(tidyverse)
library(ggrrr)

File output

determining where an output file when you may want date versioning.

# an output directory in the current project with date versioning in the filename itself
# out = outputter(here::here("output"))
# out("figure1.png")

# an output directory in a temp directory which has versioned subdirectories
out2 = outputter(normalizePath(tempdir(), mustWork = FALSE),datedSubdirectory = TRUE)
out2("figure1.png")
out2("supplementary1.xlsx",delete = TRUE)

# unversioned files in temp directory
out3 = outputter(normalizePath(tempdir(), mustWork = FALSE),datedSubdirectory = FALSE,datedFile = FALSE)
out3("figure1.png")

Ggplot utilities

# set a range of defaults for graphs
ggrrr::gg_pedantic(font = "Roboto")

# Create a graph and save it to a png and pdf with near exact matches in output layout and to fit in a third A4 page
plot = ggplot(diamonds, aes(x=carat,y=price,color = color))+geom_point()+annotate("label",x=2,y=10000,label="Hello")+labs(tag = "A")
tmp = plot %>% gg_save_as(out2("diamonds1"), size = std_size$third)

message("Files were saved as: \n",tmp$png,"\n",tmp$pdf)
tmp

Tabular data in ggplots

A simple table

tableExample = diamonds %>% 
  mutate(size = cut(carat, breaks=c(-Inf,quantile(carat, probs = c(0.25,0.75)),Inf), labels=c("small","medium","large")) %>% as.factor()) %>%
  group_by(size,cut) %>%
  summarise(
    N = n(),
    depth = sprintf_list("%1.2f (IQR %1.2f \u2014 %1.2f)", quantile(depth,c(0.5,0.25,0.75))),
    price = sprintf_list("%1.0f (IQR %1.0f \u2014 %1.0f)", quantile(price,c(0.5,0.25,0.75)))
  )


tableExample %>% gg_simple_table(font = "Roboto")