Skip to content

Instantly share code, notes, and snippets.

@trinker
Last active October 9, 2018 15:00
Show Gist options
  • Save trinker/6e8f10ed7f37181c64b1fd020560ece9 to your computer and use it in GitHub Desktop.
Save trinker/6e8f10ed7f37181c64b1fd020560ece9 to your computer and use it in GitHub Desktop.
Write out a bunch of tables to an excel file pipeable workflow
if (!require("pacman")) install.packages("pacman"); library(pacman)
p_load(tidyverse, openxlsx, magrittr, pander, numform)
## make an environment to store everything
my_tables <- new.env()
## basic boiler plate chunk to add
## %T>%
## {assign('yearly_billings_and_percent_change', ., envir = my_tables)}
## Example table 1
mtcars %>%
mutate(perc_disp = disp * 100) %>%
head(5) %T>%
{assign('mtcars_transformed', ., envir = my_tables)} %>%
data.frame(stringsAsFactors = FALSE, check.names = FALSE) %>%
pander::pander(split.tables = Inf, justify = numform::alignment(.))
## Example table 2
CO2 %>%
mutate(
Treatment = abbreviate(Treatment),
conc_uptake = conc/uptake
) %>%
head(5) %T>%
{assign('co2_transformed', ., envir = my_tables)} %>%
data.frame(stringsAsFactors = FALSE, check.names = FALSE) %>%
pander::pander(split.tables = Inf, justify = numform::alignment(.))
## write file to multi tabbes excel
as.list(my_tables) %>%
openxlsx::write.xlsx('my_analysis_tables.xlsx')
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment