desctable usage vignette
In desctable: Produce Descriptive and Comparative Tables Easily

library(desctable)

options(DT.options = list(#scrollX = T,
                          info = F,
                          search = F,
                          dom = "Brtip",
                          fixedColumns = T))
knitr::opts_chunk$set(message = F, warning = F, screenshot.force = F)

Desctable aims to be a simple and expressive interface to building statistical tables in R.

Descriptive tables

Simple

Creating a descriptive table with desctable is as easy as

iris %>%
  desc_table()

By default, desc_table will select the most appropriate statistics for the given table, but you can choose your own as easily

mtcars %>%
  desc_table(N = length,
             mean,
             sd)

As you can see with N = length, you can give a meaningful name to the column instead of the name of the function.
You are not limited in your options, and can use any statistical function that exists in R, even your own!

You can also use purrr::map-like formulas, for example to get the first and third quartiles here

iris %>%
  desc_table(N = length,
             "%" = percent,
             Q1 = ~ quantile(., .25),
             Med = median,
             Q3 = ~ quantile(., .75))

By group

You can also create nested descriptive tables by applying group_by on your dataframe

iris %>%
  group_by(Species) %>%
  desc_table()

However, because of the grouping, you can see the resulting object is not a simple data frame, but a nested dataframe (see tidyr::nest and tidyr::unnest).
desctable provides output functions to format this object to various outputs.
Right now, desctable supports data.frame, pander, and DT outputs. These output functions will also round numerical values, as well as p values for tests (we'll see desc_tests a bit later).

mtcars %>%
  group_by(am) %>%
  desc_table() %>%
  desc_output("df")

mtcars %>%
  group_by(am) %>%
  desc_table() %>%
  desc_output("pander")

mtcars %>%
  group_by(am) %>%
  desc_table() %>%
  desc_output("DT")

Comparative tables

You can add tests to a grouped descriptive desctable

iris %>%
  group_by(Petal.Length > 5) %>%
  desc_table() %>%
  desc_tests() %>%
  desc_output("DT")

By default, desc_tests will select the most appropriate statistical tests for the given table, but you can choose your own as easily. For example, to compare Sepal.Width using a Student's t test

iris %>%
  group_by(Petal.Length > 5) %>%
  desc_table(mean, sd, median, IQR) %>%
  desc_tests(Sepal.Width = ~t.test) %>%
  desc_output("DT")

Note that the name of the test must be prepended with a tilde (~) in all cases!

You can also use purrr::map-like formulas to change tests options

iris %>%
  group_by(Petal.Length > 5) %>%
  desc_table(mean, sd, median, IQR) %>%
  desc_tests(Sepal.Width = ~t.test(., var.equal = T)) %>%
  desc_output("DT")