index.md

In MaximeWack/desctable: Produce Descriptive and Comparative Tables Easily

Desctable

Warning to existing users This version introduces a new API that should make the creation of tables more flexible. The old API is still present but in a deprecated mode. See the roadmap below, and the website for the new usage. Suggestions about this change are welcome !

Introduction

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

Installation

Install from CRAN with

install.packages("desctable")

or install the development version from github with

devtools::install_github("desctable/desctable")

Basic usage

Load the package

library(desctable)

Simply apply desc_table on a dataframe or a grouped dataframe to get a statistical table

iris %>%
  desc_table()

##                   Variables   N        % Min  Q1  Med     Mean  Q3 Max
## 1              Sepal.Length 150       NA 4.3 5.1 5.80 5.843333 6.4 7.9
## 2               Sepal.Width 150       NA 2.0 2.8 3.00 3.057333 3.3 4.4
## 3              Petal.Length 150       NA 1.0 1.6 4.35 3.758000 5.1 6.9
## 4               Petal.Width 150       NA 0.1 0.3 1.30 1.199333 1.8 2.5
## 5               **Species** 150       NA  NA  NA   NA       NA  NA  NA
## 6     **Species**: *setosa*  50 33.33333  NA  NA   NA       NA  NA  NA
## 7 **Species**: *versicolor*  50 33.33333  NA  NA   NA       NA  NA  NA
## 8  **Species**: *virginica*  50 33.33333  NA  NA   NA       NA  NA  NA
##          sd IQR
## 1 0.8280661 1.3
## 2 0.4358663 0.5
## 3 1.7652982 3.5
## 4 0.7622377 1.5
## 5        NA  NA
## 6        NA  NA
## 7        NA  NA
## 8        NA  NA

Declare the statistics you want to see, and give them the name of your choice

iris %>%
  desc_table("N" = length,
             "%" = percent,
             mean,
             sd)

##                   Variables   N        %     mean        sd
## 1              Sepal.Length 150       NA 5.843333 0.8280661
## 2               Sepal.Width 150       NA 3.057333 0.4358663
## 3              Petal.Length 150       NA 3.758000 1.7652982
## 4               Petal.Width 150       NA 1.199333 0.7622377
## 5               **Species** 150       NA       NA        NA
## 6     **Species**: *setosa*  50 33.33333       NA        NA
## 7 **Species**: *versicolor*  50 33.33333       NA        NA
## 8  **Species**: *virginica*  50 33.33333       NA        NA

Create comparative tables, compute statistical tests and output to pander for crisp markdown rendering!

mtcars %>%
  dplyr::mutate(cyl = factor(cyl),
                vs = factor(vs, labels = c("V-shaped", "straight")),
                am = factor(am, labels = c("automatic", "manual"))) %>%
  group_by(am) %>%
  desc_table(N = length,
             "%" = percent,
             "Median" = median,
             IQR) %>%
  desc_tests(vs = ~chisq.test) %>%
  desc_output("pander")

|   | am = manual (N = 13) N | % | Median | IQR | am = automatic (N = 19) N | % | Median | IQR | p | test | |:-------------|:---------------------------------|:----|:-------|:-----|:------------------------------------|:----|:-------|:-----|:--------|:------------| | mpg | 13 | | 23 | 9.4 | 19 | | 17 | 4.2 | \< 0.01 | wilcox.test | | cyl | 13 | | | | 19 | | | | \< 0.01 | fisher.test | |     4 | 8 | 62 | | | 3 | 16 | | | | | |     6 | 3 | 23 | | | 4 | 21 | | | | | |     8 | 2 | 15 | | | 12 | 63 | | | | | | disp | 13 | | 120 | 81 | 19 | | 276 | 164 | \< 0.01 | wilcox.test | | hp | 13 | | 109 | 47 | 19 | | 175 | 76 | 0.046 | wilcox.test | | drat | 13 | | 4.1 | 0.37 | 19 | | 3.1 | 0.63 | \< 0.01 | wilcox.test | | wt | 13 | | 2.3 | 0.84 | 19 | | 3.5 | 0.41 | \< 0.01 | wilcox.test | | qsec | 13 | | 17 | 2.1 | 19 | | 18 | 2 | 0.27 | wilcox.test | | vs | 13 | | | | 19 | | | | 0.56 | chisq.test | |     V-shaped | 6 | 46 | | | 12 | 63 | | | | | |     straight | 7 | 54 | | | 7 | 37 | | | | | | gear | 13 | | 4 | 1 | 19 | | 3 | 0 | \< 0.01 | wilcox.test | | carb | 13 | | 2 | 3 | 19 | | 3 | 2 | 0.74 | wilcox.test |

Read more in the vignette !

MaximeWack/desctable documentation built on April 6, 2022, 5:38 a.m.