In JMLuther/tabletools: Helpful Tools to Make html Tables

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
library(dplyr)
library(ggplot2)
library(htmlTable)
library(tabletools)
library(tidyr)

tabletools

This package contains a group of convenience functions for metabolic, cardiovascular, and renal calculations, in addition to data summary functions useful for html table generation.

The original goal of tabletools was to provide functions are helpful for generating summary html tables. For details on the functions, please see help documentation in the package.

Installation

Install from Github: devtools::install_github("JMLuther/tabletools", build_vignettes = TRUE)

These functions are most useful in conjunction with an html table generating package::functions such as:

htmlTable::htmlTable Tables with htmlTable and some alternatives
knitr::kable see Create Awesome HTML Table with knitr::kable and kableExtra
formattable

`my_summary` custom summary

This summary function is customized to my preferences, and should provide enough data to pipe into ggplot or a simple summary table. Just provides a summary for a single continuous variable.

Table:

mtcars %>% 
  group_by(cyl) %>% 
  my_summary(mpg, digits = 1) %>% # override the default 2 decimal point rounding
  htmlTable::htmlTable(rnames=F, align = "c",
                       css.cell = rbind(rep("padding-left: .5em; padding-right: .5em;",times=ncol(.)),
                                        matrix("padding:0 5px 0 5px;", ncol=ncol(.), nrow=nrow(.))))

Plot:

mtcars %>% 
  group_by(cyl) %>% 
  my_summary(mpg) %>% 
  ggplot(aes(factor(cyl), mpg_mean,
             ymin = mpg_ci_025, ymax = mpg_ci_975)) +
  geom_linerange() +
  geom_point(color = "red", size=2) +
  labs(x="No. of Cylinders",
       y= "Average MPG",
       title= "Average MPG by number of Cylinders") +
  theme_bw()

Summary text functions

mtcars %>%
  summarise(mean_sd = txt_mean_sd(mpg),
            mean_sem = txt_mean_sem(mpg),
            mean_range = txt_mean_range(mpg),
            median_iqr = txt_median_iqr(mpg),
            pct_fr = txt_pct_fr(vs, 1)
            ) %>% 
  tidyr::gather(txt_f, output) %>% # this is better than using t() which creates a matrix
  htmlTable::htmlTable(rnames=F, align = "l", align.header = "l", 
                       caption = "Example results",
                       css.cell = rbind(rep("padding-left: .5em; padding-right: .5em;",times=ncol(.)),
                                        matrix("padding:0 5px 0 5px;", ncol=ncol(.), nrow=nrow(.))))