In graggsd/tidyhTbl: A tidy data implementation of the htmlTable package

Introduction

The tidyhTbl package is meant to act as a wrapper function for the htmlTable function in the htmlTable package so that data in a tidy format can be used to fully specify complex html tables.

A strong understanding of the capabilities of the htmlTable package is a pre-requisite for appropriate use of this package. A knowledge of tidy data and the tidyverse are also key to implementing this package appropriately.

Some Examples

Prepare Data

We'll begin by turning the mtcars data into a tidy dataset. The gather function is called to collect 3 performance metrics into a pair of key and value columns.

library(magrittr)
library(tidyr)
library(dplyr)
library(tidyhTbl)
library(tibble)
td <- mtcars %>%
    rownames_to_column %>%
    select(rowname, cyl, gear, hp, mpg, qsec) %>%
    gather(per_metric, value, hp, mpg, qsec)

Now we will compute 4 summary statistics for each of the 3 performance metrics. This will be further grouped by number of cylinders and gears.

tidy_summary <- td %>%
    group_by(cyl, gear, per_metric) %>% 
    summarise(Mean = round(mean(value), 1),
              SD = round(sd(value), 1),
              Min = round(min(value), 1),
              Max = round(max(value), 1)) %>%
    gather(summary_stat, value, Mean, SD, Min, Max) %>% 
    ungroup %>% 
    mutate(gear = paste(gear, "Gears"),
           cyl = paste(cyl, "Cylinders"))

At this point, we are ready to implement the htmlTable_td function. Essentially, this constructs an html table using arguments similar to the htmlTable function. However, whereas htmlTable required the user to manually arrange the data and specify the column groups, headers, row names, row-groups, etc., each of these components of the table is mapped to a column within the input data.

Output html table

Example 1

tidy_summary  %>% 
    htmlTable_td(header_td = "gear",
                 cgroup1_td = "cyl",
                 cell_value = "value", 
                 rnames_td = "summary_stat",
                 rgroup_td = "per_metric")

Example 2

tidy_summary  %>% 
    htmlTable_td(header_td = "summary_stat",
                 cgroup1_td = "per_metric",
                 cell_value = "value", 
                 rnames_td = "gear",
                 rgroup_td = "cyl")