Code Through Assignment

Introduction

Creating complex tables which are easier to read has never been simpler. KableExtra function makes it possible to create professional looking complex table in Rmarkdown document. It allows for lots of customizations. KableExtra uses %>% function which makes the language very intuitive and making it easier to code. It can also be easily used with packages like dplyr, ggplot .

Getting started

The following packages and libraries are needed for this purpose.

# install.packages() cannot be included in an RMD file when knitting
#install.packages("kableExtra")
#install.packages("prettydoc")
#install.packages("dplyr")
library(knitr)
library(kableExtra)
library(prettydoc)
library(dplyr)

The dataset, USAarrest, is used for this assignment. This data set has 50 rows and 4 columns but for the purpose of this assignment we will use first 8 rows.

data ("USArrests")
dat<- USArrests
dim (dat)
## [1] 50  4

The basic Kable function presents data without any formatting in the following view.

Basic Table

dat<- USArrests [1:8,1:4]
kable(dat)
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Styling Table

kable_styling() function can be used to style the table in various ways. Here is the most basic version.

dat %>%
  kable() %>%
  kable_styling()
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

KableExtra offers many styling options. Some of the most popular ones are striped lines, group columns, change row colors, condensed table, flexible font sizes, change of indentation, texts, explanations, and notations. There are endless possibilities around this package. Few of them are explained below.

Table width

In this style, striped lines of alternate colors can be added to the rows to make it visually interesting. Kable, by default, takes up the whole screen when displaying the output.

kable(dat) %>%
kable_styling(bootstrap_options = c("striped", "hover"))
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

However, “full_width = F”, as an argument, can be added so the output does not take up the whole screen. This does not change any grid options of the table.

kable(dat) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))%>%
  kable_styling (full_width = F)
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Condensed

Output can be printed in condensed form. condensed argument in kable_styling () function makes this possible. It can be used when dealing with huge datasets to improve the readability. This condenses the row height and column width as well. It is different than full_width = F. The effect will be more visible if there were more columns in the example.

kable(dat) %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed"))
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Responsive

In today’s day and age output is not just limited to a computer screen. Mobile or handheld devices should be taken into consideration as well. To overcome this situation and improve readability across various mediums kable_styling () offers responsive option which allows users to scroll data horizontally. The data will look the same on a computer screen.

kable(dat) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Positioning table

There are also options available to justify the table left, right or center of the page. If there are lots of explanatory texts related to the table float can be used to position table to the left or right to include text using the argument position = “float_right” or position = “float_left”

kable(dat) %>%
  kable_styling(bootstrap_options = "striped", full_width = F, position = "right")
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Font size

Font size can also be adjusted by using font_size in the argument.

Increasing Font size

kable(dat) %>%
kable_styling(font_size = 20)
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Decreasing Font Size

kable(dat) %>%
kable_styling(font_size = 10)
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Conditional Logic

Conditional logic can be easily applied using cell_spec(). This makes it easier to analyze data visually.

dat %>%
  mutate(
    States = row.names(.),
    Murders = cell_spec(Murder, "html", color = ifelse(Murder > 9, "firebrick", "darkblue")),
    Assaults = cell_spec(Assault, "html", color = ifelse(Assault > 250, "firebrick", "darkblue")), 
    UrbanPops = cell_spec(UrbanPop, "html", color = ifelse(UrbanPop > 75, "firebrick", "darkblue") ),
    Rapes = cell_spec(Rape, "html", color = ifelse(Rape > 30, "firebrick", "darkblue"))                
  ) %>%
  select(States,Murders,Assaults, UrbanPops, Rapes) %>%
  kable(format = "html", escape = F) %>%
  kable_styling("striped", full_width = F)
States Murders Assaults UrbanPops Rapes
Alabama 13.2 236 58 21.2
Alaska 10 263 48 44.5
Arizona 8.1 294 80 31
Arkansas 8.8 190 50 19.5
California 9 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Header rows

Adding one header row

Sometimes adding a header row to explain the data table is required. It is easy to do so by using %>% in Kable. The table output can be piped to add extra row using add_header_above() function.

kable(dat) %>%
  kable_styling("striped") %>%
  add_header_above(c(" " = 1, "Crime group 1" = 2, "Crime Group 2" = 2))
Crime group 1
Crime Group 2
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Adding multiple header rows

Additional header rows can be added to further enhance the table.

kable(dat) %>%
  kable_styling(c("striped", "bordered")) %>%
  add_header_above(c(" ", "Crime Group 1" = 2, " Crime Group 2" = 2)) %>%
  add_header_above(c(" ", "Group 3" = 1, "Group 4" = 3)) %>%
  add_header_above(c(" ", "Statewise Crime Data" = 4))
Statewise Crime Data
Group 3
Group 4
Crime Group 1
Crime Group 2
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Formatting header row

Header row can be easily formatted using row_spec(). Position of the header can be adjusted by changing the angle. Changing the color is easy as well.

kable(dat) %>%
  kable_styling("striped", full_width = F) %>%
  row_spec(0, angle = -15, color = "steelblue")
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8

Adding footnote

Sometimes adding footnote is a required to explain the data set in the table. add_footnote () function can be used for this. Within this function symbol, number or alphabets can be assigned to explain footnote. Here is an example using alphabets. It can be customized by changing argument notation = "" within the function.

Alphabet

kable(dat) %>%
  kable_styling("striped") %>%
  add_footnote(c(" Statewise Crime Data under 4 categories ", "Displaying First 8 states only."),notation = "alphabet" )
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8
a Statewise Crime Data under 4 categories
b Displaying First 8 states only.

Number

kable(dat) %>%
  kable_styling("striped") %>%
  add_footnote(c(" Statewise Crime Data under 4 categories ", "Displaying First 8 states only."), notation = "number")
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8
1 Statewise Crime Data under 4 categories
2 Displaying First 8 states only.

Symbol

kable(dat) %>%
  kable_styling("striped") %>%
  add_footnote(c(" Statewise Crime Data under 4 categories ", "Displaying First 8 states only."), notation = "symbol")
Murder Assault UrbanPop Rape
Alabama 13.2 236 58 21.2
Alaska 10.0 263 48 44.5
Arizona 8.1 294 80 31.0
Arkansas 8.8 190 50 19.5
California 9.0 276 91 40.6
Colorado 7.9 204 78 38.7
Connecticut 3.3 110 77 11.1
Delaware 5.9 238 72 15.8
* Statewise Crime Data under 4 categories
† Displaying First 8 states only.

Acknowledgement

There are many functions available within this package. The following resources were used to create this tutorial for the assignment. To explore more please click the following links.

rpubs

github

cran.rstudio

Cran.r-project

haozhu233.github