Source

Overview

The goal of kableExtra is to help you build common complex tables and manipulate table styles. It imports the pipe %>% symbol from magrittr and verbalize all the functions, so basically you can add “layers” to a kable output in a way that is similar with ggplot2 and plotly.

Load Packages

library(kableExtra)

Table Styles

When used on a HTML table, kable_styling() will automatically apply twitter bootstrap theme to the table.

Bootstrap table classes

If you are familiar with twitter bootstrap, you probably have already known its predefined classes, including striped, bordered, hover, condensed and responsive.

dt <- mtcars[1:5, 1:6]
dt %>%
  kable() %>%
  kable_styling()
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Striped and Hover 
# For example, to add striped lines (alternative row colors) to your table and you want to highlight the hovered row
kable(dt) %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Condensed 
# The option condensed can also be handy in many cases when you don’t want your table to be too large. It has slightly shorter row height.
kable(dt) %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed"))
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440

Full Width & Position

kable(dt) %>%
  kable_styling(bootstrap_options = "striped", full_width = F)
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Position 
# Align the table to center, left or right side of the page
kable(dt) %>%
  kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Front Size
kable(dt) %>%
  kable_styling(bootstrap_options = "striped", font_size = 7)
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440

Column/Row Specification

text_tbl <- data.frame(
  Items = c("Item 1", "Item 2", "Item 3"),
  Features = c(
    "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Proin vehicula tempor ex. Morbi malesuada sagittis turpis, at venenatis nisl luctus a. ",
    "In eu urna at magna luctus rhoncus quis in nisl. Fusce in velit varius, posuere risus et, cursus augue. Duis eleifend aliquam ante, a aliquet ex tincidunt in. ", 
    "Vivamus venenatis egestas eros ut tempus. Vivamus id est nisi. Aliquam molestie erat et sollicitudin venenatis. In ac lacus at velit scelerisque mattis. "
  )
)
# Column spec 
# you may want to highlight a column (e.g. a “Total” column) by making it bold. 
kable(text_tbl) %>%
  kable_styling(full_width = F) %>%
  column_spec(1, bold = T, border_right = T) %>%
  column_spec(2, width = "30em", background = "yellow")
Items Features
Item 1 Lorem ipsum dolor sit amet, consectetur adipiscing elit. Proin vehicula tempor ex. Morbi malesuada sagittis turpis, at venenatis nisl luctus a.
Item 2 In eu urna at magna luctus rhoncus quis in nisl. Fusce in velit varius, posuere risus et, cursus augue. Duis eleifend aliquam ante, a aliquet ex tincidunt in.
Item 3 Vivamus venenatis egestas eros ut tempus. Vivamus id est nisi. Aliquam molestie erat et sollicitudin venenatis. In ac lacus at velit scelerisque mattis.
# Row Spec 
# you can either bold or italiciz an entire row.
kable(dt) %>%
  kable_styling("striped", full_width = F) %>%
  column_spec(5:7, bold = T) %>%
  row_spec(3:5, bold = T, color = "white", background = "#D7261E")
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Header Rows 
kable(dt) %>%
  kable_styling("striped", full_width = F) %>%
  row_spec(0, angle = -45)
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440

Cell/Text Specificaiton

Conditional Logic

library(dplyr)
options(knitr.table.format = "html") 
mtcars[1:10, 1:2] %>%
  mutate(
    car = row.names(.),
    mpg = cell_spec(mpg, "html", color = ifelse(mpg > 20, "red", "blue")),
    cyl = cell_spec(cyl, "html", color = "white", align = "c", angle = 45, 
                    background = factor(cyl, c(4, 6, 8), 
                                        c("#666666", "#999999", "#BBBBBB")))
  ) %>%
  select(car, mpg, cyl) %>%
  kable(format = "html", escape = F) %>%
  kable_styling("striped", full_width = F)
car mpg cyl
Mazda RX4 21 6
Mazda RX4 Wag 21 6
Datsun 710 22.8 4
Hornet 4 Drive 21.4 6
Hornet Sportabout 18.7 8
Valiant 18.1 6
Duster 360 14.3 8
Merc 240D 24.4 4
Merc 230 22.8 4
Merc 280 19.2 6

Viridis color for continuous variables

This package also comes with a few helper functions, including spec_color, spec_font_size & spec_angle. These functions can rescale continuous variables to certain scales.

iris[1:10, ] %>%
  mutate_if(is.numeric, function(x) {
    cell_spec(x, bold = T, 
              color = spec_color(x, end = 0.9),
              font_size = spec_font_size(x))
  }) %>%
  mutate(Species = cell_spec(
    Species, color = "white", bold = T,
    background = spec_color(1:10, end = 0.9, option = "A", direction = -1)
  )) %>%
  kable(escape = F, align = "c") %>%
  kable_styling(c("striped", "condensed"), full_width = F)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa
4.6 3.4 1.4 0.3 setosa
5 3.4 1.5 0.2 setosa
4.4 2.9 1.4 0.2 setosa
4.9 3.1 1.5 0.1 setosa

Text Specification

if you need extra markups other than bold or italic, you may use this function to color, change font size or rotate your text. An aliased function text_spec is also provided for a more literal writing experience.

sometext <- strsplit(paste0(
  "You can even try to make some crazy things like this paragraph. ", 
  "It may seem like a useless feature right now but it's so cool ",
  "and nobody can resist. ;)"
), " ")[[1]]
text_formatted <- paste(
  text_spec(sometext, color = spec_color(1:length(sometext), end = 0.9),
            font_size = spec_font_size(1:length(sometext), begin = 5, end = 20)),
  collapse = " ")
# To display the text, type `r text_formatted` outside of the chunk

You can even try to make some crazy things like this paragraph. It may seem like a useless feature right now but it’s so cool and nobody can resist. ;)

Grouped Columns / rows

Add header rows to group columns

Tables with multi-row headers can be very useful to demonstrate grouped data. For your convenience, if column span equals to 1, you can ignore the =1 part so the function below can be written as `add_header_above(c(" “,”Group 1" = 2, “Group 2” = 2, “Group 3” = 2)).

# Header rows 
kable(dt) %>%
  kable_styling("striped") %>%
  add_header_above(c(" " = 1, "Group 1" = 2, "Group 2" = 2, "Group 3" = 2))
Group 1
Group 2
Group 3
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
kable(dt) %>%
  kable_styling(c("striped", "bordered")) %>%
  add_header_above(c(" ", "Group 1" = 2, "Group 2" = 2, "Group 3" = 2)) %>%
  add_header_above(c(" ", "Group 4" = 4, "Group 5" = 2)) %>%
  add_header_above(c(" ", "Group 6" = 6))
Group 6
Group 4
Group 5
Group 1
Group 2
Group 3
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Group rows 
kable(mtcars[1:10, 1:6], caption = "Group Rows") %>%
  kable_styling("striped", full_width = F) %>%
  group_rows(index = c(" " = 3, "Group 1" = 4, "Group 2" = 3))
Group Rows
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160.0 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875
Datsun 710 22.8 4 108.0 93 3.85 2.320
Group 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440
Valiant 18.1 6 225.0 105 2.76 3.460
Duster 360 14.3 8 360.0 245 3.21 3.570
Group 2
Merc 240D 24.4 4 146.7 62 3.69 3.190
Merc 230 22.8 4 140.8 95 3.92 3.150
Merc 280 19.2 6 167.6 123 3.92 3.440
kable(mtcars[1:10, 1:6], caption = "Group Rows") %>% 
  kable_styling("striped", full_width = F) %>%
  group_rows("Group 1", 4, 7) %>%   # same result with group 1=4
  group_rows("Group 2", 8, 10)
Group Rows
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160.0 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875
Datsun 710 22.8 4 108.0 93 3.85 2.320
Group 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440
Valiant 18.1 6 225.0 105 2.76 3.460
Duster 360 14.3 8 360.0 245 3.21 3.570
Group 2
Merc 240D 24.4 4 146.7 62 3.69 3.190
Merc 230 22.8 4 140.8 95 3.92 3.150
Merc 280 19.2 6 167.6 123 3.92 3.440
# Row Indentation 
kable(dt) %>%
  kable_styling("striped", full_width = F) %>%
  add_indent(c(1, 3, 5))
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
# Define row css for the group labeling 
kable(dt) %>%
  kable_styling("striped", full_width = F) %>%
  group_rows("Group 1", 3, 5, label_row_css = "background-color: #666; color: #fff;")
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Group 1
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440

Table Footnote

There are four notation systems in footnote, namely general, number, alphabet and symbol. The last three types of footnotes will be labeled with corresponding marks while general won’t be labeled.

kable(dt, align = "c") %>%
  kable_styling(full_width = F) %>%
  footnote(general = "Here is a general comments of the table. ",
           number = c("Footnote 1; ", "Footnote 2; "),
           alphabet = c("Footnote A; ", "Footnote B; "),
           symbol = c("Footnote Symbol 1; ", "Footnote Symbol 2")
           )
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
Note:
Here is a general comments of the table.
1 Footnote 1;
2 Footnote 2;
a Footnote A;
b Footnote B;
* Footnote Symbol 1;
Footnote Symbol 2
#
dt_footnote <- dt
names(dt_footnote)[2] <- paste0(names(dt_footnote)[2], 
                                footnote_marker_symbol(1))
row.names(dt_footnote)[4] <- paste0(row.names(dt_footnote)[4], 
                                footnote_marker_alphabet(1))
kable(dt_footnote, align = "c", 
      # Remember this escape = F
      escape = F) %>%
  kable_styling(full_width = F) %>%
  footnote(alphabet = "Footnote A; ",
           symbol = "Footnote Symbol 1; ",
           alphabet_title = "Type II: ", symbol_title = "Type III: ",
           footnote_as_chunk = T)
mpg cyl* disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drivea 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
Type II: a Footnote A;
Type III: * Footnote Symbol 1;
# With mark 
# If you need to add footnote marks in table, you need to do it manually (no fancy) using  footnote_mark_***(). Remember that similar with cell_spec, you need to tell this function whether you want it to do it in HTML (default) or LaTeX. You can set it for all using the knitr.table.format global option.
kable(dt, align = "c") %>%
  kable_styling(full_width = F) %>%
  footnote(general = "Here is a general comments of the table. ",
           number = c("Footnote 1; ", "Footnote 2; "),
           alphabet = c("Footnote A; ", "Footnote B; "),
           symbol = c("Footnote Symbol 1; ", "Footnote Symbol 2"),
           general_title = "General: ", number_title = "Type I: ",
           alphabet_title = "Type II: ", symbol_title = "Type III: ",
           footnote_as_chunk = T, title_format = c("italic", "underline")
           )
mpg cyl disp hp drat wt
Mazda RX4 21.0 6 160 110 3.90 2.620
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875
Datsun 710 22.8 4 108 93 3.85 2.320
Hornet 4 Drive 21.4 6 258 110 3.08 3.215
Hornet Sportabout 18.7 8 360 175 3.15 3.440
General: Here is a general comments of the table.
Type I: 1 Footnote 1; 2 Footnote 2;
Type II: a Footnote A; b Footnote B;
Type III: * Footnote Symbol 1; Footnote Symbol 2

Scroll Box for HTML

kable(cbind(mtcars, mtcars)) %>%
  kable_styling() %>%
  scroll_box(width = "500px", height = "200px")
mpg cyl disp hp drat wt qsec vs am gear carb mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
# spcify width suing a percentage 
kable(cbind(mtcars, mtcars)) %>%
  kable_styling() %>%
  scroll_box(width = "100%", height = "200px")
mpg cyl disp hp drat wt qsec vs am gear carb mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2

Save HTML table directly

kable(mtcars) %>%
  kable_styling() %>%
  save_kable(file = "table1.html", self_contained = T)

Integration with other Packages

formattable

You can combine the good parts from kableExtra & formattable together into one piece. Read more at http://haozhu233.github.io/kableExtra/use_kableExtra_with_formattable.html

library(formattable)
mtcars[1:5, 1:4] %>%
  mutate(
    car = row.names(.),
    mpg = color_tile("white", "orange")(mpg),
    cyl = cell_spec(cyl, angle = (1:5)*60, 
                    background = "red", color = "white", align = "center"),
    disp = ifelse(disp > 200,
                  cell_spec(disp, color = "red", bold = T),
                  cell_spec(disp, color = "green", italic = T)),
    hp = color_bar("lightgreen")(hp)
  ) %>%
  select(car, everything()) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = F) %>%
  column_spec(5, width = "3cm") %>%
  add_header_above(c(" ", "Hello" = 2, "World" = 2))
Hello
World
car mpg cyl disp hp
Mazda RX4 21.0 6 160 110
Mazda RX4 Wag 21.0 6 160 110
Datsun 710 22.8 4 108 93
Hornet 4 Drive 21.4 6 258 110
Hornet Sportabout 18.7 8 360 175

tables

tables: formula-driven table generation https://cran.r-project.org/web/packages/tables/index.html