Introduction
I’m not a big fan of the default options for printing dataframes as specified in the YAML header (e.g., default, paged, tibble, kable) of Rmarkdown. Here I hope to:
- Customize the aesthetics of data table printing from Rmarkdown to HTML.
- Generate a function that bundles these preferences.
- Pass this custom function to ‘df_print’ in the YAML header of Rmarkdown so that all tables successively knitted under this function call will retain my preferred aesthetics.
We are going to tweak the aesthetics of some fake data with the kableExtra package.
and awaaay we go!
Let’s work with mtcars from base R
dat <- mtcars
str(dat)
## 'data.frame': 32 obs. of 11 variables:
## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
## $ disp: num 160 160 108 258 360 ...
## $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
## $ qsec: num 16.5 17 18.6 19.4 17 ...
## $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
## $ am : num 1 1 1 0 0 0 0 0 0 0 ...
## $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
## $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
print(dat)
## 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
## Mazda RX4 Wag 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
## Hornet 4 Drive 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
## Valiant 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
## Merc 240D 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
## Merc 280 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
## Merc 450SE 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
## Merc 450SLC 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
## Lincoln Continental 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
## Fiat 128 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
## Toyota Corolla 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
## Dodge Challenger 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
## Camaro Z28 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
## Fiat X1-9 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
## Lotus Europa 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
## Ferrari Dino 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
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
That’s fairly ugly, but it gets the job done.
Base table
Let’s see what we can improve on using kableExtra. We will use the almighty pipe for these bits of code. Here’s the most stripped down version similar to what you might encounter when you specify df_print: kable. Here I am using indices to limit the output to all columns but only the first 10 rows. Cells are now left-aligned and output is limited to two decimal places.
dat[1:10, ] %>% kbl(digits = 2, align = "l") %>% kable_styling() #max decimals to print is two places
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Hover & Condense
This one is a bit too squashed.
dat[1:10, ] %>% kbl(digits = 2, align = "l") %>% kable_paper("hover", full_width = F)
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Kable Classic I
Change font, font size, add caption
dat[1:10, ] %>% kbl(digits = 2, align = "l", caption = "Here's a caption!") %>% kable_classic(full_width = F,
html_font = "Helvetica", font_size = 14) #change font and font size
Here’s a caption!
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Kable Classic II
dat[1:10, ] %>% kbl(digits = 2, align = "l", caption = "Here's a caption!") %>% kable_classic_2(full_width = F,
html_font = "Helvetica", font_size = 14) #condensed
Here’s a caption!
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
dat[1:10, ] %>% kbl(digits = 2, align = "l", caption = "Larger tables better streched full width") %>%
kable_classic_2(full_width = T, html_font = "Helvetica", font_size = 14) #full width
Larger tables better streched full width
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Bootstrap options applied
dat[1:10, ] %>% kbl(digits = 2, align = "l", caption = "Here's a nice version") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
html_font = "Helvetica", font_size = 14)
Here’s a nice version
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Positioning
left
best for smaller tables not stretched to full width
dat[1:10, ] %>% kbl(digits = 2, align = "l", caption = "I'm on the left side") %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left",
html_font = "Helvetica", font_size = 14)
I’m on the left side
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Float figure and wrap text
dat[1:10, ] %>% kbl(digits = 2, align = "l", caption = "I'm on the right side now") %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "float_right",
html_font = "Helvetica", font_size = 14) #wrap text
I’m on the right side now
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
Here’s some bullshit to test out textwrapping from a paper we just published in the Journal of Neurolinguistics. Word meanings are often suffused with sensory, motor, and affective features. For many of us, a word such as beach evokes a diverse range of pleasant associations including blue skies (visual),gritty sand (tactile), crashing waves (auditory), and the distinctive smell of sunscreen (olfactory).Aristotle argued for a hierarchy of the senses where vision and audition eclipse the lesser modalities of odor, taste, and touch. A direct test of Aristotle’s premise was recently made possible with the establishment of the Lancaster Sensorimotor Norms (2019), a crowdsourced database cataloging sensorimotor salience for nearly 40,000 English words. Neurosynth, a metanalytic database of functional magnetic resonance imaging studies, can potentially confirm if Aristotle’s sensory hierarchy is reflected in functional activation within the human brain. We correlated sensory salience of English words as assessed by subjective ratings of vision, audition, olfaction, touch, and gustation (Lancaster Ratings) with volumes of cortical activation for each of these respective sensory modalities (Neurosynth). English word ratings reflected the following sensory hierarchy: vision > audition > haptic > olfaction gustation. This linguistic hierarchy nearly perfectly correlated with voxel counts of functional activation maps by each sensory modality (Pearson r = .99). These findings are grossly consistent with Aristotle’s hierarchy of the senses. We discuss implications and counterevidence from other natural languages.
Putting it all together
dat %>% kbl(digits = 2, align = "l") %>% kable_styling(fixed_thead = T, position = "float_right") %>%
kable_paper("striped", full_width = T, fixed_thead = T, html_font = "Helvetica",
font_size = 12) %>% row_spec(0, color = "white", background = "#84BA8C") %>%
scroll_box(width = "850px", height = "300px")
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
|
Merc 280C
|
17.8
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.90
|
1
|
0
|
4
|
4
|
|
Merc 450SE
|
16.4
|
8
|
275.8
|
180
|
3.07
|
4.07
|
17.40
|
0
|
0
|
3
|
3
|
|
Merc 450SL
|
17.3
|
8
|
275.8
|
180
|
3.07
|
3.73
|
17.60
|
0
|
0
|
3
|
3
|
|
Merc 450SLC
|
15.2
|
8
|
275.8
|
180
|
3.07
|
3.78
|
18.00
|
0
|
0
|
3
|
3
|
|
Cadillac Fleetwood
|
10.4
|
8
|
472.0
|
205
|
2.93
|
5.25
|
17.98
|
0
|
0
|
3
|
4
|
|
Lincoln Continental
|
10.4
|
8
|
460.0
|
215
|
3.00
|
5.42
|
17.82
|
0
|
0
|
3
|
4
|
|
Chrysler Imperial
|
14.7
|
8
|
440.0
|
230
|
3.23
|
5.34
|
17.42
|
0
|
0
|
3
|
4
|
|
Fiat 128
|
32.4
|
4
|
78.7
|
66
|
4.08
|
2.20
|
19.47
|
1
|
1
|
4
|
1
|
|
Honda Civic
|
30.4
|
4
|
75.7
|
52
|
4.93
|
1.61
|
18.52
|
1
|
1
|
4
|
2
|
|
Toyota Corolla
|
33.9
|
4
|
71.1
|
65
|
4.22
|
1.83
|
19.90
|
1
|
1
|
4
|
1
|
|
Toyota Corona
|
21.5
|
4
|
120.1
|
97
|
3.70
|
2.46
|
20.01
|
1
|
0
|
3
|
1
|
|
Dodge Challenger
|
15.5
|
8
|
318.0
|
150
|
2.76
|
3.52
|
16.87
|
0
|
0
|
3
|
2
|
|
AMC Javelin
|
15.2
|
8
|
304.0
|
150
|
3.15
|
3.44
|
17.30
|
0
|
0
|
3
|
2
|
|
Camaro Z28
|
13.3
|
8
|
350.0
|
245
|
3.73
|
3.84
|
15.41
|
0
|
0
|
3
|
4
|
|
Pontiac Firebird
|
19.2
|
8
|
400.0
|
175
|
3.08
|
3.85
|
17.05
|
0
|
0
|
3
|
2
|
|
Fiat X1-9
|
27.3
|
4
|
79.0
|
66
|
4.08
|
1.94
|
18.90
|
1
|
1
|
4
|
1
|
|
Porsche 914-2
|
26.0
|
4
|
120.3
|
91
|
4.43
|
2.14
|
16.70
|
0
|
1
|
5
|
2
|
|
Lotus Europa
|
30.4
|
4
|
95.1
|
113
|
3.77
|
1.51
|
16.90
|
1
|
1
|
5
|
2
|
|
Ford Pantera L
|
15.8
|
8
|
351.0
|
264
|
4.22
|
3.17
|
14.50
|
0
|
1
|
5
|
4
|
|
Ferrari Dino
|
19.7
|
6
|
145.0
|
175
|
3.62
|
2.77
|
15.50
|
0
|
1
|
5
|
6
|
|
Maserati Bora
|
15.0
|
8
|
301.0
|
335
|
3.54
|
3.57
|
14.60
|
0
|
1
|
5
|
8
|
|
Volvo 142E
|
21.4
|
4
|
121.0
|
109
|
4.11
|
2.78
|
18.60
|
1
|
1
|
4
|
2
|
Test driving print functions
df.out1
df.out1 <- function(x) {
x <- x %>% kbl(digits = 2, align = "l") %>% kable_styling(fixed_thead = T, position = "float_right") %>%
kable_paper("striped", full_width = T, fixed_thead = T, html_font = "Helvetica",
font_size = 12) %>% row_spec(0, color = "white", background = "#84BA8C") %>%
scroll_box(width = "600px", height = "300px")
return(x)
}
df.out1(dat)
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
|
Merc 280C
|
17.8
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.90
|
1
|
0
|
4
|
4
|
|
Merc 450SE
|
16.4
|
8
|
275.8
|
180
|
3.07
|
4.07
|
17.40
|
0
|
0
|
3
|
3
|
|
Merc 450SL
|
17.3
|
8
|
275.8
|
180
|
3.07
|
3.73
|
17.60
|
0
|
0
|
3
|
3
|
|
Merc 450SLC
|
15.2
|
8
|
275.8
|
180
|
3.07
|
3.78
|
18.00
|
0
|
0
|
3
|
3
|
|
Cadillac Fleetwood
|
10.4
|
8
|
472.0
|
205
|
2.93
|
5.25
|
17.98
|
0
|
0
|
3
|
4
|
|
Lincoln Continental
|
10.4
|
8
|
460.0
|
215
|
3.00
|
5.42
|
17.82
|
0
|
0
|
3
|
4
|
|
Chrysler Imperial
|
14.7
|
8
|
440.0
|
230
|
3.23
|
5.34
|
17.42
|
0
|
0
|
3
|
4
|
|
Fiat 128
|
32.4
|
4
|
78.7
|
66
|
4.08
|
2.20
|
19.47
|
1
|
1
|
4
|
1
|
|
Honda Civic
|
30.4
|
4
|
75.7
|
52
|
4.93
|
1.61
|
18.52
|
1
|
1
|
4
|
2
|
|
Toyota Corolla
|
33.9
|
4
|
71.1
|
65
|
4.22
|
1.83
|
19.90
|
1
|
1
|
4
|
1
|
|
Toyota Corona
|
21.5
|
4
|
120.1
|
97
|
3.70
|
2.46
|
20.01
|
1
|
0
|
3
|
1
|
|
Dodge Challenger
|
15.5
|
8
|
318.0
|
150
|
2.76
|
3.52
|
16.87
|
0
|
0
|
3
|
2
|
|
AMC Javelin
|
15.2
|
8
|
304.0
|
150
|
3.15
|
3.44
|
17.30
|
0
|
0
|
3
|
2
|
|
Camaro Z28
|
13.3
|
8
|
350.0
|
245
|
3.73
|
3.84
|
15.41
|
0
|
0
|
3
|
4
|
|
Pontiac Firebird
|
19.2
|
8
|
400.0
|
175
|
3.08
|
3.85
|
17.05
|
0
|
0
|
3
|
2
|
|
Fiat X1-9
|
27.3
|
4
|
79.0
|
66
|
4.08
|
1.94
|
18.90
|
1
|
1
|
4
|
1
|
|
Porsche 914-2
|
26.0
|
4
|
120.3
|
91
|
4.43
|
2.14
|
16.70
|
0
|
1
|
5
|
2
|
|
Lotus Europa
|
30.4
|
4
|
95.1
|
113
|
3.77
|
1.51
|
16.90
|
1
|
1
|
5
|
2
|
|
Ford Pantera L
|
15.8
|
8
|
351.0
|
264
|
4.22
|
3.17
|
14.50
|
0
|
1
|
5
|
4
|
|
Ferrari Dino
|
19.7
|
6
|
145.0
|
175
|
3.62
|
2.77
|
15.50
|
0
|
1
|
5
|
6
|
|
Maserati Bora
|
15.0
|
8
|
301.0
|
335
|
3.54
|
3.57
|
14.60
|
0
|
1
|
5
|
8
|
|
Volvo 142E
|
21.4
|
4
|
121.0
|
109
|
4.11
|
2.78
|
18.60
|
1
|
1
|
4
|
2
|
df.out2
df.out2 <- function(x) {
x <- x %>% kbl(digits = 2, align = "l") %>% kable_styling(fixed_thead = T, position = "float_right") %>%
kable_paper("striped", full_width = T, fixed_thead = T, html_font = "Helvetica",
font_size = 13) %>% row_spec(0, color = "white", background = "#5b705f") %>%
scroll_box(width = "600px", height = "300px")
return(x)
}
df.out2(dat)
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
|
Merc 280C
|
17.8
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.90
|
1
|
0
|
4
|
4
|
|
Merc 450SE
|
16.4
|
8
|
275.8
|
180
|
3.07
|
4.07
|
17.40
|
0
|
0
|
3
|
3
|
|
Merc 450SL
|
17.3
|
8
|
275.8
|
180
|
3.07
|
3.73
|
17.60
|
0
|
0
|
3
|
3
|
|
Merc 450SLC
|
15.2
|
8
|
275.8
|
180
|
3.07
|
3.78
|
18.00
|
0
|
0
|
3
|
3
|
|
Cadillac Fleetwood
|
10.4
|
8
|
472.0
|
205
|
2.93
|
5.25
|
17.98
|
0
|
0
|
3
|
4
|
|
Lincoln Continental
|
10.4
|
8
|
460.0
|
215
|
3.00
|
5.42
|
17.82
|
0
|
0
|
3
|
4
|
|
Chrysler Imperial
|
14.7
|
8
|
440.0
|
230
|
3.23
|
5.34
|
17.42
|
0
|
0
|
3
|
4
|
|
Fiat 128
|
32.4
|
4
|
78.7
|
66
|
4.08
|
2.20
|
19.47
|
1
|
1
|
4
|
1
|
|
Honda Civic
|
30.4
|
4
|
75.7
|
52
|
4.93
|
1.61
|
18.52
|
1
|
1
|
4
|
2
|
|
Toyota Corolla
|
33.9
|
4
|
71.1
|
65
|
4.22
|
1.83
|
19.90
|
1
|
1
|
4
|
1
|
|
Toyota Corona
|
21.5
|
4
|
120.1
|
97
|
3.70
|
2.46
|
20.01
|
1
|
0
|
3
|
1
|
|
Dodge Challenger
|
15.5
|
8
|
318.0
|
150
|
2.76
|
3.52
|
16.87
|
0
|
0
|
3
|
2
|
|
AMC Javelin
|
15.2
|
8
|
304.0
|
150
|
3.15
|
3.44
|
17.30
|
0
|
0
|
3
|
2
|
|
Camaro Z28
|
13.3
|
8
|
350.0
|
245
|
3.73
|
3.84
|
15.41
|
0
|
0
|
3
|
4
|
|
Pontiac Firebird
|
19.2
|
8
|
400.0
|
175
|
3.08
|
3.85
|
17.05
|
0
|
0
|
3
|
2
|
|
Fiat X1-9
|
27.3
|
4
|
79.0
|
66
|
4.08
|
1.94
|
18.90
|
1
|
1
|
4
|
1
|
|
Porsche 914-2
|
26.0
|
4
|
120.3
|
91
|
4.43
|
2.14
|
16.70
|
0
|
1
|
5
|
2
|
|
Lotus Europa
|
30.4
|
4
|
95.1
|
113
|
3.77
|
1.51
|
16.90
|
1
|
1
|
5
|
2
|
|
Ford Pantera L
|
15.8
|
8
|
351.0
|
264
|
4.22
|
3.17
|
14.50
|
0
|
1
|
5
|
4
|
|
Ferrari Dino
|
19.7
|
6
|
145.0
|
175
|
3.62
|
2.77
|
15.50
|
0
|
1
|
5
|
6
|
|
Maserati Bora
|
15.0
|
8
|
301.0
|
335
|
3.54
|
3.57
|
14.60
|
0
|
1
|
5
|
8
|
|
Volvo 142E
|
21.4
|
4
|
121.0
|
109
|
4.11
|
2.78
|
18.60
|
1
|
1
|
4
|
2
|
df.out3
df.out3 <- function(x) {
x <- x %>% kbl(digits = 2, align = "l", booktabs = T) %>% kable_styling(fixed_thead = T,
position = "float_right") %>% kable_paper("striped", full_width = T, fixed_thead = T,
html_font = "Helvetica", font_size = 11) %>% row_spec(0, color = "yellow",
background = "#5b705f", font_size = 12) %>% scroll_box(width = "700px", height = "300px")
return(x)
}
df.out3(dat)
|
|
mpg
|
cyl
|
disp
|
hp
|
drat
|
wt
|
qsec
|
vs
|
am
|
gear
|
carb
|
|
Mazda RX4
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.62
|
16.46
|
0
|
1
|
4
|
4
|
|
Mazda RX4 Wag
|
21.0
|
6
|
160.0
|
110
|
3.90
|
2.88
|
17.02
|
0
|
1
|
4
|
4
|
|
Datsun 710
|
22.8
|
4
|
108.0
|
93
|
3.85
|
2.32
|
18.61
|
1
|
1
|
4
|
1
|
|
Hornet 4 Drive
|
21.4
|
6
|
258.0
|
110
|
3.08
|
3.21
|
19.44
|
1
|
0
|
3
|
1
|
|
Hornet Sportabout
|
18.7
|
8
|
360.0
|
175
|
3.15
|
3.44
|
17.02
|
0
|
0
|
3
|
2
|
|
Valiant
|
18.1
|
6
|
225.0
|
105
|
2.76
|
3.46
|
20.22
|
1
|
0
|
3
|
1
|
|
Duster 360
|
14.3
|
8
|
360.0
|
245
|
3.21
|
3.57
|
15.84
|
0
|
0
|
3
|
4
|
|
Merc 240D
|
24.4
|
4
|
146.7
|
62
|
3.69
|
3.19
|
20.00
|
1
|
0
|
4
|
2
|
|
Merc 230
|
22.8
|
4
|
140.8
|
95
|
3.92
|
3.15
|
22.90
|
1
|
0
|
4
|
2
|
|
Merc 280
|
19.2
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.30
|
1
|
0
|
4
|
4
|
|
Merc 280C
|
17.8
|
6
|
167.6
|
123
|
3.92
|
3.44
|
18.90
|
1
|
0
|
4
|
4
|
|
Merc 450SE
|
16.4
|
8
|
275.8
|
180
|
3.07
|
4.07
|
17.40
|
0
|
0
|
3
|
3
|
|
Merc 450SL
|
17.3
|
8
|
275.8
|
180
|
3.07
|
3.73
|
17.60
|
0
|
0
|
3
|
3
|
|
Merc 450SLC
|
15.2
|
8
|
275.8
|
180
|
3.07
|
3.78
|
18.00
|
0
|
0
|
3
|
3
|
|
Cadillac Fleetwood
|
10.4
|
8
|
472.0
|
205
|
2.93
|
5.25
|
17.98
|
0
|
0
|
3
|
4
|
|
Lincoln Continental
|
10.4
|
8
|
460.0
|
215
|
3.00
|
5.42
|
17.82
|
0
|
0
|
3
|
4
|
|
Chrysler Imperial
|
14.7
|
8
|
440.0
|
230
|
3.23
|
5.34
|
17.42
|
0
|
0
|
3
|
4
|
|
Fiat 128
|
32.4
|
4
|
78.7
|
66
|
4.08
|
2.20
|
19.47
|
1
|
1
|
4
|
1
|
|
Honda Civic
|
30.4
|
4
|
75.7
|
52
|
4.93
|
1.61
|
18.52
|
1
|
1
|
4
|
2
|
|
Toyota Corolla
|
33.9
|
4
|
71.1
|
65
|
4.22
|
1.83
|
19.90
|
1
|
1
|
4
|
1
|
|
Toyota Corona
|
21.5
|
4
|
120.1
|
97
|
3.70
|
2.46
|
20.01
|
1
|
0
|
3
|
1
|
|
Dodge Challenger
|
15.5
|
8
|
318.0
|
150
|
2.76
|
3.52
|
16.87
|
0
|
0
|
3
|
2
|
|
AMC Javelin
|
15.2
|
8
|
304.0
|
150
|
3.15
|
3.44
|
17.30
|
0
|
0
|
3
|
2
|
|
Camaro Z28
|
13.3
|
8
|
350.0
|
245
|
3.73
|
3.84
|
15.41
|
0
|
0
|
3
|
4
|
|
Pontiac Firebird
|
19.2
|
8
|
400.0
|
175
|
3.08
|
3.85
|
17.05
|
0
|
0
|
3
|
2
|
|
Fiat X1-9
|
27.3
|
4
|
79.0
|
66
|
4.08
|
1.94
|
18.90
|
1
|
1
|
4
|
1
|
|
Porsche 914-2
|
26.0
|
4
|
120.3
|
91
|
4.43
|
2.14
|
16.70
|
0
|
1
|
5
|
2
|
|
Lotus Europa
|
30.4
|
4
|
95.1
|
113
|
3.77
|
1.51
|
16.90
|
1
|
1
|
5
|
2
|
|
Ford Pantera L
|
15.8
|
8
|
351.0
|
264
|
4.22
|
3.17
|
14.50
|
0
|
1
|
5
|
4
|
|
Ferrari Dino
|
19.7
|
6
|
145.0
|
175
|
3.62
|
2.77
|
15.50
|
0
|
1
|
5
|
6
|
|
Maserati Bora
|
15.0
|
8
|
301.0
|
335
|
3.54
|
3.57
|
14.60
|
0
|
1
|
5
|
8
|
|
Volvo 142E
|
21.4
|
4
|
121.0
|
109
|
4.11
|
2.78
|
18.60
|
1
|
1
|
4
|
2
|
Apply global dataframe print option
Delete the df_print line from the YAML header, then paste this print function in the code block right after the YAML header (after the libraries). Now your dataframes and tables will all automatically print in this glorious style.
print.me <- function(x, ...) {
x %>% kbl(digits = 2, align = "l", booktabs = T) %>% kable_styling(fixed_thead = T,
position = "float_left") %>% kable_paper("striped", full_width = T, fixed_thead = T,
html_font = "Helvetica", font_size = 11) %>% row_spec(0, color = "white",
background = "#5b705f", font_size = 12) %>% scroll_box(width = "700px", height = "300px") %>%
asis_output()
}
registerS3method("knit_print", "data.frame", print.me)
# registerS3method(genname, class, method, envir = parent.frame())